NASA Astronaut Dosimetry

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Title:
NASA Astronaut Dosimetry Implementation of Scalable Human Phantoms and Benchmark Comparisons of Deterministic versus Monte Carlo Radiation Transport
Physical Description:
1 online resource (683 p.)
Language:
english
Creator:
Bahadori, Amir Alexander
Publisher:
University of Florida
Place of Publication:
Gainesville, Fla.
Publication Date:

Thesis/Dissertation Information

Degree:
Doctorate ( Ph.D.)
Degree Grantor:
University of Florida
Degree Disciplines:
Biomedical Engineering
Committee Chair:
Bolch, Wesley E
Committee Members:
Hintenlang, David E
Delp, Michael
Woodard, Richard P
Van Baalen, Mary
Shavers, Mark

Subjects

Subjects / Keywords:
bryntrn -- carlo -- deterministic -- dosimetry -- hzetrn -- monte -- nasa -- phantom -- phits -- radiation -- space -- transport
Biomedical Engineering -- Dissertations, Academic -- UF
Genre:
Biomedical Engineering thesis, Ph.D.
Electronic Thesis or Dissertation
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )

Notes

Abstract:
Astronauts are exposed to a unique radiation environment in space.  United States terrestrial radiation worker limits, derived from guidelines produced by scientific panels, do not apply to astronauts.  Limits for astronauts have changed throughout the Space Age, eventually reaching the current National Aeronautics and Space Administration limit of 3% risk of exposure induced death, with an administrative stipulation that the risk be assured to the upper 95% confidence limit.  Much effort has been spent on reducing the uncertainty associated with evaluating astronaut risk for radiogenic cancer mortality, while tools that affect the accuracy of the calculations have largely remained unchanged.  In the present study, the impacts of using more realistic computational phantoms with size variability to represent astronauts with simplified deterministic radiation transport were evaluated.  Next, the impacts of microgravity-induced body changes on space radiation dosimetry using the same transport method were investigated.  Finally, dosimetry and risk calculations resulting from Monte Carlo radiation transport were compared with results obtained using simplified deterministic radiation transport.  The results of the present study indicated that the use of phantoms that more accurately represent human anatomy can substantially improve space radiation dose estimates, most notably for exposures from solar particle events under light shielding conditions.  Microgravity-induced changes were less important, but results showed that flexible phantoms could assist in optimizing astronaut body position for reducing exposures during solar particle events.  Finally, little overall differences in risk calculations using simplified deterministic radiation transport and 3D Monte Carlo radiation transport were found; however, for the galactic cosmic ray ion spectra, compensating errors were observed for the constituent ions, thus exhibiting the need to perform evaluations on a particle differential basis with common cross-section libraries.
General Note:
In the series University of Florida Digital Collections.
General Note:
Includes vita.
Bibliography:
Includes bibliographical references.
Source of Description:
Description based on online resource; title from PDF title page.
Source of Description:
This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Thesis:
Thesis (Ph.D.)--University of Florida, 2012.
Local:
Adviser: Bolch, Wesley E.
Electronic Access:
RESTRICTED TO UF STUDENTS, STAFF, FACULTY, AND ON-CAMPUS USE UNTIL 2013-12-31
Statement of Responsibility:
by Amir Alexander Bahadori.

Record Information

Source Institution:
UFRGP
Rights Management:
Applicable rights reserved.
Classification:
lcc - LD1780 2012
System ID:
UFE0044848:00001


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1 NASA ASTRONAUT DOSIMETRY: IMPLEMENTATION OF SCALABLE HUMAN PHANTOMS AND BENCHMARK COMPARISONS OF DETERMINISTIC VERSUS MONTE CARLO RADIATION TRANSPORT By AMIR ALEXANDER BAHADORI A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2012

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2 2012 Amir Alexander Bahadori

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3 To my family

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4 ACKNOWLEDGMENTS In addition to representing the culmination of over three years of graduate work, this dissertation serves as a testament to the people who contributed to my education over the first twenty eight years of my life. I owe a great deal of gratitude to my parents, Naser and Michelle, who consistently put me in a position to succeed and encouraged me to always give my best effort. My sisters, Mariam, Elah, and Nadia, each supported me in her own way, and I hope that I have made them as proud of me as I am of them. My grand father, Myron Cailteux, taught me to accomplish as much as I can each day, but that it is alright to leave a little bit of work for tomorrow. My grandmother, Sharon Cailteux, taught me that the best first step to understanding the present is to learn abou t the past. Every member of my family, in America or abroad, named here or not, inspired me to succeed and continues to do so. I have no doubt that a large part of my success is a direct result of early identification and nurturing of my desire to learn. Mrs. Paluka, my kindergarten teacher, and Mrs. Beverly Hodges, the principal of my elementary school, realized that I needed to be academically challenged and encouraged my parents to seek my inclusion in the district gifted program. In high school, I wa s lucky to have teachers who continued to push me; Mrs. Tonya Schuckman and Mr. Robert Hampton took particular interest in ensuring that I was never bored. At Kansas State University, Dr. David Pacey taught me the importance of being organized and clearly communicating results, while the infectious enthusiasm of Dr. Ken Shultis for Nuclear Engineering almost forced me to explore a career in radiation. At the University of Florida, Dr. Wesley Bolch, the chairman of my Master of Science and Doctor of Philoso phy committees, sought to involve me as much as

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5 possible in his research group and encouraged me to explore non traditional research topics in Medical Physics. He allowed me to continue my dissertation work while employed at NASA Johnson Space Center, whi ch provided me with unique opportunities to interface with experts in the field of space radiation and radiation risk. These experts include: Dr. Tatsuhiko Sato, a PHITS developer in Japan, whom I thank for answering innumerable emails regarding PHITS and for his hospitality to my wife and me on our visit; Dr. Martha Clowdsley, Dr. Steve Blattnig, and Dr. Tony Slaba, HZETRN developers at NASA Langley Research Center, whom I thank for meeting me and helping me use HZETRN; vided the Badhwar and Dr. David Pawel, the lead author of the 2011 EPA radiation risk model, whom I thank for helping me understand how to apply his work to the specific needs of NASA. The rest of my Doctor of Philosophy committee also played a vital role in my success; I thank Dr. Michael Delp, Dr. David Hintenlang, Dr. Richard Woodard, Dr. Mark Shavers, and Mrs. Mary Van Baalen for taking the time to serve on my committee. Mr. Mark Langford, the administrator of the NASA Space Radiat ion Analysis Group cluster, helped me greatly by ensuring the computing resources I needed were available. Finally, I especially thank my intelligent, beautiful, and eminently patient wife, Alexandra. She supported me throughout the entire process, from the Doctor of Philosophy qualifying exam through the dissertation defense. Alexandra put up with me sacrificing time that could have been spent with her to work on research and this dissertation. She never lost faith that I would finish what I started, e ven when I doubted. No matter what I achieve, the greatest triumph of my life will always be her love.

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6 TABLE OF CONTENTS page ACKNOWLEDGMENTS ................................ ................................ ................................ .. 4 LIST OF TABLES ................................ ................................ ................................ .......... 10 LIST OF FIGURES ................................ ................................ ................................ ........ 12 LIST OF ABBREVIATIONS ................................ ................................ ........................... 36 ABSTRACT ................................ ................................ ................................ ................... 40 CHAPTER 1 INTRODUCTION ................................ ................................ ................................ .... 42 2 BACKGROU ND AND LITERATURE REVIEW ................................ ....................... 49 NASA Astronaut Phantoms ................................ ................................ ..................... 49 Early Astronaut Representations ................................ ................................ ...... 49 CAM: A Detailed Male Astronaut Representation ................................ ............. 49 Development of CAMERA and Improvements to CAM ................................ .... 51 CAF: A Female Astronaut Phantom ................................ ................................ 52 NASA Space Radiation Transport Methods ................................ ............................ 53 Early Space Radiation Transport Methods ................................ ....................... 53 BRYNTRN and HZETRN ................................ ................................ .................. 53 Recent Updates to HZETRN: HZETRN2010 ................................ .................... 56 Space Radiation Dosimetry ................................ ................................ .................... 59 Dosimetric Calculations ................................ ................................ .................... 59 NASA Space Radiation Limits ................................ ................................ .......... 60 Historical Perspectives of the NASA Space Radiation Risk Posture ................ 61 ................................ ....................... 61 1989 NCRP recommendations ................................ ................................ .. 62 2000 N CRP recommendations ................................ ................................ .. 63 Application of uncertainty analysis to risk estimates ................................ .. 64 Astronaut Dose Evaluation Using Deterministic Transport ................................ ..... 69 Deterministic Dose Evaluations with CAM and CAF ................................ ........ 69 Deterministic Dose Evaluations with MAX and FAX ................................ ......... 72 Monte Carlo Simulation of Space Radiation Transport ................................ ........... 75 Codes Used for Space Radiation Transport ................................ ..................... 75 Three Dimensional Monte Carlo Space Radiation Transport ........................... 77 Summary of Background and Literature Review ................................ ..................... 80 3 RAY TRACING FOR ASTRONAUT DOSIMETRY ................................ ................. 86 Ray Tracing Methods ................................ ................................ .............................. 86

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7 The Voxel Ba sed Ray Tracer ................................ ................................ .................. 86 Implementation of Voxel Based Ray Tracing with Astronaut Phantoms ........... 86 Validation Using Sphere and CAM ................................ ................................ ... 91 University of Florida Hybrid Phantoms ................................ ................................ .... 92 Development of First Version of UF Astronaut Phantoms ................................ ....... 93 Target Anthropometric Data ................................ ................................ ............. 93 Initial Scaling Methods ................................ ................................ ..................... 94 Body Self Shielding Distributions for First Version of UF Astronaut Phantoms ....... 95 Chapter Summary ................................ ................................ ................................ ... 99 4 DETERMINISTIC TRANSPORT AND DOSIMETRY ................................ ............ 109 Space Radiation Environment Models ................................ ................................ .. 109 Geomagnetically Trapped Protons ................................ ................................ 109 Galactic Cosmic Rays ................................ ................................ .................... 110 Solar Part icle Events ................................ ................................ ...................... 110 Deterministic Transport Results ................................ ................................ ............ 111 Geomagnetically Trapped Protons ................................ ................................ 111 Galactic Cosmic Rays ................................ ................................ .................... 112 Solar Part icle Events ................................ ................................ ...................... 112 Organ Dose Equivalent Results for First Version of UF Astronaut Phantoms ....... 113 Chapter Summary ................................ ................................ ................................ 115 5 EFFECT OF ANATOMICAL MODELING ON SPACE RADIATION DOSE ESTIMATES ................................ ................................ ................................ ......... 128 Changes to Phantoms for Comparison ................................ ................................ 128 Updated Anthropometric Parameters ................................ ............................. 128 Uniform Scaling Procedure ................................ ................................ ............. 129 Dosime try with Updated Phantoms ................................ ................................ ....... 129 Body Self Shielding Distributions ................................ ................................ ... 130 Organ Dosimetry ................................ ................................ ............................ 131 Effective Dose Results ................................ ................................ ................... 134 Chapter Summary ................................ ................................ ................................ 135 6 DOSIMETRIC IMPACTS OF MICROGRAVITY ................................ .................... 157 Microgravity Induced Body Changes ................................ ................................ .... 157 Application of Microgravity Induced Body Changes to UF Hybrid Phantoms ........ 158 Dosimetry with Microgravity Phantoms ................................ ................................ 160 Body Self Shielding Distributions ................................ ................................ ... 160 Microgravity Phantom Dosimetry ................................ ................................ .... 161 Organ dose equivalent results ................................ ................................ 161 Co mparison with Earth based phantoms ................................ ................. 162 Implications for space dosimetry ................................ .............................. 163 Applicability to exploratory missions ................................ ........................ 164 Effective Dose Results ................................ ................................ ................... 165

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8 Chapter Summary ................................ ................................ ................................ 166 7 COMPARISON OF RISK ESTIMATES USING PHITS AND HZETRN ................. 185 HZETRN2010 Transport ................................ ................................ ....................... 185 Spectral Input ................................ ................................ ................................ 185 HZETRN2010 Modules and Post Processing ................................ ................ 186 PHITS 2.30 Transport ................................ ................................ ........................... 187 PHITS Input File Structure ................................ ................................ .............. 188 Parameters section ................................ ................................ .................. 188 Source section ................................ ................................ ......................... 191 Materials and ge ometry set up ................................ ................................ 192 Tally sections ................................ ................................ ........................... 193 PHITS Parallel Mode ................................ ................................ ...................... 194 PHITS Post Processing ................................ ................................ .................. 195 Determining Radiogenic Cancer Mortality Risk ................................ ..................... 196 Measures o f Radiogenic Cancer Mortality Risk ................................ .............. 196 US EPA Radiogenic Cancer Risk Model ................................ ........................ 198 Justification for use of US EPA model ................................ ..................... 198 Novel method for determining breast cancer REID ................................ .. 199 Benchmarking MATLAB code of US EPA model ................................ ............ 201 Organ Dosimetry Results from HZETRN2010 and PHITS 2.30 ............................ 202 SPE and Trapped Spectrum Organ Dosimetry ................................ ............... 203 GCR Organ Dosimetry ................................ ................................ ................... 204 Organ Differential Energy Flux Comparison ................................ ................... 204 Effective Dose and REID Results ................................ ................................ ......... 205 Chapter Summary ................................ ................................ ................................ 207 8 CONCLUSION ................................ ................................ ................................ ...... 229 Need for the Present Study ................................ ................................ ................... 229 Findings ................................ ................................ ................................ ................ 230 Limitations ................................ ................................ ................................ ............. 236 Future Work ................................ ................................ ................................ .......... 237 APPENDIX A RAY TRACING DIRECTION COSINES ................................ ................................ 239 B MEVDP RAY SELECTION ................................ ................................ ................... 25 4 C VOBRAT SOURCE CODE ................................ ................................ ................... 256 D INITIAL BODY SELF SHIE LDING DISTRIBUTIONS ................................ ............ 370 E INITIAL ORGAN DOSE EQUIVALENTS ................................ .............................. 400 F EARTH BASED BODY SELF SHIELDING DISTRIBUTIONS .............................. 424

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9 G EARTH BASED ORGAN DOSE EQUIVALENT RESULTS ................................ .. 438 H EARTH BASED FRACTIONAL DIFFERENCE ................................ ..................... 453 I MICROGRAVITY BODY SELF SHIELDING DISTRIBUTIONS ............................ 468 J MICROGRAVITY ORGAN DOSE EQUIVALENT RESULTS ................................ 482 K MICROGRAVITY FRACTIONAL DIFFERENCE (VS. 50 th PCTL) ........................ 497 L MICROGRAVITY FRACTIONAL DIFFERENCE (VS. EARTH BASED) ............... 512 M HZETRN MATLAB INTERPOLATION CODES ................................ .................... 527 N EXAMPLE PHITS INPUT FILE ................................ ................................ ............. 534 O PHITS USER SOURCE DEFINITION ................................ ................................ ... 567 P PHITS POST PROCESSING MATLAB CODE ................................ ..................... 570 Q US EPA REID MATLAB CODE ................................ ................................ ............ 581 R PHITS AND HZETRN ORGAN ABSORBED DOSES (PHITS VS. HZETRN) ....... 608 S PHITS AND HZETRN ORGAN DOSE EQUIVALENT VALUES ........................... 623 T PHITS AND HZETRN ORGAN ABSORBED DOSE PERCENT DIFFERENCES 638 U PHITS AND HZETRN ORGAN DOSE EQUIVALENT PERCENT DIFFERENCES ................................ ................................ ................................ .... 653 V PHITS AND HZETRN REID COMPARISON ................................ ........................ 668 LIST OF REFERENCES ................................ ................................ ............................. 674 BIOGRAPHICAL SKETCH ................................ ................................ .......................... 683

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10 LIST OF TABLES Table page 2 1 Quality factor d efinition ................................ ................................ ....................... 85 2 2 Dose limits fo r non cancer e ffects ................................ ................................ ...... 85 2 3 Career effective dose limits derived from risk limit ................................ .............. 85 3 1 Sele cted anthropometric data ................................ ................................ ........... 108 4 1 Relative abundances of ions comprising G CR at three energies ...................... 122 4 2 Organ dose equivalents (Sv) August 1972 SPE with suit shielding .................. 122 4 3 GCR organ dose equivalent rates (mSv d 1 ) with PV shielding ......................... 124 4 4 February 1956 SPE organ dose equivalents with shelter shielding .................. 125 5 1 Phantom targ et statures and masses ................................ ............................... 153 5 2 Phantom scaling factors with respect to NASA MSIS 50 th PCTL ...................... 153 5 3 Quality factors for February 1956 SPE radiation environment with suit shielding (Earth based anthropometrics) ................................ .......................... 154 5 4 Quality factors for GCR radiation environment with PV shielding (Earth based anthropometrics) ................................ ................................ .................... 155 5 5 Quality factors for August 1972 SPE radiation environment with shelter shielding (Earth based anthropometrics) ................................ .......................... 156 5 6 Tissue weighting factors ................................ ................................ ................... 156 6 1 Implementa tion of microgravity induced changes ................................ ............. 181 6 2 Earth and microgravity based phantom mass comparison .............................. 181 6 3 Quality factors for February 1956 SPE radiation environment with suit shielding (microgravity based anthropometrics) ................................ ............... 182 6 4 Quality factors for GCR radiation environment with PV shielding (microgravity based anthropometrics) ................................ .............................. 183 6 5 Quality factors for August 1972 SPE radiation environment with shelter shielding (microgravity based anthropometrics) ................................ ............... 184 7 1 Elements comprising each GCR ion group ................................ ....................... 226

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11 7 2 PHITS parameters affecting transport or tallies chosen for the present study .. 226 7 3 Constants defined in PHITS inp ut file ................................ ............................... 226 7 4 Published results (EPA 2011) for females (LAR per 10 5 person Gy) ................ 227 7 5 EPA model MATLAB code results for females (REID per 10 5 person Gy) ....... 227 7 6 Published results (EPA 2011) for males (LAR per 10 5 person Gy) ................... 228 7 7 EPA model MATLAB code results for males (REID per 10 5 person Gy) .......... 228 A 1 Direction cosines used for ray tracing ................................ ............................... 239 E 1 Trapped proton organ dose equivalent rates (mSv d 1 ) with suit shielding ....... 400 E 2 GCR organ dose equivalent rates (mSv d 1 ) with suit shielding ........................ 401 E 3 February 1956 SPE organ dose equivalents (Sv) with suit shielding ................ 403 E 4 October 1989 SPE organ dose equivalents (Sv) with suit shielding ................. 404 E 5 August 1972 SPE organ dose equivalents (Sv) with suit shielding ................... 406 E 6 Trapped proton organ dose equivalent rates (mSv d 1 ) with PV shielding ........ 408 E 7 GCR organ do se equivalent rates (mSv d 1 ) with PV shielding ......................... 409 E 8 February 1956 SPE organ dose equivalents (Sv) with PV shielding ................ 411 E 9 October 1989 SPE organ dose equivalents (Sv) with PV shielding .................. 412 E 10 August 1972 SPE organ dose equivalents (Sv) with PV shielding .................... 414 E 11 Trapped proton organ dose equivalent rates (mSv d 1 ) with shelter shielding .. 415 E 12 GCR organ dose equivalent rates (mSv d 1 ) with shelter shielding ................... 417 E 13 February 1956 SPE organ dose equivalents (Sv) with shelter shielding .......... 419 E 14 October 198 9 SPE organ dose equivalents (Sv) with shelter shielding ............ 420 E 15 August 1972 SPE organ dose equivalents (Sv) with shelter shielding .............. 422

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12 LIST OF FIGURES Figure page 2 1 Early astronaut phantom ................................ ................................ .................... 83 2 2 Full body view of CAM ................................ ................................ ........................ 83 2 3 Vi ew of CAM head and shoulders ................................ ................................ ...... 84 2 4 Equivalence of mono directional slab irradiation and isotropic irradiation through spherical geometries for a dose point ................................ .................... 84 3 1 Determining the amount of material separating a source point and a dose point in a collection of arbitrary regions ................................ ............................ 100 3 2 Comparison of CAMERA output and VoBRaT output for right eye lens dose point in CAM ................................ ................................ ................................ ..... 100 3 3 Comparison of CAMERA output and VoBRaT output for heart dose point in CAM ................................ ................................ ................................ ................. 101 3 4 CAM phantom external view CA M phantom internal view UF h ybrid adult male phantom ................................ ................................ ................................ ... 101 3 5 UF hybrid adult male 5 th PCTL 50 th PCTL and 95 th PCTL phantoms .............. 102 3 6 UF hybrid adult female 5 th PCTL 50 th PCTL and 95 th PCTL phantoms ........... 102 3 7 Right testis body self shielding distributions ................................ ..................... 103 3 8 Right ovary body self shielding distributions ................................ ..................... 103 3 9 Rectosigmoid colon body self shielding distributions ................................ ........ 104 3 10 Right breast body self shielding distributions ................................ ................... 104 3 11 BFO body self shielding distributions with 35 random dose points ................... 105 3 12 Skin body self shielding distributions with 35 random dose points ................... 105 3 13 Right eye lens body self shielding distributions ................................ ................ 106 3 14 BFO body self shielding distributions with 1000 random dose points ............... 106 3 15 Skin body self shielding distributions with 1000 random dose points ............... 107 4 1 Trapped proton spectrum for altitude of 351.5 km and orbital inclination of 51.6 degrees at solar minimum ................................ ................................ ........ 117

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13 4 2 Free space GCR energy spectra (selected elements) for 1977 solar minimum ................................ ................................ ................................ ........... 117 4 3 SPE spectra for three large historic events ................................ ...................... 118 4 4 Dose equivalent rate as a function of aluminum and water thickness for trapped proton spectrum ................................ ................................ .................. 118 4 5 Dose equivalent rate as a function of aluminum and water thickness for GCR spectrum ................................ ................................ ................................ .. 1 19 4 6 Dose equivalent as a function of aluminum an d water thickness for February 1956 SPE proton spectrum ................................ ............................... 119 4 7 Dose equivalent as a function of aluminum and water thickness for Oc tober 1989 SPE proton spectrum ................................ ................................ .............. 120 4 8 Dose equivalent as a function of aluminum and water thickness for August 1972 SPE proton spe ctrum ................................ ................................ .............. 120 4 9 Testes body self shielding distributions with 500 random dose points ............. 121 4 10 Eye lenses body self shielding distributions with all eye lens voxels ................ 121 5 1 Comparison of phantom statures from NASA MSIS and Radiation Health Office ................................ ................................ ................................ ................ 137 5 2 Comparison of phantom masses from NASA MSIS and Radiation Health Office ................................ ................................ ................................ ................ 137 5 3 Testes body self shielding distributions (Earth base d anthropometrics) ........... 138 5 4 Ovaries body self shielding distributions (Earth based anthropometrics) ......... 138 5 5 Colon body self shielding distributions (Earth based anthropometrics) ............ 139 5 6 Breasts body self shielding distributions (Earth based anthropometrics) ......... 139 5 7 BFO body self shielding distributions (Earth based anthropometrics) .............. 140 5 8 Skin body self shielding distributions (Earth based anthropometrics) .............. 140 5 9 Eye lenses body self shielding distributions (Earth based anthropometrics) .... 141 5 10 Trapped proton male and female organ dose equivalent rate s for PV shielding (Earth based anthropometrics) ................................ .......................... 142 5 11 GCR male and female organ dose equivalent rates for PV shielding (Earth b ased anthropometrics) ................................ ................................ .................... 143

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14 5 12 August 1972 SPE male and female organ dose equivalents for suit shielding (Earth based anthropometric s) ................................ .......................... 144 5 13 August 1972 SPE male and female organ dose equivalents for shelter shielding (Earth based anthropometrics) ................................ .......................... 145 5 14 Trapped proton male and female fractional differences for PV shielding (Earth based anthropometrics) ................................ ................................ ......... 146 5 15 GCR male and female fractional differences for PV shielding (Earth based anthropometrics) ................................ ................................ ............................... 147 5 16 August 1972 SPE male and female fractional differences for suit shielding (Earth based anthropometrics) ................................ ................................ ......... 148 5 17 August 1972 SPE male and female fractional differences for shelter shielding (Earth based anthropometrics) ................................ .......................... 149 5 18 Trapped proton effective dose rates (Earth based anthropometrics) ................ 150 5 19 GCR effective dose rates (Earth based anthropometrics) ................................ 150 5 20 February 1956 SPE effective doses (Earth based anthropometrics) ................ 151 5 21 October 1989 SPE effective doses (Earth based anthropometrics) ................. 151 5 22 August 1972 SPE effective doses (Earth based anthropometrics) ................... 152 6 1 Neutral body posture ................................ ................................ ........................ 167 6 2 Male microgravity based phantoms at the 5 th 50 th and 95 th height and weight percentiles ................................ ................................ ............................. 168 6 3 Female microgravity based phantoms at the 5 th 50 th and 95 th height and weight percentiles ................................ ................................ ............................. 169 6 4 Trapped proton male and female organ dose equivalent rates for PV shielding (microgravity based anthropometrics) ................................ ............... 170 6 5 GCR male and female organ dose equivalent rates for PV shielding (microgravity based anthropometrics) ................................ .............................. 171 6 6 August 1972 SPE male and female organ dose equivalents for suit shielding (microgravity based anthropometrics) ................................ ............... 172 6 7 August 1972 SPE male and female organ dose equivalents for shelter shielding (microgravity based anthropometrics) ................................ ............... 173

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15 6 8 Trapped proton male and female microgravity fractional differences for PV shielding (comparison with Earth based values) ................................ .............. 174 6 9 GCR male and female microgravity fractional differences for PV shielding (comparison with Earth based values) ................................ ............................. 175 6 10 August 1972 SPE male and female microgravity fractional differences for suit shielding (comparison with Earth based values) ................................ ........ 176 6 11 August 1972 SPE male and female microgravity fractional differences for shelter shielding (comparison with Earth based values) ................................ ... 177 6 12 Trapped proton effective dose rates (Earth based vs. microgravity based) ..... 178 6 13 GCR effective dose rates (Earth based vs. microgravity based) ...................... 178 6 14 February 1956 SPE effective doses (Earth based vs. microgravity based) ...... 179 6 15 October 1989 SPE effective doses (Earth based vs. microgravity based) ....... 179 6 16 Aug ust 1972 SPE effective doses (Earth based vs. microgravity based) ......... 180 7 1 Male organ dose equivalent and associated percent differences for August 1972 SPE irradiation with shelter geometry ................................ ...................... 209 7 2 Male organ dose equivalent and associa ted percent differences for trapped irradiation with PV geometry ................................ ................................ ............. 210 7 3 Male organ dose equivalent and associated percent differen ces for February 1956 SPE irradiation with PV geometry ................................ ............ 211 7 4 Male organ dose equivalent and associated percent differences for GCR proton irradiation with PV geometry ................................ ................................ .. 212 7 5 Male organ dose equivalent and associated percen t differences for GCR alpha irradiation with PV geometry ................................ ................................ ... 213 7 6 Male organ dose equivalent and associated percent differences for GCR iron with PV geometry ................................ ................................ ...................... 214 7 7 PV GCR proton irradiation pro ton flux comparison for male skin and BFO ...... 215 7 8 PV GCR alpha irradiation al pha flux comparison for male skin and BFO ......... 216 7 9 PV GCR alpha irradiation helion flux comparison for male BFO ...................... 217 7 10 PV GCR alpha irradiation triton flux comparison for male BFO ........................ 217 7 11 PV GCR alpha irradiation deuteron flux comparison for male BFO .................. 218

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16 7 12 PV GCR alpha irradiation proton flux comparison for male BFO ...................... 218 7 13 SPE effective doses calculated with HZETRN2010 and PHITS 2.30 ............... 219 7 14 SPE effective dose percent differences (HZETRN2010 v. PHITS 2.30) ........... 219 7 15 Free space 1977 solar minimum GCR primary ion effe ctive dose contributions for male and female ................................ ................................ ..... 220 7 16 Percent differences in free space 1977 solar minimum GCR primary ion effective dose rate contributions for male and female ................................ ...... 221 7 17 GCR primary ion contributions to total effective dose rate ................................ 222 7 18 GCR and trapped environment e ffective dose rates calculated with HZETRN2010 and PHITS 2.30 ................................ ................................ ......... 222 7 19 GCR and trapped environment effective dose rate percent diffe rences (HZETRN2010 vs. PHITS 2.30) ................................ ................................ ........ 223 7 20 REID values for August 1972 SPE with suit shielding ................................ ...... 223 7 21 Percent differences in REID values for August 1972 SPE with suit shielding ... 224 7 22 REID values for GCR with PV shielding ................................ ........................... 224 7 23 Percent differences in REID val ues for GCR with PV shielding ........................ 225 D 1 BFO initial body self shielding distributions using 1000 randomly selected points ................................ ................................ ................................ ................ 370 D 2 Skin initial body self shielding distributions using 1000 radomly selected points ................................ ................................ ................................ ................ 370 D 3 Small intestines initial body self shielding distributions using 500 radomly selected points ................................ ................................ ................................ .. 371 D 4 Muscle initial body self shielding distributions using 1000 radomly selected points ................................ ................................ ................................ ................ 371 D 5 Right eye lens initial body self shielding distributions ................................ ....... 372 D 6 Left eye lens initial body self shielding distributions ................................ .......... 372 D 7 Right eyeball initial body self sh ielding distributions ................................ ......... 373 D 8 Left eyeball initial body self shielding distributions ................................ ............ 373 D 9 Anterior stomach initial body self shielding distributions ................................ ... 374

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17 D 10 Posterior stomach initial body self shielding distributions ................................ 374 D 11 Ascending colon initial body self shielding distributions ................................ .... 375 D 12 Transverse colon initial body self shielding distributions ................................ .. 375 D 13 Descending colon initial body self shielding distributions ................................ 376 D 14 Rectosigmoid colon initial body self shielding distributions ............................... 376 D 15 Left liver initial body self shielding distributions ................................ ................ 377 D 16 Right liver initial body self shielding distributions ................................ .............. 377 D 17 Right upper mid lung initial body self shielding distributions ............................. 378 D 18 Left upper mid lung initial body self shielding distributions ............................... 378 D 19 Right middle anterior lung initial body self shielding distributions ..................... 37 9 D 20 Right middle mid lung initial body self shielding distributions ........................... 379 D 21 Right middl e posterior lung initial body self shielding distributions ................... 380 D 22 Left middle anterior lung initial body self shielding distributions ........................ 380 D 23 Left middle mid lung initial body self shielding distributions .............................. 381 D 24 Left middle posterior lung initial body self shielding distributions ...................... 381 D 25 Right base anterior lung initial body self shielding distributions ........................ 382 D 26 Right base posterior lung initial body self shielding distributions ...................... 382 D 27 Left base anterior lung initial body self shielding distributions .......................... 383 D 28 Left base posterior lung initial body self shielding distributions ........................ 383 D 29 Esophagus initial body self shielding distributions ................................ ............ 384 D 30 Bladder initial body self shielding distributions ................................ ................. 384 D 31 Left thyroid initial body self shielding distributions ................................ ............ 385 D 32 Right thyroid initial body self shielding distributions ................................ .......... 385 D 33 Anterior brain initial body self shielding distributions ................................ ........ 386 D 34 Mid brain initial body self shielding distributions ................................ ............... 386

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18 D 35 Posterior brain initial body self s hielding distributions ................................ ....... 387 D 36 Left parotid initial body self shielding distributions ................................ ............ 387 D 37 Right parotid initial body self shielding distributions ................................ .......... 388 D 38 Left adrenal initial body self shielding distributions ................................ ........... 388 D 39 Right adrenal initial body self shielding distributions ................................ ......... 389 D 40 ET region initial body self shielding distributions ................................ .............. 389 D 41 Gallbladder initial body self shielding distributions ................................ ............ 390 D 42 Heart initial body self shielding distributions ................................ ..................... 390 D 43 Left kidney initial body self shielding distributions ................................ ............. 391 D 44 Right kidney initial body self shielding distributions ................................ .......... 391 D 45 Lateral pancreas initial body self shielding distributions ................................ ... 392 D 46 Mid pancreas initial body self shielding distributions ................................ ........ 392 D 47 Medial pancreas initial body self shielding distributions ................................ .... 393 D 48 Spleen initial body self shielding distributions ................................ ................... 393 D 49 Left thymus initial body self shielding distributions ................................ ........... 394 D 50 Right thymus initial body self shielding distributions ................................ ......... 394 D 51 Oral mucosa initial body self shielding distributions ................................ .......... 395 D 52 Left testis initial body self shielding distributions ................................ ............... 395 D 53 Right testis initial body self shielding distributions ................................ ............ 396 D 54 Prostate initial body self shielding distributions ................................ ................. 396 D 55 Left ovary initial body self shielding distributions ................................ .............. 397 D 56 Right ovary initial body self shielding d istributions ................................ ............ 397 D 57 Uterus initial body self shielding distributions ................................ ................... 398 D 58 Left breast initial body self shielding distributions ................................ ............. 398 D 59 Right breast initial body self shielding distributions ................................ ........... 399

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19 F 1 Earth based eye lenses body self shielding distributions ................................ 424 F 2 Earth based BFO body self shielding distributions ................................ ........... 424 F 3 Earth based colon body self shielding distributions ................................ .......... 425 F 4 Earth based lung body self shielding distributions ................................ ............ 425 F 5 Earth based stomach body self shielding distributions ................................ ..... 426 F 6 Earth based breasts body self shielding distributions ................................ ....... 426 F 7 Earth based ovaries body self shielding distributions ................................ ....... 427 F 8 Earth based testes body self shielding distributions ................................ ......... 427 F 9 Earth based bladder body self shielding distributions ................................ ...... 428 F 10 Earth based esophagus body self shielding distributions ................................ 428 F 11 Earth based liver body self shielding distributions ................................ ............ 429 F 12 Earth based thyroid body self shielding distributions ................................ ........ 429 F 13 Earth based brain body self shielding distributions ................................ .......... 430 F 14 Earth based salivary glands body self shielding distributions ........................... 430 F 15 Earth based skin body self shielding distributions ................................ ............ 431 F 16 Earth based adrenals body self shielding distributions ................................ ..... 431 F 17 Earth based ET region body self shielding distributions ................................ ... 432 F 18 Earth based gallbladder body self shielding distributions ................................ 432 F 19 Earth based heart body self shielding distributions ................................ .......... 433 F 20 Earth based kidneys body self shielding distributions ................................ ...... 433 F 21 Earth based muscle body self shielding distributions ................................ ....... 434 F 22 Earth based oral mucosa body self shielding distributions ............................... 434 F 23 Earth based pancreas body self shielding distributions ................................ .... 435 F 24 Earth based prostate body self shielding distributions ................................ ..... 435 F 25 Earth based small intestines body self shielding distributions .......................... 436

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20 F 26 Earth based spleen body self shielding distributions ................................ ........ 436 F 27 Earth based thymus body self shielding distributions ................................ ....... 437 F 28 Earth based uterus body self shielding distributions ................................ ........ 437 G 1 Male suit trapped proton Earth based organ dose equivalent rates ................. 438 G 2 Female suit trapped proton Earth based organ dose equivalent rates ............. 438 G 3 Male suit GCR Earth based organ dose equivalent rates ................................ 439 G 4 Female suit GCR Earth base d organ dose equivalent rates ............................ 439 G 5 Male suit February 1956 SPE Earth based organ dose equivalents ................ 440 G 6 Female suit February 1956 SPE Earth based organ dose equivalents ............ 440 G 7 Male suit October 1989 SPE Earth based organ dose equivalents .................. 441 G 8 Female suit October 1989 SPE Earth based organ dose equivalents .............. 441 G 9 Male suit August 1972 SPE Earth based organ dose equivalents .................... 442 G 10 Female suit August 1972 SPE Earth based organ dose equivalents ............... 442 G 11 Male PV trapped proton Earth based organ dose equivalent rates .................. 443 G 12 Female PV trapped proton Earth based organ dose equivalent rates .............. 443 G 13 Male PV GCR Earth based organ dose equivalent rates ................................ 444 G 14 Female PV GCR Earth based organ dose equivalent rates ............................. 444 G 15 Male PV February 1956 SPE Earth based organ dose equivalents ................. 445 G 16 Female PV February 1956 SPE Earth based organ dose equivalents ............. 445 G 17 Male PV October 1989 SPE Earth based organ dose equivalents ................... 446 G 18 Female PV October 198 9 SPE Earth based organ dose equivalents ............... 446 G 19 Male PV August 1972 SPE Earth based organ dose equivalents .................... 447 G 20 Female PV August 1972 SPE Earth based organ dose equivalents ................ 447 G 21 Male shelter trapped proton Earth based organ dose equivalent rates ............ 448 G 22 Female shelter trapped proton Earth based organ dose equivalent rates ........ 448

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21 G 23 Male shelter GCR Earth based organ dose equivalent rates ........................... 449 G 24 Female shelter GCR Earth based organ dose equivalent rates ....................... 449 G 25 Male shelter February 1956 SP E Earth based organ dose equivalents ........... 450 G 26 Female shelter February 1956 SPE Earth based organ dose equivalents ....... 450 G 27 Male shelter October 1989 SPE Earth based organ dose equivalents ............. 451 G 28 Female shelter October 1989 SPE Earth based organ dose equivalents ......... 451 G 29 Male shelter August 1972 SPE Earth based organ dose equivalents .............. 452 G 30 Female shelter August 1972 SPE Earth based organ dose equivalents .......... 452 H 1 Male suit trapped proton Earth based organ dose equivalent fractional difference ................................ ................................ ................................ .......... 453 H 2 Female suit trapped proton Earth based organ dose equivalent fractional difference ................................ ................................ ................................ .......... 453 H 3 Male suit GCR Earth based organ dose equivalent fractional difference ......... 454 H 4 Female suit GCR Eart h based organ dose equivalent fractional difference ..... 454 H 5 Male suit February 1956 SPE Earth based organ dose equivalent fractional ... 455 H 6 Female suit February 1956 SPE Earth based organ dose equivalent fractional difference ................................ ................................ .......................... 455 H 7 Male suit October 1989 SPE Earth based organ dose equivalent fractional difference ................................ ................................ ................................ .......... 456 H 8 Female suit October 1989 SPE Earth based organ dose equivalent fractional difference ................................ ................................ .......................... 456 H 9 Male suit August 1972 SPE Earth based organ dose equivalent fractional difference ................................ ................................ ................................ .......... 457 H 10 Female suit August 1972 SPE Earth based organ dose equivalent fractional difference ................................ ................................ ................................ .......... 457 H 11 Male PV trapped proton Earth based organ dose equivalent fractional difference ................................ ................................ ................................ .......... 458 H 12 Female PV trapped proton Earth based organ dose equivalent fractional difference ................................ ................................ ................................ .......... 458

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22 H 13 Male PV GCR Earth based organ dose equivalent fractional difference .......... 459 H 14 Female PV GCR Earth based organ dose equivalent fractional difference ...... 459 H 15 Male PV February 1956 SPE Earth based organ dose equivalent fractional difference ................................ ................................ ................................ .......... 460 H 16 Female PV February 1956 SPE Earth based organ dose equivalent fractional difference ................................ ................................ .......................... 460 H 17 Male PV October 1989 SPE Earth based organ dose equivalent fractional difference ................................ ................................ ................................ .......... 461 H 18 Female PV October 1989 SPE Earth based organ dose equivalent fracti onal difference ................................ ................................ .......................... 461 H 19 Male PV August 1972 SPE Earth based organ dose equivalent fractional difference ................................ ................................ ................................ .......... 462 H 20 Female PV August 1972 SPE Earth based organ dose equivalent fractional difference ................................ ................................ ................................ .......... 462 H 21 Male shelter trapped proton Earth based organ dose equivalent fractional difference ................................ ................................ ................................ .......... 463 H 22 Female shelter trapped proton Earth based organ dose equivalent fractional difference ................................ ................................ ................................ .......... 463 H 23 Male shelter GCR Earth based organ dose equivalent fractional difference .... 464 H 24 Female shelter GCR Earth based organ dose equivalent fractional difference ................................ ................................ ................................ .......... 464 H 25 Male shelter February 1956 SPE Earth based organ dose equivalent fr actional difference ................................ ................................ .......................... 465 H 26 Female shelter February 1956 SPE Earth based organ dose equivalent fractional difference ................................ ................................ .......................... 465 H 27 Male shelter October 1989 SPE Earth based organ dose equivalent fractional difference ................................ ................................ .......................... 466 H 28 Female shelter October 1989 SPE Earth based organ dose equivalent fractional difference ................................ ................................ .......................... 466 H 29 Male shelter August 1972 SPE Earth based organ dose equivalent fractional difference ................................ ................................ .......................... 467

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23 H 30 Female shelter August 1972 SPE organ dose equivalent fractional difference ................................ ................................ ................................ .......... 467 I 1 Microgravity eye lenses body self shielding distributions ................................ 468 I 2 Microgravity BFO body self shielding distributions ................................ ........... 468 I 3 Microgravity colon body self shielding distributions ................................ .......... 469 I 4 Microgravity lungs body self shielding distributions ................................ .......... 469 I 5 Microgravity stomach body self shielding distributions ................................ ..... 470 I 6 Microgravity breasts body self shielding distributions ................................ ....... 470 I 7 Microgravity ovaries body self shielding distributions ................................ ....... 471 I 8 Microgravity testes body self shielding distributions ................................ ......... 471 I 9 Microgravity bladder body self shielding distributions ................................ ....... 472 I 10 Microgravity esophagus body self shielding distributions ................................ 472 I 11 Microgravity liver body self shielding distributions ................................ ............ 473 I 12 Microgravity thyroid body self shielding distributions ................................ ........ 473 I 13 Microgravity brain body self shielding distributions ................................ ........... 474 I 14 Microgravity salivary glands body self shielding distributions ........................... 474 I 15 Microgravity skin body self shielding distributions ................................ ............ 475 I 16 Microgravity adrenals body self shielding distributions ................................ ..... 475 I 17 Microgravity ET region body self shielding distributions ................................ ... 476 I 18 Microgravity gallbladder body self shielding distributions ................................ 476 I 19 Microgravity heart body self shielding distributions ................................ .......... 477 I 20 Microgravity kidneys body self shielding distributions ................................ ...... 477 I 21 Microgravity muscle body self shieldi ng distributions ................................ ....... 478 I 22 Microgravity oral mucosa body self shielding distributions ............................... 478 I 23 Microgravity pancreas body self shielding distributions ................................ .... 479 I 24 Microgravity prostate body self shielding distributions ................................ ...... 479

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24 I 25 Microgravity small intestines body self shielding distributions .......................... 480 I 26 Microgravity spleen body self shielding distributions ................................ ........ 480 I 27 Microgravity thymus body self shielding distributions ................................ ....... 481 I 28 Microgravity uterus body self shielding distributions ................................ ......... 481 J 1 Male suit trapped proton microgravity organ dose equivalent rates .................. 482 J 2 Female suit trapped proton microgravity organ dose equivalent rates ............. 482 J 3 Male suit GCR microgravity organ dose equivalent rates ................................ 483 J 4 Female suit GCR microgravity organ dose equivalent rates ............................. 483 J 5 Male suit February 1956 SPE microgravity organ dose equivalents ................. 484 J 6 Female suit February 1956 SPE microgravity organ dose equivalents ............ 484 J 7 Male suit October 1989 SPE microgravity organ dose equivalents .................. 485 J 8 Female suit October 1989 SPE microgravity organ dose equivalents .............. 485 J 9 Male suit August 1972 SPE microgravity organ dose equivalents .................... 486 J 10 Female suit August 1972 SPE microgravity organ dose equivalents ................ 486 J 11 Male PV trapped proton microgravity organ dose equivalent rates .................. 487 J 12 Female PV trapped proton microgravity organ dose equivalent rates .............. 487 J 13 Male PV GCR microgravity organ dose equivalent rates ................................ .. 488 J 14 Female PV GCR microgravit y organ dose equivalent rates ............................. 488 J 15 Male PV February 1956 SPE microgravity organ dose equivalents ................. 4 89 J 16 Female PV February 1956 SPE microgravity organ dose equivalents ............. 489 J 17 Male PV October 1989 SPE microgravity organ dose equivalents ................... 490 J 18 Female PV October 1989 SPE microgravity organ dose equivalents ............... 490 J 19 Male PV August 1972 SPE microgravity organ dose equivalents ..................... 491 J 20 Female PV August 1972 SPE microgravity organ dose equivalents ................ 491 J 21 Male shelter trapped proton microgravity organ dose equivalent rates ............ 492

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25 J 22 Female shelter trapped proton microgravity organ dose equivalent rates ........ 492 J 23 Male shelter GCR microgravity organ dose equiva lent rates ............................ 493 J 24 Female shelter GCR microgravity organ dose equivalent rates ....................... 493 J 25 Male shelter February 1956 SPE microgravity organ dose equivalents ........... 494 J 26 Female shelter February 1956 SPE microgravity organ dose equivalents ....... 494 J 27 Male shelter October 1989 SPE microgravity organ dose equivalents ............. 495 J 28 Female sh elter October 1989 SPE microgravity organ dose equivalents ......... 495 J 29 Male shelter August 1972 SPE microgravity organ dose equivalents ............... 496 J 30 Female shelter August 1972 SPE microgravity organ dose equivalents .......... 496 K 1 Male suit trapped proton microgravity organ dose equivalent fractional difference vs. 50 th PCTL ................................ ................................ ................... 497 K 2 Female suit trapped proton microgravity organ dose equivalent fractional difference vs. 50 th PCTL ................................ ................................ ................... 497 K 3 Male suit GCR microgravity organ dose equivalent fractional difference vs. 50 th PCTL ................................ ................................ ................................ ......... 498 K 4 Female suit GCR microgravity organ dose equivalent fractional difference vs. 50 th PCTL ................................ ................................ ................................ .... 498 K 5 Male suit February 1956 SPE microgravity organ dose equivalent fractional difference vs. 50 th PCTL ................................ ................................ ................... 499 K 6 Female suit February 1956 SPE microgravity organ dose equivalent fractional difference vs. 50 th PCTL ................................ ................................ .... 499 K 7 Male suit Octo ber 1989 SPE microgravity organ dose equivalent fractional difference vs. 50 th PCTL ................................ ................................ ................... 500 K 8 Female suit October 1989 SPE microgravity organ dose equivalent fractional difference vs. 50 th PCTL ................................ ................................ .... 500 K 9 Male suit August 1972 SPE microgravity organ dose eq uivalent fractional difference vs. 50 th PCTL ................................ ................................ ................... 501 K 10 Female suit August 1972 SPE microgravity organ dose equivalent fractional dif ference vs. 50 th PCTL ................................ ................................ ................... 501

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26 K 11 Male PV trapped proton microgravity organ dose equivalent fractional difference vs. 50 th PCTL ................................ ................................ ................... 502 K 12 Female PV trapped proton microgravity organ dose equivalent fractional difference vs. 50 th PCTL ................................ ................................ ................... 502 K 13 Male PV GCR microgravity organ dose equivalent fractional difference vs. 50 th PCTL ................................ ................................ ................................ ......... 503 K 14 Female PV GCR microgravity organ dose equivalent fractional difference vs. 50 th PCTL ................................ ................................ ................................ .... 503 K 15 Male PV February 1956 SPE microgravity organ dose equivalent fractional difference vs. 50 th PCTL ................................ ................................ ................... 504 K 16 Female PV February 1956 SPE microgravity organ dose equivalent fractional difference vs. 50 th PCTL ................................ ................................ .... 504 K 17 Male PV October 1989 SPE microgravity organ dose equivalent fractional difference vs. 50 th PCTL ................................ ................................ ................... 505 K 18 Female PV October 1989 SPE microgravity organ dose equivalent fractional difference vs. 50 th PCTL ................................ ................................ .... 505 K 19 Male PV August 1972 SPE microgravity organ dose equivalent fractional difference vs. 50 th PCTL ................................ ................................ ................... 506 K 20 Female PV August 1972 SPE microgravity organ dose equivalent fractional difference vs. 50 th PCTL ................................ ................................ ................... 506 K 21 Male shelter trapped proton microgravity organ dose equivalent fractional difference vs. 50 th PCTL ................................ ................................ ................... 507 K 22 Female shelter trapped proton microgravity organ dose equivalent fractional difference vs. 50 th PCTL ................................ ................................ ................... 507 K 23 Male shelter GCR microgravity organ dose equivalent fractional difference vs. 50 th PCTL ................................ ................................ ................................ .... 508 K 24 Female shelter GCR microgravity organ dose equivalent fractional difference vs. 50 th PCTL ................................ ................................ ................... 508 K 25 Male shelter February 1956 SPE microgravity organ dose equivalent fractional difference vs. 50 th PCTL ................................ ................................ .... 509 K 26 Female shelter February 1956 SPE microgravity organ dose equivalent fractional difference vs. 50 th PCTL ................................ ................................ .... 509

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27 K 27 Male shelter October 1989 SPE microgravity organ dose equivalent fractional difference vs. 50 th PCTL ................................ ................................ .... 510 K 28 Female shelter October 1989 SPE microgravity organ dose equivalent fractional difference vs. 50 th PCTL ................................ ................................ .... 510 K 29 Male shelter August 1972 SPE microgravity organ dose equivalent fractional difference vs. 50 th PCTL ................................ ................................ .... 511 K 30 Female shelter August 1972 SPE microgravity organ dose equivalent fractional difference vs. 50 th PCTL ................................ ................................ .... 511 L 1 Male suit trapped proton microgravity organ dose equivalent fractional difference vs. Earth based ................................ ................................ ................ 512 L 2 Female suit trapped proton microgravity organ dose equivalent fractional difference vs. Earth based ................................ ................................ ................ 512 L 3 Male suit GCR microgravity organ dose equivalent fractional difference vs. Earth based ................................ ................................ ................................ ...... 513 L 4 Female suit GCR microgravity organ dose equivalent fractional difference vs. Earth based ................................ ................................ ................................ 513 L 5 Male suit February 1956 SPE microgravity organ dose equivalent fractional difference vs. Earth based ................................ ................................ ................ 514 L 6 Female suit February 1956 SPE microgravity organ dose equivalent fractional difference vs. Earth based ................................ ................................ 514 L 7 Male suit October 1989 SPE microgravity organ dose equivalent fractional difference vs. Earth based ................................ ................................ ................ 515 L 8 Female suit October 1989 SPE microgravity organ dose equivalent fractional difference vs. Earth based ................................ ................................ 515 L 9 Male suit August 1972 SPE microgravity organ dose equivalent fractional difference vs. Earth based ................................ ................................ ................ 516 L 10 Female suit August 1972 SPE microgravity organ dose equivalent fractional difference vs. Earth based ................................ ................................ ................ 516 L 11 Male PV tra pped proton microgravity organ dose equivalent fractional difference vs. Earth based ................................ ................................ ................ 517 L 12 Female PV trapped proton microgravity organ dose equivalent fractional difference vs. Earth based ................................ ................................ ................ 517

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28 L 13 Male PV GCR microgravity organ dose equivalent fractional dif ference vs. Earth based ................................ ................................ ................................ ...... 518 L 14 Female PV GCR microgravity organ dose equivalent fractional difference vs. Earth based ................................ ................................ ................................ 518 L 15 Male PV February 1956 SPE microgravity organ dose equivalent fractional difference vs. Earth based ................................ ................................ ................ 519 L 16 Female PV February 1956 SPE microgravity organ dose equivalent fractional difference vs. Earth based ................................ ................................ 519 L 17 Male PV October 1989 SPE microgravity organ dose equivalent fractional difference vs. Earth based ................................ ................................ ................ 520 L 18 Female PV October 1989 SPE microgravity organ dose equivalent fractional difference vs. Earth based ................................ ................................ 520 L 19 Male PV August 1972 SPE microgravity organ dose equivalent fractional difference vs. Earth based ................................ ................................ ................ 521 L 20 Female PV August 1972 SPE microgravity organ dose equivalent fractional difference vs. Earth based ................................ ................................ ................ 521 L 21 Male shelter trapped proton microgravity organ dose equivalent fractional difference vs. Earth based ................................ ................................ ................ 522 L 22 Female shelter trapped proton microgravity organ dose equivalent fractional difference vs. Earth based ................................ ................................ ................ 522 L 23 Male shelter GCR microgravity organ dose equivalent fractional difference vs. Earth based ................................ ................................ ................................ 523 L 24 Female shelter GCR microgravity organ dose equivalent fractional difference vs. Earth based ................................ ................................ ................ 523 L 25 Male shelter February 1956 SPE microgravity organ dose equivalent fractional difference vs. Earth based ................................ ................................ 524 L 26 Female shelter February 1956 SPE microgravity organ dose equivalent fractional difference vs. Earth based ................................ ................................ 524 L 27 Male shelter October 1989 SPE microgravity organ dose equivalent fractional difference vs. Earth based ................................ ................................ 525 L 28 Female shelter October 1989 SPE microgravity organ dose equivalent fracti onal difference vs. Earth based ................................ ................................ 525

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29 L 29 Male shelter August 1972 SPE microgravity organ dose equivalent fractional difference vs. E arth based ................................ ................................ 526 L 30 Female shelter August 1972 SPE microgravity organ dose equivalent fractional difference vs. Earth based ................................ ................................ 526 R 1 August 1972 SPE with suit shielding male D T (PHITS vs. HZETRN) ................ 608 R 2 August 1972 SPE with suit shielding female D T (PHITS vs. HZETRN) ............. 608 R 3 August 1972 SPE with suit shielding female D T (PHITS vs. HZETRN) ............. 609 R 4 August 1972 SPE with shelt er shielding female D T (PHITS vs. HZETRN) ....... 609 R 5 February 1956 SPE with suit shielding male D T (PHITS vs. HZETRN) ............ 610 R 6 February 1956 SPE with suit shielding female D T (PHITS vs. HZETRN) ......... 610 R 7 February 1956 SPE with shelter shielding male D T (PHITS vs. HZETRN) ....... 611 R 8 February 1956 SPE with shelter shielding female D T (PHITS vs. HZETRN) .... 611 R 9 Trapped environment with PV shielding male D T (PHITS vs. HZETRN) ........... 612 R 10 Trapped environment with PV shielding female D T (PHITS vs. HZETRN ) ........ 61 2 R 11 GCR hydrogen irradiation with PV shielding male D T (PHITS vs. HZETRN) .... 613 R 12 GCR hydrogen irradiation with PV shielding female D T (PHITS vs. HZETRN) ................................ ................................ ................................ .......... 613 R 13 GCR helium irradiation with PV shielding male D T (PHITS vs. HZETRN) ........ 614 R 14 GCR helium irradiation with PV shielding female D T (PHITS vs. HZETRN) ..... 614 R 15 GCR carbon irradiation with PV shielding male D T (PHITS vs. HZETRN) ........ 615 R 16 GCR carbon irradiation with PV shielding female D T (PHITS v s. HZETRN) ..... 615 R 17 GCR oxygen irradiation with PV shielding male D T (PHITS vs. HZETRN) ....... 616 R 18 GCR oxygen irradiation with PV shielding female D T (PHITS vs. HZETRN) .... 616 R 19 GCR magnesium irradiation with PV shielding male D T (PHITS vs. HZETRN) ................................ ................................ ................................ .......... 617 R 20 GCR magnesium irradiation with PV shielding female D T (PHITS vs. HZETRN) ................................ ................................ ................................ .......... 617

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30 R 21 GCR silicon irradiation with PV shielding male D T (PHITS vs. HZETRN) ......... 618 R 22 GCR silicon irradiation with PV shielding female D T ( PHITS vs. HZETRN) ...... 618 R 23 GCR iron irradiation with PV shielding male D T (PHITS vs. HZETRN) ............. 619 R 24 GCR iron irradiation with PV shielding female D T (PHITS vs. HZETRN) .......... 619 R 25 GCR ion group 1 irradiation with PV shielding male D T (PHITS vs. HZETRN) ................................ ................................ ................................ .......... 620 R 26 GCR ion group 1 irradiation with PV shielding female D T (PHITS vs. HZETRN) ................................ ................................ ................................ .......... 620 R 27 GCR ion group 2 irradiation with PV shielding male D T (PHITS vs. HZETRN) ................................ ................................ ................................ .......... 621 R 28 GCR ion group 2 irradiation with PV shielding female D T (PHITS vs. HZETRN) ................................ ................................ ................................ .......... 621 R 29 GCR ion group 3 irradiation with PV shielding male D T (PHITS vs. HZETRN) ................................ ................................ ................................ .......... 622 R 30 GCR ion group 3 irradiation with PV shielding female D T (PHITS vs. HZETRN) ................................ ................................ ................................ .......... 622 S 1 August 1972 SPE with suit shielding male H T (PHITS vs. HZETRN) ................ 623 S 2 August 1972 SPE with suit shielding female H T (PHITS vs. HZETRN) ............. 623 S 3 August 1972 SPE with shelter shielding male H T (PHITS vs. HZETRN) .......... 624 S 4 August 1972 SPE with shelter shielding female H T (PHITS vs. HZETRN) ....... 624 S 5 February 1956 SPE with suit shielding male H T (PHITS vs. HZETRN) ............ 625 S 6 February 1956 SPE with suit shielding female H T (PHITS vs. HZETRN) ......... 625 S 7 February 1956 SPE with shelter shielding male H T (PHITS vs. HZETRN) ....... 626 S 8 February 1956 SPE with shelter shielding female H T (PHITS vs. HZETRN) .... 626 S 9 Trapped environment with PV shielding male H T (PHITS vs. HZETRN) ........... 627 S 10 Trapped environment with PV shielding female H T (PHITS vs. HZETRN) ........ 627 S 11 GCR hydrogen irradiation with PV shielding male H T (PHITS vs. HZETRN) .... 628

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31 S 12 GCR hydrogen irradiation with PV shielding female H T (PHITS vs. HZETRN) ................................ ................................ ................................ .......... 628 S 13 GCR helium irradiation with PV shielding male H T (PHITS vs. HZETRN) ........ 629 S 14 GCR helium irradiation with PV shielding female H T (PHITS vs. HZETRN) ..... 629 S 15 GCR carbon irradiation with PV shielding male H T (PHITS vs. HZETRN) ........ 630 S 16 GCR carbon irradiation with PV shielding female H T (PHITS vs. HZETRN) ..... 630 S 17 GCR oxygen irradiation with PV shielding male H T (PHITS vs. HZETRN) ....... 631 S 18 GCR oxygen irradiation with PV shielding female H T (PHITS vs. HZETRN) .... 631 S 19 GCR magnesium irradiation with PV shielding male H T (PHIT S vs. HZETRN) ................................ ................................ ................................ .......... 632 S 20 GCR magnesium irradiation with PV shielding female H T (PHITS vs. HZETRN) ................................ ................................ ................................ .......... 632 S 21 GCR silicon irradiation with PV shielding male H T (PHITS vs. HZETRN) ......... 633 S 22 GCR silicon irradiation with PV shielding female H T (PHITS vs. HZETRN) ...... 633 S 23 GCR iron irradiation with PV shielding male H T (PHITS vs. HZETRN) ............. 634 S 24 GCR iron irradiation with PV shielding female H T (PHITS vs. HZETRN) .......... 634 S 25 GCR ion group 1 irradiation with PV shielding male H T (PHITS vs. HZETRN) ................................ ................................ ................................ .......... 635 S 26 GCR ion group 1 irradiation with PV shielding female H T (PHITS vs. HZETRN) ................................ ................................ ................................ .......... 635 S 27 GCR ion group 2 irradiation with PV shielding male H T (PHITS vs. HZETRN) ................................ ................................ ................................ .......... 636 S 28 GCR ion group 2 irradiation with PV shielding female H T (PHITS vs. HZETRN) ................................ ................................ ................................ .......... 636 S 29 GCR ion group 3 irradiation with PV shielding male H T (PHITS vs. HZETRN) ................................ ................................ ................................ .......... 637 S 30 GCR ion group 3 irradiation with PV shielding female H T (PHITS vs. HZETRN) ................................ ................................ ................................ .......... 637 T 1 August 1972 SPE with suit shielding D T PD (P HITS vs. HZETRN) .................. 638

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32 T 2 August 1972 SPE with suit shielding female D T PD (PHITS vs. HZETRN) ....... 638 T 3 August 1972 SPE with shelter shielding male D T PD (PHITS vs. HZETRN) .... 639 T 4 August 1972 SPE with shelter shielding female D T PD (PHITS vs. HZETRN) 639 T 5 February 1956 SPE with suit shielding male D T PD (PHITS vs. HZETRN) ...... 640 T 6 February 1956 SPE with suit shielding female D T PD (PHITS vs. HZETRN) ... 640 T 7 February 1956 SPE with shelter shielding male D T PD (PHITS vs. HZETRN) ................................ ................................ ................................ .......... 641 T 8 February 1956 SPE with shelter shielding female D T PD (PHITS vs. HZETRN) ................................ ................................ ................................ .......... 641 T 9 Trapped environment with PV shielding male D T PD (PHITS vs. HZETRN) ..... 642 T 10 Trapped environment with PV shielding female D T PD (PHITS vs. HZETRN) .. 642 T 11 GCR hydrogen irradiation with PV shielding male D T PD (PHITS vs. HZETRN) ................................ ................................ ................................ .......... 643 T 12 GCR hydrogen irradiation with PV shielding female D T PD (PHITS vs. HZETRN) ................................ ................................ ................................ .......... 643 T 13 GCR helium irradiation with PV shielding male D T PD (PHITS vs. HZETRN) .. 644 T 14 GCR helium irradiation with PV shielding female D T PD (PHITS vs. HZETRN) ................................ ................................ ................................ .......... 644 T 15 GCR carbon irradiation with PV shielding male D T PD (PHITS vs. HZETRN) .. 645 T 16 GCR carbon irradiation with PV shielding female D T PD (PHITS vs. HZETRN) ................................ ................................ ................................ .......... 645 T 17 GCR oxygen irradiation with PV shielding male D T PD (PHITS vs. HZETRN) 646 T 18 GCR oxygen irradiation with PV shielding female D T PD (PHITS vs. HZETRN) ................................ ................................ ................................ .......... 646 T 19 GCR magnesium irradiation with PV shielding male D T PD (PHITS vs. HZETRN) ................................ ................................ ................................ .......... 647 T 20 GCR magnesium irradiation with PV shielding female D T PD (PHITS vs. HZETRN) ................................ ................................ ................................ .......... 647 T 21 GCR silicon irradiation with PV shielding male D T PD (PHITS vs. HZETRN) ... 648

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33 T 22 GCR silicon irradiation with PV shielding female D T PD (PHITS vs. HZETRN) ................................ ................................ ................................ .......... 648 T 23 GCR iron irradiation with PV shielding male D T PD (PHITS vs. HZETRN) ....... 649 T 24 GCR iron irradiation with PV shielding female D T PD (PHITS vs. HZETRN) .... 649 T 25 GCR ion group 1 irradiation with PV shielding male D T PD (PHITS vs. HZETRN) ................................ ................................ ................................ .......... 650 T 26 GCR ion group 1 irradiation with PV shielding female D T PD (PHITS vs. HZETRN) ................................ ................................ ................................ .......... 650 T 27 GCR ion group 2 irradiation with PV shielding male D T PD (PHITS vs. HZETRN) ................................ ................................ ................................ .......... 651 T 28 GCR ion group 2 irradiation with PV shielding female D T PD (PHITS vs. HZETRN) ................................ ................................ ................................ .......... 651 T 29 GCR ion group 3 irradiation with PV shielding male D T PD (PHITS vs. HZETRN) ................................ ................................ ................................ .......... 652 T 30 GCR ion group 3 irradiation with PV shielding female D T PD (PHITS vs. HZETRN) ................................ ................................ ................................ .......... 652 U 1 August 1972 SPE with suit shielding male H T PD (PHITS vs. HZETRN) .......... 653 U 2 August 1972 SPE with suit shielding female H T PD (PHITS vs. HZETRN) ....... 653 U 3 August 1972 SPE with shelter shielding male H T PD (PHITS vs. HZETRN) .... 654 U 4 August 1972 SPE with shelter shielding female H T PD (PHITS vs. HZETRN) 654 U 5 February 1956 SPE with suit shielding male H T PD (PHITS vs. HZETRN) ...... 655 U 6 February 1956 SPE with suit shielding female H T PD (PHITS vs. HZETRN) ... 655 U 7 February 1956 SPE with shelter shielding male H T PD (PHITS vs. HZETRN) ................................ ................................ ................................ .......... 656 U 8 February 1956 SPE with shelter shielding female H T PD (PHITS vs. HZETRN) ................................ ................................ ................................ .......... 656 U 9 Trapped environment with PV shielding male H T PD (PHITS vs. HZETRN) ..... 657 U 10 Trapped environment with PV shielding female H T PD (PHITS vs. HZETRN) .. 657 U 11 GCR hydrogen irradiation with PV shielding male H T PD (PHITS vs. HZETRN) ................................ ................................ ................................ .......... 658

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34 U 12 GCR hydrogen irradiation with PV shielding female H T PD (PHITS vs. HZETRN) ................................ ................................ ................................ .......... 658 U 13 GCR helium irradiation with PV shielding male H T PD (PHITS vs. HZETRN) .. 659 U 14 GCR helium irradiation with PV shielding female H T PD (PHITS vs. HZETRN) ................................ ................................ ................................ .......... 659 U 15 GCR carbon irradiation with PV shielding male H T PD (PHITS vs. HZETRN) .. 660 U 16 GCR carbon irradiation with PV shielding female H T PD (PHITS vs. HZETRN) ................................ ................................ ................................ .......... 660 U 17 GCR oxygen irradiation with PV shielding male H T PD (PHITS vs. HZETRN) 661 U 18 GCR oxygen irradiation with PV shielding female H T PD (PHITS vs. HZETRN) ................................ ................................ ................................ .......... 661 U 19 GCR magnesium irradiation with PV shielding male H T PD (PHITS vs. HZETRN) ................................ ................................ ................................ .......... 662 U 20 GCR magnesium irradiation with PV shielding female H T PD (PHITS vs. HZETRN) ................................ ................................ ................................ .......... 662 U 21 GCR silicon irradiation with PV shielding male H T PD (PHITS vs. HZETRN) ... 663 U 22 GCR silicon irradiation with PV shielding female H T PD (PHITS vs. HZETRN) ................................ ................................ ................................ .......... 663 U 23 GCR iron irradiation with PV shielding male H T PD (PHITS vs. HZETRN) ....... 664 U 24 GCR iron irradiation with PV shielding female H T PD (PHITS vs. HZETRN) .... 664 U 25 GCR ion group 1 irradiation with PV shielding male H T PD (PHITS vs. HZETRN) ................................ ................................ ................................ .......... 665 U 26 GCR ion group 1 irradiation with PV shielding female H T PD (PHITS vs. HZETRN) ................................ ................................ ................................ .......... 665 U 27 GCR ion group 2 irradiation with PV shielding male H T PD (PHITS vs. HZETRN) ................................ ................................ ................................ .......... 666 U 28 GCR ion group 2 irradiation with PV shielding female H T PD (PHITS vs. HZETRN) ................................ ................................ ................................ .......... 666 U 29 GCR ion group 3 irradiation with PV shielding male H T PD (PHITS vs. HZETRN) ................................ ................................ ................................ .......... 667

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35 U 30 GCR ion group 3 irradiation with PV shielding female H T PD (PHITS vs. HZETRN) ................................ ................................ ................................ .......... 667 V 1 REID values for August 1972 SPE with suit shielding ................................ ...... 668 V 2 Percent differences in REID values for August 1972 SPE with suit shielding ... 668 V 3 REID values for August 1972 SPE with shelter shielding ................................ 669 V 4 Percent differences in REID values f or August 1972 SPE with shelter shielding ................................ ................................ ................................ ........... 669 V 5 REID values for February 1956 SPE with suit shielding ................................ ... 670 V 6 Percent differences in REID values for February 1956 SPE with suit shielding ................................ ................................ ................................ ........... 670 V 7 REID values for February 1956 SPE with shelter shielding .............................. 671 V 8 Percent differences in REID values for February 1956 SPE with shelter shielding ................................ ................................ ................................ ........... 671 V 9 REID value s for trapped environment with PV shielding ................................ .. 672 V 10 Percent differences in REID values for trapped environment with PV shielding ................................ ................................ ................................ ........... 672 V 11 REID values for GCR with PV shielding ................................ ........................... 673 V 12 Percent differences in REID values for GCR with PV shielding ........................ 673

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36 LIST OF ABBREVIATION S 1D One dimensional 3D Three dimensional A Ion mass number ALARA As Low As Reasonably Achievable ARRBOD Acute Radiation Risk and BRYTRN Organ Dose projections BEIR Biological Effects of Ionizing Radiation BFO Blood Forming Organ BRYNTRN BaRYoN TRaNsport code CAF Computerized Anatomical Female CAM Computerized Anatomical Man CAMERA Program used to ray trace CAM and CAF CI Confidence Interval CL Confidence Limit CM Command Module CNS Central Nervous System CPD Crew Personal Dosimeter CT Computed Tomography DDREF Dose and Dose Ra te Effectiveness Factor DOE Department of Energy D T Organ absorbed dose EAR Excess Absolute Risk EGS Elect ron Gamma Shower ENDF Evaluated Nuclear Data File EPA Environmental Protection Agency

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37 ERR Excess Relative Risk ET Extrathoracic FAX Fem ale Adult voXel phantom FLUKA FLUctuating KAskades GCR Galactic Cosmic Rays HETC HEDS High Energy Transport Code for Human Exploration and Development in Space H T Organ dose equivalent HZE High charge and energy HZETRN HZE TRaNsport code ICRP International Committee on Radiological Protection ISS International Space Station JAERI Japan Atomic Energy Research Institute JAM Jet AA Microscopic transport model JQMD JAERI Quantum Molecular Dynamics model LAR Lifetime Attributable Risk LEO Low Earth Orbit LET Linear Energy Tra nsfer LNT Linear No Threshold LUT Look Up Table MAX Male Adult voXel phantom MCNP Monte Carlo N Particle MCNPX Monte Carlo N Particle eXtended MCNPX_HI Monte Carlo N Particle eXtended Heavy Ion MEVDP Modified Element Volume Dose Program MORSE Multigroup Oa k Ridge Stochastic Experiment code

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38 MSIS Man System Integration Standards NAS National Academy of Sciences NASA National Aeronautics and Space Administration NCRP National Council on Radiation Protection NRC National Research Council NUCFRG2 NUClear FRaGmen tation model version 2 NURBS Non Uniform Rational B Spline OSHA Occupational Safety and Health Administration PCTL Percentile PD Percent Difference PV Pressure V essel PEANUT Pre Equilibrium Approach to Nuclear Thermalization PHITS Particle and Heavy Ion Transport code System RBE Relative Biological Effectiveness RD Relative Difference REIC Risk of Exposure Induced Cancer REID Risk of Exposure Induced Death RHO Radiation Health Officer SAA South Atlantic Anomaly SPE Solar Particle Event SRAG Space Radiatio n Analysis Group STS Space Transportation System TEPC Tissue Equivalent Proportional Counter TLD Thermoluminescent dosimeter TP Technical Paper

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39 UF University of Florida UFHADF University of Florida Hybrid ADult Female (often stated with percentile) UFHADM University of Florida Hybrid ADult Male (often stated with percentile) UNSCEAR United Nations Scientific Committee on the Effects of Atomic Radiation US United States USAF United States Air Force VoBRaT Voxel Based Ray Tracer Z Ion charge number

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40 Abstract of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy NASA ASTRONAUT DOSIMETRY: IMPLEMENTATION OF SCALABLE HUMAN PHANTOMS AND BENCHMARK COMPARISONS OF DETERMINISTIC VERSUS MONTE CARLO RADIATION TRANSPORT By Amir Alexander Bahadori December 2012 Chair: Wesley E. Bolch Major: Biomedical Engineering Astronauts are exposed to a unique radiation environment in space. United States terrestrial radiation worker limits, derived from guidelines produced by scientific panels, do not apply to astronauts. Limits for astronauts hav e changed throughout the Space A ge, eventually reaching the current National Aeronautics and Space Administra tion limit of 3% risk of exposure induced death, with an administrative stipulation that the risk be assured to the upper 95% confidence limit. Much effort has been spent on reducing the uncertainty associated with evaluating astronaut risk for radiogenic cancer mortality while tools that affect the accuracy of the calculations have largely remained unchanged. In the present study, the impacts of using more realistic computational phantoms with size variability to represent astronauts with simplified dete rministic radiation transport were evaluated Next, the impacts of microgravity induced body changes on space radiation dosimetry using the same transport method were investigated Finally, dosimetry and risk calculations resulting from Monte Carlo radia tion transport were compared with results obtained using simplified deterministic radiation transport.

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41 The results of the present study indicated that the use of phantoms that more accurately represent human anatomy can substantially improve space radiation dose estimates, most notably for exposures from solar particle events under light shielding conditions Microgravity induced changes were less important, but results showed that flexible phantoms could assist in optimizing astronau t body position for reducing exposure s during solar particle event s Finally, little overall difference s in risk calculations using simplified deterministic radiation transport and 3D Monte Carlo radiation transport were found ; however, for the galactic c osmic ray ion spectra compensating errors were observed for the constituent ions, thus exhibiting the need to perform evaluations on a particle differential basis with common cross section libraries

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42 CHAPTER 1 INTRODUCTION Humans have long been fascinated by the idea of leaving the friendly confines of Earth and traveling through space. Significant obstacles littered the path to human exploration of this new frontier. Before the historic Space Race between the United States and the Soviet Union, a lack of viable technology kept humans within the limits of the geo political impetus to explore further, or even to maintain the frontier at the Moon, led to a different kind of exploration: expanding our knowledge of the response of the human system to the space environment through low Earth orbit (LEO) missions. In the case of the Space Shuttle program, these missions were short in duration (generally less than 2 weeks) and had other primary objectives, such as deploying satellites or ferrying astronauts to space stations for longer duration missions. The knowledge and experience gained during the Salyut, Skylab, and Mir space station programs and the early part of the Space Shuttle program, informed the engineering and human factor s practices in use today on the International Space Station (ISS). The ISS, including construction, maintenance, and continuous occupation is among the most significant achievements in human history. It also represents a major shift in how the National Aeronautics and Space Administration ( NASA ) views risk, particularly that from radiatio n exposure, in the context of human exploration of space Space travel is an inherently risky endeavor. The world population is acutely aware of accidents that occur red in training ( e. g. Apollo 1), during launch ( e. g. Space Shuttle Challenger), during f light ( e. g. A pollo 13 ), and upon attempting to re enter the e. g. Space Shuttle Columbia ). In addition to these apparent risks,

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43 there are insidious risks to the human system that could manifest in severe health consequences during or after a mission ( Barratt and Pool 2008 ; Cucinotta et al. 2011 ) These include bone and muscle los s ( LeBlanc et al. 2000 ; Lang et al. 2004 ; McCarthy 2005 ; Amin 2010 ) d eterioration of cardiac muscle ( Vernikos 1996 ; Perhonen et al. 2001 ) immunosuppression ( Barratt and Pool 2008 ) and vision degradation ( Mader et al. 2011 ) Risk s resulting from exposure to the space radiation environment, which is very different from the radiation environment on Earth, are among the least understood, mostly owing to an inability to characterize the cons equences of these exposures through direct observation of the exposed individual. During the Space Race, radiation protection experts were aware of some of the potential for danger posed by the space radiation environment ( NRC 1967 ) Their e valuation of the radiation danger from spaceflight focused on deterministic effects with ( NRC 1967 ) N o radiation dose or risk limits were imposed on the Apollo astronauts; inst ead a recommendation for a guideline of dose equivalent to the blood forming organ (BFO), thought to result in a doubling of mortality due to malignant disease for a white male between ages 35 and 55 was issued in 19 70 by the National Academy of Sciences National Resea r ch Council (NAS NRC) ( NRC 1970 ) The guideline was presented in instead of a defined limit; t he risk of cancer posed by space radiation was not to preclude the successful completion a particular mission. Since the late 1960s, much has been learned about the risks of radiation exposure. The data from the Japanese Atomic Bomb Survivor cohort has matured, new exposed cohorts have emerged, and many animal and c ell experiments have been

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44 performed using particle types and energies relevant to the space radiation environment We know with great certainty that radiation is a carcinogen, can cause cataracts, and, in large enough doses, can ablate cell populations w ithin the human There are also indications that radiation exposure also has deleterious effect s on the central nervous system (CNS) and cardiovascular system ( NCRP 2006 ) Concurrent with the increase in knowledge of radiation effects, NASA and other partner space agencies have established a consistent human presence in LEO through the aforementioned programs, particularly the ISS. To control the amount of risk resultin g from radiation incurred by the larger astronaut population associated with these programs, and in the absence of a sense of urgency similar to that of the Apollo program, radiation limits evolved to 3% risk of exposure induced death (REID) ( NCRP 1989 2000 ) It should be emphasized that unlike other occupational radiation exposure limits, NASA uses a risk limit instead of a dose limit thus making a ny derived dose limits inherently age and gender dependent A supplementary condition that the REID for a particular astronaut not exceed 3% with 97.5% confidence (upper 95% confidence limit [CL] ), has been adopted as an administrative limit ( NASA 2007 ) For LEO exposures, the NASA administrative limit is approximately equal to a 1% REID point estimate ( Cucinotta 2007 ) In short NASA has shifted from accepting a doubling in cancer mortality over ages 35 to 55 from radiation exposure f or the Apollo program to a 1% REID limit for the ISS program Space radiation presents a unique challenge in terms of radiation protection. The three basic ways in which cumulative radiation exposure can be controlled are reduction of time of exposure, in creasing distance between the person and the source of the

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45 exposure, and increasing the shielding between the person and the source of exposure. Unfortunately, the space radiation environment is omnidirectional ( Wilson et al. 1991b ) and it is thus impossible to increase distance. Increasing shielding in the spacecraft can reduce the exposure resulting from trapped radiation belt sources, and certain solar particle events (SPE), but most materials are only marginally effective at reducing exposure from the much more energetic and penetrating galactic cosmic rays (GCR), the major contributor to risk of radiation carcinogenesis for both LEO missions and missions outside of Earth orbit ( C ucinotta et al. 2002 ; Cucinotta et al. 2005 ; Cucinotta et al. 2011 ) Time of exposure remains as the only effective method by which one may control cumulative radiation exposure. As in othe protection ALARA is implemented through the NASA administrative limit and practical actions such as lining the crew quarters of the ISS with polyethylene to reduce primary and secondary proton and neutron exposures ( Shavers et al. 2004 ) and through the timing of extravehicular activities ( NCRP 2000 2002 ) Since the radiation risk from a sing le 6 month ISS mission does not exceed the NASA administrative limit, regardless of age and gender, the length of the ISS mission need not be altered to maintain ALARA. Instead, crew assignments to ISS Expeditions are used to manage the REID from radiati on exposure. The major factors that assist in limiting the exposure (and thus risk) from a single 6 month ISS mission are the geomagnetic shielding provided by the Earth and the length of the mission. Unfortunately, both of these factors are absent in lo ng term missions to the Moon or Mars. In fact, understanding and managing risk of

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46 radiation exposure has been iden tified as one of the major problems that must be solved before embarking on an extended exploration mission ( NRC 2012a ) The increasing number of astronauts with multip le ISS missions and the need to understand and manage risk of radiation exposure for extended exploration missions has led to a large research effort to decrease the uncertainties associated with evaluating and project ing risks from space radiation Much of the focus has been on reducing the uncertainty of human biological response from high charge and energy (HZE) radiation, which comprises a large fraction of space radiation ( Cucinotta et al. 2002 ; Cucinotta et al. 2005 ; Cucinotta et al. 2011 ) The characterization and reduction of un certainty in space radiation risk estimates is vital to improving the precision of these estimates and reducing the relatively large confidence interval dominated by the biological uncertainties. However, one must keep in mind that the absolute NASA risk limit is based upon the point estimate of risk, in contrast with the NASA administrative risk limit, which is based upon both the point estimate of risk and the uncertainty characterization of that point estimate. Thus, the accuracy of the point estimate of risk should be evaluated and improved when possible. Historically, two mathematical phantoms have been used to represent the male and female NASA astronaut for the purposes of space radiation dosimetry: Computerized Anatomical Man (CAM) ( Billings and Yucker 19 73 ) and Comput erized Anatomical Female (CAF) ( Yucker and Huston 1990 ) One dimensional (1D) deterministic radiation transport has been utilized for NASA radiation transpor t calculations, in part due to the h istorical lack of computational power and the intractable nature of solving the Boltzmann transport equation for arbitrary thr ee dimensional (3D)

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47 geometries Recently, a new set of computational phantoms, which are used to represent the human in simulatio ns of radiation exposure, have been evaluated for use with the NASA High Charge and Energy Transport (HZ ETRN) code ( Kim et al. 2010b ; Slaba et al. 2010c ) and the details of the transport methods used by HZETRN to simulate space radiation interacti ons are being actively updated ( Slaba et al. 2010a ; Slaba et al. 2010b ) However, there remains a need to evaluate impacts of other variables on the space radiation risk estimates, especially considering the recent advances in computa tional phantoms ( Lee et al. 2010 ) and the availability of af fordable high performance computing for implementing computationally intensive transport methods The purpose of the present study is to determine the following: 1. The impacts of differences in size and anthropometric modeling on effective dose; 2. The impacts of microgravity on effective dose; and 3. The impacts of using a state of the art Monte Carlo radiation transport code instead of HZETRN on risk from space radiation exposures. To address items 1 and 2, current operational versions of NASA transpor t codes, which pre date the current version of HZETRN but are based on the same principles, were used, and effective dose was used as a surrogate for radiation risk per National Council on Radiation Protection and Measurements (NCRP) Report No. 132, Radiat ion Protection Guidance for Activities in Low Earth Orbit ( 2000 ) In light of the imminent update to the NASA spa ce radiation cancer risk model ( Cucinotta et al. 2011 ; NRC 2012b ) the most recent version of HZETRN was compared to the most recent version of the Particle and Heavy Ion Transport code System (PHITS) ( Niita et al. 2006 ; Niita et al. 2010 ) an advanced Monte Carlo radiation transport code to address item 3. Risk was represented both by effective dose per NCRP Report No. 132 and REID as

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48 calculat ed using methods from the updated radiation risk model used by the US Environmental Protection Agency (EPA) ( EPA 2011 ) These changes were made to ensure that the transport code comparison will remain as relevant as possible to codes that will be implemented operationally by NASA in the near fut ure.

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49 CHAPTER 2 BACKGROUND AND LITER ATURE REVIEW NASA Astronaut Phantoms Early Astronaut Representation s Early NASA space radiation dose analyses were performed using simple approaches to anatomical modeling. An example of such early analyses is a mathematical analysis of the space radiation dose as a function of depth in a model astronaut, performed for the Apollo program ( Fortney and Duckworth 1964 ) The Apollo command module ( CM ) was constructed of a sphere, cone, and toroid, while the astronaut phantom was constructed of two right elliptical cylinders with dimensions determined from United States Air Force ( USAF ) flying personnel, as shown in Figure 2 1 ( Fortney and Duckworth 1964 ) The equivalent sphere model was a simpler mod el used to perform space radiation dose analyses. The skin dose was approximated as the dose at a depth of 0.1 mm; the eye lens dose was approximated as the dose at a depth of 3 mm; and the dose to the BFO was approximated as the dose at a depth of 5 cm ( Townsend and Zapp 1999 ) The purpose of the simple models was to give estimates of radiation dose as a function of depth within the astronaut. CAM: A Detailed Male Astronaut Representation The scientists performing space radiation dose analyses later recognized that the radiation exposure levels encountered in space could approach specific organ limits. Radiation dose estimates with greater accuracy were required to ensure that these was developed to improve the radiation dose estimates ( Kase 1970 ) A highly stylized computational phantom, known as CAM was constructed based on 132 anthropometric

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50 meas urements of over 4000 USAF flying personnel for the original purpose of skin tight garment design ( Kase 1970 ) Some of the measurements required for the cons truction of CAM were not available from these data. The measurements missing from the USAF data were taken from an individual representing the 50 th PCTL 1950 USAF male ( Kase 1970 ; Yucker and Huston 1990 ) Artists and medical consultants resolved anthropometric inconsistencies and scaled the skeletal model to the appropriate dimensions for the outer body contour ( Kase 1970 ) The initial iteration of CAM was constructed through Boolean logic, for compatibility with Modified Element Volume Dose Program ( MEVDP ) using six shapes ( Liley and Hamilton 1971 ) : H exahedron, R ight circular cylinder, S phere, H emisphere T r uncated or pristine right circular cone, and T runcated or pristine ellipsoid with t runcation from up to two planes The outer body contour and skeleton were modeled separately and then combined to force compatibility. Internal organs were then modeled to fit within the skeletal structure. Several approximations were implemented to limit the complexity of CAM, including ( Kase 1970 ) I gnoring hair, S implificati on of skull structure, M odeling the ribs as a thin shell instead of individual components, E mploying a homogeneous skeletal structure, and I gnoring fluids. Organ volumes were determined by placing a mock dose point at the center of each organ and tracing rays emanating from the mock dose point, with each ray representing approximately the same solid angle increment ( Kase 1970 ) The method resulted in

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51 exact values for spheres, hemispheres, and ellipsoids, and approximate values for objects with corners. Kase ( 1970 ) found that 512 rays limited th e error in volume to 1% for shapes compatible with MEVDP, and so 512 rays became the standard size for a set of rays to determine body self shielding Development of CAMERA and Improvements to CAM After the initial development of CAM, Billings and Yucker ( 1973 ) converted the geometrical form to evaluate and improve anatomical representations and implement CAMERA (acr onym unknown) a ray tracing utility for point kernel radiation shielding analyses. The ME VDP geometry system, in which complex volumes are constructed of elemental volumes, was inefficient for ray tracing since it required the simultaneous solution of the ray equation and the equation defining each elemental volume comprising a complex volume An improved geometry system describe d the given model as a collection of homogeneous regions with boundaries defined by 2 1 where A ijk is a real valued coefficient and x y and z are the standard Car tesian coordinates ( Billings and Yucker 1973 ) Each region was defined by material, a list of surfaces bounding it, and a point within the region for ambiguity indexing. With this definiti on, holes and overlaps of boundaries could occur, and so a ray recovery procedure was included in CAMERA to attempt to overcome these errors. The major anatomical improvement made with CAM by Billings and Yucker was the modeling of BFO. Instead of represe nting each bone as a homogeneous structure, a marrow location with the same shape as the outer contour but reduced in size was specified ( Billings and Yucker 1973 ) Red and yellow marrow locations we re

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52 distinguished by different material indices. Dose points were also chosen in this phase. Points within the skin, BFO, and gastrointestinal region were randomly selected since they are distributed organs; other organs, such as the testes and eye lens, were represented by single dose points ( Billings and Yucker 1973 ) Images of CAM are shown in Figure 2 2 and Figure 2 3 CAF: A Female Astronaut Phantom A corresponding female astronaut phantom, CAF was developed in 1990 ( Yucker and Huston 1990 ) CAM and CAMERA were modified to accommodate female anatomy and physiques other than the 50 th PCTL 1950 USAF man. For anthropometric parameters, 1968 USAF women were chosen to represent CAF ( Yucker and Huston 1990 ; Yucker 1992 ) The anthropometric parameters for this cohort and CAM were compared, and a linear scaling factor of 0.92 was employed, despite the finding that the values were approximately equal for the hips and waist ( Yucker and Huston 1990 ) Instead of scaling the phantom, the scaling functionality in CAMERA transformed a desired dose point to the corresponding point in the unscaled model. Sub sequent to ray tracing, the path segments were scaled by the linear scaling factor to return the appropriate ray lengths. For this reason, the International Committee on Radiological Protection ( ICRP ) reference values for the uterus, ovaries, and breasts were scaled by the inverse of the linear scaling factor so that the size s of each relative to other organs was correct ( Yucker and Huston 1990 ) The m ale organs were removed and the models for the female organs were inserted. Later, variable scaling in an approximate treatment was included by adjusting the direction cosines of rays; a linear scaling factor of 1.02 was implemented for the hip breadth, w hile the other linear scaling factors remained the same ( Yucker 1992 )

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53 NASA Space Radiation Transport Methods Early Space Radiation Transport Methods The development of NASA space radiation transport methods reflects the development of NASA astronaut phantoms: simple representation followed by a more complex treatment. In the Apollo CM shielding study, relatively crude environmental models were employe d. These included a geomagnetically trapped proton spectrum and a typical SPE ( Fortney and Duckworth 1964 ) A 1D transport code written specifically for proton shielding analyses transported the external environment along rays intersect ing both the Apollo CM model and the astronaut model. This transport code used simple stopping power relation for ionization losses for incident proton energies above 200 MeV and an exponential range relationship for incident proton energies below 200 MeV while inelastic collisions were addressed using proton and neutron yield data ( Fortney and Duckworth 1964 ) Curves of dose rate as a function of homogeneous tissue thickness were generated for various CM wall thicknesses. While this method was not a detailed treatment of charged particle and neutron transpo rt, and did not address GCR it laid the groundwork for subsequent transport codes in two major ways: (1) the deconvolution of the transport into a 1D ray tracing problem, and (2) the assumption of the straight ahead approximation, which equate s mono directional irradiation of slab geometry to isotropic irradiation through a sphere or spherical shell, as illustrated in Figure 2 4 BRYNTRN and HZETRN A much more detailed method of space radiation transport was developed first through Baryon Transport code ( BRYNTRN ) for proton irradiation ( Wilson et al. 1989 ) and late r through HZETRN for proton and heavy ion irradiation ( Wilson et al. 1991a )

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54 Both programs solve the time independent Boltzmann equation using the continuously slowing down approximation ( CSDA ) ( Wilson et al. 1991b ) where, generally, 2 2 where is the flux of particle type j at position heading in direction with energy E S j (E) is the stopping power of particle type j with energy E is the total cross section of particle type j with energy E and is the cross section for particles of type k with energy and direction creating particles of type j with energy E and direction BRYNTRN is capable of transporting incident protons and secondary neut rons, and roughly treats heavier secondary charged particles using stopping power scaling methods ( Wilson et al. 1989 ) Considering a 1D solution the Boltzmann equation reduced to three separate equations, 2 3 2 4 2 5 where f kj is the cross section for particles of type k with energy creating particles of type j with energy E Equations 2 3, 2 4, and 2 5 address protons, neutrons, and target fragments, respectively ( Wilson et al. 1989 ) Note here the introduction of the

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55 range scaling parameter, Extending transport to particles with mass numbers ( A ) less than or equal to 4 ( Hoff et al. 2004 ) nsport equations were given by ( Wilson et al. 1989 ; Wilson et al. 1991b ) 2 6 The functions are not well behaved in the energy domain. Therefore, Equation 2 6 was rewritten, using a transformation of variables, to 2 7 where r is the residual proton range ( Wilson et al. 1989 ; Wilson et al. 1991b ) Equation 2 7 was then rearranged and solved numerically Transporting GCR which are modeled with ions rang ing from protons to nickel ions, require d an expansion of the methods and approximations used for BRYNTRN; HZETRN was created for this purpose. In HZETRN, the transport equation for heavy ions ( A > 4) in CSDA with the straight ahead approximation was given as ( Wilson et al. 2006 ) 2 8 Once again, introducing the residual proton range, Equation 2 8 became 2 9 which was then rearranged and solved numerically ( Wilson et al. 2006 ) Both BRYNTRN and HZETRN use the Bethe Bloch theory to calculate stopping s, and both employ fits to quantum models for

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56 cross section calculations ( Wilson et al. 1989 ; Wilson et al. 1991a ; Wilson et al. 1991b ; Sihver et al. 2008 ) In HZETRN, the semiemperical NUClear FRaGmentation model version 2 (NUCFRG2) is used to calculate fragmentation cross sections using the abrasion ablation model. In the abrasion ablation model, f ragmentation consist s of two steps: (1) abrasion, in which nucleons are removed in the overlap region of the projectile and ta ( Sihver et al. 2008 ) The codes were validated against Monte Carlo codes with simple geometries, usually consisting of an aluminu m slab followed by a water slab; reasonable agreement was shown for these comparisons ( Wilson et al. 1989 ; Wilson et al. 1991b ; Wilson et al. 2006 ) Recent Updates to HZETRN : HZETRN2010 HZETRN ha s recently been updated for the purposes of documentation, improving efficiency and stability of the code, and quantifying discretization error associated with step sizes in spatial and energy grids ( Slaba et al. 2010b ) In previous versions (including the version used by the NASA Radiation Health Officer [RHO] and the phant om evaluation portion of the present study ), the numerical convergence criterion was violated, which resulted in a systematic underprediction of light (A < 5) charged target fragments below energies of 50 MeV u 1 ( Slaba et al. 2010b ) Also, round off error resulting from subtractive cancellation associated with the use of si ngle precis ion instead of double precision was found to be substantial for shielding thicknesses greater than about 50 g cm 2 ( Slaba et al. 2010b ) Acceleration of the code through more efficien t numerical methods allows the user to run SPE spectra about 100 times faster than in previous versions and GCR spectra about 10 times faster ( Slaba et al. 2010b ) A series of convergence tests were developed to baseline the performance of the code,

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57 determine the optimum discretization in space and energy, and provide a configuration controlled method for ensuring that future alterations of the code do not result in unexpected deviations ( Slaba et al. 2010b ) HZETRN2010 also includes improvements to the neutron transport algorithm ( Slaba et al. 2010a ) Previous versions were noted to have a deficiency in low energy neutron transport ( Shinn et al. 1994 ) These versions assumed the straight ahead approximation, in which fragments pr opagate in the same direction as the projectile for all particles The approximation is accurate for high energy charged particles, but breaks down for low energy neutrons ( Alsmiller et al. 1965 ) A series of neutron transport methods were tested in previous versions of HZETRN. These include Forward Backward, in which low energy neutrons are split into forward and backward components; Directionally Coupled, which consists of the Forward Backward method with multiple reflections; and Multi group methods, which are common in reactor theory and assume fluences and cross sections are constant over regions of the neutron energy spectrum. Light ion transport was coupled to both the Forward Backward method and Directionally Coupled method. Little difference was observed for proton fluence, but uncoupled transport resulted in fluences for light i ons with mass number greater than 1 that were substantially smaller than fluences for the same ions with coupled light ion transport ( Slaba et al. 2010a ) The differences were large enough to alter absorbed dose and dose equivalent values at water depths from 0 to 30 g cm 2 after 20 g cm 2 aluminum ( Slaba et al. 2010a ) An extensive comparison of HZETRN2010 and measurements on the ISS was performed as a part of its validation ( Slaba et al. 2011 ) The authors noted that past

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58 studies and current practice rely on considering the cumulative mission duration for radiation dosimetry purposes, which might result in errors in estimated quantities and unrepresentative accuracy assessments ( Slaba et al. 2011 ) To avoid errors associated with considering the entire mission duration, co mparisons were made for ISS exposures at 30 s intervals from 6 July 2001 to 13 July 2001 between HZETRN calculated values and measurements from Liulin detectors small silicon based semiconductor detectors, and the Tissue Equivalent Proportional Counter ( T EPC ) Due to the large uncertainties associated with trapped proton models, South Atlantic Anomaly ( SAA ) exposures were removed from the comparison ( Slaba et al. 2011 ) The authors noted that although NASA codes in the past relied upon tabular interpolation, HZETRN2010 was accelerated to the point where ray by ray analysis could be performed with practically no limit on the ordering or number of materials for transport ( Slaba et al. 2011 ) After considering only attenuated GCR in LEO, the authors found that the results for calculated values compared well with measured data as a function of time. Trends resulting from variations in the geomagnetic transmission function were accurately reproduced, with all calculated values were within 3.5 uGy h 1 of the average measurement of the corresponding detector at all geomagnetic cutoff rigidities ( Slaba et al. 2011 ) The average error at the lowest cutoff rigidity evaluated was 22%, indicating that for missions beyond LEO where the cutoff rigidity is effectively zero, the average error for an ISS like vehicular geometry would be on the order of 20% ( Slaba et al. 2011 ) In general it was found that HZETRN under pre dicted measured data at high cutoff rigidities, and percent errors decreased with decreasing rigidity, due to simplified

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59 models of the anisotropies in the geomagnetic field, no consideration of pions, and simplified high energy physics models ( Slaba et al. 2011 ) The comparisons in the phantom evaluation p ortion of the present study use d BRYNTRN and HZETRN2005 because these were the codes in use by the NASA RHO at the time of writing and were immediately available for study The improvements made to HZETRN in the form of HZETRN2010 were substantial and the effects of these improvements on the evaluation of radiation dose and risk to astronauts should be evaluated before it is adopted for operational use. Results from HZETRN2010 were compared with 3D Monte Carlo results in the transport method evaluation po rtion of the present study to contribute to the evaluation of HZETRN2010 as an operational tool Space Radiation Dosimetry Dosimetric Calculations While performing transport, both BRYNTRN and HZETRN calculate absorbed dose and dose equivalent as a function of slab thickness. The absorbed dose at a depth of x within the slab is calculated as 2 10 while the dose equivalent is calculated as 2 11 where Q j (E) is the quality factor for particle type j at energy E ( Wilson et al. 1991b ) The quality factor is currently defined as a function of linear energy transfer ( LET ) using the ICRP Publication 60 ( ICRP 1991 ) definition; the function is shown in Table 2 1

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60 Once the absorbed dose a nd dose equivalent are determined as a function of depth, the ray trace results from CAM and CAF are used to determine the organ absorbed dose and organ dose equivalent by averaging the values for each of the 512 rays. This method is valid since the solid angle increment represented by each of the rays is approximately the same. In practice, BRYNTRN and HZETRN output absorbed dose and dose equivalent in the form of a two dimensional matrix representing depths of aluminum for external shielding and depths of water for body self shielding. Thus, two interpolations are performed: one uses the vehicular ray distribution and the other uses the phantom distribution. Originally, the phantom and vehicular shielding were coupled in an attempt to account for varia tions in astronaut location and orientation throughout a mission ( Billings and Langley 1971 ) The amount of computation time required was excessive, and so the two sources of shielding were decoupled, as the astronaut location and orientation were found to have weak correlations with dose and were difficult to accurately determi ne ( Billings and Langley 1971 ) NASA Space Radiation Limits NASA is concerned with both deterministic effects, such as cataracts, and radiogenic cancer induction. NCRP Report No. 132, Radiation Protection for Activities in Low Earth Orbit provided recommendations for dose limits addressing both deterministic and stochastic effects ( NCRP 2000 ) Deterministic limits for BFO, skin, and eye lens were given as absorbed dose weighted by relative biological effectiveness ( RBE ) NASA STD 3001, NASA Space Flight Human System Standard also included limits for the heart and CNS as radiation epidemiology has indicated that these organs are sensitive to the deterministic effects of radiation ( NASA 2007 ) The limits in NASA STD 3001 are shown i n

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61 Table 2 2 (all units are in milligray equivalent unless otherwise specified). The NCRP recommended ( 2000 2006 ) and NASA adopted ( 2007 ) a maximum REID of 3% over the lifetime of an astronaut. Furthermore, the REID resulting from space radiation exposure must be less than 3% with 97.5% assurance ( i.e. less than the upper 95% CL ). The ef fective dose limits corresponding to the 3% REID limit for a mission with duration of 1 year or less which vary as a function of age and gender, are shown in Table 2 3 The effective dose limits are about a factor of 3 smaller for the additional 95% CL criterion. As in all applications of radiation protection, the ALARA principle is a legal requirement ( NASA 2007 ) The deterministic dose limits shown in Table 2 2 and stochastic dose limits shown in Table 2 3 are not to be viewed as a resource to be consumed, regardless of circumstances. Every practical effort must be made to avoid unnecessary radiation exposure. Historical Perspectives of the NASA Space Radiation Risk Posture and risk limits are designed to provide protection against detrimental effects on the health of astronauts during a mission ( early effects) and throughout the life of the astronaut (cancer and other late effects). Health effects that occur as a result of radiation exposure include acute radiation syndrome, cancer, late effects such as cataracts, hereditary effects, and neurolog ical disorders, among others ( NCRP 2000 ; Cucinotta et al. 2002 ; Cucinotta et al. 2005 ; Cuci notta et al. 2011 ) A s early as 1961, an ad hoc NAS board was convened to address the issue of s pace radiation in human spaceflight ( NRC 1967 ; NCRP 2000 ) In 1967, the board issued a report, Radiobiological Factors in Manned Space Flight, in which it presented methods for evaluating radiation risk, but declined to present dose limits, as these limits were

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62 viewed as a factor that might jeopardize a mission ( NRC 1967 ; Cucinotta et al. 2002 ) In 1969, NASA requested radiation protection guidelines, with the perspective that radiation risks were thought to be insignificant in comparison to other risks ass ociated with human spaceflight ( NRC 1970 ; NCRP 2000 ) Guidelines were provided for a narrow population, in the form of a doubling dose of 4 Sv, and specific recommendations for organs at risk for deterministic effects ( NRC 1970 ; NCRP 2000 ; Cucinotta et al. 2002 ) 1989 NCRP recommendations The first federally mandated standards for radiation workers were established in 1971 by the Occupational Safety and Health Administration ( OSHA ) and applied to all agencies of the United States ( US ) Governm ent by executive order in 1980 ( NCRP 2000 ) Federal agencies were allowed to adopt supplementary standards based on cost benefit analyses, and in the early 1980s, NASA requested that the NCRP re evaluate its radiation protection guidelines ( NCRP 2000 ) The NCRP issued recommendations in 1989, which considered reports b y the NAS, the United Nations Scientific Committee on the Effects of Atomic Radiation ( UNSCEAR ) the US Department of Energy ( DOE ) updated HZE particle research and improvements in estimates of cancer risk in the years since the 1970 NAS recommendations were adopted ( NCRP 2000 ) The 19 3% increase in cancer mortality with respect to the US population, resulting in age and gender dependent dose limits with limits for specific organs designed to prevent deterministic effects ( NCRP 1989 2000 ; Cucinotta et al. 2002 ) The value of 3% which was strictly applicable to LEO missions, was derived from statistics on work relat ed ( NCRP 1989 2000 ) The 1989 NCRP report

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63 recommended dose limits ranging from 1 Sv for 25 year old females to 4 Sv for 55 year old mal es, considering a 10 y career beginning at the specified age ( NCRP 1989 ) NASA petitioned OSHA for separate radiation protection guidelines, with five key justifications ( NCRP 2000 ) : The r isk was limited to a small population, A radiation hazards appraisal would be conducted before every mission, Detailed cre w exposure records would be maintained, ALARA would be practiced, and Formal operational procedures for limiting exposure would be implemented. OSHA approved the NASA petition in 1990 ( NCRP 2000 ) 2000 NCRP recommendations A reappraisal of the 1989 NCRP recommendations was deemed neces sary as a result of updated reports from the NAS NRC and UNSCEAR, updates from the Japanese Atomic Bomb Survivor cohort, and revisions to recommendations for terrestrial radiation workers from the ICRP and NCRP ( NCRP 2000 ; Cucinotta et al. 2002 ) The NCRP re iterated that in general, radiation protection is based upon three principles ( NCRP 2000 ) : Societal justification for the exposure, The total societal detriment resulting from exposure be kept ALARA, and Limitation of risk for individuals or groups. The basis for LEO limits was re evalua ted As in the 1989 NCRP recommendations, the application of terrestrial radiation worker limits to astronauts was deemed unreasonable, given the short career length of astronauts ( NCRP 2000 ) Drops in occupational death rates, coupled with a reclassification of what constituted an occupational death, rendered the justification of using death rates industries invalid ( NCRP 2000 ; Cucinotta et al. 2002 ) Instead, it was noted that the

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64 1990 ICRP recommendat ions for dose limits of a 5 y average of 20 mSv y 1 ( ICRP 1991 ) resulted in a maximum lifetime risk of between 3% and 4%, and the 1993 NCRP recommendations for dose limits of 50 mSv y 1 and cumulative limit of the product of age and 10 mSv ( NCRP 1993 ) resulted in a maximum lifetime risk of about 3% ( NCRP 2000 ) Recommended limits were again specified as a function of age and gender for a 10 y career beginning at a given age. Deterministi c limits were specified for BFO, eye l ens, and skin for career, 1 y, and 30 d such that the limit for a particular effect was below its estimated threshold ( NCRP 2000 ) For the first time, deterministic limits were specified as the product of absorbed dose and RBE, with recomm end ed RBE values taken from publications investigating proton irradiation and ICRP Publication 58, which addressed neutrons and heavy charged particles ( NCRP 2000 ) The career effective dose limits decreased substantially, with 0.4 Sv recommended for a 25 year old female and 3.0 Sv reco mmended for a 55 year old male ( NCRP 2000 ) Application of uncertainty analysis to risk estimates The 2000 NCRP recommendations briefly addressed uncertainty at the end of the document. The NCRP stated that there was substantial uncertainty in the dose specification, as colon dose was us ed for estimates of solid cancer risk and BFO dose was used for estimates of leukemia risk ( NCRP 2000 ) It may be inferred from the report that the NCRP assumed that crew personal dosimeter ( CPD ) dose would be used as a surrogate for effective dose to the astronaut, as the use of CPD dos e is stated to exaggerate risk estimates ( NCRP 2000 ) Additionally, the 2000 NCRP recommendations noted that from the results of NCRP Report No. 126 ( 1997 ) the 90% confidence interval ( CI ) for risk per unit dose range d from 1.15% to 8.1% per Sv ( NCRP 2000 ) Although CPD dose is used to normalize calculations for trapped protons

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65 ( Cucinotta et al. 2008 ) it is not used as a surrogate for effective dose operationally; in additi on, uncertainty contributions from the high LET components of the space radiation environment were not addressed in NCRP Report No. 126 A NASA technical paper ( TP ) by Cucinotta et al. ( 2002 ) was the first to present a systematic uncertainty analysis of the risk of cancer mortality from space radiation exposu re using the Monte Carlo method The 2002 NASA TP considered low LET uncertainty contributors as presented in NCRP Report No. 126 1 ( NCRP 1997 ) These contributors were ( Cucinotta et al. 2002 ) : Errors in estimation of doses received by Japanese Atomic Bomb Survivor lifespan study ( LSS ) cohor t, Uncertainty in the risk per unit dose, Uncertainty in transfer between populations, Uncertainty in the projection of cancer risks over a lifetime, Unknown uncertainty, and Uncertainty in the dose and dose rate effectiveness factor ( DDREF ) Each contrib utor was represented by a subjective uncertainty distribution. The uncertainty in the DDREF dominate d the low LET uncertainties, contributing about 40% to the total uncertainty ( NCRP 1997 ) Uncertainty in high LET risks was addressed in a similar manner. A key assumption made for high LET risks was additivity: one may calculate the total risk from a given space radiation environment by summing over components of the environment ( Cucinotta et al. 2002 ) As recommended by ICRP Publication 60 ( 1991 ) the LET dependent quality factor was used to represent the relat ive effectiv eness of an ion at a given LET ( Cucinotta et al. 2002 ) The probability 1 Bias in reporting of cancer deaths was ignored without justification.

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66 density functions for quality were taken to be trapezoids, stated in terms of a quality f actor multiplier 2 ; different parameters were used for LET less than or equal to 10 keV m 1 and above 10 keV m 1 ( Cucinotta et al. 2002 ) Environmental uncertainty and transport code uncertainty were also taken into account. Results from the uncertainty analysis indicated that the ratio of upper 95% CL to the point estimate was on the order of 4 .0 to 6 .0 depending upon the exposure scen ario ( Cucinotta et al. 2002 ) T his ratio can be viewed as a factor by which one must divide the number of sk to protect to the upper 95% CL. Clearly, the reduction of uncertainties is important for embarking on missions of extended duration. Another NASA TP by Cucinotta et al. ( 2005 ) updated the uncertainty analysis presented initially in 2002. Instead of using cancer mortality rates, a life table methodology w as employed to account for competing risks ( Cucinotta et al. 2005 ) Again, the 2005 NASA TP considered low LET uncertainty contributors as presented in NCRP Report No. 126 3 ( NCRP 1997 ) These contributors were ( Cucinotta et al. 2005 ) : Errors in estimation of doses received by LSS cohort, Uncertainty in the risk per unit dose, Bias in reporting of cancer deaths Uncertainty in transfer between populations, and Uncertainty in the DDREF. Instead of sampling high LET uncertainties from subjective probability density functions as done previously, a trial function was introduced ( Cucinotta e t al. 2005 ) Parameters describing the trial function were assigned subjective probability density functions based 2 The measures of central tendency of the probability density functions devia ted substantially from the ICRP Publication 60 value for Q It is not evident from the report how the authors mitigated this issue. 3 Uncertainty in projection of cancer risks over a lifetime was ignored, with age of astronaut population and maturity of L SS data given as justification. Unknown uncertainties were ignored without justification.

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67 upon a review of the available radiobiological data 4 ( Cucinotta et al. 2005 ) Environmental and transport uncertainties were captured in a single variable, with the probability density function represented by a normal distribution with standard deviation varying with LET 5 ( Cucinotta et al. 2005 ) Results from the updated uncertainty analysis indicated that the ratio of upper 95% CL to the point estimate was on the order of 3 .0 to 3.5, depending upon the exposure scenario ( Cucinotta et al. 2005 ) A proposed update to the NASA space radiation risk model was recently published ( Cucinotta et al. 2011 ) Three parts of the risk model were dramatically changed: I ncidence based organ specific risk transfer models were implemented wit h an adjustment for mortality, A never smoker population was used as represent ati ve of the astronaut corps, and R adiation quality was recast in terms of effective charge and ion energy instead of LET, with distinct quality factors for solid cancers and leukemia ( Cucinotta et al. 2011 ) Incidence based risk transport was used in the Biological Effects of Ionizing Radiation ( BEIR ) VII report ( NRC 2006a ) and in the updated EPA risk model ( EPA 2011 ) among others. Incidence based risk transport is considered to be more robust than radiation induced mortality e stimates based on cancer mortality data because of statistical advantages (cancer incidence rates a re about double cancer mortality rates ) and reliability (cancer deaths are often misdiagnosed) ( NRC 2006a ) Organ specific incidence models were taken from variety of sources, with the UNSCEAR models 4 Again, the measures of central tendency of the probability density functions deviated substantially the ICRP Publication 60 values for the parameters that describe Q(L) It is not evident from the report how the authors mitigated this issue. 5 The standard deviations in the 2005 NASA TP have no units and so it is difficult to interpret their meaning. Also, the probability density function is assigned a median of 0.65 with unclear justification.

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68 favored for most organs, BEIR VI I models used for the breast and thyroid, and Preston et al ( 2007 ) model s used for organs not add ressed by UNSCEAR or BEIR VII. A never smoker population was used to represent the astronaut corps since over 90% of astronauts were never smokers at the time with the remainder being former smokers ( Cucinotta et al. 2011 ) Age and gender specific lung cancer incidence and mortality rates for never smokers ( Thun et al. 2008 ) were used, age averaged gender specific risks for never smokers relative to the US population were used for other radiation induced cancers associated with tobacco (oral and digestive) and the survival pro babilities were adjusted accordingly ( Cucinotta et al. 2011 ) The re parameterization of radiation quality using effective charge and energy instead of LET was prompted by research indicating that LET does not sufficiently describe the energy deposition characteristics of an ion near the ion track, which manifests in differences in measures of radiation damage at the microscopic level among particles with the same LET but different charge ( Thacker et al. 1979 ; Cucinotta et al. 1997 ; Cucinotta et al. 2000 ) Biophysical models were used to derive a risk cross section, which can be rearranged in a form analogous to the quality factor ( Cucino tta et al. 2011 ) Other changes included revisions to the probability density functions used in uncertainty analysis and a reduction in the DDREF to 1.75 from the NCRP recommended value of 2 ( Cucinotta et al. 2011 ) Overall, risk per unit dose decreased slightly for younger ages and increased substantially for older ages, muting the age at exposure dependen ce exhibited in NCRP Report No. 132 ( Cucinotta et al. 2011 ) risk model were recently reviewed by the NAS ( NRC 2012b ) Requested revisions included choosing a DDREF

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69 based on more recent data, an analysis of epidemiological artifacts induced by using the incidence b ased organ specific risk model (such as those associated with changes in breast cancer incidence and mortality rates ), justification for the radiobiological parameters chosen in the parameterization of quality fact or, and changes to the never smoker implementation ( NRC 2012b ) The updates to the model will likely take months to complete and be accepted as NASA policy and so the pr esent study largely focused on calculation of effective dose as a surrogate for risk as per NCRP Report No. 132 ( 2000 ) protection program at the time of the present study Astronaut Dose Evaluation Using Determinis tic Transport Evaluations of astronaut dose due to a variety of space radiation environments have been published in literature. Phantoms used in the deterministic transport formalism of BRYNTRN and HZETRN include CAM and CAF, CAM with body size variations incorporated, and voxel phantoms. Deterministic Dose Evaluations with CAM and CAF T he August 1972 and the October 1989 SPEs, large integral fluence events with relatively soft proton energy spectra, have been evaluated for astronaut doses using CAM and CA F. Possible acute effects of SPE exposure include lymphocyte depression and vomiting, while possible late effects include cataract formation ( Simonsen et al. 1992 ) In a study by Simonsen et al. ( 1992 ) the radiation doses to CAM and CAF were evaluated for the October 1989 SPE. The proton energy spectrum was represented using the rigidity parameterization 2 12

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70 where F is the integral proton fluence, F 0 and R 0 are fitting parameters, and R is the rigidity, which is given by 2 13 where E is proton energy in MeV. Transport was performed using BRYNTRN and doses were evaluated for water shield thicknesses of 0.5 g cm 2 2.0 g cm 2 5.0 g cm 2 and 10 g cm 2 Comparisons were made of CAM to the equivalent slab approximations for BFO and skin dose equivalent, which showed that the approximation overestimated the dose equivalent by 20% to 50% depending on water shield thickness ( Simonsen et al. 1992 ) Absorbed d oses and dose equivalents were calculated for various organs of CAM and CAF for the October 1989 SPE, an d dose equivalents for selected organs for the August 1972 SPE were shown for comparison. At small shield thicknesses, the absorbed doses from the August 1972 SPE were larger than those resulting from the October 1989 SPE, while at large shield thicknesse s, the opposite was true; this behavior resulted from the fa ct that the October 1989 SPE had a slightly harder spectrum than the August 1972 SPE ( Simonsen et al. 1992 ) Townsend and Zapp ( 1999 ) also evaluated differences between CAM and the equivalent sphere approximation for the October 1989 SPE for the skin, eye lens, and BFO. The aut hors fitted their own spectra to various data points using Equation 2 12, and noted that reasonable differences in data fitting could result in 30% to 40% variations in predicted dose ( Townsend and Zapp 1999 ) In particular, extrapolating from fitting low energy data points was shown to gr ossly underestimate dose. Once again, large differences were found between doses for CAM and doses for the

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71 equ ivalent sphere approximation. T he authors concluded that realistic geometry models should be used for astronaut dose evaluation ( Townsend and Zapp 1999 ) For spectra such as the A ugust 1972 SPE, deterministic effects to the skin, eye lens, and BFO are of greatest concern. Wilson et al. ( 1999 ) noted that many historical SPEs had the potential to induce adverse skin and eye lens effe cts, but only the August 1972 SPE and October 1989 SPE had the potential for significant BFO damage. The had significantly higher proton fluence for energies between 70 and 110 MeV, and occurred over hours rather than days, indicating a much higher dose rate ( Wilson et al. 1999 ) It was found that 10 g cm 2 aluminum shielding would reduce the BFO doses to the exposure limits, and that potentially lethal doses resulted from shielding representative of a space suit or a pressure vessel (PV) ( Wilson et al. 1999 ) The average dose, especially to skin and BFO, has also been recognized to be deficient in representing the range of possible doses for these organs in different parts of the body resulting from differing degrees of shielding. A variety of environments were evaluated in a study investigating distribution of skin and BFO doses including the February 1956 SPE, the August 1972 SPE, the October 1989 SPE, and the 1977 GCR spectrum at solar minimum ( Hoff et al. 2004 ) The differences in do se as a function of position on the body were smaller for GCR spectra than they were for SPE spectra which was expected due to the flat response of GCR with shielding ( Hoff et al. 2004 ) While many studies have investigated radiation doses to CAM and CAF, very few have researched effects of size variations on organ dose equivalent. One such study was performed comparing organ doses for the October 1989 SPE for 5 th 50 th and 95 th

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72 percentile ( PCTL ) scaled versions of CAM ( Zapp et al. 2 002 ) BRYNTRN was once again employed to transport the protons, and the SPE spectrum was represented in the same manner as shown in Equation 2 12 and Equation 2 13. Phantom s caling was performed by scaling the unit vectors of the Cartesian set instead of making changes to CAM ( Zapp et al. 2002 ) Very little difference was observed in skin dose equivalent, while differences of 10% to 15% were seen when comparing results for other organs from the 5 th PCTL and 95 th PCTL to th e results from the 50 th PCTL phantom ( Zapp et al. 2002 ) Results from deterministic simulation using BRYNTRN and HZETRN have been compared to actual measurements performed on a Shuttle mission. A fully instrumented Alderson Ra ndo Phantom torso was flown in the SpaceHab aboard Space Transportation System ( STS ) 91 (orbital inclination 51.6 degrees and altitude 380 km), along with the Alpha Magnetic Spectrometer, which provided high resolution spectral data for hydrogen and heliu m nuclei ( Badhwar et al. 2002 ) The au thors used CAM, scaled to the dimensions of the Alderson Rando Phantom and with arms and legs removed, to calculate organ absorbed dose and dose equivalent ( Badhwar et al. 2002 ) The ratio of BFO absorbed dose to skin absorbed dose was fou nd to be about 80%, which agreed with previous observ ations, but the absorbed dose and dose equivalent measurements did not fit model calculations ( Badhwar et al. 2002 ) In addition, HZETRN underpredicted particle fluxes by 20% ( Badhwar et al. 2002 ) Deterministic Dose Evaluations with MAX and FAX While most previous studies performed astronaut space radiation dose analysis using CAM and CAF, some investigated the use of a different set of phantoms, Male Adult voXel phantom ( MAX ) and Female Adult voXel phantom ( FAX ) MAX a nd FAX

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73 are voxel models based on computed tomography ( CT ) images which were re sampled to a voxel resolution of 3.6 mm ( Kramer et al. 2003 ; Kr amer et al. 2004 ) The organs of the phantoms were altered to match ICRP reference masses by adding and subtracting voxel layers from each organ or adding organs missing from the segmented images ( Kramer et al. 2003 ; Kramer et al. 2004 ) To compare the two phantom sets, CAM and CAF were voxelized by sampling the mathematical regions with the same resolution as MAX and FAX. In general, the organ masses for the voxelized versions of CAM and CAF did not compare well with ICRP reference masses ( Slaba et al. 2010c ) Slaba et al. ( 2010c ) attempted to distribute dose points evenly using a mathematical algorithm known as dtmesh3d which employ ed a signed distance function to iterativel y insert and delete points to achieve even spacing instead of using single points to represent organs. The dtmesh3d algorithm resulted in erroneous dose point distributions for organs that were not contiguous or approximately convex, and so dose points in organs with these characteristics were manually selected. Groupings of dose points were used to calculate organ absorbed dose and organ dose equivalent. The maximum number of dose points used per organ was 8000 800 points for the skin and 500 50 for all other organs ( Slaba et al. 2010c ) The authors transported the August 1972 SPE spectrum and the 1977 solar minimum GCR spectrum using HZETRN. They calculated average organ dose equivalent for each group o f points and chose the value corresponding to the group with the smallest number of points such that the maximum deviation in the group was less than 15% for the aluminum depths evaluated as the representative organ dose equivalent ( Slaba et al. 2010c ) Differences between the male phantoms (CAM and MAX) and the female phantoms (CAF and FAX)

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74 routinely exceeded 15%, and differences in excess of 50% were observed for some organs for the August 1972 SPE; much lower variations were observed for the 1977 solar minimum GCR spectrum ( Slaba et al. 2010c ) Slaba et al. compared their work with a study using the Monte Carlo radiation transport code FLUctuating KAskades ( FL UKA ) to determine radiation doses resulting from the August 1972 SPE for the male voxel phantom G olem and a hermaphroditic mathematical phantom ( Ballarini et al. 2006 ) The skin and BFO doses for MAX, FAX, voxelized CAM, and voxelized CAF were within 40 45% of FLUKA results and the corresponding effective doses were within 30 35% of FLUKA results ( Slaba et al. 2010c ) Kim et al. ( 2010b ) investigated differences between CAM and MAX as well. They used ICRP Publication 103 ( 2007 ) weighting factors instead of the standard ICRP Publication 60 ( ICRP 1991 ) weighting factors. Considerable difference was observed in the RBE weighted BFO dose between CAM and MAX ( Kim et al. 2010b ) The effective doses for CAM and MAX were calculated as a function of spacecraft shielding equivalent thickness for t he August 1972 SPE in interplanetary space, the annual trapped radiation at solar minimum in ISS orbit, the annual GCR at solar minimum in interplanetary space, and the annual GCR at solar minimum in ISS orbit ( Kim et al. 2010b ) The differences in effective dose between CAM and M AX were large at low values of spacecraft shielding equivalent thickness for the August 1972 SPE, with percent differences exceeding 70%. The differences decreased markedly with spacecraft shielding for this environment, as low energy protons were removed and the transported environment hardened. In contrast, both GCR environments (interplanetary space and ISS) resulted in differences less than 10%, with the ISS GCR environment

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75 resulting lower percent differences at small ray thicknesses due to the remova l of lower conclusions regarding the effects of differences in body morphometry must be accompanied by a detailed description of the spacecraft shielding and spectrum used f or evaluation. Monte Carlo Simulation of Space Radiation Transport Codes Used for Space Radiation Transport The use of Monte Carlo radiation transport codes for space radiation dose analyses is becoming more practical with the increase of the availability of affordable high performance computing. These codes include High Energy Transport Code for Human Exploration and Development in Space ( HETC HEDS ) Monte Carlo N Particle eXtended ( MCNPX ) FLUKA, and PHITS. HETC HEDS is an extension of High Energy Trans port Code ( HETC ) a high energy nucleon meson Monte Carlo code developed at Oak Ridge National Laboratory in the 1970s ( Sihver et al. 2008 ) Originally, HETC transported protons, ne utrons, pions, and muons, while neutrons below 20 MeV and photons were stored for later transport by another code, such as Multigroup Oak Ridge Stochastic Experiment code ( MORSE ) Monte Carlo N Particle ( MCNP ) or Electron Gamma Shower ( EGS ) ( Townsend et al. 2005 ; Sihver et al. 2008 ) Charged particle energy loss was performed using the Bethe Bloch stopping power formula with range straggling and scaling relations were used to relate proton stopping power to charged pion and muon stopping power ( Townsend et al. 2005 ) Elastic collisions on elements other tha n hydrogen were neglected for protons and pions and inelastic collisions were based on a combination of experimental cross sections and models ( Townsend et al. 2005 ; Sihver et al. 2008 ) Heavy ion transport was incorporated in HETC to allow for

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76 GCR modeling. Nucleus nucleus cross sections were determined using a combination of the optical potential model and the Tripathi model ( Townsend et al. 2005 ) A nuclear collision module was included using the NUCFRG2 code, which was employed in HZETRN prior to HZETRN2010 to calculate production cross sections for elements with A greate r than 4 ( Townsend et al. 2005 ) In HETC HEDS, the cross sections are randomly sampled to determine fragments produced in a collision; the momentum distribution of projectile products is considered to be isotropic within the projectile rest frame, while the momentum distribution of target products is considered to be isotropic within the target rest frame ( Townsend et al. 2005 ) HETC HEDS only allows combinatorial geometric input; lattice geometries are not available ( Heinbockel et al. 2009a ; Heinbockel et al. 2009b ) Monte Carlo N Particle eXtended Heavy Ion ( MCNPX_HI ) was an alpha version of heavy ion transport, developed for integration with MCNP or MCNPX, which originally transported only light ions ( Sihver et al. 2008 ) It was based on the Los Alamos Quark Gluon String Model (L AQGSM ) event generator, which was benchmarked for a variety of permutations of particle and nucleus interactions for energies ranging from 10 MeV n 1 to 800 GeV n 1 ( Sihver et al. 2008 ) MCNPX_HI was subsequently integrated with MCNPX. FLUKA and PHITS are the two most popular Monte Carlo radiation transport codes used for space environments. FLUKA is capable of transporting hadrons, heavy ions, and electromagnetic particles for energies ranging from a few kiloelectron volts to GCR energies ( Sihver et al. 2008 ) Ionization energy loss is based on a statistical approach instead of stopping power relations ( Sihver et al. 2008 ) An interaction module known as the Pre Equilibrium Approach to Nuclear Thermalization ( PEANUT )

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77 handles hadron nucleus interactions, while nucleus nucleus interactions are addressed with external event generators ( Sihver et al. 2008 ) FLUKA has a GCR generator add on feature and can handle complex geometries, either in the form of combinatorial geometry or lattice structures ( Heinbockel et al. 2009a ) Recently, FLUKA and HETC HEDS were used to evaluate the performance of HZETRN for transport of the February 1956 SPE ( Heinbockel et al. 2009a ) and the 1977 solar minimum GCR spectrum ( Heinbockel et al. 2009b ) The irradiati on geometry consisted of a mono directional beam incident on a 20 g cm 2 aluminum slab, followed by a 30 g cm 2 water slab for both evaluations ( Heinbockel et al. 2009a ; Heinbockel et al. 2009b ) Good agreement among the three codes was observed for the February 1956 SPE for absorbed dose and dose equivalent as a function of depth in water after transport through 20 g cm 2 of aluminum. Much less agreement was observed among the three codes for the 1977 solar minimum GCR spectrum. The discrepancy for GCR was attributed primarily to differences among cross section values for the codes ( Heinbockel et al. 2009b ) Three Dimensional Monte Carlo Space Radiation Tra nsport Balla rini et al. ( 2006 ) examined GCR and SPE organ doses using mathematical and voxel phantoms in FLUKA with 3D irradiation geometries. The mathematical phantom was hermaphroditic; the voxel phantom, Golem was derived from a whole body CT with voxel resolution of 2.08 mm by 2.0 8 mm by 8.00 mm ( Balla rini et al. 2006 ) Aluminum equivalent shielding thicknesses of 1 g cm 2 2 g cm 2 5 g cm 2 and 10 g cm 2 were evaluated, with a cylindrical shell filled with air used as the shielding structure ( Ballarini et al. 2006 ) The August 1972 SPE and GCR spectra at solar min imum and maximum were transported through the shielding and phantom from an isotropically emitting sphere ( Ballarini et al. 2006 ) The results indicated sharply

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78 decreasing dose equivalent with increasing shielding thickness and that the skin dose equivalent greatly exceeded the dose equivalent to other organs for the SPE ( Ballarini et al. 2006 ) A 10 g cm 2 aluminum shelter was found to be sufficient to meet the NCRP limits for LEO for a similar event ( Ballarini et al. 2006 ) For the GCR spectra, an effective dose rate of between 1 and 2 m Sv d 1 was observed, and skin dose was not observed to decrease with increasing aluminum shielding ( Ballarini et al. 2006 ) PHITS has been used extensively in 3D space radiation transport. It simulates ionization through transport processes and uses the mean free path to de termine when collisions occur ( Niita et al. 2006 ; Sihver et al. 2007 ) Ionization transport includes angle and energy straggling, showing good agreement for Bragg peaks and fragmentation tails ( Niita et al. 2006 ) Tabulated nuclear cross section data are used for neutron interactions below 20 MeV, the Los Alamos extension of the Evaluated Nuclear Data File (ENDF) libraries are used for neutron interactions up to 150 MeV, and evaluated data are used for gamma and electron transport below 1 GeV ( Niita et al. 2006 ) High energy neutron and heavy charged particle interactions are simulated through t he Jet AA Microscopic transport model ( JAM ) which addresses hadron hadron interactions, and the Japan Atomic Energy Research Institute (JAERI) Quantum Molecular Dynamics model ( JQMD ) which addresses hadron nucleus and nucleus nucleus interactions, up to energies of 200 GeV n 1 ( Niita et al. 2006 ; Sato et al. 2006 ; Sihver et al. 2007 ) JAM uses a hadronic cascade model, with hadron hadron cross sections parameterized by a resonance model and a string model ( Sihver et al. 200 7 ; Sihver et al. 2008 ) The Breit Wigner resonance model is used at center of mass energies less than around 4 GeV, at which point the resonances widen and the

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79 distances between the discrete levels decrease, and soft processes with little transverse momentum transfer occur ( Sihver et al. 2008 ) Below energies of 10 MeV n 1 only ionization processes are considered for nuclei transport; above this energy, JQMD is used to transport nucl ei ( Niita et al. 2006 ; Sato et al. 2006 ) JQMD considers the nucleus to be a self binding system of nucleons and can estimate the yields of light particles, fragments, and excited residual nuclei ( Niita et al. 2006 ; Sihver et al. 2007 ) Both JAM and JQMD are used for the dynamic portion of the nuclear reaction, but once the dynamics are complete d, the General Evaporation M odel is used to address nuclear de excitation through particle emission in a statistical manner ( Niita et al. 2006 ; Sihver et al. 2007 ) The total nucleus nucleus cross sections used in PHITS are the same as those used by NASA codes ( Niita et al. 2006 ) which is not true o f FLUKA. Previously, the space environment conditions for STS 89 were determined using the Cosmic Ray Effects on Micro Electronics 96 code ( CREME96 ) and 3D Monte Carlo simulations were performed using PHITS ( Sato et al. 2006 ) Measurements performed using a Bonner Ball Neutron Detector were recreated using a simplified model of SpaceHab; the results showed good agreement with the original measured values ( Sato et al. 2006 ) In three other studies, fluence to dose conversion coefficients were calculated for neutrons and protons ( Sato et al. 2009 ) and heavy ions ( Sato et al. 2010 ) up to incident particle energies of 100 GeV n 1 and for charged mu ons and pions up to incident particle energies of 200 GeV n 1 ( Sato et al. 2011 ) In particular, the dose equivalent was calculated using knowledge of the LET spectrum in accordance with ICRP Publication 60 and NASA radiation protection practice ( Sato et al. 2009 ; Sato et al. 2010 ; Sato et al. 2011 )

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80 As with the NASA deterministic codes, results from Monte Carlo simulation using PHITS have been compared to actual measurements performed on orbit. The Matroshka experiment was externally mounted on ISS from 26 February 2005 to 18 October 2005 ( Gustafsson et al. 2010 ) Thermo luminescent d osimeter ( TLD ) measurements were made in 14 of 33 phantom slices every 25 mm on a 3D Cartesian grid ( Gustafsson et al. 2010 ) The GCR source was based on the CREME96 code for solar minimum, while trapped proton fluence was determined from orbital data ( Gustafsson et al. 2010 ) For PHITS simulation, the source was split into a proton only run and a run including GCR ions other than protons. To avoid statistical fluctuations resulting from small heavy ion fluences, GCR ion fluences were weighted by ion charge squared and the contribution to dose was reduced by the same factor after simulation ( Gustafsson et al. 2010 ) Summary of Background and Literature Review NASA developed very detailed computati onal phantoms for the purposes of space radiation dosimetry at a time when the rest of the radiation protection community was only considering simplistic models. CAM and CAF are impressive in their ability to accurately represent human anatomy, but exhibi t almost no ability to accommodate anything but the most simple changes in body morphometry The anatomical realism of CAM and CAF is rare for mathematical phantoms, which are traditionally limited in their ability to represent human anatomy but flexible in terms of sizing MAX and FAX are the only other set of phantoms to be evaluated for utilizati on in space radiation dosimetry. H owever, these are voxel phantoms, which also are also difficult to alter to represent a variety of morphometries. Hybrid ph antoms, which merge the anatomical realism of voxel phantoms and flexibility of traditional mathematical phantoms, have

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81 been shown to represent a variety of human forms ( Johnson et al. 2009 ) could be used to represent astronauts with sizes and morpho metries differing from that of CAM and CAF. Space radiation transport methods at NASA focused almost entirely on the deterministic solution of the 1D Boltzmann radiation transport equation using BRYNTRN and HZETRN. NASA uses these codes operationally for space radiation dose and risk analyses. Several benchmarking efforts, which considered other deterministic and Monte Carlo radiation transport codes, have indicated reasonable agreement among the codes. Three dimensional simulation of the space radiation environment has been used to compare space flight dosimetry and calculated values; however, a systematic compar ison of 1D deterministic codes and 3D Monte Carlo codes with 3D irradiation geometry has not been performed. This sort of analysis would indica te the degree to which transport methods (deterministic vs. Monte Carlo) and geometric factors (1D vs. 3D) affect dosimetry results. From the history of NASA space radiation r isk analysis methods, a clear trend of increasing complexity is observed, moving from simple radiation protection dose limits (doubling dose for cancer with organ specific limits to prevent deterministic effects) to an intricate calculation of REID, considering age and gender specific risk factors and elaborate uncertainty analysis pr ocedures. The maturation of risk modeling has outpaced the development of new computational phantoms and incorporation of alternative transport methods for use in the NASA operational dosimetry framework. A systematic analysis that considered updates to both the human phantom and transport method was warranted.

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82 In the present study, the University of Florida ( UF ) hybrid phantoms were scaled to match 5 th 50 th and 95 th PCTL anthropometric parameters of NASA astronauts in a n Earth based environment Organ dose equivalent and effective dose values, calculated using BRYNTRN and HZETRN, were compared to values for CAM and CAF first using sets of manually selected dose points to determine organ body self shielding with non uniform scaling and then using many randomly selected dose points with uniform scaling Next, the UF hybrid phantoms were altered to accommodate changes to the human body in microgravity Dosimetry was again performed using BRYNTRN and HZETRN for comparison with the Earth based phanto ms. Finally, PHITS was used to calculate organ dose equivalent and effective dose values for the Earth based 50 th PCTL UF phantoms using a 3D isotropic irradiation geometry. T he results of the present study indicate the degree to which phantom size affe cts the calculation of risk associated with space radiation exposure, whether the e ffects of microgravity are relevant in terms of space radiation dosimetry, and how transport method and irradiation geometry affect space radiation dose estimates.

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83 Figure 2 1 Early astronaut phantom ( Fortney and Duckworth 1964 ) Figure 2 2 Full body view of CAM ( ANS 2005 )

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84 Figure 2 3 View of CAM head and shoulders ( ANS 2005 ) Figure 2 4 Equivalence of mono directional slab irradiation and isotropic irradiation through spherical geometries for a dose point ( Fortney and Duckworth 1964 )

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85 Table 2 1 Quality factor definition ( ICRP 1991 ; NCRP 2000 ) Unrestricted LET in water (keV m 1 ) Q(L) < 10 1 10 to 100 0.32L 2.2 > 100 300(L ) 0.5 Table 2 2 Dose limits for non cancer effects ( NASA 2007 ) Organ 30 day Limit 1 year Limit Career Limit Lens 1000 2000 4000 Skin 1500 3000 4000 BFO 250 500 N/A Heart 250 500 1000 CNS (all) 500 1000 1500 N/A 100 250* Units for these values are mGy instead of mGy Eq Table 2 3 Career effective dose limits derived from risk limit ( NASA 2007 ) Age Male Limit (mSv) Fe male Limit (mSv) 25 520 370 30 620 470 35 720 550 40 800 620 45 950 750 50 1150 920 55 1470 1120

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86 CHAPTER 3 RAY TRACING FOR ASTRONAUT DOSIMETRY Ray Tracing Methods For radiation transport purposes ray tracing is used to determine the radiological path length between a source point and a dose point, as shown in Figure 3 1 Particle transport may be performed separately or concurrently. There are t wo main methods for performing ray tracing for radiation transport: mathematical or voxel based approaches. Mathematical ray tracing requires that the surfaces be defined by equations. Then, the intersection of the ray and the surface can be calculated a nalytically or numerical procedures can be used to step a certain length along the ray to determine when a boundary is passed. Mathematical ray tracing can be computationally intensive, especially if complex volumes are defined by a large number of surfac es. In contrast, voxel based ray tracing relies on knowledge of the spacing of orthogonal planes defining the voxel array. The set of intersected planes and the parametric value of the ray at these intersections are determined. Using a reference to a lo ok up table ( LUT ) path length metrics are calculated directly. Voxel based ray tracing is ideally suited to the present study as the UF hybrid phantoms are routinely voxelized for radiation transport programs such as MCNPX. The Voxel Based Ray Tracer Im plementation of Voxel Based Ray Tracing with Astronaut Phantoms For ray tracing voxel phantoms, a Visual Basic (Microsoft Corporation, Redmond, WA) code, Voxel Based Ray Tracer (VoBRaT), was written. Two LUT s, mass density and 50 MeV proton range are use d in VoBRaT to standardize all rays to linear path lengths in water as required for use with tabular data generated by BRYNTRN and

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87 HZETRN. The mass densities for the UF phantom constituents were taken from International Commission on Radiation Units and M easurements ( ICRU ) Report No. 46 ( 1992 ) while the densities for CAM were taken from the material definitions in the CAM report ( Billings and Yucker 1973 ) The 50 MeV proton ranges for the UF phantom materials were calculated using SRIM 2008 ( Ziegler et al. 2008 ) Once the user specifies the phantom type a nd the program loads the voxel array definition file, the density LUT is used to calculate the total mass of the phantom as 3 1 where i is the voxel index; N is the total number of voxels; d x d y and d z are the voxel resolutions in the x y and z directions, respectively; and i is the density of voxel i The ray tracing procedure requires the specification of a dose point and a source point. The first vers ion of VoBRaT used manual dose point selection for all organs except the skin, muscle, BFO, and small intestine. Historically, dose points for these organs were randomly selected ( Billings and Yucker 1973 ) The random selection procedure for organs other than BFO is straightforward: the indices of all voxels comprising the organ are determined and the program randomly selects a row number which indicates a set of coordinates to use as the dose po int. When a row is chosen, it is removed from the array to prevent the possibility of repeating a dose point. As an error preventing measure, if the number of voxels comprising an organ is less than the desired number of random points, the user is notifi ed and every voxel is ray traced. The BFO, though, is a distributed, inhomogeneous organ. In the UF skeletal model, 13 skeletal sites are defined as containing active marrow. These sites are the

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88 Cervical vertebrae, Clavicle, Cranium, Proximal femur, P roximal humerus, Lumbar vertebrae, Mandible, Pelvis, Ribs, Sacrum, Scapulae, Sternum, and Thoracic vertebrae. In a manner similar to that used for the other organs, the indices of all voxels comprising each skeletal site are determined. The desired number of BFO dose points is entered, and the number of points selected from each skeletal site is apportioned based on the relative proportion of act ive marrow in each skeletal site ( Hough et al. 2011 ) Once the dose points are selected, the source point selec tion process commences. First, the distance from the dose point to each corner of the voxel array is determined, and the radius of the sampling sphere is taken to be the maximum distance plus 1 cm to ensure that the entire phantom is enveloped by the samp ling sphere. Next, the program determines the direction cosines to be used in ray tracing. Previously, CAMERA utilized the random and systematic direction cosine methods from MEVDP. For random ray selection, three random numbers ( 1 2 and 3 ) were selected from a uniform distribution in the inclusive interval between 0 and 1 Un normalized ray direction cosines were calculated as 3 2 The magnitude of the un normalized ray direction cosine vector is

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89 3 3 and the normalized direction cosines are thus given by 3 4 While the random selection of rays is straightforward, this method complicates the calculation of dose, since the rays do not represent approximately equal solid angle increments surrounding the dose point. The systematic ray selection procedure is more complex. T he number of desired rays is specified and each ray is def ined as the center of an equal solid angle increment of the unit sphere. For a ray defined by and in spherical coordinates, the direction cosines are given as 3 5 The details of the calculation of and can be found in the MEVDP Technical Report ( Liley and Hamilton 1971 ) For the pres ent study direction cosines determined using the systematic ray selection method with 512 rays were used which mirrors the way in which the NASA body self shielding distributions were generated ( Billin gs and Yucker 1973 ) The direction cosines are given in Appendix A The code for generating direction cosines for more rays has been written following the prescribed method and can be implemented in future versions of VoBRaT if desired. This code is presented in Appendix B. Using the selected direction cosines, the source point coordinates are calculated as

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90 3 6 where x d y d and z d are the dose point coordinates; r is the radius of the sampling sphere; and and are the direction cosines. In order to ensure that division by zero does not occur later in the ray tracing process, if the coordinates of the dose point and source point are equal in any dimension, t he source point coordinate is offset by 1 m. The ray tracing algorithm employed by VoBRaT is based on that previously outlined by Siddon ( 1985 ) For a given source point and dose point, the bounds of intersected planes and the corresponding parametric values for the ray are calculated using the plane indices of the voxels containing the source and dose points and their relative position. The Cartesian coordinates and indices of the first intersected voxel at the entrance to the voxel array are found using the appropriate ray parametric value. Next, the parameter step size in the x dimension, which is constrained due to the ordered nature of the set of orthogonal planes, is calculated as 3 7 The parameter step sizes in the other directions are calculated in the same way Starting with the parametric intersecti on of the ray and the voxel array, a do loop is employed to iteratively find the next parametric intersection value, look up the density and range of 50 MeV protons for the current voxel, and calculate the parametric length through the current voxel as 3 8

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91 where a 1 is the parametric value for intersection with the current voxel, a 2 is the parametric value for intersection with the next voxel, i is the density of the current voxel, R w is the range of 50 MeV protons in water, and R i is the range of 50 MeV protons in the material comprising voxel i ( Ponomarev et al. 2007 ) The do loop is terminated when a 2 is greater than unity, indicating that the dose point is located in the etric length from the last voxel is then calculated. Finally, the total radiological path length in water is calculated as 3 9 where J is the total number of voxels intersected by the given ray. The ray tracing procedure is pe rformed in two nested for loops: (1) an outer loop which addresses each dose point, and (2) an inner loop which addresses each source point. For each run of VoBRaT, the direction cosines and resulting radiological path length in water are written to an Excel (Microsoft Corporation, Redmond, WA) file for later use. The VoBRaT source code is given in Appendix C. Validation Using Sphere and CAM VoBRaT was validated to ensure that the calculations were performed as expected. The first case tested for validation was a 30 cm diameter unit density water sphere surrounded by vacuum. The dose point was taken to be the center of the sphere. For the 512 ray systematic distribution, the mean radiological path length in water was found t o be 14.984 cm (0.11% error), with a standard deviation of 0.069 cm or 0.46%. The time required for the calculation was 0.2 ms per ray on a Dell Precision T3400 workstation with an Intel Core 2 Duo E4600 2.4 GHz processor and 3.25 GB of random access memo ry ; thus, the time required for ray tracing would not preclude the

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92 use of many dose points to represent an organ for future analyses. VoBRaT performed well for this test case, considering that both the absolute standard deviation and the absolute error we re fractions of the voxel resolution, and that the relative standard deviation and relative error were small. Next, VoBRaT was validated using dose point s within CAM. First, CAMERA was used to generate the body self shielding distribution for the right ey e lens. For the same dose point, the body self shielding distribution was generated using VoBRaT. Figure 3 2 shows the two distributions. Excellent agreement was o bserved, especially above path lengths of 1 cm of water. The agreement below path lengths of 1 cm of water can be attributed to artifacts from the voxelization process, since the surfaces comprising CAM were no longer smooth. A heart dose point was also evaluated, to ensure that VoBRaT would perform well relative to CAMERA for a deeper seated organ. The results are shown in Figure 3 3 and once again indicate very g ood agreement. The validation results from the 30 cm unit density water sphere, along with the validation results from two CAM dose points, indicated that the VoBRaT was operating properly and could reliably produce body self shielding distributions for v oxel phantoms. University of Florida Hybrid Phantoms First generation computerized anatomic models are based on 3D mathematical surface equations (stylized phantoms), while second generation models are created through segmented medical images (voxel phantoms). The UF hybrid phantom is a third generation human anatomic model that combines the best features of each: an atomic flexibility, a s afforded by stylized phantoms, as well as anat omic realism, as afforded by voxel phantoms The CAM phantom ( ANS 2005 ) and the UF hybrid phantom are displayed in Figure 3 4

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93 To construct the UF Hybrid Phantom Series, organs in previously acquired CT images were segmented. The contour files were converted to polygon mesh files, and then imported into the non uniform rational B spline ( NURBS ) based solid modeling program Rhinoceros (McNeel North America, Seattle, WA) Here, NURBS models were created from the polygon mesh files. Some organs, namely the brain, lungs, and extrathoracic airways, were left in polygon mesh due to the inherent difficulty of modeling these organs with smooth surfaces. In addition, stylized representations were used for organs such as the eyeballs, urinary bladder, eye lens, tongue, and sex specific organs, due to the accuracy of simple shapes in representing these organs ( Lee et al. 2010 ) The organ masses were matched to the values reported in ICRP Publication 89 ( 2002 ) while the organ densities were matched to the values reported in ICRU Report No. 46 ( ICRU 1992 ) Internal organs and exterior body dimensions were matched to reference values to within 1% and 4%, respectively ( Lee et al. 2010 ) The UF series includes children of five ages, as well as the ICRP reference adult male and female. Development of First Version of UF As tronaut Phantoms Target Anthropometric Data Understanding the impact of body size on body self shielding required the use of target anthropometric pa rameters for scaling of the UF Hybrid ADult M ale (UFHADM) and UF Hybrid ADult Female (UFHADF) The most re anthropometric design criteria are listed in NASA CxP 70024 Revision C, Constellation Program Human Systems Integration Requirements document ( NASA 2009 ) Unfortunately, this document presents a gender pooled set of anthropometric parameters, and thus it was necessary to use data from the older NA SA STD 3000,

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94 Man Systems Integration Standards document (MSIS) ( NASA 1995 ) For both males and females, anthropometric data were provided for 5 th PCTL 50 th PCTL and 95 th PCTL It should be noted that these data were not based upon the astronaut population. The male data were for 40 year old American men, while the female data were for 40 year o ld Japanese women. T he rationale for presenting these anthropometric parameters was that the astronaut population was being drawn increasingly from the general world population instead of the United States military population, and American men represent s ome of the largest humans while Japanese women represent some of the smallest humans ( NASA 1995 ) From the anthropometric data available dimensions that were thought to most influence radiation dose calculations (primarily those associated with the torso) were selected These data, along with corresponding dimensions of CAM and CAF, are presented in Table 3 1 Initial Scaling Methods Once the anthropometric parameters were selected the phantoms were scaled in a consistent and methodical manner, developed and validated by Johnson et al. ( 2009 ) First, the upper body outer body contour and organs were scaled together in all three dimensions to match sitting height. Next, t he legs were scaled in three dimensions to match total standing height. Once the gross scaling was completed, fine level scaling was performed to match the secondary anthropometric parameters listed in Table 3 1 and further adjustments were performed to match total body mass to within 3%. Waist circumference was the one parameter that could not be matched within a reasonable tolerance. For the UF male 5 th PCTL phan tom, the waist circumference was 85.7 cm instead of 77.1 cm; for the UF female phantoms, the waist circumferences were approximately 7 cm greater than those shown i n Table 3 1 The decision to allow waist

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95 circumference to deviate from the specified values was made to accommodate total body mass matching. T he parameters listed in NASA STD 3000 are gleaned from independently calculated distributions, and so it is very likely that one individual would not have body morphometry that fully encompassed all dimensional characteristics of a single percentile. Once the phantoms were scaled appropriately, they were voxelized using an in house MATLAB code. Voxel dimensions were specified as 0.2 cm by 0.2 cm by 0.2 cm, which allowed for a reasonable skin thickness. The unvoxelized UFHADM scaled phantoms are displaye d in Figure 3 5 and the unvoxelized UFHADF scaled phantoms are displayed in Figure 3 6 Body Self Shielding Distribution s for First Version of UF Astronaut Phantoms Once the capability for creating body self shielding distributions for voxel phantoms was realized and astronaut phantoms were created the impact of body morphometry on the body self shielding distributions was investigated. T he gonads (testes and ovaries), colon, BFO, and female breast are important for the calculation of effective dose using the current NASA methods ( NCRP 2000 ) T he BFO, skin, and eye lens are important for the calculation of risk of deterministic effects using the current NASA methods ( NCRP 2000 ) All organs except the skin, BFO, muscle, and small intestines were repr esented by one or more manually selected dose points. Great care was taken to ensure that the dose po int locations were anatomically consistent across the different phantoms Since the skin and BFO are distributed organs, the results from 35 randomly selected dose points were averaged along common direction cosines. This number was chosen as it reflects th e approximate number of dose points for skin and BFO chosen in a previous analysis ( Billings et al. 1973 ) The resulting body self shielding distributions fo r selected organs are displayed in Figure 3 7 through

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96 Figure 3 13 Results from the voxelized CAM and derived CAF distributions are also shown for comparison. Body self shielding distributions from all organs are shown in Appendix D At low ray thicknesse s, the ordering of many of the distributions did not follow the expected pattern. This is clearly exhibited in the right t estis ( Figure 3 7 ), right ovary ( Figure 3 8 ), and right eye lens ( Figure 3 13 ). Since these organs were represented by single dose points, there were two possible explanations for the exhibited discrepancy: (1) voxelization artifacts or (2) artifacts induced by the non uniform scaling employed in an attempt to match a variety of anthropometric parameters and total body mass. For the right eye lens, voxelization artifacts obviously contributed to the discrepancy; the female distributions star t ed at either 0.1 cm or 0.3 cm, values separated by the voxel resolution of 0.2 cm For the other distributions, however, the contribution from the two possible explanations was not clear The effect on organ dose equivalent can only be known after perfo rming transport and interpolating the body self shielding ray lengths on the resulting depth dose distributions. For the distributed organs, it was expected that the general trend of increasing body self shielding for larger phantoms would be exhibited cle arly. This was true of the BFO distributions ( Figure 3 11 ) but not true of the skin distributions ( Figure 3 12 ). The small number of randomly selected dose points was thought to be the reason for this discrepancy. The BFO distribution was affected less since the locations of the BFO dose points were restricted based upon the ske letal region; for the skin, there was no such restriction, and so it was more likely that the distribution of skin dose points did not represent the entire organ accurately One thousand randomly selected dose points

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97 were used to generate new average body self shielding distributions for the BFO, skin, and muscle, while 500 randomly selected dose points were used to represent the small intestines. The new distributions for the BFO and skin are shown in Figure 3 14 and Figure 3 15 respectively. I t was found that the number of dose points originally used with CAM to represent the skin was insufficient. General differences between the two phantom sets result ed from some combination of body morphometry or anatomical modeling. As an example, consider the BFO and skin distributions averaged over 1000 points ( Figure 3 14 and Figure 3 15 ). For both of these distributions, the expected pattern of shielding wa s exhibited: the larger the phantom, the greater the shielding. The positions of the CAM and CAF body self shielding distributions relative to the other phantoms were not as expected For the BFO, the CAF body sel f shielding distribution followed the 5 th PCTL UF female, wh ile the CAM distribution followed the 95 th PCTL UF female. In contrast, for the skin, the CAF body se lf shielding distribution tracked with the 95 th PCTL UF female, w hile the CAM distribution tracked with the 5 th PCTL and 50 th PCTL UF m ale. By height and mass, the ordering of the skin distributions was expected, whereas the orderin g of the BFO distributions seemed awry; one would expect, based on body morphometry alone, that the pattern observed in the plot of skin distributions would a lso be exhibited in the plot of BFO distributi ons. This discrepancy indicated the importance of anatomical modeling in phantoms; the shift s of the BFO body self shielding distributions for CAM and CAF indicate that the BFO was shielded by less soft tissue than the BFO for the UF phantoms. These highly distributed organs were a special case. For organs that were localized, the local anatomical modeling was expected to

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98 have a much greater impact on body self shielding distributions as a result of the diver gence of rays emanating from a given dose point. The impact of variations in body morphometry was not consi stent over the entire phantom; the closer to the center of mass of the phantoms, the more variation was observed among the body self shielding distri butions. Greater differences were observed for dose points with more shielding An example of this was the rectosigmoid colon dose point ( Figure 3 9 ) Compared with more lightly shielded organs, such as the testes, eye lens, or even the female breasts, differences above about 10 cm of water were much greater. Organs that tend to be more centrally located within the body, especially in the abdominal region, are considered deep, and also contribute substantially to the NASA calculation of effective dose. Therefore, the differences in body self shielding could have an impact on the effecti ve dose calculation, which is used to evaluate astronaut risk. The finding that differences in deep organs were enhanced relative to differences in shallow organs can be explained by the relative position of the body with respect to the dose point. For a dose point on the periphery of the body, a smaller fractional solid angle about that dose point is subtended by the torso. Since the torso was most affected by changes in body morphometry, it was expected that the greater the solid angle subtended by the torso, the greater the differences in body self shielding distributions. Dose points in the head were an extreme example of this. The differences observed for the eye lens and brain dose points were much less than those observed for organs in the torso, particularly the abdomen.

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99 The differences in gonad shielding between the NASA phantoms and the UF phantoms were more substantial for the females than the males. This was attributed to two effects. First, the solid angle shielding effect expla ined previously accounted for fewer differences among the t estis body self shielding distributions. The ovaries, which are more deeply seated than the testes exhibit ed greater variation. Variable scaling was implemented in CAF; however it was evident that CA F provided less shielding to the ovaries than the female UF phantoms. This was due to the intestines in CAF being modeled as a uniform region of low density (0.457 g cm 3 ). The same e ffect was seen with the body self shielding distributions for the colon The UF phantoms, however, incorporate a tubular intestinal model structure with realistic densities for the intestinal walls and contents. Therefore, the body self shielding distribution for the CAF ovary was smaller than that of the UF phantom ovary a round water e quivalent thicknesses of 10 cm Chapter Summary A voxel based ray tracing code, VoBRaT, was written for the purposes of generating body self shielding distributions in voxel phantoms. Male and female UF hybrid phantoms, representing the 5 th 50 th and 95 th PCTL anthropometric values as presented in the NASA MSIS ( NASA 1995 ) w ere ray traced, and the results were compared to body self shielding distributions from voxelized versions of CAM and CAF. The i mpacts of anthropometric modeling on body self shielding distributions were found to vary with location; organs with a larger f ractional solid angle subtended by the torso exhibited larger differences in body self shielding distributions.

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100 Figure 3 1 Determining the amount of material separating a source point and a dose point in a collection of arbitrary regions Figure 3 2 Comparison of CAMERA output and VoBRaT output for right eye lens dose point in CAM ( Bahadori et al. 2011 )

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101 Figure 3 3 Comparison of CAMERA output and VoBRaT output for heart dose point in CAM ( Bahadori et al. 2011 ) Figure 3 4 CAM phantom external view (lef t), CAM phantom internal view (middle), UF hybrid adult male phantom (right) ( Bahadori et al. 2011 )

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102 Figure 3 5 UF hybrid adult male 5 th PCTL (left), 50 th PCTL (middle), and 95 th PCTL (right) phantoms ( Bahadori et al. 2011 ) Figure 3 6 UF hybrid adult fe male 5 th PCTL (left), 50 th PCTL (middle), and 95 th PCTL (right) pha ntoms ( Bahadori et al. 2011 )

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103 Figure 3 7 Right testis body self shielding distributions Figure 3 8 Right ovary body self shielding distributions

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104 Figure 3 9 Rectosigmoid colon body self shielding distributions Figure 3 10 Right breast body self shielding distributions

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105 Figure 3 11 BFO body self shielding distributions with 35 random dose points Figure 3 12 Skin body self shielding distributions with 35 random dose points

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106 Figure 3 13 Right eye le ns body self shielding distributions Figure 3 14 BFO body self shielding distributions with 1000 random dose points

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107 Figure 3 15 Skin body self shielding distributions with 1000 random dose points

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108 Table 3 1 Selected anthropometric data (from NASA 1995 unless otherwise noted) Measurement (unit) CAM M5 a M50 M95 CAF F5 F50 F95 Stature (cm) 175.5 b 169.7 179.9 190.1 161.5 d 148.9 157.0 165.1 Sitting height (cm) 93.7 b 88.9 94.2 99.5 86.2 e 78.3 84.8 91.2 Mass (kg) 69.5 c 65.8 82.2 98.5 55.9 f 41.0 51.5 61.7 Hip Breadth (cm) 34.3 d 32.7 35.8 39.0 35.0 d 30.5 32.9 35.3 Waist Circum (cm) 80.5 b 77.1 89.5 101.9 55.3 63.2 71.2 Buttock Circum (cm) 95.8 b 91.0 100.2 109.4 79.9 87.1 94.3 Thigh Circum (cm) 56.9 b 52.5 60.0 67.4 45.6 51.6 57.7 Biacr Breadth (cm) 37.9 41.1 44.3 32.4 35.7 39.0 Chest Breadth (cm) 29.5 d 29.7 33.2 36.7 28.0 d 24.5 26.8 29.0 Bicep Circum (cm) 32.5 b 27.3 31.2 35.1 25.6 d 21.8 25.5 29.3 a The first letter indicates gender. The number that follows indicates percentile. b Kase 1970 c Billings and Yucker 1973 d Yucker and Huston 1990 e Determined from the 0.92 vertical scaling factor f Yucker 1992

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109 CHAPTER 4 DETERMINISTIC TRANSP ORT AND DOSIMETRY Space Radiation Environment Models The space radiation environment is time varying and complex; the types of exposure scenarios can be roughly divided into geomagnetically trapped protons, GCR, and SPE. Geomagnetically Trapped Protons Geomagnetic ally trapped radiations are present in the Van Allen belts due to planetary magnetic field interactions with charged particles. There are two main belt regions: the inner and outer belts. The inner belt consists mostly of protons, whereas the outer belt consists mostly of electrons ( NRC 2006b ) LEO missions are flown within the inner belt, and so the dose contribution from geomagnetically trapped protons must be evaluated. NASA currently uses the AP8 (acronym unknown) geomagnetically trapped proton model with the 1965 International Geomagneti c Reference Field model ( Wilson et al. 1997 ; NRC 2008 ) Proton spectra for altitude s ranging from 300 km to 630 km altitude and for orbital inclinations of 28.5 degrees and 51.6 degrees are available. The solar activity le vel also has an impact on the geomagnetically trapped proton spectrum: at solar maximum, the proton levels are lower than at solar minimum due to atmospheric interactions ( NRC 2006b ) The proton spectrum for an altitude of 351.5 km (190 nautical miles) and 51.6 degrees inclination at solar minimum was used to represent a worst case scenario for geomagneti cally trapped proton levels for an orbit similar to that of the orbit of ISS. This proton spectrum is displayed in Figure 4 1

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110 Galactic Cosmic Rays GCR consist of a spectrum of heavy ions representing a low flux background level of slowly varying radiation in space. Protons comprise the majority of GCR, with helium ions being the next most abundant species at around 10% of the total ( NRC 2008 ) A much smaller fraction of GCR consists of ions heavier than h elium; iron ions are the heaviest nuclei with a significa nt abundance, but GCR spectra are usually modeled with small cobalt and nickel contributions as well ( NCRP 2006 ) The heavy ion component of GCR is a problem in space radiation shielding due to fragmentation effects and the hig h LET nature of the particles. The relative abundances of ions in GCR at three energies are shown in Table 4 1 GCR fluxes are modulated by solar activity, with maxi mum values occurring at solar minimum and minimum values occurring at solar maximum ( NRC 2008 ) F or the present study the GCR spectra and composition at the 1977 solar minimum, which represent s the highest observed GCR fluence rates, were used oxygen and iron compone nts of GCR at the 1977 solar minimum are shown in Figure 4 2 These spectra were taken from the distribution of HZETRN 2005 ( Wilson et al. 2006 ) Solar Particle Events SPE result from occurrences of spurious solar activity, which accelerate a large number of protons with high energies away from the surface of the sun. These events usually last on the order of hours or days, and have been shown to result in high doses for high fluence events, especially for small shielding thicknesses ( Simonsen et al. 1992 ; Ballarini et al. 2006 ) SPE are of concern outside of LEO, since the geomagnetic field deflects most of the ions accelerated to wards Earth during these events. Unlike

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111 geomagnetically trapped protons and GCR, SPE s are not well forecasted with current capabilities. Although SPE contain heavier ions, the relative abundances of these ions are many orders of magnitude less than that of protons. SPE proton energy spectra a substantial number of protons of very high energies. Soft spectra are of concern for lighter shi elding configurations, while hard spectra are of concern for heavier shielding configurations. Historically, a number of very high fluence events have been used to represent the most intense SPEs. The three high fluence e vents of interest for the present study were the October 1989 SPE, events are shown in Figure 4 3 These spectra were taken from the BRYNTRN code ( Wilson et al. 1989 ) Deterministic Transport Results Geomagnetically Trapped Protons The space environment spectra discussed previously were transported in slab thicknesses of aluminum and water; the trapped proton and SPE spectra were transported using BRYNTRN, while the GCR spectrum was transported using H ZETRN. The resulting depth dose distribution for the trapped proton spectrum is shown in Figure 4 4 Trapped protons were attenuated very quickly by both aluminum a nd water shielding. However, it is evident from the plot that water is a better attenuator than aluminum on a per unit mass basis This is true for two reasons: water is a low Z material with many protons, which remove the maximum kinetic energy pos sible from

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112 the incident protons, and water molecules are much less likely to fragment than aluminum atoms. Galactic Cosmic Rays In contrast, the depth dose distribution for the GCR spectrum is shown in Figure 4 5 Neither water nor aluminum was particularly adept at shielding GCR ions and resulting secondary particles in the simulation GCR ions have much more energy on a per nucleon basis than trapped protons. Even tho ugh the differential flux was orders of magnitude larger for trapped protons at low energies, the combination of high differential particle flux at high energies an d higher quality factors resulted in dose equivalent rates comparable to that of trapped protons at shallow points within the slab shields and much higher dose rates at deeper points within the slab shields. Also, GCR ions can fragment, yielding smaller secondary heavy charged particles cap able of delivering dose deeper within the shields. Based on the depth dose distributions of trapped protons and GCR ions, it was expected that organ depth and phantom size would have a much larger impact on trapped proton dose equivalent rates when compar ed with GCR dose equivalent rates. Solar Particle Events Depth dose distributions for the February 1956, October 1989, and August 1972 SPE spectra are shown in Figure 4 6 Figure 4 7 and Figure 4 8 respectively. Note that the z axis repres ents dose equivalent instead of dose equivalent rate, since the flux was integrated over the SPE duration to yield a total fluence per event. The February 1956 SPE spectrum is representative of a high fluence event with a large contribution from protons wi th high energies. Most of the a ttenuation for this event occurred in the low thickness range, where the lower energy protons were removed.

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113 The attenuation at deeper points within the slab shield was much less pronounced than fo r the trapped proton spectr um. The October 1989 and August 1972 spectra are representative of high fluence events with larger contributions from protons with low energies. At shallow depths, the dose equivalent imparted by these spectra was much larger than the dose equivalent impa rted by the February 1956 SPE spectrum. Also, much more attenuation occurred over the same aluminum and water slab thicknesses for these spectra. Therefore, it was expected that regardless of aluminum slab thickness, the dose equivalent differences for o rgans at different depths would be larger for the soft spectra than the differences resulting from the February 1956 SPE spectrum. Organ Dose Equivalent Results for First Version of UF Astronaut Phantoms To restrict the comparison, and for practical implem entation in future Monte Carlo studies, a reasonable number of aluminum equivalent shielding thicknesses were chosen for investigation. Traditionally, aluminum equivalent shielding thicknesses ranging from 0.4 g cm 2 to 10 g cm 2 have been studied, repres enting shielding during extravehicular activity (EVA) to a hypothetical radiation storm shelter ( Wilson et al. 1999 ; Zapp et al. 2002 ; Slaba et al. 2010c ) For the present study aluminum equivalent thicknesses of 0.5 g cm 2 2 g cm 2 and 10 g cm 2 were used to represent shielding during EVA, shielding in a PV and shielding in a radiation storm shelter, respectively. To determine organ dose equivalent the dose equivalent corresponding to each ray thickness determined from ray tracing was calcu lated. Since each ray represented an approximately equal portion of the spherical solid angle surrounding the chosen dose point, the dose equivalent to a point within an organ was calculated as the average of dose equivalent values for the 512 rays emanating from the dose point For the

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114 distributed organs (BFO, skin, small intestine, and muscle), the dose equivalent to the various points used to represent the organ were averaged This procedure was performed for all five space radiation environments of interest. Results for t he August 1972 SPE with suit shielding, GCR spectrum with PV shielding, and the February 1956 SPE with radiation storm shelter shielding are shown in Table 4 2 Table 4 3 and Table 4 4 respectively. Note that the results for the GCR spectrum are given in rate based units while the results for the SPE s are given in cumulative units Results for all combinations of shielding and space radiation environment are presented in Appendix E In general, the results indicate d that the larger the phantom, the smaller the organ dose equivalent There were exceptions, especially when comparing CAM and CAF to the UF male and female phantoms, which can be attributed to the effects o f anatomical modeling. For soft proton spectra this effect was more pronounced, while for the harder proton spectrum and the GCR spectrum, there was less variation in organ dose equivalent. However, some results appear ed to be spurious; the female eye le ns in Table 4 2 is an example for which the 95 th PCTL UF female phantom exhibited a much higher dose equivalent than the 50 th PCTL UF female phantom. Other organs that exhibited unexpected behavior include the colon, testes thyroid, parotid, and lung. Deviations from expected results tend ed to occur for proton irradiation and small thicknesses of aluminum equivalent shielding, indicating that the deviation for low ray thicknesses observed while ray tracin g the phantoms impact ed the dose calculation and needed to be addressed.

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115 Previously, it was hypothesized that the differences in body self shielding distributions could be attributed to either voxelization artifacts or non uniform scaling. In an attempt t o dec ipher which of these contributed to some of the observed differences, test cases were run with the testes and eye lenses, in which a large number of randomly selected voxels were ray traced, with the distributions for each point averaged. This method muted the effects of voxelization artifacts The results for the testes are shown in Figure 4 9 while the results for the eye lenses are shown in Figure 4 10 It was evident that below ray thicknesses of around 13 cm for the testes and 3 cm for the eye lenses in the case of the UF female phantoms, the order of the body self shie lding distributions was not consistent with what would be expected based on body size alone. Therefore, the method of scaling employed for the first version of UF astronaut phantoms induced artifacts in organ dose equivalent because of the steep decline o f dose equivalent with water thickness for small aluminum equivalent shielding thicknesses. Chapter Summary The three major sources of radiation of concern in spaceflight (trapped protons, GCR, and SPE) were described. Representative spectra of each of source were transported through water and aluminum shielding using BRYNTRN and HZETRN. The softer space radiation spectra, such as the August 1972 SPE and October 1989 SPE, exhibited substantial attenuation with increasing shielding for both materials, wh ile the more energetic space radiation spectra, such as the 1977 solar minimum GCR, showed relatively little attenuation with increasing shielding. After interpolating for organ dose equivalent, inconsistencies were found among the values for some dose po ints and space radiation spectra resulting from inconsistencies in the body self shielding

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116 distributions. Our original hypothesis, that the unexpected pattern of body self shielding distributions was caused primarily by voxelization artifacts, was shown t o be false, as inconsistencies in the body self shielding distributions were observed for the testes and female eye lens despite ray tracing more points in these organs.

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117 Figure 4 1 Trapped proton spe ctrum for altitude of 351.5 km and orbital inclination of 51.6 degrees at solar minimum ( Bahadori et al. 2011 ) Figure 4 2 Free space GCR energy spectra (selected elements) for 1977 solar minimum ( Bahadori et al. 2011 )

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118 Figure 4 3 SPE spectra for three large historic events ( Bahadori et al. 2011 ) Figure 4 4 Dose equivalent rate as a function of aluminum and water thickness for trapped proton spectrum

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119 Figure 4 5 Dose equivalent rate as a function of aluminum and water thickness for GCR spectrum Figure 4 6 Dose equivalent as a function of aluminum and water thickness for February 1956 SPE proton spectrum

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120 Figure 4 7 Dose equivalent as a function of aluminum and water thickness for October 1989 SPE proton spectrum Figure 4 8 Dose equivalent as a function of aluminum and water thickness for August 1972 SPE proton spectrum

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121 Figure 4 9 Testes body self shielding distributions with 500 random dose points Figure 4 10 Eye lenses body self shielding distributions with all eye lens voxels

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122 Table 4 1 Relative abundances of ions comprising GCR at three energies ( NCRP 2006 ) Z Element 0.2 GeV n 1 1 GeV n 1 5 GeV n 1 1 H 2,200,000 500,000 2,800,000 500,000 4,600,000 700,000 2 He 340,000 80,000 250,000 30,000 230,000 30,000 3 Li 1,000 60 1,400 140 960 100 4 Be 450 50 730 67 680 53 5 B 2,100 90 2,340 102 1,600 69 6 C 8,500 290 7,100 285 6,460 258 7 N 1,940 80 2,000 82 1,610 61 8 O 7,770 280 6,430 243 6,190 214 9 F 183 13 145 11 115 6 10 Ne 1,120 60 1,050 43 960 35 11 Na 273 34 224 12 188 8 12 Mg 1,430 60 1,330 54 1,260 46 13 Al 252 30 229 12 207 9 14 Si 1000 1000 1000 15 P 40 7 47 4 37 2 16 S 164 12 206 11 190 8 17 Cl 36 5 45 4 37 2 18 Ar 63 6 90 7 68 4 19 Ca 51 6 66 6 51 4 20 K 135 10 147 10 119 6 21 Sc 29 5 33 3 22 2 22 Ti 107 9 98 8 74 4 23 V 57 6 44 4 38 3 24 Cr 109 10 98 4 83 5 25 Mn 72 12 55 5 56 4 26 Fe 602 32 607 34 685 37 27 Co 2 1 3 1 4 1 28 Ni 29 4 27 4 36 3 Table 4 2 Organ dose equivalent s (Sv) August 1972 SPE with suit shielding Organ CAM M5 M50 M95 CAF F5 F50 F95 BFO 1.83 1.86 1.77 1.71 2.08 2.59 2.46 2.03 Skin 18.09 19.16 18.85 18.97 18.86 19.95 19.51 19.61 Small Intestine 1.62 1.17 0.80 0.67 1.87 1.43 1.33 1.13 Muscle 4.71 4.51 4.04 3.78 5.13 4.98 4.48 4.49 R Eye Lens 13.92 13.81 11.64 10.94 14.64 22.71 15.75 19.97 L Eye Lens 14.57 13.79 11.61 10.92 15.30 21.76 15.78 18.41 R Eyeball 2.70 3.25 3.40 3.20 3.08 3.74 3.58 3.56 L Eyeball 2.83 3.25 3.40 3.20 3.22 3.56 3.59 3.35 Anterior Stomach 1.42 1.41 1.02 1.09 1.64 2.41 2.75 1.87 Posterior Stomach 0.51 0.47 0.45 0.34 0.63 1.01 0.90 0.85 Ascending Colon 2.04 1.25 1.11 0.79 2.33 1.44 1.26 0.95

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123 Table 4 2. Continued Organ CAM M5 M50 M95 CAF F5 F50 F95 Transverse Colon 2.14 6.71 6.36 7.06 2.44 8.24 8.05 7.22 Descending Colon 2.17 1.07 0.87 0.70 2.48 1.26 1.22 0.98 Rectosigmoid Colon 1.11 0.74 0.40 0.36 1.31 0.69 0.49 0.43 L Liver 0.50 0.48 0.42 0.45 0.61 0.89 1.04 0.73 R Liver 0.53 0.54 0.42 0.32 0.65 0.71 0.58 0.59 R Upper Mid Lung 1.49 1.38 1.27 1.22 1.75 2.09 1.77 1.64 L Upper Mid Lung 1.61 1.29 1.26 1.17 1.88 2.11 1.88 1.76 R Mid dle Anterior Lung 2.37 1.28 1.18 1.31 2.70 2.08 2.37 1.85 R Mid dle Mid Lung 1.35 1.37 1.15 1.08 1.59 1.69 1.67 1.38 R Mid dle Posterior Lung 1.69 1.23 1.14 1.07 1.96 1.44 1.33 1.14 L Mid dle Ant erior Lung 2.24 1.26 1.26 1.44 2.57 2.32 2.86 2.10 L Mid dle Mid Lung 1.48 1.19 1.09 1.05 1.74 1.53 1.61 1.29 L Mid dle Post erior Lung 1.71 1.09 1.06 0.97 1.99 1.47 1.32 1.22 R Base Ant erior Lung 1.67 1.70 1.20 1.16 1.94 1.68 1.91 1.26 R Base Post erior Lung 1.60 1.21 1.24 1.11 1.87 1.51 1.42 1.11 L Base Ant erior Lung 1.67 1.74 1.45 1.31 1.94 1.78 1.92 1.27 L Base Post erior Lung 1.62 1.29 1.52 1.60 1.89 1.35 1.24 1.05 Esophagus 0.73 0.41 0.37 0.32 0.89 0.68 0.55 0.50 Bladder 0.45 0.44 0.27 0.23 0.55 0.60 0.62 0.56 L Thyroid 8.98 2.27 1.84 1.89 9.58 4.36 3.60 2.57 R Thyroid 8.98 2.67 2.06 2.26 9.58 5.20 3.79 2.59 Anterior Brain 1.16 1.06 0.91 0.81 1.39 1.28 1.11 0.97 Mid Brain 1.06 0.96 0.85 0.78 1.28 1.15 1.03 0.87 Posterior Brain 2.33 2.19 1.88 1.71 2.69 2.49 1.82 2.02 L Parotid 4.45 5.09 4.55 4.40 4.92 4.42 5.26 4.77 R Parotid 4.41 4.67 4.55 4.02 4.88 4.93 4.51 4.68 L Adrenal 0.85 0.39 0.42 0.32 1.02 0.77 0.61 0.57 R Adrenal 0.77 0.42 0.45 0.34 0.93 0.86 0.70 0.60 ET Region 10.51 3.46 2.60 3.03 11.16 3.39 3.12 2.05 Gallbladder 1.33 0.60 0.43 0.34 1.54 0.81 0.92 0.60 Heart 0.70 0.45 0.44 0.44 0.85 0.79 0.93 0.65 L Kidney 0.80 0.67 0.67 0.50 0.96 2.21 1.56 1.52 R Kidney 0.76 0.79 0.80 0.65 0.92 2.85 2.38 1.49 Lateral Pancreas 0.38 0.61 0.47 0.34 0.48 0.95 0.77 0.68 Mid Pancreas 0.47 0.37 0.31 0.23 0.58 0.57 0.50 0.42 Medial Pancreas 0.68 0.33 0.27 0.20 0.83 0.57 0.46 0.44 Spleen 0.78 0.71 0.98 0.86 0.93 2.41 1.60 1.39 L Thymus 2.98 0.80 0.71 0.70 3.36 1.39 1.16 1.05 R Thymus 3.00 0.77 0.79 0.82 3.38 1.37 1.16 1.02

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124 Table 4 2. Continued Organ CAM M5 M50 M95 CAF F5 F50 F95 Oral mucosa 2.06 1.13 1.02 0.91 2.39 1.33 1.12 1.03 L Testis 4.73 3.71 4.33 4.56 N/A N/A N/A N/A R Testis 4.76 3.91 4.35 4.56 N/A N/A N/A N/A Prostate 0.80 0.68 0.48 0.48 N/A N/A N/A N/A L Ovary N/A N/A N/A N/A 0.76 0.67 0.74 0.70 R Ovary N/A N/A N/A N/A 0.76 0.68 0.74 0.64 Uterus N/A N/A N/A N/A 0.55 0.52 0.49 0.42 L Breast N/A N/A N/A N/A 5.02 7.01 4.98 4.71 R Breast N/A N/A N/A N/A 5.02 6.82 5.12 5.30 Table 4 3 GCR organ dose equivalent rates (mSv d 1 ) with PV shielding Organ CAM M5 M50 M95 CAF F5 F50 F95 BFO 1.78 1.75 1.72 1.68 1.83 1.87 1.84 1.78 Skin 2.32 2.37 2.34 2.32 2.44 2.44 2.40 2.38 Small Intestine 1.77 1.66 1.59 1.53 1.83 1.74 1.71 1.66 Muscle 1.98 1.96 1.91 1.87 2.02 2.04 1.99 1.96 R Eye Lens 2.41 2.36 2.31 2.28 2.44 2.50 2.41 2.45 L Eye Lens 2.42 2.36 2.31 2.28 2.46 2.48 2.41 2.43 R Eyeball 2.01 2.03 2.02 1.99 2.07 2.10 2.06 2.04 L Eyeball 2.02 2.03 2.03 1.99 2.08 2.09 2.06 2.03 Anterior Stomach 1.72 1.71 1.65 1.64 1.77 1.88 1.91 1.80 Posterior Stomach 1.57 1.55 1.52 1.47 1.63 1.72 1.69 1.66 Ascending Colon 1.83 1.73 1.68 1.60 1.88 1.77 1.73 1.66 Transverse Colon 1.86 2.05 2.00 2.01 1.91 2.11 2.07 2.05 Descending Colon 1.86 1.70 1.64 1.58 1.91 1.75 1.73 1.67 Rectosigmoid Colon 1.70 1.61 1.50 1.46 1.76 1.64 1.57 1.53 L Liver 1.55 1.54 1.50 1.49 1.61 1.68 1.68 1.60 R Liver 1.58 1.57 1.52 1.46 1.63 1.65 1.61 1.59 R Upper Mid Lung 1.84 1.84 1.81 1.79 1.89 1.94 1.90 1.86 L Upper Mid Lung 1.86 1.82 1.80 1.77 1.92 1.95 1.91 1.87 R Mid dle Anterior Lung 1.92 1.79 1.76 1.75 1.98 1.93 1.91 1.85 R Mid dle Mid Lung 1.83 1.84 1.79 1.76 1.89 1.92 1.90 1.83 R Mid dle Posterior Lung 1.87 1.80 1.78 1.75 1.92 1.88 1.84 1.79 L Mid dle Ant erior Lung 1.93 1.79 1.78 1.77 1.98 1.94 1.96 1.87 L Mid dle Mid Lung 1.85 1.81 1.78 1.75 1.91 1.89 1.88 1.81 L Mid dle Post erior Lung 1.87 1.77 1.76 1.72 1.93 1.86 1.83 1.79 R Base Ant erior Lung 1.82 1.80 1.72 1.70 1.87 1.89 1.89 1.78 R Base Post erior Lung 1.84 1.75 1.73 1.69 1.90 1.86 1.82 1.75 L Base Ant erior Lung 1.83 1.83 1.78 1.74 1.88 1.90 1.89 1.80 L Base Post erior Lung 1.85 1.78 1.79 1.77 1.90 1.83 1.80 1.74

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125 Table 4 3. Continued Organ CAM M5 M50 M95 CAF F5 F50 F95 Esophagus 1.68 1.56 1.53 1.49 1.74 1.68 1.63 1.59 Bladder 1.52 1.53 1.44 1.41 1.58 1.62 1.60 1.56 L Thyroid 2.19 1.85 1.81 1.80 2.23 2.01 1.95 1.89 R Thyroid 2.19 1.88 1.82 1.82 2.23 2.04 1.96 1.89 Anterior Brain 1.86 1.82 1.78 1.75 1.92 1.88 1.84 1.80 Mid Brain 1.83 1.81 1.77 1.74 1.90 1.86 1.82 1.78 Posterior Brain 2.01 1.98 1.93 1.90 2.06 2.04 1.94 1.95 L Parotid 2.07 2.08 2.04 2.01 2.12 2.07 2.08 2.04 R Parotid 2.06 2.06 2.04 1.99 2.11 2.10 2.06 2.04 L Adrenal 1.64 1.51 1.50 1.44 1.70 1.65 1.60 1.57 R Adrenal 1.62 1.52 1.50 1.45 1.67 1.67 1.61 1.57 ET Region 2.26 1.94 1.87 1.89 2.30 1.98 1.95 1.87 Gallbladder 1.72 1.57 1.51 1.46 1.77 1.66 1.66 1.58 Heart 1.64 1.55 1.53 1.51 1.70 1.69 1.69 1.61 L Kidney 1.63 1.57 1.55 1.49 1.68 1.83 1.75 1.73 R Kidney 1.64 1.60 1.59 1.53 1.69 1.88 1.83 1.73 Lateral Pancreas 1.53 1.59 1.53 1.47 1.58 1.70 1.65 1.61 Mid Pancreas 1.55 1.51 1.47 1.41 1.60 1.62 1.57 1.53 Medial Pancreas 1.61 1.49 1.44 1.39 1.67 1.62 1.57 1.54 Spleen 1.63 1.61 1.63 1.58 1.69 1.86 1.78 1.73 L Thymus 1.97 1.68 1.64 1.62 2.02 1.82 1.77 1.74 R Thymus 1.96 1.66 1.66 1.65 2.01 1.82 1.78 1.73 Oral mucosa 1.96 1.79 1.76 1.73 2.02 1.85 1.80 1.78 L Testis 1.77 1.76 1.74 1.74 N/A N/A N/A N/A R Testis 1.77 1.77 1.74 1.74 N/A N/A N/A N/A Prostate 1.47 1.51 1.44 1.42 N/A N/A N/A N/A L Ovary N/A N/A N/A N/A 1.58 1.55 1.54 1.51 R Ovary N/A N/A N/A N/A 1.58 1.55 1.54 1.50 Uterus N/A N/A N/A N/A 1.50 1.52 1.49 1.46 L Breast N/A N/A N/A N/A 1.93 2.02 1.94 1.93 R Breast N/A N/A N/A N/A 1.93 2.02 1.96 1.96 Table 4 4 February 1956 SPE organ dose equivalents with shelter shielding Organ CAM M5 M50 M95 CAF F5 F50 F95 BFO 0.36 0.36 0.35 0.35 0.37 0.38 0.37 0.36 Skin 0.44 0.45 0.45 0.44 0.45 0.46 0.46 0.45 Small Intestine 0.36 0.35 0.33 0.32 0.37 0.36 0.35 0.35 Muscle 0.39 0.39 0.38 0.37 0.40 0.40 0.40 0.39 R Eye Lens 0.45 0.45 0.44 0.44 0.46 0.48 0.45 0.46 L Eye Lens 0.46 0.45 0.44 0.44 0.46 0.47 0.45 0.46 R Eyeball 0.40 0.40 0.40 0.39 0.41 0.41 0.41 0.40

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126 Table 4 4. Continued Organ CAM M5 M50 M95 CAF F5 F50 F95 L Eyeball 0.40 0.40 0.40 0.39 0.41 0.41 0.41 0.40 Anterior Stomach 0.35 0.35 0.34 0.34 0.36 0.38 0.38 0.36 Posterior Stomach 0.34 0.33 0.33 0.32 0.35 0.36 0.35 0.35 Ascending Colon 0.37 0.36 0.35 0.33 0.38 0.36 0.36 0.35 Transverse Colon 0.37 0.40 0.39 0.39 0.38 0.41 0.41 0.40 Descending Colon 0.38 0.35 0.34 0.33 0.38 0.36 0.36 0.35 Rectosigmoid Colon 0.35 0.34 0.32 0.31 0.36 0.35 0.34 0.33 L Liver 0.33 0.33 0.32 0.32 0.34 0.35 0.35 0.34 R Liver 0.34 0.34 0.33 0.32 0.35 0.35 0.34 0.34 R Upper Mid Lung 0.37 0.37 0.37 0.37 0.38 0.39 0.38 0.38 L Upper Mid Lung 0.38 0.37 0.37 0.36 0.38 0.39 0.38 0.38 R Mid dle Anterior Lung 0.39 0.37 0.36 0.36 0.39 0.39 0.38 0.37 R Mid dle Mid Lung 0.37 0.38 0.37 0.36 0.38 0.39 0.38 0.37 R Mid dle Posterior Lung 0.38 0.37 0.37 0.36 0.39 0.38 0.38 0.37 L Mid dle Ant erior Lung 0.39 0.37 0.36 0.36 0.39 0.39 0.39 0.38 L Mid dle Mid Lung 0.38 0.37 0.37 0.36 0.38 0.38 0.38 0.37 L Mid dle Post erior Lung 0.38 0.37 0.36 0.36 0.39 0.38 0.37 0.37 R Base Ant erior Lung 0.37 0.37 0.35 0.35 0.38 0.38 0.38 0.37 R Base Post erior Lung 0.37 0.36 0.36 0.35 0.38 0.38 0.37 0.36 L Base Ant erior Lung 0.37 0.37 0.36 0.36 0.38 0.38 0.38 0.37 L Base Post erior Lung 0.37 0.37 0.37 0.36 0.38 0.38 0.37 0.36 Esophagus 0.35 0.34 0.33 0.32 0.36 0.35 0.35 0.34 Bladder 0.33 0.33 0.31 0.31 0.34 0.34 0.34 0.33 L Thyroid 0.42 0.37 0.37 0.36 0.43 0.40 0.39 0.38 R Thyroid 0.42 0.38 0.37 0.37 0.43 0.40 0.39 0.38 Anterior Brain 0.38 0.37 0.37 0.36 0.39 0.38 0.38 0.37 Mid Brain 0.38 0.37 0.37 0.36 0.38 0.38 0.37 0.37 Posterior Brain 0.40 0.39 0.39 0.38 0.41 0.40 0.39 0.39 L Parotid 0.41 0.41 0.40 0.40 0.41 0.41 0.41 0.40 R Parotid 0.41 0.41 0.40 0.39 0.41 0.41 0.41 0.40 L Adrenal 0.34 0.33 0.32 0.31 0.35 0.35 0.34 0.33 R Adrenal 0.34 0.33 0.32 0.31 0.35 0.35 0.34 0.33 ET Region 0.43 0.39 0.38 0.38 0.44 0.39 0.39 0.38 Gallbladder 0.35 0.33 0.32 0.31 0.36 0.35 0.35 0.34 Heart 0.35 0.33 0.33 0.32 0.35 0.35 0.35 0.34 L Kidney 0.34 0.33 0.33 0.32 0.35 0.37 0.36 0.35 R Kidney 0.34 0.34 0.33 0.32 0.35 0.38 0.37 0.35 Lateral Pancreas 0.33 0.34 0.33 0.32 0.34 0.36 0.35 0.34 Mid Pancreas 0.33 0.33 0.32 0.31 0.34 0.35 0.34 0.33 Medial Pancreas 0.34 0.32 0.32 0.31 0.35 0.34 0.34 0.33 Spleen 0.34 0.34 0.34 0.33 0.35 0.38 0.37 0.36

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127 Table 4 4. Continued Organ CAM M5 M50 M95 CAF F5 F50 F95 L Thymus 0.39 0.35 0.34 0.34 0.40 0.37 0.36 0.36 R Thymus 0.39 0.35 0.35 0.34 0.40 0.37 0.36 0.36 Oral mucosa 0.39 0.37 0.36 0.36 0.40 0.38 0.37 0.37 L Testis 0.38 0.38 0.38 0.37 N/A N/A N/A N/A R Testis 0.38 0.38 0.38 0.37 N/A N/A N/A N/A Prostate 0.33 0.34 0.32 0.32 N/A N/A N/A N/A L Ovary N/A N/A N/A N/A 0.35 0.35 0.34 0.34 R Ovary N/A N/A N/A N/A 0.35 0.35 0.34 0.34 Uterus N/A N/A N/A N/A 0.34 0.34 0.34 0.33 L Breast N/A N/A N/A N/A 0.41 0.43 0.41 0.41 R Breast N/A N/A N/A N/A 0.41 0.43 0.42 0.41

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128 CHAPTER 5 EFFECT OF ANATOMICAL MODELING ON SPACE RA DIATION DOSE ESTIMAT ES Changes to Phantoms for Comparison The dosimetry results (described in Chapter 4) from the first method of scaling employed (described in Chapter 3) indicate d that a different scaling procedure would lead to a more appropriate comparison of organ dose equivalent for phantoms of different sizes. In addition, for the comparison to be valid for the current astronaut corps, the anthropometric parameters used were compared to those of the current corps and altered as needed 1 Updated Anthropometric Parameters Using data provided by the NASA Radiation Health Office (M. Van Baalen, personal communication, October 2010), the 5 th 50 th and 95 th PCTL statures and masses as given in the NASA MSIS ( 1995 ) were compared with the current astronaut corps. The comparison is displayed in Figure 5 1 and Figure 5 2 for stature and mass, respectively. The statures for the males as given in the two data sources compare d well, whereas for the females, the values given in the NASA MSIS were systematically lower than those provided by the NASA Radiation Health Office. For mass, the 50 th PCTL male value in the NASA MSIS was very close to the 50 th PCTL male value as given by the NASA Radiation Health Office. The range of masses for the males was larger in the NASA MSIS. For the females, the masses given in the NASA MSIS were systematically lower than the values provided by NASA. It was determined that the anthropometric parameters as given in NASA MSIS were sufficient for the 1 This chapter was derived from a published work (Bahadori et al. 2011 Phys. Med. Biol. 56 1671 93 doi:10.1088/0031 9155/56/6/010 )

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129 representation of males and insufficient for the representation of females in the current astronaut corps. The revised target statures and masses are displayed in Table 5 1 Unifor m Scaling Procedure The inconsistencies in organ dose equivalent described previously resulted from scaling each phantom individually. A uniform scaling procedure was developed to avoid these inconsistencies. To create the set of UF hybrid phantoms repre senting the 5 th 50 th and 95 th PCTL male and female astronauts, first the anthropometric parameters for the 50 th PCTL male and female in the NASA MSIS were matched. Uniform scaling factors for the males were then derived for the 5 th and 95 th PCTL males b ased on body measurements and total body mass. The entire set of female phantoms required scaling since the 50 th PCTL female as defined in the NASA MSIS did not coincide with the 50 th PCTL female astronaut. Here, scaling in the z direction was based on s tature, while a scaling factor in the x y plane was calculated to match total body mass. Scaling factors for the phantoms are given in Table 5 2 The scaling procedure ensured consistency in body self shielding distributions for all ray directions. Once the phantoms were scaled appropriately, they were voxelized using an in house MA TLAB code. Voxel dimensions were again specified as 0.2 cm b y 0.2 cm by 0.2 cm, which allowed for a reasonable skin thickness without resulting in an unreasonably large binary file (the phantom file sizes ranged from 23 MB to 49 MB). Dosimetry with Update d Phantoms The workflow for determining effective dose was comprised of a series of steps. First, the b ody self shielding distribution for each organ was found using the VoBRaT. Next, the organ dose equivalents were calculated by combining the resulting body self shielding distributions with depth dose results from BRYNTRN and HZETRN. Finally,

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130 the effective dose was calculated by performing a weighted sum of selected organ dose equivalents. Body Self Shielding Distributions The body self shielding distri butions for all organs except those not explicitly segmented in CAM (eye lens, oral mucosa, esophagus, salivary glands, adrenals, extrathoracic ( ET ) region, gallbladder, thymus, prostate, breasts, ovaries, and uterus) were generated by randomly sampling po ints within the organ. Five hundred samples were ray traced for all organs except the skin, BFO, and muscle, unless the organs were comprised of less than 500 voxels, in which case all voxels were ray traced. Eight thousand voxels were ray traced for the skin, BFO, and muscle The resulting body self shielding distributions for specific organs of interest in NASA dosimetry (gonads, colon, breasts, BFO, skin, and eye lenses) are shown in Figure 5 3 through Figure 5 9 Results from the voxelized CAM and CAF are shown for comparison. Body self shielding distributions for the entire compliment of organs analyzed are available in Appendix F T he body self shielding distributions for the UF phantoms clearly exhibit ed the trend of increasing body self shielding for larger phantoms, regardless of organ location. The differences between the UF phantoms and the NASA phantoms result ed from a combination of anthropometric modeling and overall body size. The differences were a gain most pronounced for females in the abdominal region; since CAF is a scaled version of CAM, the anthropometric modeling between the two phantom s differed little, and so CAF exhibited attributes of a male morphometry. In cont rast, the UF female phantom s were based on female morphometry, and so there were greater differences

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131 between the UF male and female phantoms. Thus, in many instances the body self shiel ding distribution for CAF tracked with CAM and the UF male phantoms. While an overall trend of ph antom size and body self shielding was observed, the impact of v ariations in body morphometry was not consistent over the entire phantom: the closer to the center of mass of the phantoms, the more variation was observed among the body self shielding distri butions. Greater differences were observed for dose points with more body self shielding. The observation consistent with what was observed in Chapter 3, is exemplified by comparing the body self shielding distributions for the colon ( Figure 5 5 ) and the skin ( Figure 5 8 ). An exception to this observation was the eye lens ( Figure 5 9 ). The eye lens is small and located on the periphery of the body. It was difficult to adequately sample the eye lens in the phantoms because it was comprised of so few voxels. When an organ is under sampled, the effects of small differences in shielding about that organ are artificially enhanced. This explains the large differences in body self shielding distributions between UFHADF5 and UFHADF50 a nd the rest of the phantoms at small ray thicknesses for the eye lens. Organ Dos imetry The space radiation exposure scenarios described in Chapter 4 were used in the evaluation of the updated phantoms. The depth dose distributions from BRYNTRN and HZETRN were used to derive organ dose equivalents, once again considering simplified vehicular shielding distributions (0.5 g cm 2 aluminum equivalent for a suit, 2 g cm 2 aluminum equivalent for PV, and 10 g cm 2 aluminum equivalent for SPE shelter). The hypot hetical shielding thicknesses were similar to those used in previous studies ( Simonsen et al. 1992 ; Hoff et al. 2004 ; Ballarini et al. 2006 ; Slaba et al. 2009 ) The body self shielding ray thicknesses were combined with the depth dose distributions at

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132 these aluminum equivalent shielding thicknesses in order to return organ dose equivalen t s Organ dose equivalent rates for trapped protons and GCR in PV shielding are shown in Figure 5 10 and Figure 5 11 respectively, while organ dose equival ent results for the August 1972 SPE for suit and shelter shielding are shown in Figure 5 12 and Figure 5 13 respectively. To better illustrate the relationship between anatomical modeling and organ dose equivalent, the fractional difference between the organ dose equivalent for the phantom of interest and the 50 th PCTL UF phantom was calculated as the ratio of the phantom of interest organ dose equivalent to the 50 th PCTL UF phantom organ dose equivalent minus unity. Fractional difference results for trapped protons and GCR in PV shielding are shown in Figure 5 14 and Figure 5 15 respectively, while fractional difference results for the August 1972 SPE for suit and shelter shielding are shown in Figure 5 16 and Figure 5 17 respectively. Plots of organ dose equivalent s and fractional difference s for all combinations of space radiation environment and vehicular shielding are available in Appendix G and Appendix H respectively. Organ dosimetry results follow ed log ically from the body self shielding results. Larger phantoms had lower organ dose equivalents than their smaller counterparts. This is exhibited clearly for organ dose equivalents in Figure 5 10 through Figure 5 13 and for fractional differences in Figure 5 14 through Figure 5 17 In addition, the differences in anatomical modeling (and dose point selection in the case of organs specifically mentioned previously) between the NASA phantoms and the UF phantoms resul ted in differ ences in organ dose equivalents. An example of this was the thyroid. The CAM and CAF thyroids were much more lightly shielded than the UF phantom

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133 thyroids (primarily due to the proximity of the thyroid to the surface of the neck), and so a much larger th yroid dose equivalent was observed for these two phantoms. In comparison, the skin dose equivalents were largely insensitive to phantom size and anatomical incongruities. Differences in small intestine dose equivalent between the UF males and CAM were la rger than differences in this quantity between the UF females and CAF. This resulted from modeling the intestines in CAM and CAF as a uniform region of low density (0.457 g cm 3 ) material and differences in morphometry. In the case of the males, the lowe r density resulted in a smaller amount of self shielding and hence a larger organ dose equivalent for CAM. In the case of the females, the density effect was partially offset by the differences in abdominal morphometry between the UF females and CAF. The degree to which size and anatomical modeling affect ed dose differences was dependent upon the space radiation spectrum analyzed. For space radiation environments with higher penetrability, such as GCR and the February 1956 SPE, the dose differences observ ed were much smaller than for space radiation environments with lower penetrability, such as the October 1989 SPE and the August 1972 SPE. Also, dose differences tend ed to decrease for increasing vehicular shielding. This is shown in Figure 5 16 and Figure 5 17 as the fractional differences among the phantoms decrease d when shielding was increased from space suit to SPE storm shelter. The effect of shielding on organ dose equivalent was very prono unced for the August 1972 SPE ( Figure 5 12 and Figure 5 13 ). Also of signifi cance to space dosimetry is the average radiation quality factor, calculated as the quotient of the organ dose equivalent and the organ absorbed dose.

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134 Tables of average radiation quality factor for the phantom organs are shown for the February 1956 SPE wi th space suit shielding ( Table 5 3 ), GCR with PV shielding ( Table 5 4 ), and the August 1972 SPE with storm shelter shielding ( Table 5 5 ). The averag e radiation quality factor varied as a function of organ location and, to a lesser extent, p hantom type. The average quality fact ors for the SPE environments were smaller in magnitude and exhibit ed less overall variation than the average quality factors for the GCR environment. These radiation quality factors compare d well with the calculated quality factors for protons and GCR exposures as given in a previous study by Badhwar et al. ( 2002 ) Effective Dose Results The effective dose is used by NASA as a surrogate for radiation risk. Here, an effective dose was approximated using organ dose equivalents and gender specific tissue weig hting factors similar to those recommended in ICRP Publication 60 ( 1991 ) These weighting factors are shown in Table 5 6 Although upda ted tissue weighting factors were available from the I CRP, it is current NASA policy to use ICRP Publication 60 tissue weighting factors in accordance with NCRP Report No. 132 recommendations ( 2000 ) Note that the male weighting factors, with zero weighting factor for the male breast, sum med to 0.95, while the female weighting factors sum med to unity. The effective dose rates as a function of vehicular shielding for the eight phantoms are shown for trapped protons and free space GCR in Figure 5 18 and Figure 5 19 respectively. Similarly, the effective doses as a function of vehicular shielding for the eight phantom s are shown for the February 1956 SPE in Figure 5 20 October 1989 SPE in Figure 5 21 and August 1972 SPE in Figure 5 22 Also shown in Figure 5 20 Figure 5 21 and Figure 5 22 are example age specific effective dose career limits as

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135 given in the NASA Space Flight Human System Standard for comparison ( NASA 2007 ) Thes e effective dose career limits correspond to the NASA risk limit of 3% REID, and are shown for a 1 y mission starting at ages of 25, 35, 45, and 55 years. Effective doses exhibit ed a trend similar to that of the organ dose equivalents: decreasin g with increasing phantom size The slope of this inverse relationship was dependent on both the space radiation environment and the vehicular shielding. For all but the softest radiation spectra, CAF tend ed to underestimate effective doses for the smaller phan toms and overestimate effectiv e doses for the larger phantoms, whereas CAM tended to overestimate effective doses for all space radiation environments. For soft radiation spectra such as the Au gust 1972 SPE, CAM greatly overestimated effective dose for al l three UF male phantoms It was observed that for this spectrum and PV shielding, the career effective dose limit for a male astronaut for a 1 y mission starting at age 55 would not be exceeded if the UF phantom was used to represent the astronaut, while it would be exceeded i f CAM was used to represent the astronaut. Effective doses observed in the present study were similar to those reported in a recent study by Kim et al. for similar radiation environments ( Kim et al. 2010b ) Chapter Summary Updated anthropometric parameters, which more accurately represented the NASA astronaut corps, were used to rescale the phantoms in a uniform manner to ensure consistent body self shielding and organ dosimetry results. As in Chapter 3, it was observed that organs with more body self shielding exhibited greater variation with varying morphometries. Differences in organ dose equivalent varied with organ location, space radiation environment, and vehicular shielding. The effective dose, which roughly charact erizes the risk of radiation carcinogenesis, was calculated for

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136 each phantom. Much larger differences in organ dose equivalent and effective dose were observed for the softer radiation spectra, especially the August 1972 SPE and October 1989 SPE with ligh t shielding similar to a space suit.

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137 Figure 5 1 Comparison of phantom statures from NASA MSIS and Radiation Health Office Figure 5 2 Comparison of phantom masses from NASA MSIS and Radiation Health Office

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138 Figure 5 3 Testes body self shielding distributions (Earth based anthropometrics) ( Bahadori et al. 2011 ) Figure 5 4 Ovaries b ody self shielding distributions (Earth based anthropometrics) ( Bahadori et al. 2011 )

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139 Figure 5 5 Colon body self shielding distributions (Earth based anthropometrics) ( Bahadori et al. 2011 ) Figure 5 6 Breasts body self shielding distributions (Earth based anthropometrics) ( Baha dori et al. 2011 )

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140 Figure 5 7 BFO body self shielding distributions (Earth based anthropometrics) ( Bahadori et al. 2011 ) Figure 5 8 Skin body self shielding distributions (Earth based anthropometrics) ( Bahadori et al. 2011 )

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141 Figure 5 9 Eye lenses body self shielding distributions (Earth based anthropometrics) ( Bahadori et al. 2011 )

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142 A B Figure 5 10 Trapped proton (A) male and (B) female organ dose equivalent rates for PV shielding (Earth based anthropometrics ) ( Bahadori et al. 2011 )

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143 A B Figure 5 11 GCR (A) male and (B) female organ dose equivalent rates for PV shielding (Earth based anthropometrics) ( Bahadori et al. 2011 )

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144 A B Figure 5 12 August 1972 SPE (A) male and (B) female organ dose equivalents for suit shielding (Earth based anthropometrics) ( Bahadori et al. 2011 )

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145 A B Figure 5 13 August 1972 SPE (A) male and (B) female organ dose equivalents for shelter shielding (Earth based anthropometrics) ( Bahadori et al. 2011 )

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146 A B Figure 5 14 Trapped proton (A) male and (B) female fractional differences for PV shielding (Earth based anthropometrics) ( Bahadori et al. 2011 )

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147 A B Figure 5 15 GCR (A) male and (B) female fractional differences for PV shielding (Earth based anthropometrics) ( Bahadori et al. 2011 )

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148 A B Figure 5 16 August 1972 SPE (A) male and (B) female fractional differences for suit shielding (Earth based anthropometrics) ( Bahadori et al. 2011 )

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149 A B Figure 5 17 August 1972 SPE (A) male and (B) female fractional differences for shelter shielding (Earth based anthropometrics) ( Bahadori et al. 2011 )

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150 Figure 5 18 Trapped prot on effective dose rates (Earth based anthropometrics) ( Bahadori et al. 2011 ) Figure 5 19 GCR effective dose rates (Earth based anthropometrics) ( Bahadori et al. 2011 )

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151 Figure 5 20 February 1956 SPE effective doses (Earth based anthropometrics) ( Bahadori et al. 2011 ) Figure 5 21 October 1989 SPE effective doses (Earth based anthropometrics) ( Bahadori et al. 2011 )

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152 Figure 5 22 August 1972 SPE effective doses (Earth based anthropometrics) ( Bahadori et al. 2011 )

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153 Table 5 1 Phantom target statures and masses ( Bahadori et al. 2011 ) Measurement (unit) CAM M5 a M50 M95 CAF F5 F50 F95 Stature (cm) 175.5 b 169.7 c 179.9 c 190.1 c 161.5 d 158.3 e 166.9 e 175.5 e Mass (kg) 69.5 d 65.8 c 82.2 c 98.5 c 55.9 f 45.2 e 60.4 e 75.6 e a The first letter indicates gender. The number that follows indicates percentile. b Kase 1970 c Billings and Yucker 1973 d Yucker and Huston 1990 e Determined from data provided from NASA Radiation Heal th Officer f Yucker 1992 Table 5 2 Phantom scaling factors with respect to NASA MSIS 50 th PCTL ( Bahadori et al. 2011 ) Scaling Factor M5 M50 M95 F5 F50 F95 z direction 0.944 1.000 1.056 1.008 1.063 1.118 xy plane 0.910 1.000 1.091 0.933 1.050 1.146

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154 Table 5 3 Quality factors for February 1956 SPE radiation environment with suit shielding (Earth based anthropometrics) ( Bahadori et al. 2011 ) Organ F5 F50 F95 CAF M5 M50 M95 CAM Eye Lens es 1.66 1.65 1.61 1.60 1.60 1.59 1.59 1.59 BFO 1.56 1.5 7 1.5 8 1.5 7 1.57 1.5 8 1.5 8 1.57 Colon 1.56 1.56 1.57 1.56 1.57 1.57 1.58 1.57 Lung s 1.56 1.56 1.57 1.55 1.56 1.57 1.58 1.56 Stomach 1.55 1.56 1.57 1.59 1.60 1.60 1.61 1.60 Breast s 1.54 1.54 1.54 1.53 N/A N/A N/A N/A Ovar ies 1.59 1.60 1.61 1.59 N/A N/A N/A N/A Test es N/A N/A N/A N/A 1.55 1.55 1.55 1.56 Bladder 1.56 1.57 1.57 1.60 1.61 1.62 1.62 1.61 Esophagus 1.58 1.60 1.61 1.58 1.60 1.61 1.62 1.59 Liver 1.57 1.58 1.58 1.59 1.59 1.60 1.60 1.60 Thyroid 1.55 1.55 1.55 1.56 1.55 1.55 1.56 1.56 Brain 1.54 1.55 1.56 1.54 1.54 1.55 1.56 1.55 Salivary Gland s 1.55 1.55 1.55 1.54 1.54 1.55 1.55 1.54 Skin 1.71 1.71 1.72 1.72 1.71 1.72 1.72 1.71 Adrenal s 1.59 1.60 1.61 1.58 1.61 1.62 1.62 1.59 ET Region 1.54 1.55 1.55 1.56 1.55 1.55 1.55 1.56 Gallbladder 1.59 1.61 1.61 1.57 1.61 1.62 1.63 1.57 Heart 1.58 1.59 1.59 1.58 1.59 1.60 1.61 1.59 Kidney 1.56 1.57 1.57 1.58 1.59 1.59 1.60 1.59 Muscle 1.55 1.56 1.56 1.55 1.56 1.56 1.56 1.56 Oral Mucosa 1.56 1.57 1.58 1.54 1.56 1.57 1.57 1.55 Pancreas 1.59 1.60 1.61 1.59 1.61 1.62 1.62 1.60 Prostate N/A N/A N/A N/A 1.61 1.62 1.62 1.60 Small Intestine s 1.57 1.58 1.59 1.56 1.59 1.59 1.60 1.57 Spleen 1.56 1.56 1.57 1.59 1.58 1.58 1.59 1.60 Thymus 1.57 1.58 1.59 1.54 1.58 1.59 1.60 1.54 Uterus 1.60 1.61 1.62 1.61 N/A N/A N/A N/A

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155 Table 5 4 Quality factors for GCR radiation environment with PV shielding (Earth based anthropometrics) ( Bahadori et al. 2011 ) Organ F5 F50 F95 CAF M5 M50 M95 CAM Eye Lens es 4.52 4.47 4.40 4.53 4.44 4.39 4.35 4.48 BFO 3. 57 3. 46 3.46 3. 38 3.40 3.3 2 3.28 3.42 Colon 3.61 3.51 3.41 3.58 3.45 3.38 3.34 3.50 Lung s 3.68 3.57 3.49 3.67 3.56 3.49 3.44 3.59 Stomach 3.62 3.51 3.43 3.33 3.24 3.17 3.12 3.24 Breast s 4.16 4.10 4.05 4.04 N/A N/A N/A N/A Ovar ies 3.32 3.21 3.13 3.44 N/A N/A N/A N/A Test es N/A N/A N/A N/A 3.67 3.61 3.59 3.72 Bladder 3.50 3.42 3.35 3.21 3.12 3.05 3.01 3.12 Esophagus 3.39 3.27 3.18 3.44 3.21 3.13 3.07 3.35 Liver 3.49 3.37 3.30 3.31 3.25 3.18 3.13 3.22 Thyroid 3.91 3.80 3.73 4.25 3.69 3.63 3.57 4.20 Brain 3.86 3.77 3.67 3.90 3.83 3.76 3.68 3.82 Salivary Gland s 3.96 3.85 3.78 4.03 3.90 3.82 3.78 3.96 Skin 4.49 4.44 4.40 4.39 4.41 4.38 4.36 4.35 Adrenal s 3.31 3.20 3.11 3.35 3.13 3.06 3.01 3.27 ET Region 3.87 3.78 3.69 4.31 3.81 3.75 3.70 4.26 Gallbladder 3.28 3.16 3.08 3.49 3.09 3.01 2.97 3.41 Heart 3.45 3.34 3.26 3.41 3.27 3.18 3.14 3.33 Kidney 3.56 3.45 3.38 3.40 3.26 3.20 3.15 3.31 Muscle 3.92 3.83 3.76 3.90 3.79 3.74 3.69 3.83 Oral Mucosa 3.69 3.57 3.47 3.87 3.64 3.56 3.49 3.78 Pancreas 3.30 3.18 3.10 3.31 3.13 3.05 3.00 3.22 Prostate N/A N/A N/A N/A 3.12 3.05 3.00 3.11 Small Intestine s 3.47 3.34 3.26 3.58 3.28 3.20 3.16 3.50 Spleen 3.60 3.49 3.41 3.32 3.36 3.29 3.25 3.24 Thymus 3.56 3.44 3.35 3.88 3.38 3.30 3.25 3.80 Uterus 3.24 3.13 3.05 3.17 N/A N/A N/A N/A

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156 Table 5 5 Quality factors for August 1972 SPE radiation environment with shelter shielding (Earth based anthropometrics) ( Bahadori et al. 2011 ) Organ F5 F50 F95 CAF M5 M50 M95 CAM Eye Lenses 1.45 1.45 1.43 1.43 1.43 1.43 1.43 1.43 BFO 1.45 1.4 6 1.4 7 1.4 6 1.4 7 1.4 7 1.4 8 1.4 7 Colon 1.45 1.45 1.45 1.46 1.46 1.46 1.46 1.46 Lungs 1.45 1.46 1.47 1.45 1.46 1.47 1.48 1.46 Stomach 1.45 1.46 1.46 1.49 1.50 1.51 1.52 1.50 Breasts 1.42 1.42 1.42 1.43 N/A N/A N/A N/A Ovaries 1.49 1.51 1.52 1.50 N/A N/A N/A N/A Testes N/A N/A N/A N/A 1.43 1.43 1.43 1.43 Bladder 1.45 1.46 1.46 1.52 1.53 1.54 1.55 1.53 Esophagus 1.49 1.51 1.53 1.49 1.53 1.54 1.56 1.50 Liver 1.46 1.47 1.48 1.49 1.49 1.50 1.51 1.51 Thyroid 1.43 1.43 1.44 1.42 1.44 1.45 1.45 1.42 Brain 1.45 1.45 1.46 1.44 1.45 1.45 1.46 1.45 Salivary Glands 1.43 1.44 1.44 1.43 1.43 1.44 1.44 1.43 Skin 1.47 1.47 1.47 1.47 1.47 1.47 1.47 1.47 Adrenals 1.49 1.51 1.53 1.48 1.53 1.55 1.56 1.49 ET Region 1.44 1.44 1.44 1.42 1.44 1.44 1.44 1.42 Gallbladder 1.51 1.53 1.55 1.46 1.55 1.57 1.59 1.47 Heart 1.48 1.49 1.50 1.48 1.50 1.52 1.52 1.49 Kidney 1.45 1.46 1.46 1.48 1.49 1.49 1.50 1.49 Muscle 1.43 1.43 1.44 1.43 1.44 1.44 1.44 1.43 Oral Mucosa 1.46 1.47 1.48 1.44 1.46 1.47 1.48 1.45 Pancreas 1.50 1.52 1.54 1.50 1.54 1.56 1.57 1.51 Prostate N/A N/A N/A N/A 1.53 1.54 1.55 1.51 Small Intestines 1.46 1.48 1.48 1.46 1.49 1.50 1.50 1.46 Spleen 1.45 1.46 1.46 1.49 1.47 1.48 1.48 1.50 Thymus 1.47 1.48 1.49 1.44 1.49 1.50 1.51 1.44 Uterus 1.52 1.54 1.56 1.53 N/A N/A N/A N/A Table 5 6 Tissue weighting factors ( Bahadori et al. 2011 ) Organ Male Weighting Factor Female Weighting Factor Testes 0.2 0 Ovaries 0 0.2 BFO 0.18 0.18 Colon 0.12 0.12 Lung 0.12 0.12 Stomach 0.12 0.12 Bladder 0.05 0.05 Breast 0 0.05 Liver 0.05 0.05 Esophagus 0.05 0.05 Thyroid 0.05 0.05 Skin 0.01 0.01

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157 CHAPTER 6 DOSIMETRIC IMPACTS O F MICROGRAVITY Microgravity Induced Body Changes The space environment is truly foreign to humans. The microgravity environment of space causes pronounced changes in the body and all organ systems are affected to some degree ( Williams et al. 2009 ) These changes include altered circulation and cardio pulmonary function, muscle atrophy, loss of extracellular fluids, bone demineralization, and altered vestibular function, among others ( Vernikos 1996 ) Microgravity induced changes on the tissue, and even cellular level converge to cause a severe departure from Earth bound homeostasis 1 The adaptation responses of the various body systems occur at different rates, ranging from days to weeks; for some, such as fluid regulation, the endpoint is known, whereas for others, such as bone density changes, the endpoint is not known ( Barratt and Po ol 2008 ) Data on specific responses are difficult to obtain in a controlled manner due to the many changes that are taking place and the other important demands placed upon crewmembers such as conducting other experiments in space ( Barratt and Pool 2008 ; Williams et al. 2009 ) Despite these challenges, much has been learned about the adaptive responses, both th rough actual spaceflight data and bed rest studies, which have been identified as a useful analog to spaceflight ( Schneider et al. 1995 ; Perhonen et al. 2001 ) The changes resulting from exposure to microgravity are largely caused by the combination of fluid redistribution and mechanical unloading ( Barratt and Pool 2008 ) An immediate change observed in 1 This chapter is derived from a published work (Bahadori et al. 2012 Phys. Med. Biol. 57 1047 1070 doi:10.1088/0031 9155/57/4/1047 )

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158 astronauts is fluid redistribution ( Vernikos 1996 ; Barratt and Pool 2 008 ; Williams et al. 2009 ) At launch, astronauts are in a recumbent position t hat causes a minor fluid shift, and once the vehicle reaches orbit the shift becomes more pronounced ( Barratt and Pool 2008 ) The volume of the lower limbs decreases significantly, with body fluids moving towards the upper body resulting in the well bird syndrome ( Williams et al. 2009 ) Microgravity causes mechanical unloading On Earth, gravity requires that the muscles and bones work together to per form simple tasks such as maintaining an upright posture. In microgravity these demands are no longer placed upon the musculo skeletal system, and thus t sture as shown in Figure 6 1 ( NASA 2010 ) Application of Microgravity Induced Body Changes to UF Hybrid Phantoms Five physiological changes resulting from microgravity were implemented in the UF hybrid phantoms: overall mass loss, loss in leg volume, increase in sitting height, cardiac atrophy, and bone mineral density loss. An overall mass loss of 4 5% for long duration spaceflight has been attributed to fluid regulat ion and tissue loss due to dietary changes and muscle disuse ( Heer et al. 2001 ; Barratt and Pool 2008 ) Leg volume decreases as a dir ect result of fluid redistribution. Mir cosmonauts experienced a 20% decrease in calf circumference, while during Skylab, about 1 L of body fluid volume was lost from the legs ( Barratt and Pool 2008 ) There is evidence of a decrease in cardiac mass during spaceflight as well. In a study comp aring 6 weeks of bed rest to 10 days of spaceflight, losses in cardiac mass as measured with MRI on the order of 10% were observed ( Perhonen et al. 2001 ) This loss is thought to be a result of decreased plasma and blood volume, resulting in less stress on the heart wall ( Vernikos 1996 ; Perhonen et al. 2001 )

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159 Loss of bone mineral density due to disuse was predicted well in advance of experience in spaceflight structure based on external forces ( Amin 2010 ) While traditionally attributed to mechanical unloading, hydrostatic pressure may also have an impact on bone physiology ( McCarthy 2005 ) Overall, the loss of bone mineral density is most pronounced in the load bearing bones such as the lower extremities, pelvis and spine ( Schneider et al. 1995 ; LeBlanc et al. 2000 ; Lang et al. 2004 ; McCarthy 2005 ; Barratt and Pool 2008 ; Williams et al. 2009 ; Amin 2010 ) The bone mineral density loss in these regions is estimated to be 1 2% per month ( LeBlanc et al. 2000 ; McCarthy 2005 ; Barratt and Pool 2008 ; Amin 2010 ) with most of the bone loss occurring in tr abecular spongiosa as opposed to the cortical region ( Lang et al. 2004 ) The phantoms used in the examination of the effect of anatomical modeling on space radiation dose esti mates were scaled to match 5 th 50 th and 95 th P CTL male and female astronauts ( Bahadori et al. 2011 ) To create each set, the 50 th PCTL phantom was created by altering the UFHADM and UFHADF to match anthropometric measurements, and the 5 th PCTL (UFHADM5 and UFHADF5) and 95 th PCTL (UFHADM95 and UFHADF95) phantoms were then scaled uniformly in the x y and z directions from the 50 th PCTL (UFHADM50 and UFHADF50) phantoms. The describ ed method was found to result in organ dose equivalents consistent with what would be expected for phantoms of differing sizes as explained in Chapter 5 T he microgravity induced changes (summarized in Table 6 1 ) were implemented for the UFHADM50 and UFHADF50 astronaut phantoms constructed previously. To simulate mass redistribution due to fluid shift, mass was removed from the lower torso only (with most

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160 removed from the posterior of the lower torso). Next the microgravity based UFHADM50 and UFHADF50 were scaled by the scaling factors as presented in Bahadori et al. ( 2011 ) to create the 5 th and 95 th PCTL phantoms 2 Since the arms, legs, and head were repositioned to simulate the neutral body po sture, care was taken to scale along the appropriate axes of these body parts. As shown in Table 6 2 the previously referenced overall mass loss of 4 5% for long dur ation spaceflight was attained for the microgravity based astronaut phantoms. After the phantoms were adjusted in the NURBS modeling program Rhinoceros (McNeel North America, Seattle, WA), they were exported as polygon mesh files, and voxelized using an in house MATLAB (The MathWorks, Natick, MA) code. The microgravity based phantoms are shown in Figure 6 2 (males) and Figu re 6 3 (females) Dosimetry with Microgravity Phantoms Body Self Shielding Distributio ns BRYNTRN and HZETRN require that the shielding of dose points within a phantom be reduced to a 1D body self shielding distribution by ray tracing to determine the amount of shielding about a given dose point. VoBRaT was created for this purpose ( Bahadori et al. 2011 ) VoBRaT was used to sample 500 dose points for all organs BFO ), for which 8000 dose points were sampled per organ. The resulting body self shielding distributions for the entire complement of or gans considered are available in Appendix I 2 It is important to note that uniform scaling was employed only because this investigation is considering hypothetical series of male and female astronauts. If detailed informa tion is known about the morphometry of an individual, a phantom that more accurately reflects that particular individual can be constructed. This capability of UFHADM and UFHADF was exhibited in Johnson et al (2009)

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161 Microgravity Phantom Dosimetry Organ dose equivalent results Results from BRYNTRN and HZETRN were combined with the body self shielding distributions to derive organ dose equivalent (for SPE irradiation) and organ dose equivalent rate (for trapped proton and GCR irradiation). Simplified vehicle shielding distributi ons were once again assumed: space suit shielding at 0.5 g cm 2 aluminum equivalent a thinly shielded PV shielding at 2 g cm 2 aluminum equivalent and an SPE storm shelter area within a spacecraft at 10 g cm 2 aluminum equivalent To return organ dose e quivalent or organ dose equivalent rate for each space radiation environment, the body self shielding ray thicknesses were interpolated over the depth dose distribution at these aluminum equivalent shielding thicknesses. Organ dose equivalent rates for tr apped protons and GCR in PV shielding are shown in Figure 6 4 and Figure 6 5 respectively, while organ dose equivalent results for the August 1972 SPE for suit shielding and shelter shielding are shown in Figure 6 6 and Figure 6 7 respectively To more explicitly illustrate the relationship between anatomical modeling and organ dose equivalent, the fractional difference between the organ dose equivalents for the microgravity 5 th PCTL or 95 th PCTL UF phantom and the microgravity 50 th PCTL UF phantom was calculated as the ratio of the microgravity 5 th PCTL or 95 th PCTL UF phantom organ dose equivalent and the microgravity 50 th PCTL UF phantom organ dose equivalent minus unity. Plots of organ dose equivalents and fractional differences for all combinations of space radiation environment and vehicular shielding are available in the Appendix J and Appendix K respectively As in Chapter 5 the average radiation quality factor was calculated as the quotient of the organ dose equivalent and organ absorbed dose. Tables of the average radiation

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162 quality factor for the phantom organs are shown for the February 1956 SPE radiation enviro nment with space suit shielding ( Table 6 3 ), GCR radiation environment with PV shielding ( Table 6 4 ), and August 1972 SPE radiation environment with shelter shielding ( Table 6 5 ). The average radiation quality factor again varied as a functio n of organ location and, to a lesser extent, phantom type. The average quality factors for the SPE environments were smaller in magnitude, and exhibit ed less overall variation, than the average quality factors for the GCR environment. These radiation quality factors compare d well with calculated quality factors for protons and GCR in previous studies ( Badhwar et al. 2002 ; Bahadori et al. 2011 ) For protons quality fa ctors from 1.4 to 1.7 were observed, while for GCR quality factors from 3.0 to 4.5 were observed. Comparison with Earth based phantoms To investigate the effect of microgravity induced changes on organ dose equivalent, the fractional differences in organ dose equivalent of each microgravity based phantom with respect to the corresponding Earth based phantom ( Bahadori et al. 2011 ) were calculated for the space radiation environments evaluated in the present study No general trend in these values was observed in terms of phantom size 3 Plots comparing the organ dose equivalent rates for the Earth and microgravity based phantom sets for trapped protons and GCR in PV shielding are shown Figure 6 8 and Figure 6 9 respectively while plots comparing the organ dose equivalents for the 3 Occasionally, values not following the general trend were observed because of the way in which the phantoms were scaled. Recall that microgravity changes were implemented with the 50 th percentile phantoms, and the 5 th and 95 th percentile microgravity based phantoms were created through sca ling (i.e., the changes were not directly applied to the 5 th and 95 th percentile Earth based phantoms). Thus, especially for small ray thickness values, some slight inconsistencies in the body self shielding distributions were observed for the 5 th and 95 t h percentile phantoms. These inconsistencies were magnified for SPE dosimetry, especially for thin vehicular shielding, due to the steepness of the depth dose distribution for these spectra at small ray thickness values.

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163 August 1972 SPE for suit shielding and shelter shielding are shown in Figure 6 10 and Figure 6 11 respectively Note that these plo ts display the organs in about the same cranio caudal order in which one would find them in the body, except for the distributed organs, which are displayed last. For each plot comparing the Earth and microgravity based phantoms, the red dashed line indic ates the average fractional difference for the microgravity based 5 th PCTL phantom (with respect to the microgravity based 50 th PCTL phantom), while the blue dashed line indicates the average fractional difference for the microgravity based 95 th PCTL phantom (with respect to the microgravity based 50 th PCTL phantom). These are included to help the reader understand the relative magnitudes of the differences in organ dose equivalent and organ dose equivalent rates resulting from (1) anatomical size an d (2) microgravity induced changes. Plots of fractional differences for all combinations of space radiation environment and vehicular shielding are available in Appendix L Implications for space dosimetry As observed in the previous study by Bahadori et al ( 2011 ) and in Chapter 5, both the body self shielding distributions and the organ dose equivalents ( Figure 6 4 Figure 6 5 Figure 6 6 and Figure 6 7 ) exhibit ed the expected general trend: more shielding and lower organ dose equivalents for the larger phantom, and less shielding and higher organ dose equivalents for the smaller phantom. Also, the variation in organ dose equivalent was heavily dependent upon the spectrum of charged particles and the amount of vehicular shielding for soft radiation spectra. Systematic differences were found when comparing the Earth and microgravity based phantoms ( Figure 6 8 Figure 6 9 Figure 6 10 and Figure 6 11 ). For small organs in the head, a decrease in organ dose equivalent resulted from the head tilt associated with the neutral body

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164 posture. The decrease was more pronounced for the males, sin ce the UFHADM neck was shorter than the UFHADF neck, and so as the head was brought closer to the torso, the body self shielding increased to a greater degree. In the upper torso, most organs were unaffected by the microgravity induced changes. The excep tion was the female breast. Here, a decrease in organ dose equivalent was observed, likely resulting from the change in arm position. In the mid to lower torso, an increase in organ dose equivalent was observed as most of the mass was removed from this region to accommodate the total body mass decrease. The greatest increases were observed for the male bladder and prostate, and for the female uterus. The female bladder dose equivalent increased, but not as much as the uterus, since almost all of the ma ss was removed from the posterior portion of the lower torso. The change in leg position caused the testis organ dose equivalent to decrease substantially. The skin exhibited a slight increase in organ dose equivalent with the muscle showing a greater i ncrease. The reduction in trabecular bone density coupled with the decrease in overall body mass, resulted in an increase in BFO dose equivalent on par with the other two distributed organs. Applicability to exploratory missions The greatest differences in organ dose equivalent and effective dose were observed for light vehicular shielding and soft radiation spectra. On an exploratory class mission, astronauts might find the mselves in this very situation; for instance, if they are performing an EVA and a n SPE occurs. Even if warned about the impending wave of protons resulting from the SPE, astronauts on EVA might not have enough time to return to a solar storm shelter. In this situa tion, the guiding principle (and legal requirement) of ALARA must be pr eserved. Astronauts performing an EVA should be

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165 well versed in how to minimize radiation exposure to critical organs in the event of an SPE. The results of the present study indicate d that posture can affect organ dose equivalent resulting from space rad iation exposure 4 Therefore, future studies should investigate the optimum body positioning for astronauts on EVA if irradiated by SPE of varying intensity and hardness. Effective Dose Results Once again, an effective dose was approximated using organ dose equivalents and gender specific tissue weighting factors similar to those recommended in ICRP Publication 60 ( 1991 ) ( Table 5 6 ). The effective dose rates as a function of vehicular shielding are shown for trapped protons and free space GCR in Figure 6 12 and Figure 6 13 respectively. Similarly, the effective doses as a function of vehicular shielding are shown for the February 1956 SPE in Figure 6 14 October 1989 SPE in Figure 6 15 and August 1972 SPE in Figure 6 16 Also shown are the effective dose results from the Earth based phantoms, from Chapter 5 and a previous study ( Bahadori et al. 2011 ) Slight increases in effective dose rate were observed for both male and female phantoms irradiated by trapped protons, while almost no differences in effective dose rate were observed for the GCR spectrum. When irradiated by the soft SPEs (October 1989 and August 1972) the female phantoms exhibited slight increases in effective dose, while the male phantoms exhibited decreases in effective dose (resulting from the decrease in testis dose equ ivalent). For the harder February 1956 SPE, very slight increases in female effective dose and very slight decreases in male effective dose 4 One must consider the risk from exposure to SPE as a function of time to evaluate the practicality of using posture as a counter measure. SPE can last for days; in this case, an astronaut might use posture as a counter measure for the first portion of the SPE and then move to a shelter for long term protection.

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166 were observed. Generally, the differences between the Earth and microgravity based phantoms, both in terms of org an dose equivalent and effective dose, were more pronounced for softer radiation spectra and decreased with increasing vehicular shielding. The same pattern was observed for the organ dose equivalent and effective dose differences resulting from variation s in phantom size. Chapter Summary The results of Bahadori et al ( 2011 ) and the present study indicate d that greater differences in effective dose (and hence, risk) were observed from changes in astronaut size than from microgravity induced changes. Anthropometric measurements of the astronauts should be utilized to create astronaut specific phantoms, which could then be used to prospectively or retrospectively evaluate the radiological risk of space missions. Eve n scaling the UF hybrid phantom by hand, an astronaut phantom could be easily created in a few day s In the future, existing CT or MR data and external body scans could be used to create an image based astronaut speci fic phantom. In this scenario, the outer body contour of the phantom would be iteratively changed so as to minimize differences with the segmented image set. Organ shapes and sizes would similarly be changed to match those of the astronaut. Under the li kely scenario that only a partial body CT was available, anatomy out of the field of view would be inferred based on the anatomy in the field of view.

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167 Figure 6 1 Neutral body posture ( NASA 2010 )

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168 A B Figure 6 2 Male microgravity based phantoms at the 5 th (left), 50 th (middle), and 95 th (right) height and weight percentiles ( Bahadori et al. 2012 )

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169 A B Figu re 6 3 Female microgravity based phantoms at the 5 th (left), 50 th (middle), and 95 th (right) height and weight percentiles ( Bahadori et al. 2012 )

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170 A B Figure 6 4 Trapped proton (A) male and (B) female organ dose equivalent rates for PV shielding ( microgravity based anthropometrics) ( Bahadori et al. 2012 )

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171 A B Figure 6 5 GCR (A) male and (B) female organ dose equivalent rates for PV shielding ( microgravity based anthropometrics) ( Bahadori et al. 20 12 )

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172 A B Figure 6 6 August 1972 SPE (A) male and (B) female organ dose equivalents for suit shielding ( microgravity based anthropometrics) ( Bahadori et al. 2012 )

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173 A B Figure 6 7 August 1972 SPE (A) male and (B) female organ dose equivalents for shelter shielding ( microgravity based anthropo metrics) ( Bahadori et al. 2012 )

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174 A B Figure 6 8 Trapped proton (A) male and (B) female microgravity fractional differences for PV shielding (comparison with Earth based values) ( Bahadori et al. 2012 )

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175 A B Figure 6 9 GCR (A) male and (B) female microgravity fractional differences for PV shielding (comparison with Earth based values) ( Bahadori et al. 2012 )

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176 A B Figure 6 10 August 1972 SPE (A) male and (B) female microgravity fracti onal differences for suit shielding (comparison with Earth based values) ( Bahadori et al. 2012 )

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177 A B Figure 6 11 August 1972 SPE (A) male and (B) female microgravity fractional differences for shelter shielding (comparison with Earth based values) ( Bahadori et al. 2012 )

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178 Figure 6 12 Trapped proton effective dose rates ( Earth based vs. microgravity based ) ( Bahadori et al. 2012 ) Figure 6 13 GCR effective dose rates (Earth based vs. microgravity based) ( Bahadori et al. 2012 )

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179 Figure 6 14 February 1956 SPE effective d oses (Earth based vs. microgravity based) ( Bahadori et al. 2012 ) Figure 6 15 October 1989 SPE effective doses (Earth based vs. microgravity based) ( Bahadori et al 2012 )

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180 Figure 6 16 August 1972 SPE effective doses (Earth based vs. microgravity based) ( Bahadori et al. 2012 )

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181 Table 6 1 Implementation of microgravity induced changes ( Bahadori et al. 2012 ) Microgravity Effect UF Hybrid Phantom Change Loss of leg volume Scale legs in 2D to reduce leg volume by 10% Sitting height increase Scale torso outer body contour and spine by a factor of 1.03 in z direction Cardiac atrophy Reduce overall heart volume by 10% Bone mineral density loss Reduce bone density of trabecular bone by 10% for spine, hips, and proximal femora Overall mass loss Remove mass from lower torso, targeting 4 5% mass loss Neutral body posture Reposition arms, legs, and head, using Figure 6 1 as a guide Table 6 2 Earth and microgravity based phantom mass comparison ( Bahadori et al. 2012 ) Phantom Earth Based Mass (kg) Microgravity Based Mass (kg) Change (%) UFHADM5 66.6 63.4 4.8 UFHADM50 83.4 79.2 5.0 UFHADM95 99.9 94.9 5.0 UFHADF5 46.5 44.5 4.2 UFHADF50 62.0 59.2 4.5 UFHADF95 77.6 74.0 4.6

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182 Table 6 3 Quality factors for February 1956 SPE radiation environment with suit shielding ( microgravity based anthropometrics) ( Bahadori et al. 2012 ) Organ F5 F50 F95 M5 M50 M95 Eye Lens es 1.65 1.62 1.62 1.60 1.59 1.59 BFO 1.5 6 1.56 1.5 7 1.5 7 1.5 8 1.5 8 Colon 1.56 1.56 1.57 1.56 1.57 1.58 Lung s 1.55 1.56 1.57 1.56 1.57 1.58 Stomach 1.56 1.57 1.57 1.59 1.60 1.61 Breast s 1.54 1.54 1.54 N/A N/A N/A Ovar ies 1.58 1.59 1.60 N/A N/A N/A Test es N/A N/A N/A 1.56 1.56 1.56 Bladder 1.56 1.57 1.58 1.59 1.60 1.61 Esophagus 1.58 1.60 1.60 1.60 1.61 1.62 Liver 1.57 1.58 1.58 1.59 1.60 1.60 Thyroid 1.55 1.55 1.55 1.55 1.56 1.56 Brain 1.54 1.55 1.56 1.54 1.55 1.55 Salivary Gland s 1.55 1.55 1.55 1.55 1.55 1.55 Skin 1.72 1.72 1.72 1.72 1.72 1.72 Adrenal s 1.59 1.60 1.61 1.61 1.61 1.62 ET Region 1.55 1.55 1.56 1.55 1.56 1.56 Gallbladder 1.60 1.61 1.61 1.61 1.62 1.63 Heart 1.58 1.59 1.59 1.59 1.60 1.61 Kidney 1.56 1.56 1.57 1.59 1.59 1.60 Muscle 1.55 1.56 1.56 1.56 1.56 1.56 Oral Mucosa 1.56 1.57 1.58 1.57 1.58 1.58 Pancreas 1.59 1.60 1.61 1.61 1.61 1.62 Prostate N/A N/A N/A 1.60 1.60 1.61 Small Intestine s 1.57 1.58 1.58 1.58 1.59 1.60 Spleen 1.55 1.56 1.56 1.57 1.58 1.58 Thymus 1.57 1.58 1.59 1.58 1.59 1.60 Uterus 1.59 1.60 1.60 N/A N/A N/A

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183 Table 6 4 Quality factors for GCR radiation environment with PV shielding ( microgravity based anthropometrics) ( Bahadori et al. 2012 ) Organ F5 F50 F95 M5 M50 M95 Eye Lens es 4.44 4.36 4.31 4.32 4.26 4.20 BFO 3.6 5 3.5 4 3. 46 3.46 3.39 3.34 Colon 3.67 3.56 3.49 3.51 3.42 3.35 Lung s 3.68 3.57 3.49 3.58 3.50 3.45 Stomach 3.59 3.49 3.41 3.26 3.19 3.13 Breast s 4.10 4.01 3.95 N/A N/A N/A Ovar ies 3.39 3.28 3.19 N/A N/A N/A Test es N/A N/A N/A 3.62 3.57 3.55 Bladder 3.56 3.45 3.36 3.23 3.15 3.11 Esophagus 3.39 3.28 3.18 3.21 3.13 3.08 Liver 3.50 3.37 3.29 3.28 3.21 3.15 Thyroid 3.87 3.77 3.69 3.62 3.55 3.51 Brain 3.87 3.76 3.68 3.82 3.74 3.68 Salivary Gland s 3.96 3.84 3.75 3.82 3.72 3.67 Skin 4.56 4.51 4.47 4.50 4.46 4.44 Adrenal s 3.34 3.21 3.13 3.15 3.07 3.02 ET Region 3.84 3.72 3.63 3.72 3.64 3.59 Gallbladder 3.27 3.16 3.07 3.10 3.02 2.97 Heart 3.42 3.32 3.24 3.26 3.19 3.12 Kidney 3.60 3.49 3.43 3.30 3.24 3.18 Muscle 4.00 3.91 3.84 3.89 3.83 3.78 Oral Mucosa 3.64 3.51 3.42 3.55 3.47 3.41 Pancreas 3.32 3.20 3.11 3.16 3.08 3.03 Prostate N/A N/A N/A 3.25 3.18 3.13 Small Intestine s 3.50 3.39 3.31 3.31 3.23 3.19 Spleen 3.68 3.56 3.48 3.42 3.35 3.29 Thymus 3.54 3.43 3.34 3.37 3.29 3.24 Uterus 3.38 3.27 3.19 N/A N/A N/A

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184 Table 6 5 Quality factors for August 1972 SPE radiation environment with shelter shielding ( microgravity based anthropometrics) Organ F5 F50 F95 M5 M50 M95 Eye Lenses 1.45 1.44 1.44 1.43 1.43 1.43 BFO 1.45 1.4 6 1.46 1.46 1.4 7 1.47 Colon 1.44 1.45 1.45 1.45 1.46 1.47 Lungs 1.45 1.46 1.47 1.46 1.47 1.47 Stomach 1.45 1.46 1.47 1.50 1.51 1.52 Breasts 1.42 1.43 1.43 N/A N/A N/A Ovaries 1.49 1.50 1.52 N/A N/A N/A Testes N/A N/A N/A 1.44 1.44 1.44 Bladder 1.45 1.46 1.47 1.50 1.51 1.52 Esophagus 1.49 1.51 1.53 1.53 1.55 1.56 Liver 1.46 1.47 1.48 1.49 1.50 1.51 Thyroid 1.43 1.44 1.44 1.45 1.45 1.45 Brain 1.44 1.45 1.46 1.45 1.45 1.45 Salivary Glands 1.43 1.44 1.44 1.44 1.44 1.44 Skin 1.47 1.48 1.47 1.47 1.48 1.48 Adrenals 1.49 1.51 1.53 1.53 1.54 1.56 ET Region 1.44 1.44 1.45 1.44 1.45 1.45 Gallbladder 1.51 1.53 1.55 1.55 1.58 1.59 Heart 1.48 1.49 1.50 1.50 1.51 1.53 Kidney 1.45 1.46 1.46 1.48 1.49 1.50 Muscle 1.43 1.43 1.43 1.43 1.43 1.44 Oral Mucosa 1.46 1.47 1.49 1.47 1.48 1.48 Pancreas 1.50 1.52 1.54 1.53 1.55 1.56 Prostate N/A N/A N/A 1.51 1.52 1.52 Small Intestines 1.46 1.47 1.48 1.48 1.49 1.50 Spleen 1.45 1.45 1.46 1.47 1.47 1.48 Thymus 1.47 1.48 1.49 1.49 1.50 1.51 Uterus 1.49 1.51 1.53 N/A N/A N/A

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185 CHAPTER 7 COMPARISON OF RISK ESTIMATES USING PHIT S AND HZETRN HZETRN2010 Transport For the final portion of the present study, HZETRN2010, the most recent version of the NASA heavy ion transport code was used As previously discussed, HZETRN2010 was greatly improved over previous versions, both in terms of neutron transport ( Slaba et al. 2010a ) and step size and energy grid convergence ( Slaba et al. 2010b ) Spectral Input Another important aspect of HZETRN2010 is the simplification of spectral input. Previous versions of the NASA transport codes ( Wilson et al. 1989 ; Wilson et al. 2006 ) had spectra built in, including the Badhwar ( O'Neill 2006 ) Instead of inputting the spectra directly, the user inputted parameters associated with a particular Earth orbit and solar conditions when transporting trapped proton or GCR environments. For SPE environments, a built in spectrum was chosen for transport in BRYNTRN. This posed challenges in determining th e spectrum transported by the codes. HZETRN2010 utilizes environment input files instead of built in space radiation environments. V astly improved documentation assisted in determining how the spectra needed to be represented in the environment input fil es. The drawback of this approach is that for LEO environments, the trapped proton and GCR spectra must be determined separately from the transport code; however, methods to do so are well documented ( Badavi et al. 2006 ) In the present study, the February 1956 SPE and August 1972 SPE were investigated, representing hard and soft spectra, respectively. A trapped proton and

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186 albedo neutro n spectrum for an altitude of 400 km and 51.6 degree inclination, generated using the AP8 model of the 1965 solar minimum, was used. While the SPE and trapped proton spectra investigated were distributed with HZETRN2010, the Badhwar ( O'Neill 2010 ) was used to generate the 1977 solar minimum GCR spectrum for elements hydrogen thr ough nickel on the HZETRN2010 energy grid. The Badhwar model was previously shown to be the most accurate of several available models for the most recent solar cycle ( Mrigakshi et al. 2012 ) Seven elem ents that contribute substantially to organ dose equivalent (H, He, C, O, Mg, Si, and Fe) were transported individually, and the remaining ions were grouped into three sets with each group being transported collectively The GCR ions included in each gro up are presented in Table 7 1 The most abundant isotope of each element was used to represent each GCR ion. HZETRN2010 Modules and Post Processing In addition to the improved spectral input, cross section generation was modularized. To transport particles or calculate dosimetric quantities within a given material, the cross sections governing the probabilities of interaction and resulting products m ust be generated. HZETRN2010 requires the user to define the material by specifying the atomic number, mass number, and number density of each constituent element to generate the cross sections. This process is repeated for each material that the user de sires to include in the transport procedure. For the present study, only aluminum, representing shielding external to the astronaut, and water, representing astronaut body self shielding, were considered. Once the aluminum and water cross sections were g enerated, transport was executed. The user has various options for the

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187 transport module, most notably the number of layers and corresponding materials, the method of neutron transport, and the depths at which the user wishes to tally fluence and subsequen t dosimetric quantities. When the user executes the transport module, particle fluence values at the specified depths of material are calculated. Subsequent to transport, the response function module was executed to generate absorbed dose and dose equiv alent (using the LET dependent quality factor definition as before) per ICRP Publication 60 ( 1991 ) Interpolation post processing was required to return organ absorbed dose and organ dose equivalent for UFHADM50 and UFHADF50. Previously, an altered form of the NASA risk code was used to generate organ averaged dosimetric quantities. The code used for the present chapter was rewritten for clarity and simplicity; also, a MATLAB code was written to interpolate for organ averaged fluence spectra using the results of the HZETRN2010 t ransport module. The se interpolation codes are presented in Appendix M. PHITS 2.30 Transport Despite the advances in HZETRN to date, it is limited in the types of radiation it can transport in its current form. HZETRN does not address photons, electrons or positrons, or mesons, although the incorporation of contributions from these particles is in work (T. Slaba, personal communication). HZETRN also relies on representing the transport geometry using 1D slabs, which requires the use of an external ray tr acing code. Thus, 3D effects cannot be simulated. PHITS version 2.30 ( Niita et al. 2010 ) was used to generate organ absorbed dose and organ dose equivalent for geometry equivalent to that used for processing the HZETRN2010 simulation results. PHITS was chosen for the comparison for the reasons stated in Chapter 2; primarily these relate to the ease of parallelization, similarity with HZETRN in ca lculation of total interaction

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188 cross sections, and treatment of particles of interest. The goal was to determine whether calculations of risk quantities related to radiation carcinogenesis were substantially different using organ dosimetry results from th e two codes. PHITS Input File Structure The general structure of a PHITS input file is independent of whether the code is run in serial or parallel mode. Input files for the present study included the following sections: Title, Parameters, Source, Material Cell, Surface, and Tallies. The user specifies a descriptive phrase for the problem in the Title section. The parameters that govern transport, such as energy cut offs and cross section calculation methods sect ion. The user defines the type, energy, physical bodies (including lattice struct sections. Finally, values to be recorded in the problem are specified in tallies, each of which has its own section. An example PHITS input file used to generate data for the present chapter is included in App endix N. Parameters section n for the present study that affected particle transport and tally recording are shown in Table 7 2 These values were

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189 variable governs the type of PHITS run that is executed. Other than normal execution, options for this variable include geomet ry checking by voiding all materials and plotting number of particles per batch and number of batches, respectively. In parallel The values chosen for these variables in the PHITS runs balanced run times while achieving acceptable error values. T to record tally output after every batch so that the progress of a particular run could be monitored record information regarding particles that pass below the minimum energies for transport for neutrons and gammas, respectively. The default values have recently been changed to 0, but since previous versions of PHITS had different defaults, the values needed to be set in the input file. e seed number for the pseudo random number generator. A value of less than 0 causes the seed number to be chosen based upon the system time, and a value of greater than 0 causes the seed number to be set to that value. locat ions for input and output files used by PHITS cross section library file, the gamma decay file, and the giant dipole resonance file, respectively. The default values were 1.0 MeV for protons, neutrons, pions, muons, and kaons;

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190 9 MeV for electrons, positrons and gammas and 10 9 MeV n 1 for charged particles heavier than protons effectively preventing transport. The proton minimum energy was reduced to 1 keV, and the minimum energy for charged particles heavier than protons was reduced to 1 keV n 1 The neutron minimum energy was reduced to 10 4 eV, while electron and positrons were cut off at 1 MeV to avoid a bug in PHITS when electrons and positrons are transported below 1 MeV P hotons were transported to 1 keV. The maximum energy for cross section libraries for neutrons was se t at 20 MeV, and 1 GeV was used as the maximum energy for cross section libraries for electrons, positrons, and gammas. The default value of 150 MeV for proton transport using cross section libraries was unchanged. Decay gammas were considered by setting b Bertini model to simulate nucleon nucleus interactions. This was set to 20 MeV. The The event generator ( Niita et al. 2011 ) allows PHITS to sample the results of nuclear reac tions, which is particularly important for determining the quality factor for products of low energy neutron reactions. Thus, charged particles resulting from neutron interactions were statistically creat ed and a true measure of the dose equivalent imparted as a result of secondary charged particles from neutron interactions was calculated. Finally, the use of voxel phantoms is greatly simplified in PHITS by including the and executed, a binary file using the voxel array is

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191 the voxel phantom. This procedure speeds up the reading of voxel information in PHITS and prevents the entire voxel array from being echoed in th e output file. Source section source u sed i n the PHITS simulation. T his variable was set to 100, indicating that a user defined source was used. The user defined source relies on PHITS being present study is inclu ded in Appendix O For the source geometry, the isotropic irradiation scheme as described by Rajon and Bolch ( 2003 ) was utilized Here, the center of a source plane was defined by sampling for the azimuthal and polar angles. T he source plane was represented as a circle with radius 500.1 cm, just larger than the outer diameter of the spherical shell representing nominal vehicular shielding. The source plane was placed 500.1 cm away from the center of the spherical she ll. Once the source plane was defined, particle start position on the source plane was determined by sampling for radius and polar angle The particle originated at the sampled position and was given a trajectory parallel to the vector from the center of the source plane to the center of the spherical shell. The code to perform particle type and energy sampling was provided by Dr. Tatsuhiko Sato at JAEA. When multiple particles were used in a single si mulation (for the grouped GCR ions) the source algorithm sampled uniformly between 0 and 1 and determined the particle type to simulate by comparing the sampled value to a cumulative distribution function based upon total number of particles. As an example,

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192 consider two particle typ es, Type A and Type B. If the total number of particles of each type is the same, the cumulative distribution function value associated with Type A is 0.5, while the cumulative distribution function value associated with Type B is 1. Thus, if the sampled value is between 0 and 0.5, Type A is simulated, while if the sampled value is between 0.5 and 1, Type B is simulated. The energy of the particle was determined by sampling uniformly from 0 to 1 and determining the energy corresponding to the sampled cum ulative distribution function value. An input file, definitions required for the user defined source To confirm that the input spectrum was represented properly, a test run was completed for each irradiation case in which the created particles were tallied, resulting in a fluence spectrum for comparison with the fluence spectrum as represented in HZETRN2010. In addition to defining the source type, various constant constants used are presented in Table 7 3 Materials and geometry set up The materials and geometry of the problem (other than source geometry) were file. In mass of each constituent element was defined. Here, the most abundant isotope was used to represent each element (except for carbon), as ENDF VII data for the natural element s are generally not available tells PHITS how to set up the lattice array in the problem geometry and how to fill the lattice with materials, was defined. Although the lattice data c an be input directly in the PHITS input file, it is not practical to do so for large lattices, such as those representing

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193 human phantoms. Instead, the lattice data was located in a different input file, which was compiled for use in PHITS as described pre viously. After the lattice structure definition, the information for each organ index used in the lattice data was given. This included the material, density, and volume of each organ. Finally, the general geometry of the problem was defined, which incl uded The phantom box (volume encompassing the lattice) Vacuum between the phantom box and the spherical shell, Spherical shell (representing nominal vehicular shielding), Vacuum outside of the spherical shell, and The particle graveyard, at which point p articles are no longer transported. dimensions of the surfaces defining the geometry previously described were given. In addition to defining the outer dimensions of the phantom box, the voxel dimensions were define d. The inner diameter of the spherical shell was defined as 500.0 cm minus the spherical shell thickness, and the particle graveyard was defined as everything outside of a sphere of radius 10 m. The inclusion of a particle graveyard is necessary to limit particles that cannot return to the tally cells. Tally sections PHITS allows the user to specify quantities resulting from simulation to be recorded. These are called tallies, and provide a window into the transport process es of the simulation. Each tally is afforded its own section, in which parameters governing how the tally is executed are defined. The first set of tallies used in my PHITS was recorded. One hundred energy bins between 1 keV and 10 TeV were used, and specific particles of interest were specified. These particles corresponded to the

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194 particles transported in HZETRN2010 to allow for a direct comparison of organ averaged partic le fluence. A lthough the user inputs the energy spectrum in energy per nucleon, PHITS tallies output in terms of absolute energy on a per source particle basis. Therefore, appropriate post processing must be performed to directly compare fluence spectra weighted volumetric energy Deposit used the ICRP Publication 60 ( 1991 ) qu ality factor definition implemented in a PHITS source file. As a practical matter, any weighting factor can be implemented by coding the algorithm in FORTRAN and recompiling PHITS. Current ly, PHITS can be compiled with two algorithms; the specific algori thm to be used variable. The material in which the LET is calculated must also be defined; otherwise, variable, since LET must be determined in water per ICRP Publication 60 ( 1991 ) The Deposit Deposit conversion was employed to convert to units of absorbed dose density. Finally, LET present study. PHITS Parallel Mode PHITS was run in parallel mode to reduce computation times to manageable levels. Most of the simulations were performed on the NASA Space Radiation Analysis Group (SRAG) cluster known as Watson. Watson has twenty AMD 6176 nodes with 24 processors per node and 32 GB of random access memory per node, and eight AMD

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195 6276 nodes wi th 32 processors per node and 32 GB of random access memory per node. A few of the simulations were completed on the UF Advanced Laboratory for Radiation Dosimetry Studies (ALRADS) cluster, Trogdor. Trogdor consists of five nodes with 16 Intel Xeon E5640 processors per node and one node with 24 Intel Xeon E5640 processors; all nodes have 24 GB of random access memory. Whether run in serial or parallel mode, there are no differences in the input files for PHITS. The major differences occur in the compila tion of the code, which requires references to different source files and a compiler capable of parallel operations. Subsequent to compilation, test files were run to confirm that install ation was performed correctly. Although running PHITS in parallel re duced s imulation time considerably, it is not yet feasible to use PHITS in operational eva luations of astronaut dosimetry Firstly, for the GCR ions, the high energy and fragmentation resulted in simulation times on the order of a few days for more than 1 00 processors. The uncertainty requirements could be relaxed in order to reduce computation time, but for structures larger than the 500 cm outer diameter spherical shell simulated in the present study, such as the ISS, the statistics for a given number of incident particles would be much worse due to a larger simulation volume. Also, it is difficult at present to incorporate complex structures in PHITS due to the simplified geometry mechanisms currently used. PHITS Post Processing Although PHITS states a relative error for each tally, this value represents the error associated with the mean of the tally for a single random number. To gain a true representation of the uncertainty in a tally, PHITS must be executed multiple times and the standard error of the mean should be calculated. PHITS was executed four times for most simulation s (all except the August 1972 SPE with shelter shielding, which was

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196 executed six times ) to characterize the standard error of the mean for each tallied quantity. The tally output files for the four runs in each simulation were post processed using MATLAB code. Since geometry and physics are coupled in PHITS, the PHITS post processing code was much simpler than the post processing code used for HZETRN2010. The MATLAB code i ncluded the appropriate corrections to organ absorbed dose and organ dose equivalent using organ density. The standard error of the mean was calculated to characterize the uncertainty associated with each tallied quantity. Fluence units from PHITS were c onverted to be in accord with fluence units from HZETRN2010 to allow for direct comparison. The MATLAB post processing code for PHITS output is included in Appendix P Determining Radiogenic Cancer Mortality Risk Measures of Radiogenic Cancer Mortality Ri sk While the concept of radiogenic cancer mortality risk is simple, there are different methods for quantifying it some of which are complicated Two of the most often utilized methods are lifetime attributable risk (LAR) and radiation exposure induced d eath ( REID ) ( Thomas et al. 1992 ) (it should be noted here that radiogenic mortality resulting from other causes, such as cardiovascular or even CNS effects can be included in the risk calculation for both LAR and REID, although these are usually omitted, as the mortality hazard functions for radiation risks other than carcinogenic risks are poorly understood at present ). LAR is used by entities such as BEIR VII ( NRC 2006a ) and the US EPA ( 2011 ) to characterize radiogenic cancer incidence and mortality risks. Mathematically, LAR for radiogenic cancer mortality is an integration of the radiogenic cancer mortality hazard function over all ages. Thus, L AR does not include the reduction in radiogenic cancer mortality risk that occur s as a result of

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197 increases in the mortality hazard function from the exposure. When the linear no threshold (LNT) theory is applied, LAR from a specific organ is directly prop ortional to the dose used to characterize the radiation exposure to that organ. REID, however, is the integral over all ages of the product of the radiogenic cancer mortality hazard function and a reduction factor, equal to the exponential of the negative integral of the radiogenic cancer mortality hazard function from time of exposure to a given age, which accounts for radiogenic cancer deaths from the time of exposure to a given age. REID from a specific organ is therefore not directly proportional to t he dose characterizing the exposure of the organ even under the assumption of LNT The REID formulation complicates the case of multiple exposures. Technically, REID from separate exposures are not additive; it is instead the mortality hazard functions that are additive. Practically speaking, though, the reduction factor in the REID formulation is only marginally different from unity at whole body exposures less than about 1 Sv ( Kellerer et al. 2001 ) (the rule of thumb is of course dependent upon the absolute values of the radiogenic cancer mortality hazard function). This exposure level is greater than most career dose values derived from the 3% REID career limit, and so in practice, REID from separate exposures are summed to derive a point estimate for the REID. For the comparison of risk estimates resulting from HZETRN2010 and PHITS space radiation transport, two methods for characterization of risk were considered The first was the effective dose as characterized previously ( Bahadori et al. 2011 ; Bahadori et al. 2012 ) as calculated in Chapter 5 and Chapter 6. The tissue weighting factors used for the calculation of effective dose are given in Table 5 6. The NASA RHO currently uses age and gender dependent coeffic ients to determine REID from

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198 effective dose; however, since the coefficients are linear with effective dose, percent differences in effective dose result in equivalent percent differences in risk. REID directly calculated from each cancer site is preferab le to the currently employed effective dose method, as it does not rely on tissue weighting factors that contain inherent assumptions as to the relative contribution of risk from each cancer site. This is especially true of the gonads and thyroid, which e xhibit large tissue weighting factors, but actually contribute little to adult radiogenic cancer mortality. Also, age and gender dependence is included in the site specific models, negating the need for the inclusion of epidemiology based upon the effecti ve dose. Several models for site specific risk have been published ( NRC 2006a ; Preston et al. 2007 ; UNSCEAR 2008 ) as the site specific statistics from the Japanese Atomic Bomb Survivor dataset have matured. A recent publication by Cucinotta et al. ( 2011 ) detailed the pl anned updates to the NASA space radiation cancer risk model, which includes using site specific risks to calculate REID. US EPA Radiogenic Cancer Risk Model Justification for use of US EPA model In the present study, the most recent update to the US EPA ra diogenic cancer risk model ( EPA 2011 ) was used to calculate REID resulting from space radiation exposures. This particular risk model was chosen for a variety of reasons. Firstly, the radiation risk models and methods used were clearly explained in a published report, and the lead author, Dr. David Pawe l, was very helpful as the models were coded in MATLAB. Secondly, the US EPA model is largely based upon the BEIR VII radiogenic cancer excess incidence and mortality hazard functions, the details of which have also been published ( NRC 2006a ) Unlike Preston et al ( 2007 ) and UNSCEAR radiation risk

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199 models ( UNSCEAR 2008 ) a complete set of recommendations were made, including weights for relative contributions of excess absolute risk (EAR) and exce ss relative risk (ERR) models for each cancer site and a DDREF. Finally, the US EPA model incorporated novel techniques for the calculation of mortality risk resulting from breast cancer, which takes into account changing rates of incidence and mortality with time The method used for breast cancer presented an opportunity to develop a ne w method for calculation of breast cancer REID Novel method for determining breast cancer REID Although the US EPA model uses LAR to characterize radiogenic cancer mortality, REID can be calculated using the same tools as LAR. This is accomplished by including the radiogenic cancer mortality hazard function reduction factor as previously described. The organ that presented the largest challenge wa s the breast. Here, a formula that deviates from the standard conversion of incidence to mortality, which uses the ratio of mortality rate at a given age to the incidence rate at a given age, was used. Instead, incidence rates and five year survival rate s were folded with the EAR model radiogenic breast cancers served to decrease the calculated risk. The breast cancer REID calculation for the present study required a unique approach, in which the mortality hazard function was deduced from the risk calculation. The US EPA ( 2011 ) model lifetime attributable risk of radiogenic breast cancer death resulting from a breast dose D at age e is given as 7 1

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200 where a M is age of breast cancer mortality, a I is age of breast cancer incidence, h(a I ) is the probability that a breast cancer will result in death if diagnosed at age a I is the hazard function for radiogenic breast cancer incidence at age a I for a breast dose D given at age e and R(t, a I ) is the relative survival rate with breast cancer for a time t after diagnosis at age a I Since this formulation accounts for deaths du e to radiogenic breast cancer, it is not a strict measure of LAR. Consider a generic formulation for partial breast REID, 7 2 where is the hazard function for radiogenic breast cancer mortality at age a M for a breast dose D given at age e Note that for the standard REID calculation, the mortality hazard function in the exponential integral term accounts for all radiogenic cancer ins tead of just breast radiogenic cancer. Now, equating the formulations as given in Equation 7 1 and Equation 7 2, differentiating, and canceling like terms resulted in 7 3 The goal was to determine the mortality hazard function for all a M All other variables were known. Unfortunately, there was no closed form analytic solution, so numerical methods were used to solve the problem. First, the left side of Equation 7 3 was defined as 7 4

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201 with dependence on D and e implicit. If a M is considered to be a discrete vector, and the first element of a M is set to e F(a M [1]) is equal to zero, since the integral in Equation 7 4 has no width. Thus, by Equation 7 3, must also be zero. Under the assumption of trapezoidal numerical integration, and by combining Equations 7 3 and 7 4, the relationship among all variables for element i > 1 in vector a M is given as 7 5 where 7 6 and 7 7 Equations 7 5, 7 6, and 7 7 must be solved numerically. T he built in MATLAB function was used which finds the zero for a single variable in a non linear equation. Once all exposure was calculated as 7 8 Benchmarking MATLAB code of US EPA model To benchmark the MATLAB code associated with this radiation risk model, Table 3 13 from the US EPA radiation risk report ( EPA 2011 ) was recreated, using a test dose of 0.1 mSv for each or gan, as the difference between REID and LAR is negligible at this low dose Comparisons of the results from my MATLAB code and the

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202 US EPA radiation risk report are shown in Table 7 4 and Table 7 5 for females and Table 7 6 and Table 7 7 for males, indicating good agreement. The US EPA radiation risk MATLAB code is presented in Appendix Q Organ Dosimetry Results from HZETRN2010 and PHITS 2.30 The organ absorbed dose and organ dose equivalent values (with associa ted standard errors of the mean) for the different irradiation conditions considered are shown in Appendix R and Appendix S respectively. Note that organs displayed are limited to those that contributed to the effective dose or REID calculation. To quantify the differences observed in the two dosimetric quantities, the percent differences between or gan absorbed doses resulting from PHITS and HZETRN transport were calculated as 7 9 where is the organ absorbed dose resulting from PHITS and is the organ absorbed dose resulting from HZETRN. Similarly, the percent difference between organ dose equivalents resulting from PHITS and HZETRN transport were calculated as 7 10 where is the organ dose equivalent resulting from PHITS and is the organ absorbed dose resulting from HZETRN. The error formulas in the present study were calculated using the standard National Institute of Standards and Technolog y (NIST) formula, based on the work of Ku

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203 ( 1966 ) The error formula associated with the percent difference in organ absorbed doses was 7 11 w here is the standard error in organ absorbed dose from PHITS. Similarly, the error formula associated with the percent difference in organ dose equivalents was 7 12 w here is the standard error in organ dose equivalent from PHITS. Note that it is assumed in the NIST formula that there is no covariance between th e variables in the equation. The HZETRN derived organ dosimetry values were constant and not random variables like the PHITS derived organ dosimetry values. There is no covariance between a constant and a random variable; therefore, the NIST formula was applicable in this situation. The percent differences in organ absorbed dose and percent differences in organ absorbed dose are presented in Appendix T while the percent differences in organ dose equivalent are presented in Appendix U SPE and Trapped Spe ctrum Organ Dosimetry Excellent agreement was observed for the August 1972 SPE (e.g. Figure 7 1 ) which is comprised mostly of lower energy protons, and the trapped spectrum (e.g. Figure 7 2 ) which is comprised of lower energy protons and albedo neutrons. Good agreement was also observed for the February 1956 SPE (e.g. Figure 7 3 ) Differences were larger than expected for lightly shielded organs, especially the skin, for these proton dominant environments. For the HZETRN organ absorbed doses, the center of

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204 a randomly selected voxel was ray traced. However, at light shielding t hicknesses, there was a large gradient in absorbed dose and dose equivalent. The center of the voxel was thus not representative of the organ absorbed dose or organ dose equivalent because of the non linear behavior of the depth dose curves at these low r ay thicknesses. One way to improve the ray tracing procedure for the skin voxels is to add another sampling step in which the position within a voxel is sampled after a given voxel is chosen for ray tracing. The extra step would allow for the characteriz ation of the impacts of all possible ray thicknesses in a given voxel. GCR Organ Dosimetry Separating transport for 7 major GCR ions allowed for a more complete comparison of PHITS and HZETRN. For the GCR proton irradiation, the agreement in organ absorbe d dose and organ dose equivalent was within 10% (e.g. Figure 7 4 ) The organ dosimetry values were markedly different for GCR alpha irradiation, with organ absorbed doses showing 30 40% difference and organ dose equivalents showing 40 50% difference (e.g. Figure 7 5 ) The differences in organ absor bed dose decreased with increasing Z; the differences in organ dose equivalent decreased with increasing Z, except for iron, for which there was a slight increase in organ dose equivalent percent differences (e.g. Figure 7 6 ) Differences in organ absorbed dose and organ dose equivalent for GCR ions heavier than helium were within 15%, except for GCR iron organ dose equivalent percent differences, which were within 20%. Organ Differential Energy Flux Comparison To investigate differences in organ dosimetry between PHITS and HZETRN, a MATLAB function was written to compare the organ specific differential energy flux resulting from each code. The proton differential energy fluxes in the male skin and

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205 BFO resulting from GCR proto n irradiation from both codes are shown in Figure 7 7 The differential energy flux from HZETRN exceeds the differential energy flux from PHITS for bo th organs for energies greater than around 1 MeV n 1 for skin and 5 MeV n 1 for BFO, and so it is likely that there are some differences in how higher energy protons are addressed in the codes when one considers that the dosimetry quantities for the lower energy proton environments agreed well. Similarly, the alpha differential energy fluxes in the skin and BFO resulting from GCR alpha irradiation from both codes are shown in Figure 7 8 Note that the primary ion fluxes agreed well in this case. The helion, triton, deuteron, and proton differential energy fluxes in the BFO resulting from GCR alpha irradiation from both codes are shown in Figure 7 9 Figure 7 10 Figure 7 11 and Figure 7 12 respectively. The differential energy fluxes varied considerably, and so it was determined that for ions heavier than protons, the differences in organ dosimetry resulted from differences i n how the two codes addressed secondary charged particles. The differences for light ions were greater than differences for heavy ions since the cross section models used among codes show greater variation for light ions ( Durante and Cucinotta 2011 ) Thus, it is expected that if a common set of cross sections were use d in HZETRN and PHITS, even better agreement in organ dosimetry values would be observed. Effective Dose and REID Results Although differences were observed in organ dosimetry values, the quantity of interest to NASA is REID from space radiation exposure. The effective dose was calculated as previously described to characterize the current method for evaluating astronaut REID. The effective doses for the SPE environments are displayed in Figure 7 13 and corresponding percent differences are shown in Figure 7 14 As

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206 expected, the small differences in organ dose equivalent propagated to small differences in effective dose for these environments. A radar plot exhibiting effective dose rates associated with the complement of GCR ions is given in Figure 7 15 for UFHADM50 and UFHADF50. The percent differences associated with each GCR ion or ion set are shown in Figure 7 16 The HZETRN effective doses exceeded PHITS effective doses most notably for hydrogen and iron, while the PHITS effective doses exceeded HZETRN effective doses for helium and carbon. Results for the other ions and ion sets were similar between the two codes. A breakdown of the contributions from each GCR ion and ion set to the GCR effective dose calculated for the two codes is shown in Figure 7 17 The plot shows that the differences in contribution to effective dose largely result in canceling errors. The effective dose rates for the trapped proton environment and GCR environment are shown in Figure 7 18 with corresponding percent differences shown in Figure 7 19 Despite the differences for some primary GCR ions, the overall percent difference for the GCR environment was smaller than the percent difference for the trapped proton environment. Both were low, with point estimates below 6% d ifference. The organ based REID, which represents the future of the NASA space radiation cancer risk model, was calculated using the organ dose equivalents resulting from both codes. REID associated with exposure from the August 1972 SPE with suit shieldi ng is shown in Figure 7 20 with corresponding percent differences displayed in Figure 7 21 The differences observed between males and females for risk as a function of age was striking. The REID for females was much higher than that for males due to increased risk from shallow organs in the femal e (primarily the breast) While the female REID

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207 markedly decreased with age, the male REID was relatively constant. This was attributed to physiological changes occurring in the female population between ages 25 and 55 manifesting in an overall reduction in risk with increasing age and differences in the relative contributions of organs to the overall cancer mortality risk. The patterns in percent differences were also different for males and females; percent differences were nearly constant at 1.5% for males, while they decreased with age from 1.5% at age 25 to 0.5% at age 55 for females. REID values associated with exposure from the 1977 solar minimum free space GCR spectrum with PV shielding are exhibited in Figure 7 22 with corresponding percent differences shown in Figure 7 23 Again, the REID per day calculated was almost constant for males and decreased for females. However, the REID for males was a much larger fraction of the REID for fe males, and the decrease in REID for females was less pronounced when compared with the results for th e August 1972 SPE with suit shielding. The percent differences in REID for the males of various ages were almost constant at about 2%, while the percent differences in REID for females of various ages were almost constant at about 0.6%. Plots of REID as a function of age, and the associated percent differences, for all environments evaluated are shown in Appendix V Chapter Summary Organ absorbed dose and organ dose equivalent values were calculated for UFHADM50 and UFHADF50 for various space radiation exposure and shielding configurations using PHITS version 2.30 and HZETRN2010. Differences in organ absorbed dose and organ dose equ ivalent calculated using the codes were small for the SPE and trapped proton environments. Differences in organ absorbed dose and organ dose equivalent for the GCR spectrum varied based upon the primary ion analyzed,

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208 with light ion secondary particle prod uction cross sections identified as a potential cause. The effective dose and REID associated with the exposures as calculated by PHITS and HZETRN were very similar, with all spectra showing less than 10% difference. However, canceling errors were observ ed among ions constituting the GCR spectrum. These results indicated that differences among codes can be hidden by canceling errors. Rigorous comparisons using single incident ions, and even single energies, would elucidate why the differences in organ d osimetry quantities occur. Analysis of differential quantities, such as differential energy fluence, is important for these comparisons as well.

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209 A B Figure 7 1 Male (A) organ dose equivalent and (B) associated percent dif ferences for August 1972 SPE irradiation with shelter geometry

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210 A B Figure 7 2 Male (A) organ dose equivalent and (B) associated percent differences for trapped irradiation with PV geometry

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211 A B Figure 7 3 Male (A) organ dose equivalent and (B) associated percent differences for February 1956 SPE irradiation with PV geometry

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212 A B Figure 7 4 Male (A) organ dose equivalent and (B) associated percent differences for GCR proton irradiation with PV geometry

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213 A B Figure 7 5 Male (A) organ dose equivalent and (B) associated percent differences for GCR alpha irradiation with PV geometry

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214 A B Figure 7 6 Male (A) organ dose equivalent and (B) associated percent differences for GCR iron with PV geometry

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215 A B Figure 7 7 PV GCR proton irradiation proton flux comparison for male (A) skin and (B) BFO

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216 A B Figure 7 8 PV GCR al pha irradiation alpha flux comparison for male (A) skin and (B) BFO

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217 Figure 7 9 PV GCR alpha irradiation helion flux comparison for male BFO Figure 7 10 PV GCR alpha irradiation triton flux comparison for male BFO

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218 Figure 7 11 PV GCR alpha irradiation deuteron flux comparison for male BFO Figure 7 12 PV GCR alpha irradiation proton flux comparison for male BFO

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2 19 Figure 7 13 SPE effective doses calculated with HZETRN2010 and PHITS 2.30 Figure 7 14 SPE effective dose percent differences (HZETRN2010 v. PHITS 2.30)

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220 A B Figure 7 15 Free space 1 977 solar minimum GCR primary ion effective dose contributions for (A) male and (B) female

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221 A B Figure 7 16 Percent differences in free space 1977 solar minimum GCR primary ion effective dose rate contributions for (A) male and (B) female

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222 Figure 7 17 GCR primary ion contributions to total effective dose rate Figure 7 18 GCR and trapped environment effective dose rates calculated with HZETRN2010 and PHITS 2.30

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223 Figure 7 19 GCR and trapped environment effective dose rate percent differences (HZETRN2010 vs. PHITS 2.30) Figure 7 20 REID values for August 1972 SPE with suit shielding

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224 Figure 7 21 Percent differences in REID values for August 1972 SPE with suit shielding Figure 7 22 REID values for GCR with PV shielding

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225 Figure 7 23 Percent differences in REID values for GCR with PV shielding

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226 Table 7 1 Elements comprising each GCR ion group GCR Ion Group Elements Included in Group 1 S, Ca, Ti, Cr 2 Li, Be, B, N, F, Ne, Na, Al, P 3 Cl, Ar, K, Sc, V, Mn, Co, Ni Table 7 2 PHITS parameters affecting transport or tallies chosen for the present study Parameter Value Justification icntl 0 Normal PHITS calculation maxcas Varied As required for statistics maxbch Varied As required for statistics incut 0 Cut neutron information not needed igcut 0 Cut gamma information not needed rseed 1 Determine random seed from clock emin(1) 1.0E 3 Set proton energy cut off low (1 keV) emin(2) 1E 10 Set neutron energy cut off low (1 keV) dmax(2) 20.0 Use ENDF data libraries up to 20 MeV emin(12) 1.0 Electron energy cut off at 1 MeV (bug in transport below 1 MeV) emin(13) 1.0 Positron energy cut off at 1 MeV (bug in transport below 1 MeV) emin(14) 1.0E 3 Set photon energy cut off low (1 keV n 1 ) emin(15) 1.0E 3 Set deuteron energy cut off low (1 keV n 1 ) emin(16) 1.0E 3 Set triton energy cut off low (1 keV n 1 ) emin(17) 1.0E 3 Set helion energy cut off low (1 keV n 1 ) emin(18) 1.0E 3 Set alpha energy cut off low (1 keV n 1 ) emin(19) 1.0E 3 Set nucleus energy cut off low (1 keV n 1 ) ejamnu 20.0 Use JAM above 20 MeV; JAM is more accurate than Bertini but faster than JQMD e mode 1 Use PHITS event generator to properly simulate products of neutron reactions dmax(12) 1000.0 Maximum energy for electron library transport 1 GeV dmax(13) 1000.0 Maximum energy for positron library transport 1 GeV dmax(14) 1000.0 Maximum energy for photon library transport 1 GeV igamma 1 Include gamma emission from residual nuclei ipngdr 1 Simulate Giant Nuclear Decay resonances itall 1 Tally output after every batch Table 7 3 Constants defined in PHITS input file Constant Definition c1 Linear thickness of spherical shell, calculated as quotient of aluminum areal density and aluminum mass density c2 Inner radius of spherical shell, calculated as outer radius (500.0 cm) minus c1 c3 Conversion to appropriate dosimetric units (1.6022E 10) c4 Number of particles per cm 2 ; determined by integrating energy fluence c5 Source irradiation 2 c6 Normalization factor for dosimetric units; product of c3, c4, and c5

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227 Table 7 4 Published results ( EPA 2011 ) for females (LAR per 10 5 person Gy) Cancer site 20 y 30 y 40 y 50 y 60 y 70 y 80 y Stomach 52 34 33 30 26 20 13 Colon 50 36 35 33 30 23 15 Liver 22 15 15 14 13 10 6 Lung 315 221 219 210 183 135 77 Breast 153 85 42 17 6 2 0 Uterus 8 5 5 5 4 3 2 Ovary 29 20 20 18 15 10 5 Bladder 30 22 22 22 21 18 13 Thyroid 4 2 1 0 0 0 0 Residual 157 108 100 88 70 48 24 Kidney 9 6 6 5 4 3 1 Bone 1.3 0.7 0.4 0.2 0.1 0 0 Skin 0 0 0 0 0 0 0 Solid 831 556 499 444 372 273 156 Leukemia 48 45 48 52 57 58 47 Total 878 601 547 496 429 331 203 Table 7 5 EPA model MATLAB code results for females (REID per 10 5 person Gy) Cancer site 20 y 30 y 40 y 50 y 60 y 70 y 80 y Stomach 52 34 33 30 26 20 13 Colon 50 36 36 34 30 23 15 Liver 24 16 16 15 14 12 8 Lung 320 224 223 213 187 138 82 Breast 154 85 42 17 6 2 0 Uterus 8 5 5 5 4 4 2 Ovary 29 21 20 18 15 10 5 Bladder 30 22 22 22 21 18 13 Thyroid 4 2 1 0 0 0 0 Residual 161 110 103 90 72 49 25 Kidney 9 6 6 5 4 3 1 Bone 1.3 0.7 0.4 0.2 0.1 0.0 0.0 Skin 0 0 0 0 0 0 0 Solid 842 563 506 451 379 280 165 Leukemia 47 46 48 53 57 58 46 Total 890 609 555 504 436 338 211

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228 Table 7 6 Published results ( EPA 2011 ) for males (LAR per 10 5 person Gy) Cancer site 20 y 30 y 40 y 50 y 60 y 70 y 80 y Stomach 39 26 25 22 19 14 8 Colon 81 58 57 54 47 34 19 Liver 37 26 25 24 21 16 9 Lung 141 99 98 95 84 63 35 Prostate 15 11 11 12 12 11 7 Bladder 23 17 17 17 16 14 10 Thyroid 1.1 0.6 0.3 0.1 0 0 0 Residual 134 93 88 77 59 38 18 Kidney 10 7 7 6 5 3 1 Bone 1.2 0.7 0.4 0.2 0.1 0 0 Skin 0 0 0 0 0 0 0 Solid 481 338 328 307 263 193 107 Leukemia 61 58 61 67 76 80 63 Total 542 396 389 374 339 273 170 Table 7 7 EPA model MATLAB code results for males (REID per 10 5 person Gy) Cancer site 20 y 30 y 40 y 50 y 60 y 70 y 80 y Stomach 39 26 25 22 19 14 8 Colon 81 58 57 54 47 34 19 Liver 37 26 25 24 21 16 10 Lung 143 100 100 97 86 65 38 Prostate 15 12 12 12 12 11 8 Bladder 23 17 17 17 16 14 10 Thyroid 1.1 0.6 0.3 0.1 0.0 0.0 0.0 Residual 138 96 90 79 61 39 19 Kidney 11 8 7 6 5 3 1 Bone 1.2 0.7 0.4 0.2 0.1 0.0 0.0 Skin 0 0 0 0 0 0 0 Solid 489 343 334 312 267 196 113 Leukemia 60 57 61 67 76 79 59 Total 549 400 395 379 343 276 172

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229 CHAPTER 8 CONCLUSION Need for the Present Study An extensive literature review was conducted prior to the present study. NASA began its space radiation dose analyses in earnest during the Apollo program, developing and using simple models of the human anatomy and vehicular shielding to computationally transport trapped protons and SPE ( Fortney and Duckworth 1964 ) When radiation scientists realized that t he limits for particular organs could be approached due to space radiation exposure, a detailed computational phantom of a male astronaut, CAM, was developed ( Kase 1970 ; Billings and Yucker 1973 ) Later, a detailed computational phantom of a female astronaut, CAF, was develo ped ( Yucker and Huston 1990 ) A ray tracing procedure was used to characterize the shielding around a point within the human body, usually representing the organ of interest Reducing the geometry from 3D to 1D slab geometry allowed radiation scientists to use simplified transport methods in simulating the interactions of various space radiation environ ments. NASA developed BRYNTRN ( Wilson et al. 1989 ) and later HZETR N ( Wilson et al. 1991a ) to explicitly consider the time independent Boltzm ann radiation transport equation, including atomic and nuclear interactions. Despite the advancements in phantom technology and transport code development, NASA has not deviated from using CAM and CAF in deterministic transport for space radiation dosimet ry and subsequent risk analyses. NASA space radiation exposure limits evolved considerably as the space program aged. The evolution of these exposure limits to the current NASA space radiation risk limit of 3% REID protected to the upper 95% CL ( NASA 2007 ) necessitated

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230 investigation of factors that could impact the accuracy of the methods used to evaluate risk from space radiation exposure. Initial investigations into incorporating voxel phantoms in space radiation exposu re assessments have been performed ( Slaba et al. 2009 ; Slaba et al. 2010c ) but these did not address size variations among the astronauts or the effects of microgravity changes. Monte Carlo radiation transport for the purposes of space radiation simulation were previously performed, largely for comparison to measu rements made aboard spacecraft ( Sato et al. 2006 ; Gustafsson et al. 2010 ) Monte Carlo radiation transport programs have also been used with simplistic geometry configurations for compa rison with results from HZETRN ( Heinbockel et al. 2009a ; Heinbockel et al. 2009b ) The aims of the present study were to determine the impacts of astronaut size and microgravit y body changes on dosimetry and risk as characterized by effective dose. In addition, the differences in dosimetry and risk caused by using 1D deterministic radiation transport with HZETRN and 3D Monte Carlo radiation transport with PHITS were investigate d Findings The UF hybrid adult phantoms were ideally suited for the present study, as they allow for extensive modification of size and position prior to voxelization ( Johnson et al. 2009 ; Lee et al. 2010 ) The applicability of using the UF phantoms as a part of the NASA operational dosimetry process needed to be evaluated. A voxel based ray tracer, VoBRaT, was developed to generate radiological path length in water for use with NASA one dimensional transport codes. The first iteration of scaling UF hybrid phantoms for astronaut dosimetry indicated that they were indeed com patible with the NASA operational dosimetry process; however, upon investigation of the relative

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231 positions of the body self shielding distributions for different sized astronaut phantoms, apparent inconsistencies in the ordering of the distributions were f ound The three main types of space radiation expo sure scenarios (geomagnetically trapped protons, GCR, and SPE) were transported using BRYNTRN and HZETRN. Absorbed dose and dose equivalent, using the ICRP Publication 60 quality factor definition, were ca lculated at various depths of water and aluminum shielding, representing body self shielding and vehicular shielding, respectively. Organ dose equivalent values were calculated for nominal vehicular shielding configurations. It was expected that regardle ss of vehicular shielding, smaller organ dose equivalent values would be observed for larger phantoms due to increased body self shielding. For the most part, the results indicated this to be the case. However, for the softer space radiation environments such as the August 1972 SPE and the October 1989 SPE, some apparently spurious values for certain dose points within the phantoms occurred. The scaling method, in which phantoms were individually tailored based upon anthropometric parameters, coupled wi th representing organs with a small number of manually selected dose points, resulted in aberrant dosimetry results, confirming that the inconsistencies observed in body self shielding distributions affected dosimetry for environments that exhibit extreme attenuation at shallow shielding depths. The body self shielding distribution and dosimetry results indicated that number of points used to characterize the body self shielding of CAM and CAF was insufficient. Although determined using a different approa ch, this result agreed with conclusions of a previous study using MAX and FAX ( Slaba et al. 2009 ; Slaba et al. 2010c ) Also, the scaling method initially employed was found to be ill suit ed for generically comparing dosimetry

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232 among different sized phantoms. It is important here to emphasize, however, that for these soft radiation spectra, local anatomical modeling can have a substantial impact on organ dose equivalent, drowning out the ef fects of overall body size. Next, the UF phantoms were scaled using uniform scaling factors separately for each dimension. The female anthropometric parameters were altered to better match the female contingent of the NASA astronaut corps. Many dose poin ts were used to represent each organ, minimizing the possibility of spurious results from undersampling. Body self shielding distributions and subsequent calculations of orga n dose equivalent varied with body size among the UF phantoms as expected. The d egree to which size and anatomical modeling affected differences in organ dose equivalent was dependent upon the space radiation spectrum and shielding analyzed, with larger differences observed for the softer space radiation spectra under light shielding. In terms of effective dose, differences among the UF phantoms (when compared with the 50 th PCTL) were on the order of 15% to 20% for the softer space radiation spectra and light shielding, with the differences decreasing with increasing shielding. Geomagnetically trapped proton differences were on the order of 3% to 5%, and GCR differences were on the order of 1% to 3%. T he greatest benefit to using updated phantoms with astronaut dependent morphometries would be realized when simulating SPE environments. In addition to affecting the REID resulting from repeated, small SPE exposures, using pha ntoms that more accurately represent the anatomy of a particular astronaut could have a marked impact on the estimation of probability of deterministic effects from larger SPE exposures, which is currently addressed in the Acute Radiation Risk and BRYNTRN Organ Dose projection code (ARRBOD) ( Kim et al. 2010a ) With

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233 geomagnetically trapped protons and GCR, a smaller relative benefit would result from using the percentile matched flexible phantoms, but the results for the males indicated that CAM no longer adequately represents the 50 th PCTL male NASA astronaut. Although only a marginal improvement in risk estimation would result from using a personalized phantom, it would be a straightforward process (and hence, not very costly ) to scale the male or female UF phantom to the appropriate morphometry using outer body contour scans or available CT scans from medical evaluations These phantoms could then be used for both the evaluation of deterministic effects from acute exposures and stochastic effects from chronic exposures. Several microgravity induced bo d y changes occur in spaceflight, and a subset of these changes that affect the body self shielding were implemented in the UF hybrid phantom. Organ dose equivalent results follo wed the trend observed for the phantoms with Earth based anthropometrics and standing body posture. Systematic differences in dosimetry were observed including A slight decrease in organ dose equivalent for organs in the head due to forward tilting, A de crease in female breast dose equivalent due to increased shielding from arm position change, A decrease in testis dose equivalent due to increased shielding from leg position change, Increases in organ dose equivalent for organs in the lower torso resultin g from mass removal, and Slight increases in distributed organs due to overall body size changes. The changes in organ dose equivalent were again more pronounced for soft SPE environments. Differences in effective dose were small for the geomagnetically t rapped proton and soft SPE environments and undetectable for the hard SPE and GCR environments. Differences from microgravity induced body changes were found to be

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234 less important than differences resulting from anatomical modeling. For the soft SPE spect ra under suit shielding, a decrease in effective dose was observed due to the increased shielding of the testes. Also, certain organ dose equivalent results showed large differences when the two sets of phantoms were compared. It is possible that larger differences in organ dose equivalent and risk could occur for more pronounced changes in body posture under light shielding configurations. Therefore, ALARA practices could be improved during EVA by deriving optimal body position if little warning is give n for an impending SPE. Finally, 1D deterministic transport with HZETRN2010 and 3D Monte Carlo transport with PHITS were used to analyze differences in organ absorbed dose, organ dose equivalent, effective dose, and REID. The most recent versions of the t wo codes were used. The February 1956 SPE and August 1972 SPE were analyzed for the suit and shelter shielding configurations, and the geomagnetically trapped proton (with albedo neutron) and GCR environments were analyzed for the PV shielding configurati on. For the SPE and geomagnetically trapped proton environments, small differences in organ absorbed dose and organ dose equivalent were observed. The study addressed seven of the most important GCR ions separately, and then grouped the remaining ions in three sets. Differences in organ absorbed dose tended to decrease with increasing charge for the GCR ions, while differences in organ dose equivalent tended to decrease with charge, but slightly increased for GCR iron. T he differences were attributed pr imarily to light ion cross section modeling between the two codes, with smaller contributions from differences in fragmentation between the materials as defined in PHITS and the water slabs used to perform transport and

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235 dosimetry in HZETRN2010. Energy spe ctra for particular ions were inspected to assist in explaining the discrepancies between the two codes. E ffective dose was calculated as in previous chapters, and extended the characterization of radiation carcinogenesis risk using the EPA 2011 risk mode l ( EPA 2011 ) Little differences in overall effec tive dose and REID were found for all environments, but canceling errors were noted for components of the GCR spectrum, most notably GCR helium and GCR iron. Comparisons to space s of radiation transport. However, the observation of canceling errors exemplified a problem with comparisons of calculations to space based measurements: they are almost exclusively based upon integral quantities that often have the added complexities of energy or LET dependent efficiency corrections. Code to code comparisons contribute by allowing users to investigate differences in differential quantities that are not revealed by code to measurement comparisons. This is especially important when the suspected biological response is not adequately characterized by the measured quantity. In terms of operational implementation, the time required for GCR simulation precludes the use of Monte Carlo codes, despite the advances in cluster computing. SPEs a nd geomagnetically trapped protons can be simulated quicker due to the lower energies involved and lack of projectile fragmentation. In fact, when one considers the effort required to ray trace a substantial number of points per organ and perform the inte rpolate for organ averaged quantities, the speed of SPE simulation on a cluster computing system using Monte Carlo could rival that of HZETRN. Increases in the availability of affordable computational power

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236 will make Monte Carlo simulation of space radiat ion environments more attractive in the future. Limitations Several factors limited the present study. These were generally related to either the phantom representation or the calculation of risk. Voxelization is a memory intensive process; the number of voxels limits either the resolution or the size of the voxel array. Thus, voxels cannot be arbitrarily reduced to minimize the impact of voxelization on the approximated structure. If possible, ray tracing the NURBS surface directly is desirable, but wa s not implemented because of increased complexity. VoBRaT was written on the assumption of water equivalence; a recent study by Badavi et al. ( 2010 ) indicated that this assumption is not valid for aluminum equivalence of the spacecraft. Fragmentation effects are likely much different on certain biological materials, such as bone. The BFO distrib ution for males was also assumed for females. Although applied uniformly, this could lead to some changes in BFO organ dose equivalent if grossly redistributed to areas of more or less body self shielding. For the microgravity based phantoms, only one com bination of body position and changes in anthropometric parameters was examined. I t is expect ed that more extreme changes in position would result in substantial changes in risk. In addition, potential synchronistic or antagonistic effects, such as immun osuppression and stress, were not taken into account. However, these interactions are very difficult to characterize appropriately. Organ dosimetry was not addressed in terms of deterministic limits. This would require the assumption of RBE values, which are given by NCRP ( 2006 ) but only generically defined. The present study indicates however, that if one survives a

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237 massive SPE, the stochastic effects from the exposure could be significant. Finally, it was assume d that risk was proportional to effective dose and for many organs the hazard functions for cancer incidence and mortality were proportional to organ dose equivalent. Issues with the LNT theory have been detailed elsewhere, but suffice it to say that the lack of epidemiological power to detect small increases in cancer rates resulting from radiation exposure, coupled with the lack of a validated mechanistic model for radiogenic cancer induction, is a major limitation of any study that attempts to relate ra diation exposure to risk of cancer. Future Work Much work remains to be done in the future for subjects related to the present study. Ray by ray transport is now possible with HZETRN, and so a rewrite of VoBRaT is warranted to track the length and materia l type in an array of material segments. Doing so would allow the use of the forward backward neutron transport mechanism recently incorporated in HZETRN2010. Ray tracing NURBS based geometry would mitigate any artifacts introduced by voxelization. T his would be much more computationally intensive and likely require parallel programming to be able to ray trace a comparable number of organ dose points in a reasonable amount of time. Correlation of body self shielding rays with path lengths through a give n vehicle would allow for the inclusion of the effects of environment anisotropy and perhaps greater insight into the potential for ALARA. Also, the potential for ALARA implementation of optimal body positioning when an SPE is imminent is warranted. Crea ting dose volume histograms for distributed organs such as the skin, for which different portions could have markedly different body self shielding distributions, could help in optimizing body position as well.

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238 For future Monte Carlo work, appropriat e depth dose comparisons between PHITS and HZETRN could help to elucidate the relative importance of cross sections and angular effects. Creating a PHITS based cross section database for incorporation with HZETRN would also help to clarify the roles of cr oss sections in the differences observed in the present study. One problem with Monte Carlo simulation of space radiation is the reliance on analog methods to preserve higher order moments and give a valid estimate of values such as dose equivalent. Deve loping non analog methods has the potential to speed up the simulation of GCR ions considerably. In addition, Monte Carlo simulation of uncertainties unrelated to transport could be incorporated in PHITS if adequately characterized. While delta ray trans port is not likely to affect dosimetry results for most organs, its inclusion could impact the results for organs that have very different radiological properties from surrounding material such as skin (surrounded by air or space suit) and BFO (which shar es surfaces with trabecular bone ). E valuations using the updated quality factor parameterization, based upon effective charge and velocity, are important to complete, as the new NASA risk model will us e these in evaluations of REID ( Cucinotta et al. 2011 ) Finally, d irect conversion of computer aided design geometry without the need for model simplification, coupled with graphical processing unit programming would greatly accelerate the operational implementation of PHITS and other Monte Carlo radiation transport codes. These improvements should be pursued to expand the portfolio of operational s pace radiation simulation tools.

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239 APPENDIX A RAY TRACING DIRECTIO N COSINES Table A 1. Direction cosines used for ray tracing 2.487961E 01 2.450428E 02 9.682459E 01 2.392350E 01 7.257114E 02 9.682459E 01 2.204802E 01 1.178491E 01 9.682459E 01 1.932525E 01 1.585983E 01 9.682459E 01 1.585983E 01 1.932525E 01 9.682459E 01 1.178491E 01 2.204802E 01 9.682459E 01 7.257113E 02 2.392350E 01 9.682459E 01 2.450427E 02 2.487961E 01 9.682459E 01 2.450430E 02 2.487961E 01 9.682459E 01 7.257115E 02 2.392350E 01 9.682459E 01 1.178492E 01 2.204802E 01 9.682459E 01 1.585982E 01 1.932525E 01 9.682459E 01 1.932525E 01 1.585982E 01 9.682459E 01 2.204802E 01 1.178491E 01 9.682459E 01 2.392350E 01 7.257114E 02 9.682459E 01 2.487961E 01 2.450426E 02 9.682459E 01 2.487961E 01 2.450431E 02 9.682459E 01 2.392350E 01 7.257119E 02 9.682459E 01 2.204802E 01 1.178491E 01 9.682459E 01 1.932525E 01 1.585983E 01 9.682459E 01 1.585983E 01 1.932525E 01 9.682459E 01 1.178491E 01 2.204802E 01 9.682459E 01 7.257111E 02 2.392350E 01 9.682459E 01 2.450422E 02 2.487961E 01 9.682459E 01 2.450435E 02 2.487961E 01 9.682459E 01 7.257123E 02 2.392350E 01 9.682459E 01 1.178491E 01 2.204802E 01 9.682459E 01 1.585983E 01 1.932525E 01 9.682459E 01 1.932525E 01 1.585982E 01 9.682459E 01 2.204802E 01 1.178491E 01 9.682459E 01 2.392350E 01 7.257107E 02 9.682459E 01 2.487961E 01 2.450418E 02 9.682459E 01 5.734057E 01 5.647554E 02 8.173227E 01 5.513701E 01 1.672563E 01 8.173227E 01 5.081456E 01 2.716095E 01 8.173227E 01 4.453933E 01 3.655249E 01 8.173227E 01

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240 Table A 1. Continued 3.655249E 01 4.453933E 01 8.173227E 01 2.716094E 01 5.081456E 01 8.173227E 01 1.672563E 01 5.513701E 01 8.173227E 01 5.647554E 02 5.734057E 01 8.173227E 01 5.647559E 02 5.734057E 01 8.173227E 01 1.672563E 01 5.513701E 01 8.173227E 01 2.716095E 01 5.081456E 01 8.173227E 01 3.655249E 01 4.453934E 01 8.173227E 01 4.453934E 01 3.655248E 01 8.173227E 01 5.081456E 01 2.716094E 01 8.173227E 01 5.513701E 01 1.672563E 01 8.173227E 01 5.734057E 01 5.647551E 02 8.173227E 01 5.734057E 01 5.647561E 02 8.173227E 01 5.513701E 01 1.672564E 01 8.173227E 01 5.081456E 01 2.716095E 01 8.173227E 01 4.453933E 01 3.655249E 01 8.173227E 01 3.655249E 01 4.453933E 01 8.173227E 01 2.716095E 01 5.081456E 01 8.173227E 01 1.672562E 01 5.513701E 01 8.173227E 01 5.647542E 02 5.734057E 01 8.173227E 01 5.647570E 02 5.734057E 01 8.173227E 01 1.672565E 01 5.513700E 01 8.173227E 01 2.716095E 01 5.081456E 01 8.173227E 01 3.655249E 01 4.453933E 01 8.173227E 01 4.453934E 01 3.655248E 01 8.173227E 01 5.081456E 01 2.716094E 01 8.173227E 01 5.513701E 01 1.672561E 01 8.173227E 01 5.734058E 01 5.647532E 02 8.173227E 01 7.202501E 01 7.093844E 02 6.900780E 01 6.925712E 01 2.100892E 01 6.900780E 01 6.382773E 01 3.411663E 01 6.900780E 01 5.594547E 01 4.591327E 01 6.900780E 01 4.591326E 01 5.594547E 01 6.900780E 01 3.411663E 01 6.382774E 01 6.900780E 01 2.100892E 01 6.925713E 01 6.900780E 01 7.093844E 02 7.202501E 01 6.900780E 01 7.093850E 02 7.202501E 01 6.900780E 01 2.100892E 01 6.925712E 01 6.900780E 01 3.411664E 01 6.382773E 01 6.900780E 01

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241 Table A 1. Continued 4.591326E 01 5.594547E 01 6.900780E 01 5.594547E 01 4.591326E 01 6.900780E 01 6.382774E 01 3.411663E 01 6.900780E 01 6.925712E 01 2.100892E 01 6.900780E 01 7.202501E 01 7.093840E 02 6.900780E 01 7.202501E 01 7.093853E 02 6.900780E 01 6.925712E 01 2.100893E 01 6.900780E 01 6.382773E 01 3.411664E 01 6.900780E 01 5.594547E 01 4.591327E 01 6.900780E 01 4.591327E 01 5.594547E 01 6.900780E 01 3.411663E 01 6.382774E 01 6.900780E 01 2.100891E 01 6.925713E 01 6.900780E 01 7.093829E 02 7.202501E 01 6.900780E 01 7.093865E 02 7.202500E 01 6.900780E 01 2.100894E 01 6.925712E 01 6.900780E 01 3.411663E 01 6.382774E 01 6.900780E 01 4.591327E 01 5.594547E 01 6.900780E 01 5.594548E 01 4.591326E 01 6.900780E 01 6.382774E 01 3.411662E 01 6.900780E 01 6.925713E 01 2.100890E 01 6.900780E 01 7.202501E 01 7.093817E 02 6.900780E 01 8.217180E 01 8.093216E 02 5.641184E 01 7.901398E 01 2.396863E 01 5.641184E 01 7.281970E 01 3.892294E 01 5.641184E 01 6.382700E 01 5.238147E 01 5.641184E 01 5.238147E 01 6.382700E 01 5.641184E 01 3.892294E 01 7.281970E 01 5.641184E 01 2.396863E 01 7.901398E 01 5.641184E 01 8.093216E 02 8.217180E 01 5.641184E 01 8.093222E 02 8.217180E 01 5.641184E 01 2.396863E 01 7.901398E 01 5.641184E 01 3.892295E 01 7.281970E 01 5.641184E 01 5.238146E 01 6.382700E 01 5.641184E 01 6.382700E 01 5.238146E 01 5.641184E 01 7.281970E 01 3.892293E 01 5.641184E 01 7.901398E 01 2.396863E 01 5.641184E 01 8.217180E 01 8.093212E 02 5.641184E 01 8.217180E 01 8.093226E 02 5.641184E 01 7.901397E 01 2.396865E 01 5.641184E 01

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242 Table A 1. Continued 7.281970E 01 3.892294E 01 5.641184E 01 6.382700E 01 5.238147E 01 5.641184E 01 5.238147E 01 6.382700E 01 5.641184E 01 3.892294E 01 7.281970E 01 5.641184E 01 2.396862E 01 7.901399E 01 5.641184E 01 8.093198E 02 8.217180E 01 5.641184E 01 8.093239E 02 8.217179E 01 5.641184E 01 2.396866E 01 7.901397E 01 5.641184E 01 3.892294E 01 7.281970E 01 5.641184E 01 5.238147E 01 6.382700E 01 5.641184E 01 6.382701E 01 5.238146E 01 5.641184E 01 7.281971E 01 3.892293E 01 5.641184E 01 7.901399E 01 2.396861E 01 5.641184E 01 8.217180E 01 8.093185E 02 5.641184E 01 8.943736E 01 8.808811E 02 4.385618E 01 8.600033E 01 2.608792E 01 4.385618E 01 7.925836E 01 4.236448E 01 4.385618E 01 6.947053E 01 5.701299E 01 4.385618E 01 5.701299E 01 6.947053E 01 4.385618E 01 4.236447E 01 7.925836E 01 4.385618E 01 2.608791E 01 8.600033E 01 4.385618E 01 8.808810E 02 8.943736E 01 4.385618E 01 8.808818E 02 8.943736E 01 4.385618E 01 2.608792E 01 8.600033E 01 4.385618E 01 4.236448E 01 7.925835E 01 4.385618E 01 5.701299E 01 6.947054E 01 4.385618E 01 6.947054E 01 5.701299E 01 4.385618E 01 7.925836E 01 4.236447E 01 4.385618E 01 8.600033E 01 2.608792E 01 4.385618E 01 8.943736E 01 8.808807E 02 4.385618E 01 8.943736E 01 8.808822E 02 4.385618E 01 8.600032E 01 2.608793E 01 4.385618E 01 7.925836E 01 4.236448E 01 4.385618E 01 6.947052E 01 5.701300E 01 4.385618E 01 5.701299E 01 6.947053E 01 4.385618E 01 4.236447E 01 7.925836E 01 4.385618E 01 2.608790E 01 8.600034E 01 4.385618E 01 8.808792E 02 8.943736E 01 4.385618E 01 8.808837E 02 8.943735E 01 4.385618E 01

PAGE 243

243 Table A 1. Continued 2.608795E 01 8.600032E 01 4.385618E 01 4.236447E 01 7.925836E 01 4.385618E 01 5.701300E 01 6.947053E 01 4.385618E 01 6.947054E 01 5.701298E 01 4.385618E 01 7.925837E 01 4.236446E 01 4.385618E 01 8.600034E 01 2.608789E 01 4.385618E 01 8.943736E 01 8.808777E 02 4.385618E 01 9.451211E 01 9.308631E 02 3.131789E 01 9.088007E 01 2.756817E 01 3.131789E 01 8.375555E 01 4.476827E 01 3.131789E 01 7.341235E 01 6.024796E 01 3.131789E 01 6.024796E 01 7.341235E 01 3.131789E 01 4.476826E 01 8.375555E 01 3.131789E 01 2.756816E 01 9.088007E 01 3.131789E 01 9.308630E 02 9.451211E 01 3.131789E 01 9.308638E 02 9.451211E 01 3.131789E 01 2.756817E 01 9.088007E 01 3.131789E 01 4.476828E 01 8.375554E 01 3.131789E 01 6.024796E 01 7.341235E 01 3.131789E 01 7.341235E 01 6.024796E 01 3.131789E 01 8.375555E 01 4.476826E 01 3.131789E 01 9.088007E 01 2.756817E 01 3.131789E 01 9.451211E 01 9.308626E 02 3.131789E 01 9.451211E 01 9.308643E 02 3.131789E 01 9.088006E 01 2.756819E 01 3.131789E 01 8.375555E 01 4.476828E 01 3.131789E 01 7.341234E 01 6.024797E 01 3.131789E 01 6.024796E 01 7.341235E 01 3.131789E 01 4.476827E 01 8.375555E 01 3.131789E 01 2.756816E 01 9.088007E 01 3.131789E 01 9.308611E 02 9.451211E 01 3.131789E 01 9.308658E 02 9.451211E 01 3.131789E 01 2.756820E 01 9.088005E 01 3.131789E 01 4.476827E 01 8.375555E 01 3.131789E 01 6.024796E 01 7.341235E 01 3.131789E 01 7.341236E 01 6.024795E 01 3.131789E 01 8.375556E 01 4.476826E 01 3.131789E 01 9.088007E 01 2.756814E 01 3.131789E 01 9.451212E 01 9.308595E 02 3.131789E 01

PAGE 244

244 Table A 1. Continued 9.774624E 01 9.627164E 02 1.878807E 01 9.398990E 01 2.851152E 01 1.878807E 01 8.662159E 01 4.630021E 01 1.878807E 01 7.592446E 01 6.230959E 01 1.878807E 01 6.230959E 01 7.592446E 01 1.878807E 01 4.630020E 01 8.662159E 01 1.878807E 01 2.851152E 01 9.398990E 01 1.878807E 01 9.627163E 02 9.774624E 01 1.878807E 01 9.627172E 02 9.774624E 01 1.878807E 01 2.851153E 01 9.398990E 01 1.878807E 01 4.630021E 01 8.662158E 01 1.878807E 01 6.230959E 01 7.592446E 01 1.878807E 01 7.592446E 01 6.230959E 01 1.878807E 01 8.662159E 01 4.630019E 01 1.878807E 01 9.398990E 01 2.851153E 01 1.878807E 01 9.774624E 01 9.627159E 02 1.878807E 01 9.774624E 01 9.627176E 02 1.878807E 01 9.398990E 01 2.851155E 01 1.878807E 01 8.662159E 01 4.630021E 01 1.878807E 01 7.592445E 01 6.230960E 01 1.878807E 01 6.230959E 01 7.592446E 01 1.878807E 01 4.630020E 01 8.662159E 01 1.878807E 01 2.851151E 01 9.398990E 01 1.878807E 01 9.627143E 02 9.774624E 01 1.878807E 01 9.627192E 02 9.774623E 01 1.878807E 01 2.851156E 01 9.398989E 01 1.878807E 01 4.630020E 01 8.662159E 01 1.878807E 01 6.230960E 01 7.592446E 01 1.878807E 01 7.592447E 01 6.230958E 01 1.878807E 01 8.662160E 01 4.630018E 01 1.878807E 01 9.398991E 01 2.851150E 01 1.878807E 01 9.774624E 01 9.627127E 02 1.878807E 01 9.932315E 01 9.782476E 02 6.262287E 02 9.550622E 01 2.897149E 01 6.262287E 02 8.801903E 01 4.704715E 01 6.262287E 02 7.714932E 01 6.331482E 01 6.262287E 02 6.331481E 01 7.714933E 01 6.262287E 02 4.704714E 01 8.801903E 01 6.262287E 02 2.897149E 01 9.550622E 01 6.262287E 02

PAGE 245

245 Table A 1. Continued 9.782476E 02 9.932315E 01 6.262287E 02 9.782484E 02 9.932315E 01 6.262287E 02 2.897150E 01 9.550621E 01 6.262287E 02 4.704716E 01 8.801903E 01 6.262287E 02 6.331481E 01 7.714933E 01 6.262287E 02 7.714933E 01 6.331481E 01 6.262287E 02 8.801904E 01 4.704714E 01 6.262287E 02 9.550621E 01 2.897150E 01 6.262287E 02 9.932315E 01 9.782472E 02 6.262287E 02 9.932314E 01 9.782489E 02 6.262287E 02 9.550621E 01 2.897151E 01 6.262287E 02 8.801903E 01 4.704716E 01 6.262287E 02 7.714932E 01 6.331483E 01 6.262287E 02 6.331482E 01 7.714933E 01 6.262287E 02 4.704715E 01 8.801903E 01 6.262287E 02 2.897148E 01 9.550622E 01 6.262287E 02 9.782455E 02 9.932315E 01 6.262287E 02 9.782505E 02 9.932314E 01 6.262287E 02 2.897153E 01 9.550620E 01 6.262287E 02 4.704715E 01 8.801903E 01 6.262287E 02 6.331482E 01 7.714932E 01 6.262287E 02 7.714933E 01 6.331480E 01 6.262287E 02 8.801904E 01 4.704713E 01 6.262287E 02 9.550622E 01 2.897146E 01 6.262287E 02 9.932315E 01 9.782439E 02 6.262287E 02 9.932315E 01 9.782476E 02 6.262296E 02 9.550622E 01 2.897149E 01 6.262296E 02 8.801903E 01 4.704715E 01 6.262296E 02 7.714932E 01 6.331482E 01 6.262296E 02 6.331481E 01 7.714933E 01 6.262296E 02 4.704714E 01 8.801903E 01 6.262296E 02 2.897149E 01 9.550622E 01 6.262296E 02 9.782476E 02 9.932315E 01 6.262296E 02 9.782484E 02 9.932315E 01 6.262296E 02 2.897150E 01 9.550621E 01 6.262296E 02 4.704716E 01 8.801903E 01 6.262296E 02 6.331481E 01 7.714933E 01 6.262296E 02 7.714933E 01 6.331481E 01 6.262296E 02 8.801904E 01 4.704714E 01 6.262296E 02

PAGE 246

246 Table A 1. Continued 9.550621E 01 2.897150E 01 6.262296E 02 9.932315E 01 9.782472E 02 6.262296E 02 9.932314E 01 9.782489E 02 6.262296E 02 9.550621E 01 2.897151E 01 6.262296E 02 8.801903E 01 4.704716E 01 6.262296E 02 7.714932E 01 6.331483E 01 6.262296E 02 6.331482E 01 7.714933E 01 6.262296E 02 4.704715E 01 8.801903E 01 6.262296E 02 2.897148E 01 9.550622E 01 6.262296E 02 9.782455E 02 9.932315E 01 6.262296E 02 9.782505E 02 9.932314E 01 6.262296E 02 2.897153E 01 9.550620E 01 6.262296E 02 4.704715E 01 8.801903E 01 6.262296E 02 6.331482E 01 7.714932E 01 6.262296E 02 7.714933E 01 6.331480E 01 6.262296E 02 8.801904E 01 4.704713E 01 6.262296E 02 9.550622E 01 2.897146E 01 6.262296E 02 9.932315E 01 9.782439E 02 6.262296E 02 9.774624E 01 9.627164E 02 1.878808E 01 9.398990E 01 2.851152E 01 1.878808E 01 8.662159E 01 4.630021E 01 1.878808E 01 7.592446E 01 6.230959E 01 1.878808E 01 6.230959E 01 7.592446E 01 1.878808E 01 4.630020E 01 8.662159E 01 1.878808E 01 2.851152E 01 9.398990E 01 1.878808E 01 9.627163E 02 9.774624E 01 1.878808E 01 9.627172E 02 9.774624E 01 1.878808E 01 2.851153E 01 9.398990E 01 1.878808E 01 4.630021E 01 8.662158E 01 1.878808E 01 6.230959E 01 7.592446E 01 1.878808E 01 7.592446E 01 6.230959E 01 1.878808E 01 8.662159E 01 4.630019E 01 1.878808E 01 9.398990E 01 2.851153E 01 1.878808E 01 9.774624E 01 9.627159E 02 1.878808E 01 9.774624E 01 9.627176E 02 1.878808E 01 9.398990E 01 2.851155E 01 1.878808E 01 8.662159E 01 4.630021E 01 1.878808E 01 7.592445E 01 6.230960E 01 1.878808E 01 6.230959E 01 7.592446E 01 1.878808E 01

PAGE 247

247 Table A 1. Continued 4.630020E 01 8.662159E 01 1.878808E 01 2.851151E 01 9.398990E 01 1.878808E 01 9.627143E 02 9.774624E 01 1.878808E 01 9.627192E 02 9.774623E 01 1.878808E 01 2.851156E 01 9.398989E 01 1.878808E 01 4.630020E 01 8.662159E 01 1.878808E 01 6.230960E 01 7.592446E 01 1.878808E 01 7.592447E 01 6.230958E 01 1.878808E 01 8.662160E 01 4.630018E 01 1.878808E 01 9.398991E 01 2.851150E 01 1.878808E 01 9.774624E 01 9.627127E 02 1.878808E 01 9.451211E 01 9.308631E 02 3.131789E 01 9.088007E 01 2.756817E 01 3.131789E 01 8.375555E 01 4.476827E 01 3.131789E 01 7.341235E 01 6.024796E 01 3.131789E 01 6.024796E 01 7.341235E 01 3.131789E 01 4.476826E 01 8.375555E 01 3.131789E 01 2.756816E 01 9.088007E 01 3.131789E 01 9.308630E 02 9.451211E 01 3.131789E 01 9.308638E 02 9.451211E 01 3.131789E 01 2.756817E 01 9.088007E 01 3.131789E 01 4.476828E 01 8.375554E 01 3.131789E 01 6.024796E 01 7.341235E 01 3.131789E 01 7.341235E 01 6.024796E 01 3.131789E 01 8.375555E 01 4.476826E 01 3.131789E 01 9.088007E 01 2.756817E 01 3.131789E 01 9.451211E 01 9.308626E 02 3.131789E 01 9.451211E 01 9.308643E 02 3.131789E 01 9.088006E 01 2.756819E 01 3.131789E 01 8.375555E 01 4.476828E 01 3.131789E 01 7.341234E 01 6.024797E 01 3.131789E 01 6.024796E 01 7.341235E 01 3.131789E 01 4.476827E 01 8.375555E 01 3.131789E 01 2.756816E 01 9.088007E 01 3.131789E 01 9.308611E 02 9.451211E 01 3.131789E 01 9.308658E 02 9.451211E 01 3.131789E 01 2.756820E 01 9.088005E 01 3.131789E 01 4.476827E 01 8.375555E 01 3.131789E 01 6.024796E 01 7.341235E 01 3.131789E 01

PAGE 248

248 Table A 1. Continued 7.341236E 01 6.024795E 01 3.131789E 01 8.375556E 01 4.476826E 01 3.131789E 01 9.088007E 01 2.756814E 01 3.131789E 01 9.451212E 01 9.308595E 02 3.131789E 01 8.943735E 01 8.808810E 02 4.385618E 01 8.600032E 01 2.608791E 01 4.385618E 01 7.925835E 01 4.236448E 01 4.385618E 01 6.947052E 01 5.701299E 01 4.385618E 01 5.701299E 01 6.947053E 01 4.385618E 01 4.236447E 01 7.925836E 01 4.385618E 01 2.608791E 01 8.600032E 01 4.385618E 01 8.808810E 02 8.943735E 01 4.385618E 01 8.808818E 02 8.943735E 01 4.385618E 01 2.608792E 01 8.600032E 01 4.385618E 01 4.236448E 01 7.925835E 01 4.385618E 01 5.701299E 01 6.947053E 01 4.385618E 01 6.947053E 01 5.701299E 01 4.385618E 01 7.925836E 01 4.236446E 01 4.385618E 01 8.600032E 01 2.608792E 01 4.385618E 01 8.943735E 01 8.808806E 02 4.385618E 01 8.943735E 01 8.808821E 02 4.385618E 01 8.600032E 01 2.608793E 01 4.385618E 01 7.925835E 01 4.236448E 01 4.385618E 01 6.947052E 01 5.701300E 01 4.385618E 01 5.701299E 01 6.947052E 01 4.385618E 01 4.236447E 01 7.925835E 01 4.385618E 01 2.608790E 01 8.600033E 01 4.385618E 01 8.808792E 02 8.943735E 01 4.385618E 01 8.808836E 02 8.943735E 01 4.385618E 01 2.608795E 01 8.600032E 01 4.385618E 01 4.236447E 01 7.925835E 01 4.385618E 01 5.701299E 01 6.947052E 01 4.385618E 01 6.947054E 01 5.701298E 01 4.385618E 01 7.925836E 01 4.236445E 01 4.385618E 01 8.600034E 01 2.608789E 01 4.385618E 01 8.943735E 01 8.808777E 02 4.385618E 01 8.217180E 01 8.093216E 02 5.641184E 01 7.901398E 01 2.396863E 01 5.641184E 01 7.281970E 01 3.892294E 01 5.641184E 01

PAGE 249

249 Table A 1. Continued 6.382700E 01 5.238147E 01 5.641184E 01 5.238147E 01 6.382700E 01 5.641184E 01 3.892294E 01 7.281970E 01 5.641184E 01 2.396863E 01 7.901398E 01 5.641184E 01 8.093216E 02 8.217180E 01 5.641184E 01 8.093222E 02 8.217180E 01 5.641184E 01 2.396863E 01 7.901398E 01 5.641184E 01 3.892295E 01 7.281970E 01 5.641184E 01 5.238146E 01 6.382700E 01 5.641184E 01 6.382700E 01 5.238146E 01 5.641184E 01 7.281970E 01 3.892293E 01 5.641184E 01 7.901398E 01 2.396863E 01 5.641184E 01 8.217180E 01 8.093212E 02 5.641184E 01 8.217180E 01 8.093226E 02 5.641184E 01 7.901397E 01 2.396865E 01 5.641184E 01 7.281970E 01 3.892294E 01 5.641184E 01 6.382700E 01 5.238147E 01 5.641184E 01 5.238147E 01 6.382700E 01 5.641184E 01 3.892294E 01 7.281970E 01 5.641184E 01 2.396862E 01 7.901399E 01 5.641184E 01 8.093198E 02 8.217180E 01 5.641184E 01 8.093239E 02 8.217179E 01 5.641184E 01 2.396866E 01 7.901397E 01 5.641184E 01 3.892294E 01 7.281970E 01 5.641184E 01 5.238147E 01 6.382700E 01 5.641184E 01 6.382701E 01 5.238146E 01 5.641184E 01 7.281971E 01 3.892293E 01 5.641184E 01 7.901399E 01 2.396861E 01 5.641184E 01 8.217180E 01 8.093185E 02 5.641184E 01 7.202500E 01 7.093844E 02 6.900780E 01 6.925712E 01 2.100892E 01 6.900780E 01 6.382772E 01 3.411663E 01 6.900780E 01 5.594547E 01 4.591326E 01 6.900780E 01 4.591326E 01 5.594547E 01 6.900780E 01 3.411663E 01 6.382773E 01 6.900780E 01 2.100891E 01 6.925712E 01 6.900780E 01 7.093843E 02 7.202500E 01 6.900780E 01 7.093849E 02 7.202500E 01 6.900780E 01 2.100892E 01 6.925712E 01 6.900780E 01

PAGE 250

250 Table A 1. Continued 3.411664E 01 6.382772E 01 6.900780E 01 4.591326E 01 5.594547E 01 6.900780E 01 5.594547E 01 4.591326E 01 6.900780E 01 6.382773E 01 3.411662E 01 6.900780E 01 6.925712E 01 2.100892E 01 6.900780E 01 7.202500E 01 7.093840E 02 6.900780E 01 7.202500E 01 7.093853E 02 6.900780E 01 6.925712E 01 2.100893E 01 6.900780E 01 6.382772E 01 3.411663E 01 6.900780E 01 5.594546E 01 4.591327E 01 6.900780E 01 4.591326E 01 5.594547E 01 6.900780E 01 3.411663E 01 6.382773E 01 6.900780E 01 2.100891E 01 6.925712E 01 6.900780E 01 7.093828E 02 7.202500E 01 6.900780E 01 7.093864E 02 7.202500E 01 6.900780E 01 2.100894E 01 6.925711E 01 6.900780E 01 3.411663E 01 6.382773E 01 6.900780E 01 4.591326E 01 5.594547E 01 6.900780E 01 5.594547E 01 4.591325E 01 6.900780E 01 6.382774E 01 3.411662E 01 6.900780E 01 6.925712E 01 2.100890E 01 6.900780E 01 7.202500E 01 7.093816E 02 6.900780E 01 5.734057E 01 5.647554E 02 8.173227E 01 5.513701E 01 1.672563E 01 8.173227E 01 5.081456E 01 2.716095E 01 8.173227E 01 4.453933E 01 3.655249E 01 8.173227E 01 3.655249E 01 4.453933E 01 8.173227E 01 2.716094E 01 5.081456E 01 8.173227E 01 1.672563E 01 5.513701E 01 8.173227E 01 5.647554E 02 5.734057E 01 8.173227E 01 5.647559E 02 5.734057E 01 8.173227E 01 1.672563E 01 5.513701E 01 8.173227E 01 2.716095E 01 5.081456E 01 8.173227E 01 3.655249E 01 4.453934E 01 8.173227E 01 4.453934E 01 3.655248E 01 8.173227E 01 5.081456E 01 2.716094E 01 8.173227E 01 5.513701E 01 1.672563E 01 8.173227E 01 5.734057E 01 5.647551E 02 8.173227E 01 5.734057E 01 5.647561E 02 8.173227E 01

PAGE 251

251 Table A 1. Continued 5.513701E 01 1.672564E 01 8.173227E 01 5.081456E 01 2.716095E 01 8.173227E 01 4.453933E 01 3.655249E 01 8.173227E 01 3.655249E 01 4.453933E 01 8.173227E 01 2.716095E 01 5.081456E 01 8.173227E 01 1.672562E 01 5.513701E 01 8.173227E 01 5.647542E 02 5.734057E 01 8.173227E 01 5.647570E 02 5.734057E 01 8.173227E 01 1.672565E 01 5.513700E 01 8.173227E 01 2.716095E 01 5.081456E 01 8.173227E 01 3.655249E 01 4.453933E 01 8.173227E 01 4.453934E 01 3.655248E 01 8.173227E 01 5.081456E 01 2.716094E 01 8.173227E 01 5.513701E 01 1.672561E 01 8.173227E 01 5.734058E 01 5.647532E 02 8.173227E 01 2.487961E 01 2.450428E 02 9.682459E 01 2.392350E 01 7.257114E 02 9.682459E 01 2.204802E 01 1.178491E 01 9.682459E 01 1.932525E 01 1.585983E 01 9.682459E 01 1.585983E 01 1.932525E 01 9.682459E 01 1.178491E 01 2.204802E 01 9.682459E 01 7.257113E 02 2.392350E 01 9.682459E 01 2.450427E 02 2.487961E 01 9.682459E 01 2.450430E 02 2.487961E 01 9.682459E 01 7.257115E 02 2.392350E 01 9.682459E 01 1.178492E 01 2.204802E 01 9.682459E 01 1.585982E 01 1.932525E 01 9.682459E 01 1.932525E 01 1.585982E 01 9.682459E 01 2.204802E 01 1.178491E 01 9.682459E 01 2.392350E 01 7.257114E 02 9.682459E 01 2.487961E 01 2.450426E 02 9.682459E 01 2.487961E 01 2.450431E 02 9.682459E 01 2.392350E 01 7.257119E 02 9.682459E 01 2.204802E 01 1.178491E 01 9.682459E 01 1.932525E 01 1.585983E 01 9.682459E 01 1.585983E 01 1.932525E 01 9.682459E 01 1.178491E 01 2.204802E 01 9.682459E 01 7.257111E 02 2.392350E 01 9.682459E 01 2.450422E 02 2.487961E 01 9.682459E 01

PAGE 252

252 Table A 1. Continued 2.450435E 02 2.487961E 01 9.682459E 01 7.257123E 02 2.392350E 01 9.682459E 01 1.178491E 01 2.204802E 01 9.682459E 01 1.585983E 01 1.932525E 01 9.682459E 01 1.932525E 01 1.585982E 01 9.682459E 01 2.204802E 01 1.178491E 01 9.682459E 01 2.392350E 01 7.257107E 02 9.682459E 01 2.487961E 01 2.450418E 02 9.682459E 01 5.647570E 02 5.734057E 01 8.173227E 01 1.672565E 01 5.513700E 01 8.173227E 01 2.716095E 01 5.081456E 01 8.173227E 01 3.655249E 01 4.453933E 01 8.173227E 01 4.453934E 01 3.655248E 01 8.173227E 01 5.081456E 01 2.716094E 01 8.173227E 01 5.513701E 01 1.672561E 01 8.173227E 01 5.734058E 01 5.647532E 02 8.173227E 01 2.487961E 01 2.450428E 02 9.682459E 01 2.392350E 01 7.257114E 02 9.682459E 01 2.204802E 01 1.178491E 01 9.682459E 01 1.932525E 01 1.585983E 01 9.682459E 01 1.585983E 01 1.932525E 01 9.682459E 01 1.178491E 01 2.204802E 01 9.682459E 01 7.257113E 02 2.392350E 01 9.682459E 01 2.450427E 02 2.487961E 01 9.682459E 01 2.450430E 02 2.487961E 01 9.682459E 01 7.257115E 02 2.392350E 01 9.682459E 01 1.178492E 01 2.204802E 01 9.682459E 01 1.585982E 01 1.932525E 01 9.682459E 01 1.932525E 01 1.585982E 01 9.682459E 01 2.204802E 01 1.178491E 01 9.682459E 01 2.392350E 01 7.257114E 02 9.682459E 01 2.487961E 01 2.450426E 02 9.682459E 01 2.487961E 01 2.450431E 02 9.682459E 01 2.392350E 01 7.257119E 02 9.682459E 01 2.204802E 01 1.178491E 01 9.682459E 01 1.932525E 01 1.585983E 01 9.682459E 01 1.585983E 01 1.932525E 01 9.682459E 01 1.178491E 01 2.204802E 01 9.682459E 01 7.257111E 02 2.392350E 01 9.682459E 01

PAGE 253

253 Table A 1. Continued 2.450422E 02 2.487961E 01 9.682459E 01 2.450435E 02 2.487961E 01 9.682459E 01 7.257123E 02 2.392350E 01 9.682459E 01 1.178491E 01 2.204802E 01 9.682459E 01 1.585983E 01 1.932525E 01 9.682459E 01 1.932525E 01 1.585982E 01 9.682459E 01 2.204802E 01 1.178491E 01 9.682459E 01 2.392350E 01 7.257107E 02 9.682459E 01 2.487961E 01 2.450418E 02 9.682459E 01

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254 APPENDIX B MEVDP RAY SELECTION Module Module1 Sub Main() Dim NTSA As Integer = 512 Dim PHII As Double = 0 Dim PHIF As Double = 2 Math.PI Dim THETAI As Double = 0 Dim THETAF As Double = Math.PI Dim PHIDF As Double = PHIF PHII Dim COSTH As Double = Math.Cos(THETAI) Dim DCOSTH As Double = COSTH Math.Cos(THETAF) Dim TSA As Double = Convert.ToDouble(NTSA) Dim FSA As Double = PHIDF / 4.0 DCOSTH / Math.PI Dim NSA As Integer = Convert.ToInt32(TSA FSA) Dim DTHETA As Double = THETAF THETAI Dim RATIO As Double = DTHETA / PHIDF Dim AXNTH As Double = Math.Sqrt(RATIO Convert.ToDouble(NSA)) Dim NTH As Integer = Math.Floor(AXNTH) + 1.0 Dim NPH As Integer = Math.Floor(AXNTH / RATIO) + 1.0 NSA = NTH NPH Dim NPL As Integer = NPH + 1 Dim CP As Double = Convert.ToDouble(NPH) 1 Dim L As Integer = 1 Dim C1 As Double Dim PHL(NPL 1) As Double Do Until L = NPL + 1 C1 = Convert.ToDouble(L 1) / CP PHL(L 1) = PHII + C1 PHIDF L = L + 1 Loop Dim NTK As Integer Dim CT As Double NTK = NTH + 1 CT = Convert.ToDouble(NTH) 1 Dim C2 As Double Dim THK(NTK 1) As Double Dim K As Integer = 1 Do Until K = NTK + 1 C2 = Convert.ToDouble(K 1) / CT THK(K 1) = Math.Acos(COSTH C2 DCOSTH) K = K + 1 Loop Dim THTMID(UBound(THK) 2) As Double

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255 Dim PHIMID(UBound(PHL) 2) As Double K = 1 Do Until K = NTH THTMID(K 1) = 0.5 (THK(K 1) + THK(K)) K = K + 1 Loop L = 1 Do Until L = NPH PHIMID(L 1) = 0.5 (PHL(L 1) + PHL(L)) L = L + 1 Loop End Sub End Mo dule

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256 APPENDIX C VOBRAT SOURCE CODE Module Module1 Sub Main() Define voxel array Dim N(2) As Integer Dim k As Integer voxrep: Console.WriteLine ("***** STEP 1: DEFINE VOXEL ARRAY *****") Console.WriteLine ("Input number of voxels in x, y, and z directions:") For k = 0 To 2 N(k) = Console.ReadLine() + 1 Next If N(0) <= 0 Or N(1) <= 0 Or N(2) <= 0 Then Console.WriteLine ("ERROR Number of voxels must be greater than zero") GoTo voxrep End If Dim d(2) As Single resrep: Console.WriteLine ("Input voxel resolution in x, y, and z directions (cm):") For k = 0 To 2 d(k) = Console.ReadLine() Next If d(0) <= 0 Or d(1) <= 0 Or d(2) <= 0 Then Console.WriteLine ("ERROR Voxel resolution must be greater than zero") GoTo resrep End If Console.WriteLine(" ") Define densities Dim rho1Dbyte((N(0) 1) (N(1) 1) (N(2) 1) 1) As Byte Dim rho As Single Dim range As Single Dim tagnum As Integer Dim filename1 As Stri ng Dim filename2 As String

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257 densrep: Console.WriteLine ("***** STEP 2: DEFINE ARRAY DENSITIES *****") Console.WriteLine ("Input name of file containing density array without extension:") filename1 = Console.ReadLine() filename2 = "E: \ MATLAB \ & filename1 & "(" & N(0) 1 & "x" & N(1) 1 & "x" & N(2) 1 & ").bin" Check to see if file exists If System.IO.File.Exists(filename2) Then GoTo exists Else Console.WriteLine ("ERROR File specified does not exist; please check file name") GoTo densrep End If exists: rho1Dbyte = My.Computer.FileSystem.ReadAllBytes (filename2) Dim numbyte As Integer = UBound(rho1Dbyte) 'If numint <> numbyte Then 'Console.WriteLine '("ERROR Size of density array (byte) does not match size of density array (integer)") 'GoTo voxrep 'End If Convert material tag in byte format to 3D matrix in integer format Dim tag3D(N(0) 2, N(1) 2, N(2) 2) As Integer Dim y As Integer = 0 Dim kdim As Integer = 0 Dim jdim As Integer = 0 Dim idim As Integer = 0 For kdim = 0 To N(2) 2 For jdim = 0 To N(1) 2 For idim = 0 To N(0) 2 tag3D(idim, jdim, kdim) = Convert.ToInt16(rho1Dbyte(y)) y = y + 1 Next Next Next Erase rho1Dbyte Define phantom composition information Dim gender As Integer Console.WriteLine

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258 ("Enter phantom composition information.") Console.WriteLine ("Type 1 for UFHADM.") Console.WriteLine ("Type 2 for UF/CAM.") Console.WriteLine ("Type 3 for CAM or CAF.") Console.WriteLine ("Type 4 for UFHADF.") Console.WriteLine ("Type 0 for water.") Console.WriteLine ("Type 5 for UFHADM with micro gravity bone density.") Console.WriteLine ("Type 6 for UFHADF with micro gravity bone density.") gender = Console.ReadLine() Dim range_Al As Single Dim range_H2O As Single Define dose point must be within voxel array doserep: Console.WriteLine ("***** STEP 3: DEFINE DOSE POINT(S) *****") Dim dp As Integer Console.WriteLine ("Enter 1 to loa d dose points coordinates from file.") Console.WriteLine ("Enter 0 for a single specified dose point.") Console.WriteLine ("Input organ number to randomly select voxels comprising organ.") If gender <> 3 Then Console.WriteLine("1. Skin") Console.WriteLine("2. BFO") Console.WriteLine("3. Eye lens") Console.WriteLine("4. Eyeball") Console.WriteLine("5. Stomach") Console.WriteLine("6. Colon") Console.WriteLine("7. Liver") Console.WriteLine("8. Lung") Console.WriteLine("9. Esophagus") Console.WriteLine("10. Bladder") Console.WriteLine("11. T hyroid") Console.WriteLine("12. Brain") End NASA, begin ICRP 103 Console.WriteLine("13. Salivary glands") Console.WriteLine("14. Adrenals") Console.WriteLine("15. ET region") Console .WriteLine("16. Gall bladder") Console.WriteLine("17. Heart") Console.WriteLine("18. Kidneys") Console.WriteLine("19. Muscle")

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259 Console.WriteLine("20. Pancreas") Console.WriteLine("21. Small intest ine") Console.WriteLine("22. Spleen") Console.WriteLine("23. Thymus") Console.WriteLine("24. Oral mucosa") If gender = 1 Or gender = 2 Or gender = 5 Then Console.WriteLine("25. Testes") End NASA, begin ICRP 103 Console.WriteLine("26. Prostate") ElseIf gender = 4 Or gender = 6 Then Console.WriteLine("25. Breast") Console.WriteLine("26. Ovary") 'End NASA, begin ICRP 103 Console.WriteLine("27. Uterus") End If Else Console.WriteLine("1. Muscle") '5 Console.WriteLine("2. BFO") Varies Console.WriteLine("3. Ey eball") '23 Console.WriteLine("4. Spinal Cord") '13 Console.WriteLine("5. Thyroid") '33 Console.WriteLine("6. Lung") '2 Console.WriteLine("7. Heart") '43 Console.WriteLine("8. Liver/Gall Blad der") '63 Console.WriteLine("9. Stomach") '53 Console.WriteLine("10. Spleen") '73 Console.WriteLine("11. Kidney") '83 Console.WriteLine("12. Pancreas") '103 Console.WriteLine("13. Intestines") '4 Console.WriteLine("14. Bladder") '93 Console.WriteLine("15. Skin") 99 Console.WriteLine("16. Brain") '3 Console.WriteLine("17. Testes") '113 End If dp = Console.ReadLine() If dp <> Int(dp) Or dp < 1 Or dp > 27 Then Console.WriteLine("ERROR Organ number not recognized.") GoTo doserep End If Dim p2(0, 2) As Integer Dim p2c(0, 2) As Double If dp = 1 Then dosepts: Console.WriteLine ("Please input the filename containing dose point coordinates.") Dim dosefile1 As String Dim dosefile2 As String dosefile1 = Console.ReadLine() dosefile2 = "E: \ MAT LAB \ & dosefile1 & ".csv"

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260 Dim num_rows As Integer Dim num_cols As Integer Dim xxx As Integer Dim yyy As Integer Dim strarray(1, 1) As String If System.IO.File.Exists(dosefile2) Then Dim tmpstream As System.IO.StreamReader = System.IO.File.OpenText(dosefile2) Dim strlines() As String Dim strline() As String Load content of file to strlines array strline s = tmpstream.ReadToEnd().Split(Environment.NewLine) Redimension array num_rows = UBound(strlines) strline = strlines(0).Split(",") num_cols = UBound(strline) ReDim strarray(num_rows, num_cols) Copy data to array For xxx = 0 To num_rows strline = strlines(xxx).Split(",") For yyy = 0 To num_cols stra rray(xxx, yyy) = strline(yyy) Next Next ReDim p2(num_rows, num_cols) For xxx = 0 To num_rows For yyy = 0 To num_cols p2(xxx, yyy) = Convert.ToIn t16(strarray(xxx, yyy)) Next Next Else Console.WriteLine ("ERROR File specified does not exist; please check file name") GoTo dosepts End If ElseIf dp = 0 Then Console.WriteLine ("Input i, j, and k coordinates of dose point:") For k = 0 To 2 p2(0, k) = Console.ReadLine() Next Else Dim tag(0) As Integer Dim voxcount As Integer = 0 If gender = 3 Then If dp = 1 Then

PAGE 261

261 tag(0) = 5 ElseIf dp = 2 Then ReDim tag(14) tag(0) = 207 'Cervical vertebra tag(1) = 209 'Clavicle tag(2) = 213 'Cranium tag(3) = 215 'Proximal femur tag(4) = 212 'Proximal humerus tag(5) = 239 'Lumb ar vertebra tag(6) = 14 'Mandible tag(7) = 214 'Pelvis tag(8) = 211 'Rib tag(9) = 19 'Sacrum tag(10) = 210 'Scapula tag(11) = 100 'Stern um DNE tag(12) = 208 'Thoracic vertebra tag(13) = 220 'Upper femur DNE tag(14) = 221 'Upper humerus DNE ElseIf dp = 3 Then tag(0) = 23 ElseIf dp = 4 Then tag(0) = 13 ElseIf dp = 5 Then tag(0) = 33 ElseIf dp = 6 Then tag(0) = 2 ElseIf dp = 7 Then t ag(0) = 43 ElseIf dp = 8 Then tag(0) = 63 ElseIf dp = 9 Then tag(0) = 53 ElseIf dp = 10 Then tag(0) = 73 ElseIf dp = 11 Then tag(0) = 83 ElseIf dp = 12 Then tag(0) = 103 ElseIf dp = 13 Then tag(0) = 4 ElseIf dp = 14 Then tag(0) = 93 ElseIf dp = 15 Then tag(0) = 99 ElseIf dp = 16 Then tag(0) = 3 ElseIf dp = 17 Then tag(0) = 113 End If End If If gender <> 3 Then If dp = 1 Then tag(0) = 43 ElseIf dp = 2 Then

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262 ReDim tag(14) tag(0) = 207 'Cervical vertebra tag(1) = 204 'Clavicle tag(2) = 201 'Cranium tag(3) = 212 'Proximal femur tag(4) = 224 'Proximal humerus tag(5) = 209 'Lumbar vertebra tag(6) = 202 'Mandible tag(7) = 211 'Pelvis tag(8) = 206 'Rib tag(9) = 210 'Sacrum tag(10) = 203 'Scapula tag(11) = 205 'Sternum tag(12) = 208 'Thoracic vertebra tag(13) = 213 'Upper Femur tag(14) = 225 'Upper Humerus ElseIf dp = 3 Then tag(0) = 24 ElseIf dp = 4 Then tag(0) = 12 ElseIf dp = 5 Then tag(0) = 46 ElseIf dp = 6 Then ReDim tag(2) tag(0) = 7 tag(1) = 58 tag(2) = 37 ElseIf dp = 7 Then tag(0) = 25 ElseIf dp = 8 Then ReDim tag(1) tag(0) = 26 tag(1) = 27 ElseIf dp = 9 Then tag(0) = 10 ElseIf dp = 10 Then tag(0) = 54 ElseIf dp = 11 Then tag(0) = 50 ElseIf dp = 12 Then tag(0) = 4 ElseIf dp = 13 Then ReDim tag(2) tag(0) = 39 tag(1) = 60 tag(2) = 61 ElseIf dp = 14 Then ReDim tag(1) tag(0) = 2 tag(1) = 3 ElseIf dp = 15 Then ReDim tag(3) tag(0) = 28 tag(1) = 29 tag(2) = 23

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263 tag(3) = 34 ElseIf dp = 16 Then tag(0) = 13 ElseIf dp = 17 Then tag( 0) = 15 ElseIf dp = 18 Then ReDim tag(5) tag(0) = 17 tag(1) = 18 tag(2) = 19 tag(3) = 20 tag(4) = 21 tag(5) = 22 ElseIf dp = 19 Then tag(0) = 1 RST ElseIf dp = 20 Then tag(0) = 32 ElseIf dp = 21 Then tag(0) = 41 ElseIf dp = 22 The n tag(0) = 45 ElseIf dp = 23 Then tag(0) = 49 ElseIf dp = 24 Then tag(0) = 30 End If If gender = 1 Or gender = 2 Or gender = 5 Then If dp = 25 Then tag(0) = 48 ElseIf dp = 26 Then tag(0) = 36 End If End If If gender = 4 Or gender = 6 Then If dp = 25 Then tag(0) = 5 ElseIf dp = 26 Then tag(0) = 31 ElseIf dp = 27 Then tag(0) = 56 End If End If End If Dim Ntag As Integer If dp <> 2 Then All organs except BFO For Ntag = 0 To UBound(tag) For kdim = 0 To N(2) 2 For jdim = 0 To N(1) 2 For idim = 0 To N(0) 2 If tag3D(idim, jdim, kdim) = tag(Ntag) Then voxcount = voxcount + 1

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264 End If Next Next Next Next Dim p2r(voxcount 1, 2) As Integer voxcount = 0 For Ntag = 0 To UBound(tag) For kdim = 0 To N(2) 2 For jdim = 0 To N(1) 2 For idim = 0 To N(0) 2 If tag3D(idim, jdim, kdim) = tag(Ntag) Then p2r(voxcount, 0) = idim p2r(voxcount, 1) = jdim p2r(voxcount, 2) = kdim voxcount = voxcount + 1 End If Ne xt Next Next Next Console.WriteLine(" ") Dim rando As Integer Dim randcount As Integer Dim randval As Integer Console.WriteLine ("The number of voxels available for random ray tracing is & voxcount & ".") Console.WriteLine(" ") randorep: Console.WriteLine ("Please enter the numbe r of random dose points to be ray traced in this organ (1 to 10 000):") rando = Console.ReadLine If rando <> Int(rando) Or rando < 1 Or rando > 100000.0 Then Console.WriteLine("ERROR Number of dose poi nts must be an integer between 1 and 10 000.") GoTo randorep End If If rando > voxcount Then Console.WriteLine("WARNING Number of random points exceeds number of voxels. Default to ray trace each voxel.") ReDim p2(UBound(p2r, 1), UBound(p2r, 2)) p2 = p2r Else Randomly select from p2r, removing a voxel from the set if it has been previously selected ReDim p2(rando 1, 2)

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265 Dim counter As Integer For randcount = 0 To rando 1 Randomize() randval = Int((UBound(p2r, 1) LBound(p2r, 1)) Rnd() + LBound(p2r, 1)) For k = 0 To 2 p2(randcount, k) = p2r(randval, k) Next Dim p2r_copy(UBound(p2r, 1) 1, 2) As Integer If randval = 0 Then For counter = 1 To UBound(p2r, 1) And counter <> randval For k = 0 To 2 If counter < randval Then p2r_copy(counter, k) = p2r(counter, k) Else p2r_copy(counter 1, k) = p2r(counter 1, k) End If Next Nex t Else For counter = 0 To UBound(p2r, 1) And counter <> randval For k = 0 To 2 If counter < randval Then p2r_copy(counter, k) = p2r(counter, k) Else p2r_copy(counter 1, k) = p2r(counter 1, k) End If Next Next End If ReDim p2r(UBound(p2r_copy, 1), 2) For counter = 0 To UBound(p2r_copy, 1) For k = 0 To 2 p2r(counter, k) = p2r_copy(counter, k) Next Next Erase p2r_copy Next Erase p2r End If Else BFO Dim CV_count As Integer = 0 Dim clavicle_count As Integer = 0 Dim cranium_count As Integer = 0 Dim femur_count As Integer = 0 Dim humerus_count As Integer = 0 D im LV_count As Integer = 0 Dim mandible_count As Integer = 0

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266 Dim pelvis_count As Integer = 0 Dim rib_count As Integer = 0 Dim sacrum_count As Integer = 0 Dim scapula_count As I nteger = 0 Dim sternum_count As Integer = 0 Dim TV_count As Integer = 0 Dim femur_upper_count As Integer = 0 Dim humerus_upper_count As Integer = 0 For kdim = 0 To N(2) 2 For jdim = 0 To N(1) 2 For idim = 0 To N(0) 2 If tag3D(idim, jdim, kdim) = tag(0) Then CV_count = CV_count + 1 ElseIf tag3D(idim, jdim, kdim) = tag(1) Then clavicle_count = clavicle_count + 1 ElseIf tag3D(idim, jdim, kdim) = tag(2) Then cranium_co unt = cranium_count + 1 ElseIf tag3D(idim, jdim, kdim) = tag(3) Then femur_count = femur_count + 1 ElseIf tag3D(idim, jdim, kdim) = tag(4) Then humerus_count = humerus_count + 1 ElseIf tag3D(idim, jdim, kdim) = tag(5) Then LV_count = LV_count + 1 ElseIf tag3D(idim, jdim, kdim) = tag(6) Then mandible_count = mandible_count + 1 ElseIf tag3D(idim, jdim, kdim) = tag(7) Then pelvis_count = pelvis_count + 1 ElseIf tag3D(idim, jdim, kdim) = ta g(8) Then rib_count = rib_count + 1 ElseIf tag3D(idim, jdim, kdim) = tag(9) Then sacrum_count = sacrum_count + 1 ElseIf tag3D(idim, jdim kdim) = tag(10) Then scapula_count = scapula_count + 1 ElseIf tag3D(idim, jdim, kdim) = tag(11) And gender <> 3 Then sternum_count = sternum_count + 1 ElseIf tag3D(idim, jdim, kdim) = tag(12) Then TV_count = TV_count + 1 ElseIf tag3D(idim, jdim, kdim) = tag(13) Then femur_upper_count = femur_upper _count + 1 ElseIf tag3D(idim, jdim, kdim) = tag(14) Then humerus_upper_count = humerus_upper_count + 1 End If Next Next Next Dim CV(CV_count 1, 2) As Integer Dim clavicle(clavicle_count 1, 2) As Integer Dim cranium(cranium_count 1, 2) As Integer Dim femur(femur_count 1, 2) As Integer Dim humerus(humerus_count 1, 2) As Integer Dim LV(LV_count 1, 2) As Integer Dim mandible(mandible_count 1, 2) As Integer

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267 Dim pelvis(pelvis_count 1, 2) As Integer Dim rib( rib_count 1, 2) As Integer Dim sacrum(sacrum_count 1, 2) As Integer Dim scapula(scapula_count 1, 2) As Integer Dim sternum(0, 2) As Integer If gender <> 3 Then ReDim sternum(sternum_count 1, 2) End If Dim TV(TV_count 1, 2) As Integer Dim femur_upper(0, 2) As Integer Dim humerus_upper(0, 2) As Integer If gender <> 3 Then ReDim femur_upper(femur_upper_count 1, 2) ReDim humerus_upper(humerus_upper_count 1, 2) End If CV_count = 0 clavicle_count = 0 cranium_count = 0 femur_count = 0 humerus_count = 0 LV_count = 0 mandible_count = 0 pelvis_count = 0 rib_count = 0 sacrum_count = 0 scapula_count = 0 sternum_count = 0 TV_count = 0 femur_upper_count = 0 humerus_upper_count = 0 For kdim = 0 To N(2) 2 For jdim = 0 To N(1) 2 For idim = 0 To N(0) 2 If tag3D(idim, jdim, kdim) = tag(0) Then CV(CV_count, 0) = idim CV(CV_count, 1) = jdim CV(CV_count, 2) = kd im CV_count = CV_count + 1 ElseIf tag3D(idim, jdim, kdim) = tag(1) Then clavicle(clavicle_count, 0) = idim clavicle(clavicle_count, 1) = jdim clavicle(clavicle_count, 2) = kdim clavicle_count = clavicle_count + 1 ElseIf tag3D(idim, jdim, kdim) = tag(2) Then cranium(cranium_count, 0) = idim cranium(cranium_count, 1) = jdim cranium(cranium_count, 2) = kdim cranium_count = cranium_count + 1 ElseIf tag3D(idim, jdim, kdim) = tag(3) Then femur(femur_count, 0) = idim

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268 femur(femur_count, 1) = jdim femur(femur_count, 2) = kdim femur_count = femur_count + 1 ElseIf tag3D(idim, jdim, kdim) = tag(4) Then humerus(humerus_count, 0) = idim humerus(humerus_cou nt, 1) = jdim humerus(humerus_count, 2) = kdim humerus_count = humerus_count + 1 ElseIf tag3D(idim, jdim, kdim) = tag(5) Then LV(LV_ count, 0) = idim LV(LV_count, 1) = jdim LV(LV_count, 2) = kdim LV_count = LV_count + 1 ElseIf tag3D(idim, jdim, kdim) = tag(6) Then mandible(mandible_count, 0) = idim mandible(mandible_count, 1) = jdim mandible(mandible_count, 2) = kdim mandible_count = mandib le_count + 1 ElseIf tag3D(idim, jdim, kdim) = tag(7) Then pelvis(pelvis_count, 0) = idim pelvis(pelvis_count, 1) = jdim pelvis(pelvis_count, 2) = kdim pelvis_count = pelvis_count + 1 ElseIf tag3D(idim, jdim, kdim) = tag(8) Then rib(rib_count, 0) = idim rib(rib_count, 1) = jdim rib(rib_count, 2) = kdim rib_count = rib_count + 1 ElseIf tag3D(idim, jdim, kdim) = tag(9) Then sacrum(sacrum_count, 0) = idim sacrum(sacrum_count, 1) = jdim sacrum(sacrum_count, 2) = kdim sacrum_count = sacrum_count + 1 ElseIf tag3D(idim, jdim, kdim) = tag(10) Then scapula(scapula_count, 0) = idim scapula(scapula_count, 1) = jdim scapula(scapula_count, 2) = kdim scapula_count = scapula_count + 1 ElseIf tag3D(idim, jdim, kdim) = tag(11) And gender <> 3 Then sternum(sternum_count, 0) = idim ste rnum(sternum_count, 1) = jdim sternum(sternum_count, 2) = kdim sternum_count = sternum_count + 1 ElseIf tag3D(idim, jdim, kdim) = tag(12) Then TV(TV_count, 0) = idim TV(TV_count, 1) = jdim TV(TV_count, 2) = kdim TV_count = TV_count + 1 ElseIf tag3D(idim, jdim, kdi m) = tag(13) Then femur_upper(femur_upper_count, 0) = idim femur_upper(femur_upper_count, 1) = jdim femur_upper(femur_upper_count, 2) = kdim femur_upper_count = femur_upper_count + 1 ElseIf tag3D(idim, jdim, kdim) = tag(14) Then

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269 humerus_upper(humerus_upper_count, 0) = idim humerus_upper(humerus_upper_count, 1) = jdim humerus_upper(humerus_upper_count, 2) = kdim humerus_upper_count = humerus_upper_count + 1 End If Next Next Next Console.WriteLine(" ") Dim rando As Integer Dim randcount As Integer Dim randval As Integer randoBFOrep: Console.WriteL ine ("Please enter the approximate number of random dose points to be ray traced for the BFO (10 to 10 000):") rando = Console.ReadLine If rando <> Int(rando) Or rando < 10 Or rando > 100000.0 Then Console.WriteLine("ERROR Number of dose points must be an integer between 10 and 10 000.") GoTo randoBFOrep End If Define active marrow masses in each skeletal region Dim CV_mass As Single = 32.2 Dim clavicle_mass As Single = 10.87 Dim cranium_mass As Single = 51.27 Dim femur_mass As Single = 50.82 Dim humerus_mass As Single = 34.68 Dim LV_mass As Single = 155.98 Dim mandible_mass As Single = 10.46 Dim pelvis_mass As Single = 303.77 Dim rib_mass As Single = 120.67 Dim sacrum_mass As Single = 99.19 Dim scapula_mass As Single = 108.58 Dim sternum_mass As Single = 29.33 Dim TV_mass As Single = 139.16 Dim femur_upper_mass As Single = 31.65 Dim humerus_upper_mass As Single = 8.0 Dim total_mass As Single total_mass = CV_mass + clavicle_mass + cranium_mass + femur_mass + humerus_mass + LV_mass + mandible_mass + pelvis_mass + rib_mass + sacrum_mass + scapula_mass + sternum_mass + TV_mass + femur_upper_mass + hume rus_upper_mass Apportion number of points to each skeletal region according to relative amount of AM mass Dim N_CV As Integer Dim N_clavicle As Integer Dim N_cranium As Integer

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270 Dim N_femur As Integer Dim N_humerus As Integer Dim N_LV As Integer Dim N_mandible As Integer Dim N_pelvis As Integer Dim N_rib As Integer Dim N_sacrum As Integer Dim N_scapula As Integer Dim N_sternum As Integer Dim N_TV As Integer Dim N_femur_upper As Integer Dim N_humerus_upper As Integer N_CV = Int(rando CV_mass / total_mass) N_clavicle = Int(rando clavicle_mass / total_mass) N_cranium = Int(rando cranium_mass / total_mass) N_femur = Int(rando femur_mass / total_mass) N_humerus = Int(rando humerus_mass / total_mass) N_LV = Int(rando LV_mass / total_mass) N_mandible = Int(rando mandible_mass / total_mass) N_pelvis = Int(rando pelvis_mass / total_mass) N_rib = Int(rando rib_mass / total_mass) N_sacrum = Int(rando sacrum_mass / total_mass) N_scapula = Int(rando scapula_mass / total_mass) N_sternum = Int(rando sternum_mass / total_mass) N_TV = Int(rando TV_mass / total_mass) N_femur_upper = Int(rando femur_upper_mass / total_mass) N_humerus_upper = Int(rando humerus_upper_mass / total_mass) If gender = 3 Then N_rib = N_rib + N_sternum N_sternum = 0 N_femur = N_femur + N_femur_upper N_femur_upper = 0 N_humerus = N_humerus + N_humerus_upper N_humerus_upper = 0 End If Populate dose point matrix with BFO voxels Dim rando_actual As Integer rando_actual = N_CV + N_clavicle + N_cranium + N_femur + N_humerus + N _LV + N_mandible + N_pelvis + N_rib + N_sacrum + N_scapula + N_sternum + N_TV + N_femur_upper + N_humerus_upper ReDim p2(rando_actual 1, 2) Dim CV_r(N_CV 1, 2) As Integer Dim clavicle_r(N_clavicle 1, 2 ) As Integer Dim cranium_r(N_cranium 1, 2) As Integer Dim femur_r(N_femur 1, 2) As Integer Dim humerus_r(N_humerus 1, 2) As Integer Dim LV_r(N_LV 1, 2) As Integer Dim m andible_r(N_mandible 1, 2) As Integer Dim pelvis_r(N_pelvis 1, 2) As Integer Dim rib_r(N_rib 1, 2) As Integer

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271 Dim sacrum_r(N_sacrum 1, 2) As Integer Dim scapula_r(N_scapula 1, 2) As Integer Dim sternum_r(0, 2) As Integer If gender <> 3 Then ReDim sternum_r(N_sternum 1, 2) End If Dim TV_r(N_TV 1, 2) As Integer Dim femur_upper_r(N_femur_upper 1, 2) As Integer Dim humerus_upper_r(N_humerus_upper 1, 2) As Integer Dim counter As Integer Cervical Vertebra For randcount = 0 To N_CV 1 Randomize() randval = Int((UBound(CV, 1) LBound(CV, 1)) Rnd() + LBound(CV, 1)) For k = 0 To 2 CV_r(randcount, k) = CV(randval, k) Next Dim CV_copy(UBound(CV, 1) 1, 2) As Integer If randval <> 0 Then For counter = 0 To UBound(CV, 1) And counter <> randval For k = 0 To 2 I f counter < randval Then CV_copy(counter, k) = CV(counter, k) Else CV_copy(counter 1, k) = CV(counter 1, k) End If Next Next Else For counter = 1 To UBound(CV, 1) And counter <> randval For k = 0 To 2 CV_copy(counter 1, k) = CV(counter 1, k) Next Next End If ReDim CV(UBound(CV_copy, 1), 2) For counter = 0 T o UBound(CV_copy, 1) For k = 0 To 2 CV(counter, k) = CV_copy(counter, k) Next Next Erase CV_copy Next Erase CV Clavicle For randcount = 0 To N_clavicle 1

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272 Randomize() randval = Int((UBound(clavicle, 1) LBound(clavicle, 1)) Rnd() + LBound(clavicle, 1)) For k = 0 To 2 clavicle_r(randcount, k) = clavicle(randval, k) Next Dim clavicle_copy(UBound(clavicle, 1) 1, 2) As Integer If randval <> 0 Then For counter = 0 To UBound(clavicle, 1) And counter <> randval For k = 0 To 2 If counter < randval Then clavicle_copy(counter, k) = clavicle(counter, k) Else clavicle_copy(counter 1, k) = clavicle(counter 1, k) End If Next Next Else For counter = 1 To UBound(clavicle, 1) And counter <> randval For k = 0 To 2 clavicle_copy(counter 1, k) = clavicle(counter 1, k) Next Next End If ReDim clavicle(UBound(clavicle_copy, 1), 2) For counter = 0 To UBound(clavicle_copy, 1) For k = 0 To 2 clavicle( counter, k) = clavicle_copy(counter, k) Next Next Erase clavicle_copy Next Erase clavicle Cranium For randcount = 0 To N_cran ium 1 Randomize() randval = Int((UBound(cranium, 1) LBound(cranium, 1)) Rnd() + LBound(cranium, 1)) For k = 0 To 2 cranium_r(randcount, k) = cranium(randval, k) Next Dim cranium_copy(UBound(cranium, 1) 1, 2) As Integer If randval <> 0 Then For counter = 0 To UBound(cranium, 1) And counter <> randval For k = 0 To 2 If counter < randval Then cranium_copy(counter, k) = cranium(counter, k)

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273 Else cranium_copy(counter 1, k ) = cranium(counter 1, k) End If Next Next Else For counter = 1 To UBound(cranium, 1) And counter <> randval For k = 0 To 2 cranium_copy(counter 1, k) = cranium(counter 1, k) Next Next End If ReDim cranium(UBound(cranium_copy 1), 2) For counter = 0 To UBound(cranium_copy, 1) For k = 0 To 2 cranium(counter, k) = cranium_copy(counter, k) Next Next Erase cranium_copy Next Erase cranium Femur For randcount = 0 To N_femur 1 Randomize() randval = Int((UBound(femur, 1) LBound (femur, 1)) Rnd() + LBound(femur, 1)) For k = 0 To 2 femur_r(randcount, k) = femur(randval, k) Next Dim femur_copy(UBound(femur, 1) 1, 2) As Integer If randval <> 0 Then For counter = 0 To UBound(femur, 1) And counter <> randval For k = 0 To 2 If counter < randval Then femur_copy(c ounter, k) = femur(counter, k) Else femur_copy(counter 1, k) = femur(counter 1, k) End If Next Next Else For counter = 1 To UBound(femur, 1) And counter <> randval For k = 0 To 2 femur_copy(counter 1, k) = femur(counter 1, k) Next Next End If

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274 ReDim femur(UBound(femur_copy, 1), 2) For counter = 0 To UBound(femur_copy, 1) For k = 0 To 2 femur(counter, k) = femur_copy(counter, k) Next Next Erase femur_copy Next Erase femur Humerus Fo r randcount = 0 To N_humerus 1 Randomize() randval = Int((UBound(humerus, 1) LBound(humerus, 1)) Rnd() + LBound(humerus, 1)) For k = 0 To 2 humerus_r(randcount, k) = humerus(randval, k) Next Dim humerus_copy(UBound(humerus, 1) 1, 2) As Integer If randval <> 0 Then For counter = 0 To UBound(humerus, 1) And counter <> randval For k = 0 To 2 If counter < randval Then humerus_copy(counter, k) = humerus(counter, k) Else humerus_copy(counter 1, k) = humerus(counter 1, k) End If Next Next Else For counter = 1 To UBound(humerus, 1) And counter <> randval For k = 0 To 2 humerus_copy(counter 1, k) = humerus(counter 1, k) Next Next End If ReDim humerus(UBound(humerus_copy, 1), 2) For counter = 0 To UBound(humerus_copy, 1) For k = 0 To 2 humerus(counter, k) = humerus_copy(counter, k) Next Next Erase humerus_copy Next Erase humerus LV For randcount = 0 To N_LV 1 Randomize()

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275 randval = Int((UBound(LV, 1) LBound(LV, 1)) Rnd() + LBound(LV, 1)) For k = 0 To 2 LV_r(randcount, k) = LV(randval, k) Next Dim LV_copy(UBound(LV, 1) 1, 2) As Integer If randval <> 0 Then For counter = 0 To UBound(LV, 1) And counter <> randval For k = 0 To 2 If counter < randval Then LV_copy(counter, k) = LV(counter, k) Else LV_copy(counter 1, k) = LV(counter 1, k) E nd If Next Next Else For counter = 1 To UBound(LV, 1) And counter <> randval For k = 0 To 2 LV_copy( counter 1, k) = LV(counter 1, k) Next Next End If ReDim LV(UBound(LV_copy, 1), 2) For counter = 0 To UBound(LV_copy, 1) For k = 0 To 2 LV(counter, k) = LV_copy(counter, k) Next Next Erase LV_copy Next Erase LV Mandible For randcount = 0 To N_mandible 1 Randomize() randval = Int((UBound(mandible, 1) LBound(mandible, 1)) Rnd() + LBound(mandible, 1)) For k = 0 To 2 mand ible_r(randcount, k) = mandible(randval, k) Next Dim mandible_copy(UBound(mandible, 1) 1, 2) As Integer If randval <> 0 Then For counter = 0 To UBound(mandible, 1) And counter <> randval For k = 0 To 2 If counter < randval Then mandible_copy(counter, k) = mandible(counter, k) Else mandible_copy(counter 1, k) = mandible(counter 1, k)

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276 End If Next Next Else For counter = 1 To UBound(m andible, 1) And counter <> randval For k = 0 To 2 mandible_copy(counter 1, k) = mandible(counter 1, k) Next Next End If ReDim mandible(UBound(mandible_copy, 1), 2) For counter = 0 To UBound(mandible_copy, 1) For k = 0 To 2 mandible(counter, k) = mandible_copy(counter, k) Next Next Erase mandible_copy Next Erase mandible Pelvis For randcount = 0 To N_pelvis 1 Randomize() randval = Int((UBound(pelvis, 1) LBound(pelvis, 1)) Rnd() + LBound(pelvis, 1)) For k = 0 To 2 pelvis_r(randcount, k) = pelvis(randval, k) Next Dim pelvis_copy( UBound(pelvis, 1) 1, 2) As Integer If randval <> 0 Then For counter = 0 To UBound(pelvis, 1) And counter <> randval For k = 0 To 2 If counter < randv al Then pelvis_copy(counter, k) = pelvis(counter, k) Else pelvis_copy(counter 1, k) = pelvis(counter 1, k) End If Next Next Else For counter = 1 To UBound(pelvis, 1) And counter <> randval For k = 0 To 2 pelvis_cop y(counter 1, k) = pelvis(counter 1, k) Next Next End If ReDim pelvis(UBound(pelvis_copy, 1), 2) For counter = 0 To UBound(pelvis_copy, 1)

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277 For k = 0 To 2 pelvis(counter, k) = pelvis_copy(counter, k) Next Next Erase pelvis_copy Next Erase pelvis Rib For randcount = 0 To N_rib 1 Randomize() randval = Int((UBound(rib, 1) LBound(rib, 1)) Rnd() + LBound(rib, 1)) For k = 0 To 2 rib_ r(randcount, k) = rib(randval, k) Next Dim rib_copy(UBound(rib, 1) 1, 2) As Integer If randval <> 0 Then For counter = 0 To UBound(rib, 1) And counter <> randval For k = 0 To 2 If counter < randval Then rib_copy(counter, k) = rib(counter, k) Else rib_cop y(counter 1, k) = rib(counter 1, k) End If Next Next Else For counter = 1 To UBound(rib, 1) And counter <> randval For k = 0 To 2 rib_copy(counter 1, k) = rib(counter 1, k) Next Next End If ReDim rib(UBound(rib_copy, 1), 2) For counter = 0 To UBound(rib_copy, 1) For k = 0 To 2 rib(counter, k) = rib_copy(counter, k) Next Next Erase rib_copy Next Erase rib Sacrum For randcount = 0 To N_sacrum 1 Randomize() randval = Int((UBound(sacrum, 1) LBound(sacrum, 1)) Rnd() + LBound(sacrum, 1)) For k = 0 To 2 sacrum_r(randcount, k) = sacrum(randval, k) Next

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278 Dim sacrum_copy(UBound(sacrum, 1) 1, 2) As Integer If randval <> 0 Then For counter = 0 To UBound(sacrum, 1) And counter <> randval For k = 0 To 2 If counter < randval Then sacrum_copy(counter, k) = sacrum(counter, k) Else sacrum_copy(counter 1, k) = sacrum(counter 1, k) End If Next Next Else For counter = 1 To UBound(sacrum, 1) And counter <> randval For k = 0 To 2 sacrum_copy(counter 1, k) = sacrum(counter 1, k) Next Next End If ReDim sacrum(UBound(sacrum_copy, 1), 2) For counter = 0 To UBound(sacrum_copy, 1) For k = 0 To 2 sacrum(counter, k) = sacrum_copy(counter, k) Next Next Erase sacrum_copy Next Erase sacrum Scapula For randcount = 0 To N_scapula 1 Randomize() randval = Int((UBound(scapula, 1) LBound(scapula, 1)) Rnd() + LBound(scapula, 1)) For k = 0 To 2 scapula_r(randcount, k ) = scapula(randval, k) Next Dim scapula_copy(UBound(scapula, 1) 1, 2) As Integer If randval <> 0 Then For counter = 0 To UBound(scapula, 1) And counter <> randval For k = 0 To 2 If counter < randval Then scapula_copy(counter, k) = scapula(counter, k) Else sca pula_copy(counter 1, k) = scapula(counter 1, k) End If Next Next Else

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279 For counter = 1 To UBound(scapula, 1) And counter <> randval For k = 0 To 2 scapula_copy(counter 1, k) = scapula(counter 1, k) Next Next End If ReDim s capula(UBound(scapula_copy, 1), 2) For counter = 0 To UBound(scapula_copy, 1) For k = 0 To 2 scapula(counter, k) = scapula_copy(counter, k) Next Next Erase scapula_copy Next Erase scapula Sternum If gender <> 3 Then For randcount = 0 To N_sternum 1 Randomize() randval = Int((UBound(sternum, 1) LBound(sternum, 1)) Rnd() + LBound(sternum, 1)) For k = 0 To 2 sternum_r(randcount, k) = sternum(randval, k) Next Dim sternum_copy(UBound(sternum, 1) 1, 2) As Integer If randval <> 0 Then For counter = 0 To UBound(sternum, 1) And counter <> randval For k = 0 To 2 If counter < randval Then sternum_copy(counter, k) = sternum(counter, k) Else sternum_copy(counter 1, k) = sternum(counter 1, k) End If Next Next Else For counter = 1 To UBound(sternum, 1) And counter <> rand val For k = 0 To 2 sternum_copy(counter 1, k) = sternum(counter 1, k) Next Next End If ReDim sternum(UBound(sternum_copy, 1), 2) For counter = 0 To UBound(sternum_copy, 1)

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280 For k = 0 To 2 sternum(counter, k) = sternum_copy(counter, k) Next Next Erase sternum_copy Next Erase sternum End If TV For randcount = 0 To N_TV 1 Randomize() randval = Int((UBound(TV, 1) LBound(TV, 1)) Rnd() + LBound(TV, 1)) For k = 0 To 2 TV_r(randcount, k) = TV(randval, k) Next Dim TV_copy(UBound(TV, 1) 1, 2) As Integer If randval <> 0 Then For counter = 0 To UBound(TV, 1) And counter <> randval For k = 0 To 2 If cou nter < randval Then TV_copy(counter, k) = TV(counter, k) Else TV_copy(counter 1, k) = TV(counter 1, k) End If Next Next Else For counter = 1 To UBound(TV, 1) And counter <> randval For k = 0 To 2 TV_copy(counter 1, k) = TV(counter 1, k) Next Next End If ReDim TV(UBound(TV_copy, 1), 2) For counter = 0 To UBound(TV_copy, 1) For k = 0 To 2 TV(counter, k) = TV_copy(counter, k) Next Next Erase TV_copy Next Erase TV Femur Upper For randcount = 0 To N_femur_upper 1 Randomize() randval = Int((UBound(femur_upper, 1) LBound(femur_upper, 1)) Rnd() + LBound(femur_upper, 1)) For k = 0 To 2 femur_upper_r(randcount, k) = femur_upper(randval, k) Next

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281 Dim femur_upper_copy(UBound(femur_upper, 1) 1, 2) As Integer If randval <> 0 Then For co unter = 0 To UBound(femur_upper, 1) And counter <> randval For k = 0 To 2 If counter < randval Then femur_upper_copy(counter, k) = femur_upper(counter, k) Else femur_upper_copy(counter 1, k) = femur_upper(counter 1, k) End If Next Next Else For counter = 1 To UBound(femur_upper, 1) And counter <> randval For k = 0 To 2 femur_upper_copy(counter 1, k) = femur_upper(counter 1, k) Next Next End If ReDim femur_upper(UBound(femur_upper_copy, 1), 2) For counter = 0 To UBound(femur_upper_copy, 1) For k = 0 To 2 femur_upper(counter, k) = femur_upper_copy(counter, k) Next Next Erase femur_upper_copy Next Erase femur_upper Humerus Upper For randcount = 0 To N_humerus_upper 1 Randomize() randval = Int((UBound(humerus_upper, 1) LBound(humerus_upper, 1)) Rnd() + LBound(humerus_upper, 1)) For k = 0 To 2 humerus_upper_r(randcount, k) = humerus_upper(randval, k) Next Dim humerus_upper_copy(UBound(humerus_upper, 1) 1, 2) As Integer If randval <> 0 Then For counte r = 0 To UBound(humerus_upper, 1) And counter <> randval For k = 0 To 2 If counter < randval Then humerus_upper_copy(counter, k) = humerus_upper(counter, k) Else

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282 humerus_upper_copy(counter 1, k) = humerus_upper(counter 1, k) End If Next Next Else For counter = 1 To UBound(humerus_upper, 1) And counter <> randval For k = 0 To 2 humerus_upper_copy(counter 1, k) = humerus_upper(counter 1, k) Next Next End If ReDim humerus_upper(UBound(humerus_upper_copy, 1), 2) For counter = 0 To UBound(humerus_upper_copy, 1) For k = 0 To 2 humerus_upper(counter, k) = humerus_upper_copy(counter, k) Next Next Erase humerus_upper_copy Next Erase humerus_upper Dim aa, bb, cc, dd, ee, ff, gg, hh, ii, jj, kk, ll, mm, nn, oo As Integer Combine all spongiosa sites into one array For k = 0 To 2 For aa = 0 To UBound(CV_r, 1) p2(aa, k) = CV_r(aa, k) Next For bb = 0 To UBound(clavicle_r, 1) p2(bb + aa, k) = clavicle_r(bb, k) Next For cc = 0 To UBound( cranium_r, 1) p2(cc + bb + aa, k) = cranium_r(cc, k) Next For dd = 0 To UBound(femur_r, 1) p2(dd + cc + bb + aa, k) = femur_r(dd, k) Next For ee = 0 To UBound(humerus_r, 1) p2(ee + dd + cc + bb + aa, k) = humerus_r(ee, k) Next For ff = 0 To UBound(LV_r, 1) p2(ff + ee + dd + cc + bb + aa, k) = LV_r(ff, k) Next

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283 For gg = 0 To UBound(mandible_r, 1) p2(gg + ff + ee + dd + cc + bb + aa, k) = mandible_r(gg, k) Next For hh = 0 To UBound(pelvis_r, 1) p2(hh + gg + ff + ee + dd + cc + bb + aa, k) = pelvis_r(hh, k) Next For ii = 0 To UBound(rib_r, 1) p2(ii + hh + g g + ff + ee + dd + cc + bb + aa, k) = rib_r(ii, k) Next For jj = 0 To UBound(sacrum_r, 1) p2(jj + ii + hh + gg + ff + ee + dd + cc + bb + aa, k) = sacrum_r(jj, k) Next For kk = 0 To UBound(scapula_r, 1) p2(kk + jj + ii + hh + gg + ff + ee + dd + cc + bb + aa, k) = scapula_r(kk, k) Next ll = 0 If gender <> 3 Then For ll = 0 To UBound(sternum_r, 1) p2(ll + kk + jj + ii + hh + gg + ff + ee + dd + cc + bb + aa, k) = sternum_r(ll, k) Next End If For mm = 0 To UBound(TV_r, 1) p2(mm + ll + kk + jj + ii + hh + gg + ff + ee + dd + cc + bb + aa, k) = TV_r(mm, k) Next For nn = 0 To UBound(femur_upper_r, 1) p2(nn + mm + ll + kk + jj + ii + hh + gg + ff + ee + dd + cc + bb + aa, k) = femur_upper_r(nn, k) Next For oo = 0 To UBound(humerus_upper_r, 1) p2(oo + nn + mm + ll + kk + jj + ii + hh + gg + ff + ee + dd + cc + bb + aa, k) = humerus_upper_r(oo, k) Next Next End If End If Define method of source point selection random or systematic Dim method As Integer

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284 If UBound(p2, 1) = 0 Then selrep: Console.WriteLine ("***** STEP 4: DEFINE SOURCE POINTS *****") Console.WriteLine ("Choose source point selection method Random = 1, Systematic = 2: ") method = Console.ReadLine() Else method = 2 End If Implement source point selection method to determine direction cosines Dim dircos(10000, 2) As Double Dim p1(10000, 2) As Double If method = 1 Then Follow MEVDP/CAMERA method of random ray selection Dim rays As Integer Console.WriteLine ("Specify the number of random rays to be traced:") rays = Console.ReadLine() Dim dircos_0(rays 1, 2) As Double Dim epsilon(rays 1) As Double ReDim dircos(rays 1, 2) ReDim p1(rays 1, 2) Dim raycount As Integer = 0 For raycount = 0 To rays 1 Generate random direction cosines For k = 0 To 2 Randomize() dircos_0(raycount, k) = 1 2 Rnd() Next epsilon(raycount) = Math.Sqrt(dircos_0(raycount, 0) ^ 2 + dircos_0(raycount, 1) ^ 2 + dircos_0(raycount, 2) ^ 2) For k = 0 To 2 dircos(raycount, k) = dircos_0(raycount, k) / epsilon(raycount) Next Next ElseIf method = 2 Then Use NASA direction cosines as determined from CAMERA (defaulted to 512 rays) ReDim dircos(511, 2)

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285 ReDim p1(511, 2) Dim filename3 As String filename3 = "C: \ Documents and Set tings \ Amir Bahadori \ My Documents \ Visual Studio 2008 \ Projects \ Bahadori Ray Trace \ directions.csv" Dim tmpstream As System.IO.StreamReader = My.Computer.FileSystem.OpenTextFileReader(filename3) Dim strlines() As String Dim strline() As String Dim strarray(1, 1) As String Dim num_rows As Integer Dim num_cols As Integer strlines = tmpstream.ReadToEnd().Split(Environment.NewLine) num_rows = UBound(strlines) strline = strlines(0).Split(",") num_cols = UBound(strline) ReDim strarray(num_rows, num_cols) For x = 0 To num_rows strline = strlines(x).Split(",") For y = 0 To num_cols strarray(x, y) = strline(y) Next Next For x = 0 To num_rows For k = 0 To 2 dircos(x, k) = strarray(x, k) Next Next Else Console.WriteLine ("ERROR User must specify random or systematic source point selection method") GoTo selrep End If Loop for all dose points Console.WriteLine ("***** STEP 5: PERFO RM RAY TRACE *****") Dim tracestart As Double = Timer Dim dose As Integer Dim d12(UBound(p1, 1), UBound(p2, 1)) As Double ReDim p2c(UBound(p2, 1), 2)

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286 For dose = 0 To UBound(p2, 1) If p2(dose, 0) < 0 Or p2(dose, 0) > N(0) 2 Or p2(dose, 1) < 0 Or p2(dose, 1) > N(1) 2 Or p2(dose, 2) < 0 Or p2(dose, 2) > N(2) 2 Then Console.WriteLine ("ERROR Dose point must be within voxel array") GoTo doserep End If Calculate coordinates of dose point center of voxel (p2i,p2j,p2k) For k = 0 To 2 p2c(dose, k) = p2(dose, k) d(k) + d(k) / 2 Next Console.WriteLine(" ") Calculate radius of sampling sphere Dim Xp As Double Dim Yp As Double Dim Zp As Double Xp = (N(0) 1) d(0) Yp = (N(1) 1) d(1) Zp = (N(2) 1) d(2) Dim xcorner(7) As Double Dim ycorner(7) As Double Dim zcorner(7) As Double xcorner(0) = Xp xcorner(1) = Xp xcorner(2) = Xp xcorner(3) = Xp xcorner(4) = 0 xcorner(5) = 0 xcorner(6) = 0 xcorner(7) = 0 ycorner(0) = Yp ycorner(1) = Yp ycorner(2) = 0 ycorner(3) = 0 ycorner(4) = Yp ycorner(5) = Yp y corner(6) = 0 ycorner(7) = 0 zcorner(0) = Zp zcorner(1) = 0 zcorner(2) = Zp zcorner(3) = 0 zcorner(4) = Zp zcorner(5) = 0

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287 zcorner(6) = Zp zcorner(7) = 0 Dim dist(7) As Double Dim radius As Double Dim count As Integer = 0 For c = 0 To 7 dist(c) = Math.Sqrt((p2c(dose, 0) xcorner(c)) ^ 2 + (p2c(dose, 1) ycorner(c) ) ^ 2 + (p2c(dose, 2) zcorner(c)) ^ 2) Next radius = Math.Max(dist(0), Math.Max(dist(1), Math.Max(dist(2), Math.Max(dist(3), Math.Max(dist(4), Math.Max(dist(5), Math.Max(dist(6), dist(7)))))))) radius = radius + 1.0 Console.WriteLine(radius) Calculate corresponding source points Dim counter As Integer For counter = 0 To UBound(dircos, 1) For k = 0 To 2 p1(counter, k) = radius dir cos(counter, k) + p2c(dose, k) Next Next Console.WriteLine(" ") Loop for each source point Dim src As Integer = 0 For src = 0 To UBound(d12) Initialize radiological path length to be zero d12(src, dose) = 0 'Ensure that division by zero does not occur For k = 0 To 2 If p1(src, k) = p2c(dose, k) Then p1(src, k) = p2c(dose, k) + 0.000001 End If Next 'Define plane numbers around source and dose points Dim F1(3) As Integer Dim F2(3) As Integer Dim C1(3) As Integer Dim C2(3) As Integer

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288 For k = 0 To 2 F1(k) = Math.Floor(p1(src, k) / d(k)) F2(k) = Math.Floor(p2c(dose, k) / d(k)) C1(k) = Math.Ceiling(p 1(src, k) / d(k)) C2(k) = Math.Ceiling(p2c(dose, k) / d(k)) Next Determine bounds of set of intersected planes and corresponding parametric values Dim P_first(2) As Integer Dim a_first(2) As Double Dim P_last(2) As Integer Dim a_last(2) As Double For k = 0 To 2 If p1(src, k) > p2c(dose, k) Then If F1(k) >= C2(k) Then P_first(k) = Math.Min(N(k) 1, F1(k)) P_last(k) = C2(k) a_first(k) = (P_first(k) d(k) p1(src, k)) / (p2c(dose, k) p1(src, k)) a_last(k) = (P_last(k) d(k) p1(src, k)) / (p2c(dose, k) p1(src, k)) Else No k planes are intersected P_first(k) = 0 P_last(k) = 0 a_first(k) = 0 a_last(k) = 0 End If Else If F2(k) >= C1(k) Then P_first(k) = Math.Max(0, C1(k)) P_last(k) = F2(k) a_first(k) = (P_first(k) d(k) p1(src, k)) / (p2c(dose, k) p1(src, k)) a_last(k) = (P_last(k) d(k) p1(src, k)) / (p2c(dose, k) p1(src, k)) Else No k planes are intersec ted P_first(k) = 0 P_last(k) = 0 a_first(k) = 0 a_last(k) = 0 End If End If Next Determine parametric value at entrance to voxel world Dim a_first_min(2) As Double For k = 0 To 2 If P_first(k) > 0 And P_first(k) < N(k) 1 Then a_first_min(k ) = 0

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289 Else a_first_min(k) = a_first(k) End If Next Dim a_min As Double a_min = Math.Max(a_first_min(0), Math.Max(a_first_min(1), a_first_min(2 ))) Determine coordinates of first entrance to voxel world Dim x_first(2) As Double For k = 0 To 2 x_first(k) = p1(src, k) + a_min (p2c(dose, k) p1(src, k)) Next Dim i_first(2) As Integer For k = 0 To 2 If p1(src, k) > p2c(dose, k) Then If a_min = a_first(k) Then i_first(k) = x_first(k) / d(k) 1 Else i_first(k) = Math.Floor(x_first(k) / d(k)) End If Else If a_min = a_first(k) Then i_first(k) = x_first(k) / d(k) Else i_first(k) = Math.Floor(x_first(k) / d(k)) End If End If Next Calculate raysum Dim d_a(2) As Double For k = 0 To 2 d_a(k) = Math.Abs(d(k) / (p1(src, k) p2c(dose, k))) Next Dim F_first(2) As Integer Dim C_first(2) As Integer Dim a_next(2) As Double Dim P_next(2) As Integer Dim a_store As Double Dim x_next(2) As Double Dim i_next(2) As Double

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290 Iterate until you reach the voxel containing the dose point Do For k = 0 To 2 F_first(k) = Math.Floor(x_first(k) / d(k)) C_first(k) = Math.Ceiling(x_first(k) / d(k)) Next For k = 0 To 2 If a_min = a_first(k) Then a_next(k) = a_min + d_a(k) Else If p1(src, k) > p2c(dose, k) Then P_next(k) = F_first(k) Else P_next(k) = C_first(k) End If a_next(k) = (P_next(k) d(k) p1(src, k)) / (p2c(dose, k) p1(src, k)) End If Next a_store = a_min a_min = Math.Min(a_next(0), Math.Min(a_next(1), a_next(2))) tagnum = tag3D(i_first(0), i_first(1), i_first(2)) If gender = 1 Then Use male densities (ICRP 89 or calculated from UFHADM) Convert rho as a function of organ tag to rho as a function of density in g/cm^3 Also record range for 50 MeV protons in material for aluminum conversion in g/cm^2 If tagnum = 0 Then rho = 0 range = 1 ElseIf tagnum = 1 Then rho = 1.03 Residual soft tissue range = 2.1949 '' Average soft tissue ElseIf tagnum = 2 Then rho = 1.03 Adrenal (L) range = 2.1949 '' Average soft tissue ElseIf tagnum = 3 Then rho = 1.03 Adrenal (R) range = 2.1949 '' Average soft tissue ElseIf tagnum = 4 Then rho = 1.04 Brain range = 2.1965 '' Brain

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291 ElseIf tagnum = 5 Then rho = 0.94 Breast r ange = 2.1581 '' Breast ElseIf tagnum = 6 Then rho = 1.065 Bronchi range = 0.5 (2.1949 + 2.2363) '' 50% average soft tissue, 50% cartilage (linear interpolation) ElseIf tagnum = 7 Then rho = 1.03 Right colon wall range = 2.3021 '' GI tract ElseIf tagnum = 8 Then rho = 1.03 Right colon contents range = 2.1949 '' Average soft tissue ElseIf tagnum = 9 Then rho = 1.1 Ears range = 2.2363 '' Cartilage ElseIf tagnum = 10 Then rho = 1.03 Esophagus range = 2.3021 '' GI tract ElseIf tagnum = 11 Then rho = 1.05 External nose range = 2 / 3 2.1949 + 1 / 3 2.2363 '' 67% average soft tissue, 33% cartilage (linear interpolation) ElseIf tagnum = 12 Then rho = 1.03 Eyeballs range = 2.1949 '' Average soft tissue ElseIf tagnum = 13 Then rho = 1.03 Gall bladder wall range = 2.1949 '' Average soft tissue ElseIf tagnum = 14 Then rho = 1.03 Gall bladder contents range = 2.1949 '' Average soft tissue ElseIf tagnum = 15 Then rho = 1.05 Heart wall range = 2.204 '' Heart ElseIf tagnum = 16 Then rho = 1.06 Heart contents range = 2.2112 '' Blood ElseIf tagnum = 17 Then rho = 1.05 Kidney cortex (L) range = 2.2071 '' Kidney ElseIf tagnum = 18 Then

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292 rho = 1.05 Kidney cortex (R) range = 2.2071 '' Kidney ElseIf tagnum = 19 Then rho = 1.05 Kidney medulla (L) range = 2.2071 '' Kidney ElseIf tagnum = 20 Then rho = 1.05 Kidney medulla (R) range = 2.2071 '' Kidney ElseIf tagnum = 21 Then rho = 1.05 Kidney pelvis (L) range = 2.2071 '' Kidney ElseIf tagnum = 22 Then rho = 1.05 Kidney pelvis (R) range = 2.2071 '' Kidney ElseIf tagnum = 23 Then rho = 1.065 Larynx range = 0.5 (2.1949 + 2.2363) '' 50% average soft tissue, 50% cartilage (linear interpolation) ElseIf tagnum = 24 Then rho = 1.07 Lens range = 2.2213 '' Eye lens ElseIf tagnum = 25 Then rho = 1.06 Liver range = 2.2112 '' Liver ElseIf tagnum = 26 Then rho = 0.335 Lung (L) range = 2.2092 '' Lung ElseIf tagnum = 27 Then rho = 0.335 Lung (R) range = 2.2092 '' Lung ElseIf tagnum = 28 Then rho = 1 .03 Nasal layer (A) range = 2.1949 '' Average soft tissue ElseIf tagnum = 29 Then rho = 1.03 Nasal layer (P) ra nge = 2.1949 '' Average soft tissue ElseIf tagnum = 30 Then rho = 1.03 Oral cavity layer range = 2.1949 '' Average soft tissue ElseIf tagnum = 31 Then rho = 0 ## EMPTY TAG ## range = 2.1949 '' Average soft tissue

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293 ElseIf tagnum = 32 Then rho = 1.03 Pancreas range = 2.1966 '' Pancreas ElseIf tagnum = 33 Then rho = 1.05 Penis range = 2.2103 '' Muscle ElseIf tagnum = 34 Then rho = 1.03 Pharynx range = 2.1949 '' Average soft tissue ElseIf tagnum = 35 Then rho = 1.03 Pituitary range = 2.1949 '' Average soft tissue ElseIf tagnum = 36 Then rho = 1.03 Prostate range = 2.1949 '' Average soft tissue ElseIf tagnum = 37 Then rho = 1.03 Rectosigmoid wall range = 2.1991 '' GI tract ElseIf tagnum = 38 Then rho = 0.971 Rectosigmoid contents range = 2.1949 '' Average soft tissue ElseIf tagnum = 39 Then rho = 1.03 Salivary glands (parotid) range = 2.1949 '' Average soft tissue ElseIf tagnum = 40 Then rho = 1.03 Scrotum range = 2.1949 '' Average soft tissue ElseIf tagnum = 41 Then rho = 1.03 Small intestines wall range = 2.1991 '' GI tract ElseIf tagnum = 42 Then rho = 0.44 Small intestines contents range = 2.1949 '' Avera ge soft tissue ElseIf tagnum = 43 Then rho = 1.1 Skin range = 2.211 '' Skin ElseIf tagnum = 44 Then rho = 1.04 Spinal cord range = 2.1965 '' Brain ElseIf tagnum = 45 Then rho = 1.06 Spleen

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294 range = 2.209 '' Spleen ElseIf tagnum = 46 Then rho = 1.03 Stomach wall range = 2.1991 '' GI tract ElseIf tagnum = 47 Then rho = 1.03 Stomach contents range = 2.1949 '' Average soft tissue ElseIf tagnum = 48 Then rho = 1.04 Testes range = 2.2017 '' Testes ElseIf tagnum = 49 Then rho = 1.03 Thymus range = 2.1949 '' Average soft tissue ElseIf tagnum = 50 Then rho = 1.05 Thyroid range = 2.205 '' Thyroid ElseIf tagnum = 51 Then rho = 1.05 Tongue range = 2.2103 '' Muscle ElseIf tagnum = 52 Then rho = 1.03 Tonsil range = 2.1949 '' Average soft tissue ElseIf tagnum = 53 Then rho = 1.07 Trachea range = 0.5 (2.1949 + 2.2363) '' 50% average soft tissue, 50% cartilage (linear interpolation) ElseIf tagnum = 54 Then rho = 1.04 Urinary bladder wall range = 2.2048 '' Urinary bladder ElseIf tagnum = 55 Then rho = 1.01 Urinary bladder contents range = 2.189 '' Water ElseIf tagnum = 56 Then rho = 0 ## EMPTY TAG ## range = 0 ElseIf tagnum = 57 Then rho = 0.00120484 Air range = 2.5374 '' ICRU Dry Air ElseIf tagnum = 5 8 Then rho = 1.03 Left colon wall range = 2.1991 '' GI tract

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295 ElseIf tagnum = 59 Then rho = 0.663 Left colon co ntents range = 2.1949 '' Average soft tissue ElseIf tagnum = 60 Then rho = 1.03 Salivary glands (submaxillary) range = 2.19 49 '' Average soft tissue ElseIf tagnum = 61 Then rho = 1.03 Salivary glands (sublingual) range = 2.1949 '' Average soft tissue ElseIf tagnum = 128 Then rho = 1.1 Costal cartilage (ribs) range = 2.2363 '' Cartilage ElseIf tagnum = 129 Then rho = 1.1 Cervical discs range = 2.2363 '' Cartilage ElseIf tagnum = 130 Then rho = 1.1 Thoracic discs range = 2.2363 '' Cartilage ElseIf tagnum = 131 Then rho = 1.1 Lumbar discs range = 2.2363 '' Cartilage ElseIf tagnum >= 151 And tagnum <= 188 Then rho = 1.9 Cortical bone (all bone sites) range = 2.5042 '' ICRP Cortical Bone ElseIf tagnum = 189 Then rho = 3.0 Teeth range = 2.595 '' Teeth ElseIf tagnum = 201 Then rho = 1.36 Cranium spongiosa range = 2.3299 '' ElseIf tagnum = 202 Then rho = 1.08 Mandible spongiosa range = 2.2 '' ElseIf tagnum = 207 Then rho = 1.17 Cervical vertebra spongiosa range = 2.2547 '' ElseIf tagnum = 208 Then rho = 1.1 Thoracic vertebra spongiosa range = 2.2127 ''

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296 ElseIf tagnum = 209 Then rho = 1.1 Lumbar vertebra spongiosa ran ge = 2.2337 '' ElseIf tagnum = 205 Then rho = 1.09 Sternum spongiosa range = 2.2052 '' ElseIf tagnum = 206 Then rho = 1.11 Rib spongiosa range = 2.2366 '' ElseIf tagnum = 203 Then rho = 1.13 Scapula spongiosa range = 2.2433 '' ElseIf tagnum = 204 Then rho = 1.1 Clavicle spongiosa range = 2.2152 '' ElseIf tagnum = 211 Then rho = 1.09 Os coxa spongiosa range = 2.2175 '' ElseIf tagnum = 210 Then rh o = 1.12 Sacrum spongiosa range = 2.2242 '' ElseIf tagnum = 224 Then rho = 1.08 Proximal humerus spongiosa rang e = 2.2016 '' ElseIf tagnum = 225 Then rho = 0.99 Upper shaft humerus (medullary) range = 2.1621 '' ElseIf tagnu m = 226 Then rho = 0.98 Lower shaft humerus (medullary) range = 2.1485 '' ElseIf tagnum = 227 Then rho = 1.12 Distal humerus spongiosa range = 2.2174 '' ElseIf tagnum = 228 Then rho = 1.06 Proximal radius spongiosa range = 2.1621 '' ElseIf tagnum = 229 Then rho = 0.98 Shaft radius (medullary) range = 2.1485 '' ElseIf tagnum = 230 Then rho = 1.08 Distal radius spongiosa

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297 range = 2.2176 '' ElseIf tagnum = 231 Then rho = 1 .13 Proximal ulna spongiosa range = 2.2202 '' ElseIf tagnum = 232 Then rho = 0.98 Shaft ulna (medullary) rang e = 2.1485 '' ElseIf tagnum = 233 Then rho = 1.11 Distal ulna spongiosa range = 2.21 '' ElseIf tagnum = 234 Then rho = 1.12 Wrist and hand range = 2.2174 '' ElseIf tagnum = 212 Then rho = 1.13 Proximal femur spongiosa range = 2.2227 '' ElseIf tagnum = 213 Then rho = 0.99 Upper shaft femur (medullary) range = 2.1621 '' ElseIf tagnum = 214 Then rho = 0.98 Lower shaft femur (medullary) range = 2.1485 '' ElseIf tagnum = 215 Then rho = 1.11 Distal femur spongiosa range = 2.2262 '' ElseIf tagnum = 222 Then rho = 1.11 Patella range = 2 .2262 '' ElseIf tagnum = 216 Then rho = 1.08 Proximal tibia spongiosa range = 2.2156 '' ElseIf tagnum = 217 Then rho = 0.98 Shaft tibia (medullary) range = 2.1485 '' ElseIf tagnum = 218 Then rho = 1.09 Distal tibia spongios a range = 2.2189 '' ElseIf tagnum = 219 Then rho = 1.05 Proximal fibula spongiosa range = 2.1895 '' ElseIf tagnum = 220 Then

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298 rho = 0.98 Shaft fibula (medullary) range = 2.1485 '' ElseIf tagnum = 221 Then rho = 1.11 Distal fibula spongiosa range = 2.2278 '' ElseIf tagnum = 223 Then rho = 1.11 Ankle and foot range = 2.2262 '' End If range_Al = 2.9047 range_H2O = 2.189 ElseIf gender = 5 Then Use micro gravity bone densities (all other densities are the s ame) If tagnum = 0 Then rho = 0 range = 1 ElseIf tagnum = 1 Then rho = 1.03 Residual soft tissue range = 2.1949 '' Average soft tissue ElseIf tagnum = 2 Then rho = 1.03 Adrenal (L) range = 2.1949 '' Average s oft tissue ElseIf tagnum = 3 Then rho = 1.03 Adrenal (R) range = 2.1949 '' Average soft tissue ElseIf tagnum = 4 Then rho = 1.04 Brain range = 2.1965 '' Brain ElseIf tagnum = 5 Then rho = 0.94 Breast range = 2 .1581 '' Breast ElseIf tagnum = 6 Then rho = 1.065 Bronchi range = 0.5 (2.1949 + 2.2363) '' 50% average soft tissue, 50% cartilage (linear interpolation) ElseIf tagnum = 7 Then rho = 1.03 Right colon wall range = 2.3021 '' GI tract ElseIf tagnum = 8 Then rho = 1.03 Right colon contents range = 2.1949 '' Average soft tissue

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299 ElseIf tagnum = 9 Then rho = 1.1 Ears range = 2.2363 '' Cartilage ElseIf tagnum = 10 Then rho = 1.03 Esophagus range = 2.3021 '' GI tract ElseIf tagnum = 11 Then rho = 1.05 External nose range = 2 / 3 2.1949 + 1 / 3 2.2363 '' 67% average soft tissue, 33% cartilage (linear interpolation) ElseIf tagnum = 12 Then rho = 1.03 Eyeballs range = 2.1949 '' Average soft tissue ElseIf tagnum = 13 Then rho = 1.03 Gall bladder wall range = 2.1949 '' Average soft tissue ElseIf tagnum = 14 Then rho = 1.03 Gall bladder contents range = 2.1949 '' Average soft tissue ElseIf tagnum = 15 Then rho = 1.05 Heart wall range = 2.204 '' Heart ElseIf tagnum = 16 Then rho = 1.06 Heart contents range = 2.2112 '' Blood ElseIf tagnum = 17 Then r ho = 1.05 Kidney cortex (L) range = 2.2071 '' Kidney ElseIf tagnum = 18 Then rho = 1.05 Kidney cortex (R) range = 2.2071 '' Kidney ElseIf tagnum = 19 Then rho = 1.05 Kidney medulla (L) range = 2.2071 '' Kidney ElseIf tagnum = 20 Then rho = 1.05 Kidney medulla (R) range = 2.2071 '' Kidney ElseIf tagnum = 21 Then rho = 1.05 Kidney pelvi s (L) range = 2.2071 '' Kidney ElseIf tagnum = 22 Then

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300 rho = 1.05 Kidney pelvis (R) range = 2.2071 '' Kidney ElseIf tagnum = 23 Then rho = 1.065 Larynx range = 0.5 (2.1949 + 2.2363) '' 50% average soft tissue, 50% cartilage (linear interpolation) ElseIf tagnum = 24 Then rho = 1.07 Lens range = 2.2213 '' Eye lens ElseIf tagnum = 25 Then rho = 1.06 Liver range = 2.2112 '' Liver ElseIf tagnum = 26 Then rho = 0.335 Lung (L) range = 2.2092 '' Lung ElseIf tagnum = 27 Then rho = 0.335 Lung (R) range = 2.2092 '' Lung ElseIf tagnum = 28 Then rho = 1.03 N asal layer (A) range = 2.1949 '' Average soft tissue ElseIf tagnum = 29 Then rho = 1.03 Nasal layer (P) range = 2.1949 '' Average soft tissue ElseIf tagnum = 30 Then rho = 1.03 Oral cavity layer range = 2.1949 '' Average soft tissue ElseIf tagnum = 31 Then rho = 0 ## EMPTY TAG ## range = 2.1949 '' Average soft tissue ElseIf tagnum = 32 Then rho = 1.03 Pancreas range = 2.1966 '' Pancreas ElseIf tagnum = 33 Then rho = 1.05 Penis range = 2 .2103 '' Muscle ElseIf tagnum = 34 Then rho = 1.03 Pharynx range = 2.1949 '' Average soft tissue ElseIf tagnum = 3 5 Then rho = 1.03 Pituitary range = 2.1949 '' Average soft tissue

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301 ElseIf tagnum = 36 Then rho = 1.03 Prostate range = 2.1949 '' Average soft tissue ElseIf tagnum = 37 Then rho = 1.03 Rectosigmoid wall range = 2.1991 '' GI tract ElseIf tagnum = 38 Then rho = 0.971 Rectosigmoid contents range = 2.1949 '' Average soft tissue ElseIf tagnum = 39 Then rho = 1.03 Salivary glands (parotid) range = 2.1949 '' Average soft tissue ElseIf tagnum = 40 Then rho = 1.03 Scrotum range = 2.1949 '' Average soft tissue ElseIf tagnum = 41 Then rho = 1.03 Small inte stines wall range = 2.1991 '' GI tract ElseIf tagnum = 42 Then rho = 0.44 Small intestines contents range = 2.1949 '' Average soft tissue ElseIf tagnum = 43 Then rho = 1.1 Skin range = 2.211 '' Skin ElseIf tagnum = 44 Then rho = 1.04 Spinal cord range = 2.1965 '' Brain ElseIf tagnum = 45 Then rho = 1.06 Spleen range = 2.209 '' Spleen ElseIf tagnum = 46 Then rho = 1.03 Stomach wall range = 2.1991 '' GI tract ElseIf tagnum = 47 Then rho = 1.03 Stomach contents range = 2.1949 '' Average soft tissue ElseIf tagnum = 48 Then rho = 1.04 Testes range = 2.2017 '' Testes ElseIf tagnum = 49 Then rho = 1.03 Thymus

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302 range = 2.1949 '' Average soft tissue ElseIf tagnum = 50 Then rho = 1.05 Thyroid range = 2.205 '' Thyroid ElseIf tagnum = 51 Then rho = 1.05 Tongue range = 2.2103 '' Muscle ElseIf tagnum = 52 Then rho = 1.03 Tonsil range = 2.1949 '' Average soft tissue ElseIf tagnum = 53 Then rho = 1.07 Trachea range = 0.5 (2.1949 + 2.2363) '' 50% average soft tissue, 50% cartilage (linear interpolation) ElseIf tagnum = 54 Then rho = 1.04 Urinary bladder wall range = 2.2048 '' Urinary bladder ElseIf tagnum = 55 Then rho = 1.01 Urinary bladder contents range = 2.189 '' Water ElseIf tagnum = 56 Then rho = 0 ## EMPTY TAG ## range = 0 ElseIf tagnum = 57 Then rho = 0.00120484 Air range = 2.5374 '' ICRU Dry A ir ElseIf tagnum = 58 Then rho = 1.03 Left colon wall range = 2.1991 '' GI tract ElseIf tagnum = 59 Then rho = 0.663 Left colon contents range = 2.1949 '' Average soft tissue ElseIf tagnum = 60 Then rho = 1.03 Saliva ry glands (submaxillary) range = 2.1949 '' Average soft tissue ElseIf tagnum = 61 Then rho = 1.03 Salivary glands (sublingual) range = 2.1949 '' Average soft tissue ElseIf tagnum = 128 Then rho = 1.1 Costal cartilage (ribs)

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303 range = 2.2363 '' Cartilage ElseIf tagnum = 129 Then rho = 1.1 Cervical discs range = 2.2363 '' Cartilage ElseIf tagnum = 130 Then rh o = 1.1 Thoracic discs range = 2.2363 '' Cartilage ElseIf tagnum = 131 Then rho = 1.1 Lumbar discs range = 2. 2363 '' Cartilage ElseIf tagnum >= 151 And tagnum <= 188 Then rho = 1.9 Cortical bone (all bone sites) range = 2.5042 '' ICRP Cortical Bone ElseIf tagnum = 189 Then rho = 3.0 Teeth range = 2.595 '' Teeth ElseIf tagnum = 201 Then rho = 1.36 Cranium spongiosa range = 2.3299 '' ElseIf tagnum = 202 Then rho = 1. 08 Mandible spongiosa range = 2.2 '' ElseIf tagnum = 207 Then rho = 1.14 Cervical vertebra spongiosa range = 2.2547 '' ElseIf tagnum = 208 Then rho = 1.08 Thoracic vertebra spongiosa range = 2.2127 '' ElseIf tagnum = 209 Then rho = 1.09 Lumbar vertebra spongiosa range = 2.2337 '' ElseIf tagnum = 205 Then rho = 1.09 Sternum spongiosa range = 2.2052 '' ElseIf tagnum = 206 Then rho = 1.11 Rib spongiosa range = 2.2366 '' ElseIf tagnum = 203 Then rho = 1.13 Scapula spongiosa range = 2.2433 ''

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30 4 ElseIf tag num = 204 Then rho = 1.1 Clavicle spongiosa range = 2.2152 '' ElseIf tagnum = 211 Then rho = 1.07 Os coxa spon giosa range = 2.2175 '' ElseIf tagnum = 210 Then rho = 1.09 Sacrum spongiosa range = 2.2242 '' ElseIf tagnum = 224 Then rho = 1.08 Proximal humerus spongiosa range = 2.2016 '' ElseIf tagnum = 225 Then rho = 0.99 Upper shaft humerus (medullary) range = 2.1621 '' ElseIf tagnum = 226 Then rho = 0.98 Lower shaft humerus (medullary) range = 2.1485 '' ElseIf tagnum = 227 Then rho = 1.12 Distal humerus spongiosa range = 2.2174 '' ElseIf tagnum = 228 Then rho = 1.06 Proximal radius spongiosa range = 2.1621 '' ElseIf tagnum = 229 Then rho = 0.98 Shaft radius (medullary) range = 2.1485 '' ElseIf tagnum = 230 Then rho = 1.08 Distal radius spongiosa range = 2.2176 '' ElseIf tagnum = 231 Then rho = 1.13 Proximal ulna spongiosa range = 2.2202 '' ElseIf tagnum = 232 Then rho = 0.98 Shaft ulna (medullary) range = 2.1485 '' ElseIf tagnum = 233 Then rho = 1.11 Distal ulna spongiosa range = 2.21 '' ElseIf tagnum = 234 Then rho = 1.12 Wrist and hand

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305 rang e = 2.2174 '' ElseIf tagnum = 212 Then rho = 1.1 Proximal femur spongiosa range = 2.2227 '' ElseIf tagnum = 213 Th en rho = 0.98 Upper shaft femur (medullary) range = 2.1621 '' ElseIf tagnum = 214 Then rho = 0.98 Lower shaft femur (medullary) range = 2.1485 '' ElseIf tagnum = 215 Then rho = 1.11 Distal femur spongiosa range = 2.2262 '' ElseIf tagnum = 222 Then rho = 1.11 Patella range = 2.2262 '' ElseIf tagnum = 216 Then rho = 1.08 Proximal tibia spongiosa range = 2.2156 '' ElseIf tagnum = 217 Then rho = 0.98 Shaft tibia (medull ary) range = 2.1485 '' ElseIf tagnum = 218 Then rho = 1.09 Distal tibia spongiosa range = 2.2189 '' ElseIf tagnum = 219 Then rho = 1.05 Proximal fibula spongiosa range = 2.1895 '' ElseIf tagnum = 220 Then rho = 0.98 Shaft fibula (medullary) range = 2.1485 '' ElseIf tagnum = 221 Then rho = 1.11 Distal fibula spongiosa range = 2.2278 '' ElseIf tagnum = 223 Then rho = 1.11 Ankle and foot range = 2.2262 '' End If range_Al = 2.9047 range_H2O = 2.189

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306 ElseIf gender = 2 Then Use CAM densities shoe horned into UFHADM Convert rho as a function of organ tag to rho as a functi on of density in g/cm^3 Also record range for 50 MeV protons in material for aluminum conversion in g/cm^2 If tagnum = 0 Then rho = 0 range = 1 End If If tagnum = 1 Then rho = 1.03 Residual soft tissue range = 2 / (1.287 + 1.262) '' Average soft tissue ElseIf tagnum = 2 Then rho = 1.03 Adrenal (L) range = 2 / (1.287 + 1.262) '' Average soft tissue ElseIf tagnum = 3 Then rho = 1.03 Adrenal (R) range = 2 / (1.287 + 1.262) '' Average soft tissue ElseIf tagnum = 4 Then rho = 1.058 Brain range = 1.281 ^ 1 '' Organ ElseIf tagnum = 5 Then rho = 1.03 Breast range = 2 / (1.287 + 1.262) '' Average soft tissue ElseIf tagnum = 6 Then rho = 1.03 Bronchi range = 2 / (1.287 + 1.262) '' Average soft tissue ElseIf tagnum = 7 Then rho = 0.451 Right colon wall range = 1.281 ^ 1 '' Intestine ElseIf tagnum = 8 Then rho = 0.451 Right colon contents range = 1.281 ^ 1 '' Intestine ElseIf tagnum = 9 Then rho = 1.03 Ears range = 2 / (1.287 + 1.262) '' Average soft tissue ElseIf tagnum = 10 Then rho = 1.03 Esophagus range = 2 / (1.287 + 1.262) '' Average soft tissue ElseIf tagnum = 11 Then

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307 rho = 1.03 External nose range = 2 / (1.287 + 1.262) '' Average soft tissue ElseIf tagnum = 12 Then rho = 1.058 Eyeballs range = 1.281 ^ 1 '' Organ ElseIf tagnum = 13 Then rho = 1.058 Gall bladder wall range = 1.281 ^ 1 '' Organ ElseIf tagnum = 14 Then rho = 1.058 Gall bladder contents range = 1.281 ^ 1 '' Organ ElseIf tagnum = 15 Then rho = 1.058 Heart wall range = 1.281 ^ 1 '' Organ ElseIf tagnum = 16 Then rho = 1.058 Heart contents range = 1.281 ^ 1 '' Organ ElseIf tagnum = 17 Then rho = 1.058 Kidney cortex (L) range = 1.281 ^ 1 '' Organ ElseIf tagnum = 18 Then rho = 1.058 Kidney cortex (R) range = 1.281 ^ 1 '' Organ ElseIf tagnum = 19 Then rho = 1.058 Kidney medulla (L) range = 1.281 ^ 1 '' Organ ElseIf tagnum = 20 Then rho = 1.058 Kidney medulla ( R) range = 1.281 ^ 1 '' Organ ElseIf tagnum = 21 Then rho = 1.058 Kidney pelvis (L) range = 1.281 ^ 1 '' Orga n ElseIf tagnum = 22 Then rho = 1.058 Kidney pelvis (R) range = 1.281 ^ 1 '' Organ ElseIf tagnum = 23 Then rho = 1.03 LaryN(0) range = 2 / (1.287 + 1.262) '' Average soft tissue ElseIf tagnum = 24 Then rho = 1.058 Lens range = 1.281 ^ 1 '' Organ

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308 ElseIf tagnum = 25 Then rho = 1.058 Liver range = 1.281 ^ 1 '' Organ ElseIf tagnum = 26 Then rho = 0.257 Lung (L) range = 1.281 ^ 1 '' Lung ElseIf tagnum = 27 Then rho = 0.33 Lung (R) range = 1.281 ^ 1 '' Lung ElseIf tagnum = 28 Then rho = 1.03 Nasal layer (A) range = 2 / (1.2 87 + 1.262) '' Average soft tissue ElseIf tagnum = 29 Then rho = 1.03 Nasal layer (P) range = 2 / (1.287 + 1.262) '' Average soft tissue ElseIf tagnum = 30 Then rho = 1.03 Oral cavity layer range = 2 / (1.287 + 1.262) '' Average soft tissue ElseIf tagnum = 31 Then rho = 0 ## EMPTY TAG ## range = 2 / (1.287 + 1.262) '' Average soft tissue ElseIf tagnum = 32 Then rho = 1.058 Pancreas range = 1.281 ^ 1 '' Organ ElseIf tagnum = 33 Then rho = 1.058 Penis range = 1.281 ^ 1 '' Organ ElseIf tagnum = 34 Then rho = 1.03 PharyN(0) range = 2 / (1.287 + 1.262) '' Average soft tissue ElseIf tagnum = 35 Then rho = 1.03 Pituitary range = 2 / (1.287 + 1.262) '' Average soft tissue ElseIf tagnum = 36 Then rho = 1.03 Prostate range = 2 / (1.287 + 1.262) '' Average soft tissue ElseIf tagnum = 37 Then rho = 0.451 Rectosigmoid wall range = 1.281 ^ 1 '' Intestine ElseIf tagnum = 38 Then rho = 0.451 Rectosigmoid contents range = 1.281 ^ 1 '' Intestine

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309 ElseIf tagnum = 39 Then rho = 1.03 Salivary glands (parotid) range = 2 / (1.287 + 1.262) '' Average soft tissue ElseIf tagnum = 40 Then rho = 1.03 Scrotum range = 2 / (1.287 + 1.262) '' Average soft tissue ElseIf tagnum = 41 Then rho = 0.451 Small intestines wall range = 1.281 ^ 1 '' Intestine ElseIf tagnum = 42 Then rho = 0.451 Small intestines contents range = 1.281 ^ 1 '' Intestine ElseIf tagn um = 43 Then rho = 1.03 Skin range = 2 / (1.287 + 1.262) '' Average soft tissue ElseIf tagnum = 44 Then rho = 1.058 Spi nal cord range = 1.281 ^ 1 '' Organ ElseIf tagnum = 45 Then rho = 1.058 Spleen range = 1.281 ^ 1 '' Organ ElseIf tagnum = 46 Then rho = 1.058 Stomach wall range = 1.281 ^ 1 '' Organ ElseIf tagnum = 47 Then rho = 1.058 Stomach contents range = 1.281 ^ 1 '' Organ ElseIf tagnum = 48 Then rho = 1.058 Testes range = 1.281 ^ 1 '' Organ ElseIf tagnum = 49 Then rho = 1.03 Thymus range = 2 / (1.287 + 1.262) '' Average soft tissue ElseIf tagnum = 50 Then rho = 1.058 Thyroid range = 1.281 ^ 1 '' Organ ElseIf tagnum = 51 Then rho = 1.06 Tongue range = 1.287 ^ 1 '' Muscle ElseIf tagnum = 52 Then rho = 1.03 Tonsil

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310 range = 2 / (1.287 + 1.262) '' Average soft tissue ElseIf tagnum = 53 Then rho = 1.03 Trachea range = 2 / (1.287 + 1.262) '' Average soft tissue ElseIf tagnum = 54 Th en rho = 1.058 Urinary bladder wall range = 1.281 ^ 1 '' Organ ElseIf tagnum = 55 Then rho = 1.058 Urinary bladder contents range = 1.281 ^ 1 '' Organ ElseIf tagnum = 56 Then rho = 0 ## EMPTY TA G ## range = 0 ElseIf tagnum = 57 Then rho = 0.00120484 Air range = 1.136 ^ 1 '' ICRU Dry Air ElseIf t agnum = 58 Then rho = 0.451 Left colon wall range = 1.281 ^ 1 '' Intestine ElseIf tagnum = 59 Then rho = 0.451 Left colon contents range = 1.281 ^ 1 '' Intestine ElseIf tagnum = 60 Then rho = 1.03 Salivary glands (submaxillary) rang e = 2 / (1.287 + 1.262) '' Average soft tissue ElseIf tagnum = 61 Then rho = 1.03 Salivary glands (sublingual) range = 2 / (1.287 + 1.262) '' Average soft tissue ElseIf tagnum = 128 Then rho = 1.03 Costal cartilage (ribs) range = 2 / (1.287 + 1.262) '' Average soft tissue ElseIf tagnum = 129 Then rho = 1.03 Cervical discs range = 2 / (1.287 + 1.262) '' Average soft tissue ElseIf tagnum = 130 Then rho = 1.03 Thoracic discs range = 2 / (1.287 + 1.262) '' Average soft tissue ElseIf tagnum = 131 Then r ho = 1.03 Lumbar discs range = 2 / (1.287 + 1.262) '' Average soft tissue

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311 ElseIf tagnum >= 151 And tagnum <= 188 Then rho = 1.75 Cortical bone (a ll bone sites) range = 1.202 ^ 1 '' Bone ElseIf tagnum = 189 Then rho = 1.75 Teeth range = 1.202 ^ 1 '' Bone ElseIf tagnum >= 201 And tagnum <= 234 Then rho = 1.499 Spongiosa (all bone sites) range = 1.247 ^ 1 '' Skeleton End If range_Al = 1.0 range_H2O = 1.299 ^ 1 ElseIf gender = 3 Then Use CAM/CAF densities and organ tags If tagnum = 1 Or tagnum = 11 Or tagnum = 21 Or tagnum = 0 Then rho = 0 Void range = 1 ElseIf tagnum = 2 Then rho = 0.257 Lung range = 1.281 ^ 1 ElseIf tagnum = 3 Or tagnum = 13 Or tagnum = 23 Or tagnum = 33 Or tagnum = 43 Or tagnum = 53 Or tagnum = 63 Or tagnum = 73 Or tagnum = 83 Or tagnum = 93 Or tagnum = 103 Or tagnum = 113 Then rho = 1.058 Organ range = 1.281 ^ 1 ElseIf tagnum = 4 Then rho = 0.451 Intestine range = 1.281 ^ 1 ElseIf tagnum = 5 Then rho = 1.06 Muscle range = 1.287 ^ 1 ElseIf tagnum = 6 Then rho = 1.75 Bone range = 1.202 ^ 1 ElseIf tagnum = 7 Or tagnum = 17 Then rho = 0.918 Marrow (fat) range = 1.348 ^ 1 ElseIf tagnum = 8 Or tagnum = 18 Or tagnum = 207 Or tagnum = 209 Or tagnum = 213 Or tagnum = 215 Or tagnum = 212 Or tagnum = 239 Or tagnum = 14 Or tagnum = 214 Or tagnum = 211 Or tagnum = 19 Or tagnum = 210 Or tagnum = 208 Then

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312 rho = 1.5 Skeleton (spongiosa) range = 1.247 ^ 1 ElseIf tagnum = 9 Then rho = 1 Tissue range = 1.262 ^ 1 ElseIf tagnum = 99 Then rho = 1.1 Skin range = 2.211 / 2.9047 Tissue End If range_Al = 1.0 range_H2O = 1.299 ^ 1 ElseIf gender = 4 Then 'Use UFHADF densities If tagnum = 0 Then rho = 0 range = 1 ElseIf tagnum = 1 Then rho = 1.02 Residual soft tissue range = 2.1949 '' Average soft tissue ElseIf tagnum = 2 Then rho = 1.02 Adrenal (L) range = 2.1949 '' Average s oft tissue ElseIf tagnum = 3 Then rho = 1.02 Adrenal (R) range = 2.1949 '' Average soft tissue ElseIf tagnum = 4 Then rho = 1.04 Brain range = 2.1965 '' Brain ElseIf tagnum = 5 Then rho = 0.94 Breast range = 2 .1581 '' Breast ElseIf tagnum = 6 Then rho = 1.07 Bronchi range = 0.5 (2.1949 + 2.2363) '' 50% average soft tissue, 50% cartilage (linear interpolation) ElseIf tagnum = 7 Then rho = 1.03 Right colon wall range = 2.3021 '' GI tract ElseIf tagnum = 8 Then rho = 1.02 Right colon contents range = 2.1949 '' Average soft tissue

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313 ElseIf tagnum = 9 Then rho = 1.1 Ears range = 2.2363 '' Cartilage ElseIf tagnum = 10 Then rho = 1.03 Esophagus range = 2.3021 '' GI tract ElseIf tagnum = 11 Then rho = 1.05 External nose range = 2 / 3 2.1949 + 1 / 3 2.2363 '' 67% average soft tissue, 33% cartilage (linear interpolation) ElseIf tagnum = 12 Then rho = 1.02 Eyeballs range = 2.1949 '' Average soft tissue ElseIf tagnum = 13 Then rho = 1.02 Gall bladder wall range = 2.1949 '' Average soft tissue ElseIf tagnum = 14 Then rho = 1.02 Gall bladder contents range = 2.1949 '' Average soft tissue ElseIf tagnum = 15 Then rho = 1.05 Heart wall range = 2.204 '' Heart ElseIf tagnum = 16 Then rho = 1.06 Heart contents range = 2.2112 '' Blood ElseIf tagnum = 17 Then r ho = 1.05 Kidney cortex (L) range = 2.2071 '' Kidney ElseIf tagnum = 18 Then rho = 1.05 Kidney cortex (R) range = 2.2071 '' Kidney ElseIf tagnum = 19 Then rho = 1.05 Kidney medulla (L) range = 2.2071 '' Kidney ElseIf tagnum = 20 Then rho = 1.05 Kidney medulla (R) range = 2.2071 '' Kidney ElseIf tagnum = 21 Then rho = 1.05 Kidney pelvi s (L) range = 2.2071 '' Kidney ElseIf tagnum = 22 Then rho = 1.05 Kidney pelvis (R)

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314 range = 2.2071 '' Kidney ElseIf tagnum = 23 Then rho = 1.07 Larynx range = 0.5 (2.1949 + 2.2363) '' 50% average soft tissue, 50% cartilage (linear interpolation) ElseIf tagnum = 24 Then rho = 1.07 Lens range = 2.2213 '' Eye lens ElseIf tagnum = 25 Then rho = 1.06 Liver range = 2.2112 '' Liver ElseIf tagnum = 26 Then rho = 0.34 Lung (L) range = 2.2092 '' Lung ElseIf tagnum = 27 Then rho = 0.34 Lung (R) range = 2.2092 '' Lung ElseIf tagnum = 28 Then rho = 1.02 Nasa l layer (A) range = 2.1949 '' Average soft tissue ElseIf tagnum = 29 Then rho = 1.02 Nasal layer (P) range = 2.1949 '' Average soft tissue ElseIf tagnum = 30 Then rho = 1.02 Oral cavity layer range = 2.1949 '' Av erage soft tissue ElseIf tagnum = 31 Then rho = 1.05 Ovaries range = 2.204 Ovary ElseIf tagnum = 32 Then rho = 1.02 Pancreas range = 2.1966 '' Pancreas ElseIf tagnum = 33 Then rho = 0 ## EMPTY TAG ## range = 1 ElseIf tagnum = 34 Then rho = 1.03 Pharynx range = 2.1949 '' Average soft tissue ElseIf tagnum = 35 Then rho = 1.03 Pituitary range = 2.1949 '' Average soft tissue

PAGE 315

315 ElseIf tagnum = 36 Then rho = 0 ## EMPTY TAG ## range = 1 ElseIf tagnum = 37 Then rho = 1.03 Rectosigmoid wall range = 2.1991 '' GI tract ElseIf t agnum = 38 Then rho = 1.02 Rectosigmoid contents range = 2.1949 '' Average soft tissue ElseIf tagnum = 39 Then rho = 1.02 Salivary glands (parotid) range = 2.1949 '' Average soft tissue ElseIf tagnum = 40 Then rho = 0 ## EMPTY TAG ## range = 1 ElseIf tagnum = 41 Then rho = 1.03 Small intestines wall range = 2.1991 '' GI tract ElseIf tagnum = 42 Then rho = 0.52 Small intestines contents range = 2.1949 '' Average soft tissue ElseIf tagnum = 43 Then rho = 1.1 Skin range = 2.211 '' Skin ElseIf tagnum = 44 Then rho = 1.04 Spinal cord range = 2.1965 '' Brain ElseIf tagnum = 45 Then rho = 1.06 Spleen range = 2.209 '' Spleen ElseIf tagnum = 46 Then rho = 1.0 3 Stomach wall range = 2.1991 '' GI tract ElseIf tagnum = 47 Then rho = 0.52 Stomach contents range = 2.1949 '' Average soft tissue ElseIf tagnum = 48 Then rho = 0 '## EMPTY TAG## range = 1 ElseIf tagnum = 49 Then rho = 1.03 Thymus range = 2.1949 '' Average soft tissue

PAGE 316

316 ElseIf tagnum = 50 Then rho = 1.05 Thyroid range = 2.205 '' Thyroid ElseIf tagnum = 51 Then rho = 1.05 Tongue range = 2.2103 '' Muscle ElseIf tagnum = 52 Then rho = 1.02 Tonsil range = 2.1949 '' Average soft tissue ElseIf tagnum = 53 Then rho = 1.07 Trachea range = 0.5 (2.1949 + 2.2363) '' 50% average soft tissue, 50% cartilage (linear interpolation) ElseIf tagnum = 54 Then rho = 1.04 Urinary bladder wall range = 2.2048 '' Urinary bladder ElseIf tagnum = 55 Then rho = 1.01 Urinary bladder contents range = 2.189 '' Water ElseIf tagnum = 56 Then rho = 1.05 Uterus range = 2.2103 '' Muscle ElseIf tagnum = 57 Then rho = 0.00120484 Air range = 2.5374 '' ICRU Dry Air ElseIf tagnum = 58 Then rho = 1.03 Left colon wall range = 2.1991 '' GI tract ElseIf tagnum = 59 Then rho = 1.08 Left colon contents range = 2.1949 '' Average so ft tissue ElseIf tagnum = 60 Then rho = 1.03 Salivary glands (submaxillary) range = 2.1949 '' Average soft tissue ElseIf tagnu m = 61 Then rho = 1.03 Salivary glands (sublingual) range = 2.1949 '' Average soft tissue ElseIf tagnum = 128 Then rho = 1 .1 Costal cartilage (ribs) range = 2.2363 '' Cartilage

PAGE 317

317 ElseIf tagnum = 129 Then rho = 1.1 Cervical discs rang e = 2.2363 '' Cartilage ElseIf tagnum = 130 Then rho = 1.1 Thoracic discs range = 2.2363 '' Cartilage ElseIf tagnum = 131 Then rho = 1.1 Lumbar discs range = 2.2363 '' Cartilage ElseIf tagnum >= 151 And tagnum <= 188 Then rho = 1.9 Cortical bone (all bone sites) range = 2.5042 '' ICRP Cortical Bone ElseIf tagnum = 189 Then rho = 3.0 T eeth range = 2.595 '' Teeth ElseIf tagnum = 201 Then rho = 1.36 Cranium spongiosa range = 2.3299 '' ElseIf tagnum = 202 Then rho = 1.08 Mandible spongiosa range = 2.2 '' ElseIf tagnum = 207 Then rho = 1.1 7 Cervical vertebra spongiosa range = 2.2547 '' ElseIf tagnum = 208 Then rho = 1.1 Thoracic vertebra spongiosa range = 2.2127 '' ElseIf tagnum = 209 Then rho = 1.1 Lumbar vertebra spongiosa range = 2.2337 '' ElseIf tagnum = 205 Then rho = 1.09 Sternum spongiosa range = 2.2052 '' ElseIf tagnum = 206 Then rh o = 1.11 Rib spongiosa range = 2.2366 '' ElseIf tagnum = 203 Then rho = 1.13 Scapula spongiosa range = 2.2433 ''

PAGE 318

318 ElseIf tagnum = 204 Then rho = 1.1 Clavicle spongiosa range = 2.2152 '' ElseIf tagnum = 211 Then rho = 1.09 Os coxa spongiosa range = 2.2175 '' ElseIf tagnum = 210 Then rho = 1.12 Sacrum spongiosa range = 2.2242 '' ElseIf tagnum = 224 Then rho = 1.08 Proximal humerus spongiosa range = 2.2016 '' ElseIf tagnum = 225 Then rho = 0.99 Upper shaft humerus (medullary) range = 2.1621 '' ElseIf tagnum = 226 Then rho = 0.98 Lower shaft humerus (medullary) range = 2.1485 '' ElseIf tagnum = 227 Then rho = 1.12 Distal humerus spongiosa range = 2.2174 '' ElseIf tagnum = 228 Then rho = 1.06 Proximal radius spongiosa range = 2.1621 '' ElseIf tagnum = 229 Then rho = 0.98 Shaft radius (medullary) range = 2.1485 '' ElseIf tagnum = 230 Then rho = 1.08 Distal radius spongiosa range = 2.2176 '' ElseIf tagnum = 231 Then rho = 1.13 Proximal ulna spongiosa range = 2.2202 '' ElseIf tagnum = 232 Then rho = 0.98 Shaft ulna (medullary) range = 2.1485 '' ElseIf tagnum = 233 Then rho = 1.11 Distal ulna spongiosa range = 2.21 '' ElseIf tagnum = 234 Then rho = 1.12 Wrist and hand range = 2.2174 ''

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319 ElseIf tagnum = 212 Then rho = 1.13 Proximal femur spongiosa range = 2.2227 '' ElseIf tagnum = 213 Then rho = 0.99 Upper shaft femur (medullary) range = 2.1621 '' ElseIf tagnum = 214 Then rho = 0.98 Lower shaft femur (medullary) range = 2.1485 '' ElseIf tagnum = 215 Then rho = 1.11 Distal femur spo ngiosa range = 2.2262 '' ElseIf tagnum = 222 Then rho = 1.11 Patella range = 2.2262 '' ElseIf tagnum = 216 Then rho = 1.08 Proximal tibia spongiosa range = 2.2156 '' ElseIf tagnum = 217 Then rho = 0.98 Shaft tibia (medullary) range = 2.1485 '' ElseIf tagnum = 218 Then rho = 1.09 Distal tibia spongiosa range = 2.2189 '' ElseIf tagnum = 219 Then rho = 1.05 Proximal fibula spongiosa range = 2.1895 '' ElseIf t agnum = 220 Then rho = 0.98 Shaft fibula (medullary) range = 2.1485 '' ElseIf tagnum = 221 Then rho = 1.11 Di stal fibula spongiosa range = 2.2278 '' ElseIf tagnum = 223 Then rho = 1.11 Ankle and foot range = 2.2262 '' End If range_Al = 2.9047 range_H2O = 2.189

PAGE 320

320 ElseIf gender = 6 Then Use micro gravity bone densities (all other densities the same) If ta gnum = 0 Then rho = 0 range = 1 ElseIf tagnum = 1 Then rho = 1.02 Residual soft tissue range = 2.1949 '' Average soft tissue ElseIf tagnum = 2 Then rho = 1.02 Adrenal (L) range = 2.1949 '' Average soft tissue ElseIf tagnu m = 3 Then rho = 1.02 Adrenal (R) range = 2.1949 '' Average soft tissue ElseIf tagnum = 4 Then rho = 1.04 Brain range = 2.1965 '' Brain ElseIf tagnum = 5 Then rho = 0.94 Breast range = 2.1581 '' Breast ElseIf tagnum = 6 Then rho = 1.07 Bronchi range = 0.5 (2.1949 + 2.2363) '' 50% average soft tissue, 50% cartilage (linear interpolation) ElseIf t agnum = 7 Then rho = 1.03 Right colon wall range = 2.3021 '' GI tract ElseIf tagnum = 8 Then rho = 1.02 Right c olon contents range = 2.1949 '' Average soft tissue ElseIf tagnum = 9 Then rho = 1.1 Ears range = 2.2363 '' Ca rtilage ElseIf tagnum = 10 Then rho = 1.03 Esophagus range = 2.3021 '' GI tract ElseIf tagnum = 11 Then rho = 1.05 External nose range = 2 / 3 2.1949 + 1 / 3 2.2363 '' 67% average soft tissue, 33% cartilage (linear interpolation) ElseIf tagnum = 12 Then rho = 1.02 Eyeballs

PAGE 321

321 range = 2.1949 '' Average soft tissue ElseIf tagnum = 13 Then rho = 1.02 Gall bladder wall range = 2.1949 '' Average soft tissue ElseIf tagnum = 14 Then rho = 1.02 Gall bladder contents range = 2.1949 Average soft tissue ElseIf tagnum = 15 Then rho = 1.05 Heart wall range = 2.204 '' Heart ElseIf tagnum = 16 Then rho = 1.06 Heart contents range = 2.2112 '' Blood ElseIf tagnum = 17 Then rho = 1.05 Kidney cortex (L) range = 2.2071 '' Kidney ElseIf tagnum = 18 Then rho = 1.05 Kidney cortex (R) range = 2.2071 '' Kidney ElseIf tagnum = 19 Then rho = 1.05 Kidney medulla (L) range = 2.2071 '' Kidney ElseIf tagnum = 20 Then rho = 1.05 Kidney medulla (R) range = 2.2071 '' Kidney ElseIf tagnum = 21 Then rho = 1.05 Kidney pelvis (L) range = 2.2071 '' Kidney ElseIf tagnum = 22 Then rho = 1.05 Kidney pelvis (R) range = 2.2071 '' Kidney ElseIf tag num = 23 Then rho = 1.07 Larynx range = 0.5 (2.1949 + 2.2363) '' 50% average soft tissue, 50% cartilage (linear interpolation) ElseIf tagnum = 24 Then rho = 1.07 Lens range = 2.2213 '' Eye lens ElseIf tagnum = 25 Then rho = 1.06 Liver range = 2.2112 '' Liver

PAGE 322

322 ElseIf tagnum = 26 Then rho = 0.34 Lung (L) range = 2.2092 '' Lung ElseIf tagnum = 27 Then rho = 0.34 Lung (R) range = 2.2092 '' Lung ElseIf tagnum = 28 Then rho = 1.02 Nasal layer (A) range = 2.1949 '' Average soft tissue ElseIf tagnum = 29 Then rho = 1.02 Nasal layer (P) range = 2.1949 '' Average soft tissue ElseIf tagnum = 30 Then rho = 1.02 Oral cavity layer range = 2.1949 '' Average soft tissue ElseIf tagnum = 31 Then rho = 1.05 Ovaries range = 2.204 Ovary ElseIf tagnum = 32 Then rho = 1.02 Pancreas rang e = 2.1966 '' Pancreas ElseIf tagnum = 33 Then rho = 0 ## EMPTY TAG ## range = 1 ElseIf tagnum = 34 Then rho = 1.03 Pharynx range = 2.1949 '' Average soft tissue ElseIf tagnum = 35 Then rho = 1.03 Pituitary range = 2.1949 '' Average soft tissue ElseIf tagnum = 36 Then rho = 0 ## EMPTY TAG ## range = 1 ElseIf t agnum = 37 Then rho = 1.03 Rectosigmoid wall range = 2.1991 '' GI tract ElseIf tagnum = 38 Then rho = 1.02 Rect osigmoid contents range = 2.1949 '' Average soft tissue ElseIf tagnum = 39 Then rho = 1.02 Salivary glands (parotid) range = 2.1949 '' Average soft tissue

PAGE 323

323 ElseIf tagnum = 40 Then rho = 0 ## EMPTY TAG ## range = 1 ElseIf tagnum = 41 Then rho = 1.03 Small intestines wall range = 2.1991 '' GI tract ElseIf tagnum = 42 Then rho = 0.52 Small intestines contents range = 2.1949 '' Average soft tissue ElseIf tagnum = 43 Then rho = 1.1 Skin range = 2.211 '' Skin ElseIf tagnum = 44 Then rho = 1.04 Spinal cord range = 2.1965 '' Brain ElseIf tagnum = 45 Then rho = 1.06 Spleen range = 2.209 '' Spleen ElseIf tagnum = 46 Then rho = 1.03 Stomach wall range = 2.1991 '' GI tract ElseIf tagnum = 47 Then rho = 0.52 Stomach contents range = 2.1949 '' Average soft tissue ElseIf tagnum = 48 Then rho = 0 '## EMPTY TAG## range = 1 ElseIf tagnum = 49 Then rho = 1.03 Thym us range = 2.1949 '' Average soft tissue ElseIf tagnum = 50 Then rho = 1.05 Thyroid range = 2.205 '' Thyroid ElseIf tagnum = 51 Then rho = 1.05 Tongue range = 2.2103 '' Muscle ElseIf tagnum = 52 Then rho = 1.0 2 Tonsil range = 2.1949 '' Average soft tissue ElseIf tagnum = 53 Then rho = 1.07 Trachea

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324 range = 0.5 (2.1949 + 2.2363) '' 50% average soft tissue, 50% cartilage (linear interpolation) ElseIf tagnum = 54 Then rho = 1.04 Urinary bladder wall range = 2.2048 Urinary bladder ElseIf tagnum = 55 Then rho = 1.01 Urinary bladder contents range = 2.189 '' Water ElseIf tagnum = 56 Then rho = 1.05 Uterus range = 2.2103 '' Muscle ElseIf tagnum = 57 Then rho = 0.00120484 Air range = 2.5374 '' ICRU Dry Air ElseIf tagnum = 58 Then rho = 1.03 Left colon wall range = 2.1991 '' GI tract E lseIf tagnum = 59 Then rho = 1.08 Left colon contents range = 2.1949 '' Average soft tissue ElseIf tagnum = 60 Then rho = 1 .03 Salivary glands (submaxillary) range = 2.1949 '' Average soft tissue ElseIf tagnum = 61 Then rho = 1.03 Salivary glands (sublingual) range = 2.1949 '' Average soft tissue ElseIf tagnum = 128 Then rho = 1.1 Costal cartilage (ribs) range = 2.2363 '' Cartilage ElseIf tagnum = 129 Then rho = 1.1 Cervical discs range = 2.2363 '' Cartilage ElseIf tagnum = 130 Then rho = 1.1 Thoracic discs range = 2.2363 '' Cartilage ElseIf tagnum = 131 Then rho = 1.1 Lumbar discs range = 2.2363 '' Cartilage ElseIf tagnum >= 151 And tagnum <= 188 Then

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325 rho = 1.9 Cortical bone (all bone sites ) range = 2.5042 '' ICRP Cortical Bone ElseIf tagnum = 189 Then rho = 3.0 Teeth range = 2.595 '' Teeth ElseIf tagnum = 201 Then rho = 1.36 Cranium spongiosa range = 2.3299 '' ElseIf tagnum = 202 Then rho = 1.08 Mandible spongiosa range = 2.2 '' ElseIf tagnum = 207 Then rho = 1.14 Cervical vertebra spongiosa range = 2.2547 '' ElseIf tagnum = 208 Then rho = 1.08 Thoracic vertebra spongiosa range = 2.2127 '' ElseIf tagnum = 209 Then rho = 1.09 Lumbar vertebra spongiosa range = 2.2337 '' ElseIf tagnum = 205 Then r ho = 1.09 Sternum spongiosa range = 2.2052 '' ElseIf tagnum = 206 Then rho = 1.11 Rib spongiosa range = 2.2366 '' ElseIf tagnum = 203 Then rho = 1.13 Scapula spongiosa range = 2.2433 '' ElseIf tagnum = 204 Then rho = 1.1 Clavicle spongiosa range = 2.2152 '' ElseIf tagnum = 211 Then rho = 1.07 Os coxa spongiosa range = 2.2175 '' ElseIf tagnum = 210 Then rho = 1.09 Sacrum spongiosa range = 2.2242 '' ElseIf tagnum = 224 Then rho = 1.08 Proximal humerus spongiosa range = 2.2016 ''

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326 ElseIf tagnum = 225 Then rho = 0.99 Upper shaft humerus (medullary) range = 2.1621 '' ElseIf tagnum = 226 Then rho = 0.98 Lower shaft humerus (medullary) r ange = 2.1485 '' ElseIf tagnum = 227 Then rho = 1.12 Distal humerus spongiosa range = 2.2174 '' ElseIf tagnum = 228 Then rho = 1.06 Proximal radius spongiosa range = 2.1621 '' ElseIf tagnum = 229 Then rho = 0.98 Shaft radius (medullary) range = 2.1485 '' ElseIf tagnum = 230 Then rho = 1.08 Distal radius spongiosa range = 2.2176 '' ElseIf tagnum = 231 Then rho = 1.13 Proximal ulna spongiosa range = 2.2202 '' ElseIf tagnum = 232 Then rho = 0.98 Shaft ulna (medullary) range = 2.1485 '' ElseIf tagnum = 233 Then rho = 1.11 Dis tal ulna spongiosa range = 2.21 '' ElseIf tagnum = 234 Then rho = 1.12 Wrist and hand range = 2.2174 '' ElseIf tagnum = 212 Then rho = 1.1 Proximal femur spongiosa range = 2.2227 '' ElseIf tagnum = 213 Then rho = 0.98 Upper shaft femur (medullary) range = 2.1621 '' ElseIf tagnum = 214 Then rho = 0.98 Lower shaft femur (medullary) range = 2.1485 '' ElseIf tagnum = 215 Then rho = 1.11 Distal femur spongiosa

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327 range = 2.2262 ElseIf tagnum = 222 Then rho = 1.11 Patella range = 2.2262 '' ElseIf tagnum = 216 Then rho = 1.0 8 Proximal tibia spongiosa range = 2.2156 '' ElseIf tagnum = 217 Then rho = 0.98 Shaft tibia (medullary) rang e = 2.1485 '' ElseIf tagnum = 218 Then rho = 1.09 Distal tibia spongiosa range = 2.2189 '' ElseIf tagnum = 219 Then rho = 1.05 Proximal fibula spongiosa range = 2.1895 '' ElseIf tagnum = 220 Then rho = 0.98 Shaft fibula (medullary) range = 2.1485 '' ElseIf tagnum = 221 Then rho = 1.11 Distal fibula spongiosa range = 2.2278 '' ElseIf tagnum = 223 Then rho = 1.11 Ankle and foot range = 2.2262 '' End If range_Al = 2.9047 range_H2O = 2.189 ElseIf gender = 0 Then Use unit density and water interaction information If tagnum = 0 Then rho = 0 range = 1 ElseIf tagnum >= 1 And tagnum <= 56 Then rho = 1.0 range = 1.299 ^ 1 ElseIf tagnum = 57 Then rho = 0.00120484 Air range = 1.136 ^ 1 '' ICRU Dry Air

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328 ElseIf tagnum >= 58 And tagnum <= 234 Then rho = 1.0 range = 1. 299 ^ 1 End If range_Al = 1.0 range_H2O = 1.299 ^ 1 End If If a_min < 1 Then d12(src, dose) = d12(src, dose) + (a_m in a_store) rho (range ^ 1) Else d12(src, dose) = d12(src, dose) If a_min >= 1 Then Exit Do End If For k = 0 To 2 x_ next(k) = p1(src, k) + a_min (p2c(dose, k) p1(src, k)) Next For k = 0 To 2 If p1(src, k) > p2c(dose, k) Then If a_min = a_next(k) Then i_next(k) = x_next(k) / d(k) 1 Else i_next(k) = Math.Floor(x_next(k) / d(k)) End If Else If a_min = a_next(k) Then i_next(k) = x_next(k) / d(k) Else i_next(k) = Math.Floor(x_next(k) / d(k)) End If End If Next For k = 0 To 2 a_first(k) = a_next(k) x_first(k) = x_next(k) i_first(k) = i_next(k) Next Lo op Calculate remainder distance Dim a_rest As Double Dim x_bound(2) As Double Dim i_last(2) As Integer For k = 0 To 2

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329 i_last(k) = F2(k) Next tagnum = tag3D(i_last(0), i_last(1), i_last(2)) If gender = 1 Then Use male densities (ICRP 89 or calculated from UFHADM) Convert rho as a function of organ tag to rho as a fun ction of density in g/cm^3 Also record range for 50 MeV protons in material for aluminum conversion in g/cm^2 If tagnum = 0 Then rho = 0 range = 1 ElseIf tagnum = 1 Then rho = 1.03 Residual soft tissue range = 2.1949 '' Average soft tissue ElseIf tagnum = 2 Then rho = 1.03 Adrenal (L) range = 2.1949 '' Average soft tissue ElseIf tagnum = 3 Then rho = 1.03 Adrenal (R) range = 2.1949 '' Average soft tissue ElseIf tagnum = 4 Then rho = 1.04 Brain range = 2.1965 '' Brain Else If tagnum = 5 Then rho = 0.94 Breast range = 2.1581 '' Breast ElseIf tagnum = 6 Then rho = 1.065 Bronchi range = 0.5 (2.1949 + 2.2363) '' 50% average soft tissue, 50% cartilage (linear interpolation) ElseIf tagnum = 7 Then rho = 1.03 Right colon wall range = 2.3021 '' GI tract ElseIf tagnum = 8 Then rho = 1.03 Right colon contents range = 2.1949 '' Average soft tissue ElseIf tagnum = 9 Then rho = 1.1 Ears range = 2.2363 '' Cartilage ElseIf tagnum = 10 Then

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330 rho = 1.03 Esophagus range = 2.302 1 '' GI tract ElseIf tagnum = 11 Then rho = 1.05 External nose range = 2 / 3 2.1949 + 1 / 3 2.2363 '' 67% average soft tissue, 33% cartilage (linear interpolation) ElseIf tagnum = 12 Then rho = 1.03 Eyeballs range = 2.1949 '' Average soft tissue ElseIf tagnum = 13 Then rho = 1.03 Gall bladder wall range = 2.1949 '' Average soft tissue ElseIf tagnum = 14 Then rho = 1.03 Gall bladder contents range = 2.1949 '' Average soft tissue ElseIf tagnum = 15 Then rho = 1.05 Heart wall range = 2.204 '' Heart ElseIf tagnum = 16 Then rho = 1.06 Heart contents range = 2.2112 '' Blood ElseIf tagnum = 17 Then rho = 1.05 Kidney cortex (L) range = 2.2071 '' Kidney ElseIf tagnum = 18 Then rho = 1.05 Kidney cortex (R) range = 2.2071 '' Kidney ElseIf tagnum = 19 Then rho = 1.05 Kidney medulla (L) range = 2.2071 '' Kidney ElseIf tagnum = 20 Then rho = 1.05 Kidney medulla (R) range = 2.2071 '' Kidney ElseIf tagnum = 21 Th en rho = 1.05 Kidney pelvis (L) range = 2.2071 '' Kidney ElseIf tagnum = 22 Then rho = 1.05 Kidney pelvis (R) range = 2.2071 '' Kidney ElseIf tagnum = 23 Then rho = 1.065 Larynx

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331 range = 0.5 (2.1949 + 2.2363) '' 50% average soft tissue, 50% cartilage (linear int erpolation) ElseIf tagnum = 24 Then rho = 1.07 Lens range = 2.2213 '' Eye lens ElseIf tagnum = 25 Then rho = 1.06 Liver range = 2.2112 '' Liver ElseIf tagnum = 26 Then rho = 0.335 Lung (L) range = 2.2092 '' Lung ElseIf tagnum = 27 Then rho = 0.335 Lung (R) range = 2.2092 '' Lung ElseIf tagnum = 28 Then rho = 1. 03 Nasal layer (A) range = 2.1949 '' Average soft tissue ElseIf tagnum = 29 Then rho = 1.03 Nasal layer (P) range = 2.1949 '' Average soft tissue ElseIf tagnum = 30 Then rho = 1.03 Oral cavity layer range = 2.1949 '' Average soft tissue ElseIf tagnum = 31 T hen rho = 0 ## EMPTY TAG ## range = 2.1949 '' Average soft tissue ElseIf tagnum = 32 Then rho = 1.03 Pancreas range = 2.1966 '' Pancreas ElseIf tagnum = 33 Then rho = 1.05 Penis range = 2.2103 '' Muscle ElseIf tagnum = 34 Then rho = 1.03 Pharynx range = 2.1949 '' Average soft tissue ElseIf tagnum = 35 Then rho = 1.03 Pituitary range = 2.1949 '' Average soft tissue ElseIf tagnum = 36 Then rho = 1.03 Prostate range = 2.1949 '' Average soft tissue

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332 ElseIf tagnum = 37 Then rho = 1.03 Rectosigmoid wall range = 2.1991 '' GI tract ElseIf tagnum = 38 Then rho = 0.971 Rectosigmoi d contents range = 2.1949 '' Average soft tissue ElseIf tagnum = 39 Then rho = 1.03 Salivary glands (parotid) range = 2.1949 '' Average soft tissue ElseIf tagnum = 40 Then rho = 1.03 Scrotum range = 2.1949 '' Average soft tissue ElseIf tagnum = 41 Then rho = 1.03 Small intestines wall range = 2.1991 '' GI tract ElseIf tagnum = 42 Then rho = 0.44 Small intestines contents range = 2.1949 '' Average soft tissue ElseIf tagnum = 43 Then rho = 1.1 Skin range = 2.211 '' Skin ElseIf tagn um = 44 Then rho = 1.04 Spinal cord range = 2.1965 '' Brain ElseIf tagnum = 45 Then rho = 1.06 Spleen r ange = 2.209 '' Spleen ElseIf tagnum = 46 Then rho = 1.03 Stomach wall range = 2.1991 '' GI tract ElseIf tagnum = 47 Then rho = 1.03 Stomach contents range = 2.1949 '' Average soft tissue ElseIf tagnum = 48 Then rho = 1.04 Testes range = 2.2017 '' Testes ElseIf tagnum = 49 Then rho = 1.03 Thymus range = 2.1949 '' Average soft tissue ElseIf tagnum = 50 T hen rho = 1.05 Thyroid range = 2.205 '' Thyroid

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333 ElseIf tagnum = 51 Then rho = 1.05 Tongue range = 2.210 3 '' Muscle ElseIf tagnum = 52 Then rho = 1.03 Tonsil range = 2.1949 '' Average soft tissue ElseIf tagnum = 53 Then rho = 1.07 Trachea range = 0.5 (2.1949 + 2.2363) '' 50% average soft tissue, 50% cartilage (linear interpolation) ElseIf tagnum = 54 Then rho = 1.04 Urinary bladder wall range = 2.2048 '' Urinary bladder ElseIf tagnum = 55 Then rho = 1.01 Urinary bladder contents range = 2.189 '' Water ElseIf tagnum = 56 Then rho = 0 ## EMPTY TAG ## range = 0 ElseIf tagnum = 57 Then rho = 0.00120484 Air range = 2.5374 '' ICRU Dry Air ElseIf tagnum = 58 Then rho = 1.03 Left colon wall range = 2.1991 '' GI tract ElseIf tagnum = 59 Then rho = 0.663 Left colon contents range = 2.1949 '' Average soft tissue ElseIf tagnum = 60 Then rho = 1.03 Salivary glands (submaxillary) range = 2.1949 '' Average soft tissue ElseIf tagnum = 61 Then rho = 1.03 Salivary glands (sublingual) range = 2.1949 '' Average soft tissue ElseIf tagnum = 128 Then rho = 1.1 Costal carti lage (ribs) range = 2.2363 '' Cartilage ElseIf tagnum = 129 Then rho = 1.1 Cervical discs range = 2.2363 '' Cartilage

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334 ElseIf tagnum = 130 Then rho = 1.1 Thoracic discs range = 2.2363 '' Cartilage ElseIf tagnum = 131 Then rho = 1.1 Lumbar discs range = 2.2363 '' Cartilage ElseIf tagnum >= 151 And tagnum <= 188 Then rho = 1.9 Cortical bone (all bone sites) range = 2. 5042 '' ICRP Cortical Bone ElseIf tagnum = 189 Then rho = 3.0 Teeth range = 2.595 '' Teeth ElseIf tagnum = 201 Then rho = 1.36 Cranium spongiosa range = 2.3299 '' ElseIf tagnum = 202 Then rho = 1.08 Mandible spongiosa r ange = 2.2 '' ElseIf tagnum = 207 Then rho = 1.17 Cervical vertebra spongiosa range = 2.2547 '' ElseIf tagnum = 208 Then rho = 1.1 Thoracic vertebra spongiosa range = 2.2127 '' ElseIf tagnum = 209 Then rho = 1.1 Lumbar vertebra spongiosa range = 2.2337 '' ElseIf tagnum = 205 Then rho = 1.09 Sternum spongiosa range = 2.2052 '' ElseIf tagnum = 206 Then rho = 1.11 Rib spongiosa range = 2.2366 '' ElseIf tagnum = 203 Then rho = 1.13 Scapula spongiosa range = 2.2433 '' ElseIf tagnum = 204 Then rho = 1.1 Clavicle spongiosa range = 2.2152 ''

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335 ElseIf tagnum = 211 Then rho = 1.09 Os coxa spongiosa range = 2.2175 '' ElseIf tagnum = 210 Then rho = 1.12 Sacrum spongiosa range = 2.2242 '' ElseIf tagnum = 224 Then rho = 1.08 Proximal humerus spongiosa range = 2.2016 '' ElseIf tagnum = 225 Then rho = 0.99 Upper shaft humerus (medullary) range = 2.1621 '' ElseIf tagnum = 226 Then rho = 0.98 Lower shaft humerus (medu llary) range = 2.1485 '' ElseIf tagnum = 227 Then rho = 1.12 Distal humerus spongiosa range = 2.2174 '' ElseIf tagnum = 228 Then rho = 1.06 Proximal radius spongiosa range = 2.1621 '' ElseIf tagnum = 229 Then rho = 0.98 Shaft radius (medullary) range = 2.1485 '' ElseIf tagnum = 230 Then rho = 1.08 Distal radius spongiosa range = 2.2176 '' ElseIf tagnum = 231 Then rho = 1.13 Proximal ulna spongiosa range = 2.2202 '' ElseIf tagnum = 232 Then rho = 0.98 Shaft ulna (medullary) range = 2.1485 '' ElseIf tagnum = 233 Then rho = 1.11 Distal ulna spongiosa range = 2.21 '' ElseIf tagnum = 234 Then rho = 1.12 Wrist and hand range = 2.2174 '' ElseIf tagnum = 212 Then rho = 1.13 Proximal femur spongiosa range = 2.2227 ''

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336 ElseIf tagnum = 213 Then rho = 0.99 Upper shaft femur (medullary) range = 2.1621 '' ElseIf tagnum = 214 Then rho = 0.98 Lower shaft femur (medullary) range = 2.1485 '' ElseIf tagnum = 215 Then rho = 1.11 Distal femur spongiosa range = 2.2262 '' ElseIf tagnum = 222 Then rho = 1.11 Patella range = 2.2262 '' ElseIf tagnum = 216 Then rho = 1.08 Proximal tibia spongiosa range = 2.2156 '' ElseIf tagnum = 217 Th en rho = 0.98 Shaft tibia (medullary) range = 2.1485 '' ElseIf tagnum = 218 Then rho = 1.09 Distal tibia spongiosa range = 2.2189 '' ElseIf tagnum = 219 Then rho = 1.05 Proximal fibula spongiosa range = 2.1895 '' ElseIf t agnum = 220 Then rho = 0.98 Shaft fibula (medullary) range = 2.1485 '' ElseIf tagnum = 221 Then rho = 1.11 Distal fibula spon giosa range = 2.2278 '' ElseIf tagnum = 223 Then rho = 1.11 Ankle and foot range = 2.2262 '' End If range_Al = 2.9047 range_H2O = 2.189 ElseIf gender = 5 Then Use micro gravity bone densities (all other densities are the same) If tagnum = 0 Then rho = 0

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337 range = 1 ElseIf tagnum = 1 Then rho = 1.03 Residual soft tissue range = 2.1949 '' Average soft tissue ElseIf tagnum = 2 Then rho = 1.03 Adrenal (L) range = 2.1949 '' Average soft tissue ElseIf tagnum = 3 Then rho = 1.03 Adrenal (R) range = 2.1949 '' Average soft tissue ElseIf tagnum = 4 Then rho = 1.04 Brain range = 2.1965 '' Brain ElseIf tagnum = 5 Then rho = 0.94 Breast range = 2.1581 '' Breast ElseIf tagnum = 6 Then rho = 1.065 Bronchi ra nge = 0.5 (2.1949 + 2.2363) '' 50% average soft tissue, 50% cartilage (linear interpolation) ElseIf tagnum = 7 Then rho = 1.03 Right colon wall range = 2.3021 '' GI tract ElseIf tagnum = 8 Then rho = 1.03 Right colon contents range = 2.1949 '' Average soft tissue ElseIf tagnum = 9 Then rho = 1.1 Ears range = 2.2363 '' Cartilage ElseIf tagnum = 10 Then rho = 1.03 Esophagus range = 2.3021 '' GI tract ElseIf tagnum = 11 Then rho = 1.05 External nose range = 2 / 3 2.1949 + 1 / 3 2.2363 '' 67% average soft tissue, 33% cartilage (linear interpolation) ElseIf tagnum = 12 Then rho = 1.03 Eyeballs range = 2.1949 '' Average soft tissue ElseIf tagnum = 13 Then rho = 1.03 Gall bladder wall range = 2.1949 '' Average soft tissue

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338 ElseIf tagnum = 14 Then rho = 1.03 Gall bladder contents range = 2.1949 '' Average soft tissue ElseIf tagnum = 15 Then rho = 1.05 Heart wall range = 2.204 '' Heart ElseIf tagnum = 16 Then rho = 1.06 Heart contents range = 2.2112 '' Blood ElseIf t agnum = 17 Then rho = 1.05 Kidney cortex (L) range = 2.2071 '' Kidney ElseIf tagnum = 18 Then rho = 1.05 Kidney cortex (R) range = 2.2071 '' Kidney ElseIf tagnum = 19 Then rho = 1.05 Kidney medulla (L) range = 2.2071 '' Kidney ElseIf tagnum = 20 Then rho = 1.05 Kidney medulla (R) range = 2.2071 '' Kidney ElseIf tagnum = 21 Then rho = 1.05 Kidney pelvis (L) range = 2.2071 '' Kidney ElseIf tagnum = 22 Then rho = 1.05 Kidney pelvis (R) range = 2.2071 '' Kidney ElseIf tagnum = 23 Then rho = 1.065 Larynx range = 0.5 (2.1949 + 2.2363) '' 50% average soft tissue, 50% cartilage (linear interpolation) ElseIf tagnu m = 24 Then rho = 1.07 Lens range = 2.2213 '' Eye lens ElseIf tagnum = 25 Then rho = 1.06 Liver range = 2.2112 '' Liver ElseIf tagnum = 26 Then rho = 0.335 Lung (L) range = 2.2092 '' Lung ElseIf tagnum = 27 Then

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339 rho = 0.335 Lung (R) range = 2.2092 '' Lung ElseIf tagnum = 28 Then rho = 1.03 Nasal layer (A) range = 2.1949 '' Average soft tissue ElseIf tagnum = 29 Then rho = 1.03 Nasal layer (P) range = 2.1949 '' Average soft tissue ElseIf tagnum = 30 Then rho = 1.03 Oral cavity layer range = 2.1949 '' Average soft tissue ElseIf tagnum = 31 Then rho = 0 ## EMPTY TAG ## range = 2.1949 '' Average soft tissue ElseIf tagnum = 32 Then rho = 1.03 Pancreas range = 2.1966 '' Pancreas ElseIf tagnum = 33 Then rho = 1.05 Penis range = 2.2103 '' Muscle ElseIf tagnum = 34 Then rho = 1.03 Pharynx range = 2.1949 '' Average soft tissue ElseIf tagnum = 35 Then rho = 1.03 Pituitary range = 2.1949 '' Average soft tissue ElseIf ta gnum = 36 Then rho = 1.03 Prostate range = 2.1949 '' Average soft tissue ElseIf tagnum = 37 Then rho = 1.03 Rectosigmoid wall range = 2.1991 '' GI tract ElseIf tagnum = 38 Then rho = 0.971 Rectosigmoid contents range = 2.1949 '' Average soft tissue ElseIf tagnum = 39 Then rho = 1.03 Salivary glands (parotid) range = 2.1949 '' Average soft tissue ElseIf tagnum = 40 Then rho = 1.03 Scrotum range = 2.1949 '' Average soft tissue

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340 ElseIf tagnum = 41 Then rho = 1.03 Small intestines wall range = 2.19 91 '' GI tract ElseIf tagnum = 42 Then rho = 0.44 Small intestines contents range = 2.1949 '' Average soft tissue ElseIf tagnum = 43 Then rho = 1.1 Skin range = 2.211 '' Skin ElseIf tagnum = 44 Then rho = 1.04 Spinal cord range = 2.1965 '' Brain ElseIf tagnum = 45 Then rho = 1.06 Spleen range = 2.209 '' Spleen ElseIf tagnum = 46 Then rho = 1.03 Stomach wall range = 2.1991 '' GI tract ElseIf tagnum = 47 Then rho = 1.03 Stomach contents range = 2.1949 '' Average soft tissue ElseIf tagnum = 48 Then rho = 1.04 Testes range = 2.2017 '' Testes ElseIf tagnum = 4 9 Then rho = 1.03 Thymus range = 2.1949 '' Average soft tissue ElseIf tagnum = 50 Then rho = 1.05 Thyroid range = 2.205 '' Thyroid ElseIf tagnum = 51 Then rho = 1.05 Tongue range = 2.2103 '' Muscle ElseIf tagnum = 52 Then rho = 1.03 Tonsil range = 2.1949 '' Average soft tissue ElseIf tagnum = 53 Then rho = 1.07 Trachea rang e = 0.5 (2.1949 + 2.2363) '' 50% average soft tissue, 50% cartilage (linear interpolation) ElseIf tagnum = 54 Then rho = 1.04 Urinary bladder wall

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341 range = 2.2048 '' Urinary bladder ElseIf tagnum = 55 Then rho = 1.01 Urinary bladder contents range = 2.189 '' Water ElseIf tagnum = 56 Then rho = 0 ## EMPTY TAG ## range = 0 ElseIf tagnum = 57 Then rho = 0.00120484 Air range = 2.5374 '' ICRU Dry Air ElseIf tagnum = 58 Then rho = 1.03 Left colon wall range = 2.1991 '' GI tract ElseIf tagnum = 59 Then rho = 0.663 Left colon contents range = 2.1949 '' Average soft tissue ElseIf tagnum = 60 Then rho = 1.03 Salivary glands (submaxillary) range = 2.1949 '' Average soft tissue ElseIf tagnum = 61 Then rho = 1.03 Salivary glands (sublingual) range = 2.1949 '' Average soft tissue ElseIf tagnum = 128 Then rho = 1.1 Costal cartilage (ribs) range = 2.2363 '' Cartilage ElseIf tagnum = 129 Then rho = 1.1 Cervical discs range = 2.2363 '' Cartilage ElseIf tagnum = 130 Then rho = 1.1 Thoracic discs range = 2.2363 '' Cartilage ElseIf tagnum = 131 Then rho = 1.1 Lumbar discs range = 2.2363 '' Cartilage ElseIf tagnum >= 151 And tagnum <= 188 Then rho = 1.9 Cortical bone (all bone sites) range = 2.5042 '' ICRP Cortical Bone ElseIf tagnum = 189 Then rho = 3.0 Teeth

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342 ran ge = 2.595 '' Teeth ElseIf tagnum = 201 Then rho = 1.36 Cranium spongiosa range = 2.3299 '' ElseIf tagnum = 202 Then rho = 1.08 Mandible spongiosa range = 2.2 '' ElseIf tagnum = 207 Then rho = 1.14 Cervical vertebra spongiosa ra nge = 2.2547 '' ElseIf tagnum = 208 Then rho = 1.08 Thoracic vertebra spongiosa range = 2.2127 '' ElseIf tagnum = 209 Then rho = 1.09 Lumbar vertebra spongiosa range = 2.2337 '' ElseIf tagnum = 205 Then rho = 1.09 Sternum spongiosa range = 2.2052 '' ElseIf tagnum = 206 Then rho = 1.11 Rib spongiosa range = 2.2366 '' ElseIf tagnum = 203 Then rho = 1.13 Scapula spongiosa range = 2.2433 '' ElseIf tagnum = 204 Then rho = 1.1 Clavicle spongiosa range = 2.215 2 '' ElseIf tagnum = 211 Then rho = 1.07 Os coxa spongiosa range = 2.2175 '' ElseIf tagnum = 210 Then rho = 1.09 Sacrum spongiosa range = 2.2242 '' ElseIf tagnum = 224 Then rho = 1.08 Proximal humerus spongiosa range = 2.2016 '' ElseIf tagnum = 225 Then rho = 0.99 Upper shaft humerus (medullary) range = 2.1621 ''

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343 ElseIf tagnum = 226 Then rho = 0.98 Lower shaft humerus (medullary) range = 2.1485 '' ElseIf tagnum = 227 Then rho = 1.12 Dis tal humerus spongiosa range = 2.2174 '' ElseIf tagnum = 228 Then rho = 1.06 Proximal radius spongiosa range = 2.1621 '' ElseIf tagnum = 229 Then rho = 0.98 Shaft radius (medullary) range = 2.1485 '' ElseIf tagnum = 230 Then rho = 1.08 Distal radius spongiosa range = 2.2176 '' ElseIf tagnum = 231 Then rho = 1.13 Proximal ulna spongiosa range = 2.2202 '' ElseIf tagnum = 232 Then rho = 0.98 Shaft ulna (medullary) range = 2.1485 '' ElseIf tagnum = 233 Then rho = 1.11 Distal ulna spongiosa range = 2.21 '' ElseIf tagnum = 234 Then rho = 1.12 Wrist and hand range = 2.2174 '' ElseIf tagnum = 212 Then rho = 1.1 Proximal femur spongiosa range = 2.2227 '' ElseIf tagnum = 213 Then rho = 0.98 Up per shaft femur (medullary) range = 2.1621 '' ElseIf tagnum = 214 Then rho = 0.98 Lower shaft femur (medullary) range = 2.1485 '' ElseIf tagnum = 215 Then rho = 1.11 Distal femur spongiosa range = 2.2262 '' ElseIf tagnum = 222 Then rho = 1.11 Patella range = 2.2262 ''

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344 ElseIf tagnum = 216 Then rho = 1.08 Proximal tibia spongiosa range = 2.2156 '' ElseIf tagnum = 217 Then rho = 0.98 Shaft tibia (medullary) range = 2.1485 '' ElseIf tagnum = 218 Then rho = 1.09 Distal tibia spongiosa range = 2.2189 '' ElseIf tagnum = 219 Then rho = 1.05 Proximal fibula spongiosa r ange = 2.1895 '' ElseIf tagnum = 220 Then rho = 0.98 Shaft fibula (medullary) range = 2.1485 '' ElseIf tagnum = 221 Then rho = 1.11 Distal fibula spongiosa range = 2.2278 '' ElseIf tagnum = 223 Then rho = 1.11 Ankle and foot range = 2.2262 '' End If range_Al = 2.9047 range_H2O = 2.189 ElseIf gender = 2 Then Use CAM densities shoe horned into UFHADM Convert rho as a function of organ tag to rho as a function of density in g/cm^3 Also record range for 50 MeV protons in material for aluminum conversion in g/cm^2 If tagnum = 0 Then rho = 0 range = 1 End If If tagnum = 1 Then rho = 1.03 Residual soft tissue range = 2 / (1.287 + 1.262) '' Average soft tiss ue ElseIf tagnum = 2 Then rho = 1.03 Adrenal (L) range = 2 / (1.287 + 1.262) '' Average soft tissue ElseIf tagnum = 3 Then

PAGE 345

345 rho = 1.03 Adrenal (R) range = 2 / (1.287 + 1.262) '' Average soft tissue ElseIf tagnum = 4 Then rho = 1.058 Brain range = 1.281 ^ 1 '' Organ ElseIf tagnum = 5 Then rho = 1.03 Breast range = 2 / (1.287 + 1.262) '' Average soft tissue ElseIf tagnum = 6 Then rho = 1.03 Bronchi range = 2 / (1.287 + 1.262) '' Average soft tissue ElseIf tagnum = 7 Then rho = 0.451 Right colon wall range = 1.281 ^ 1 '' Intestine ElseIf tagnum = 8 Then rho = 0.451 Right colon contents range = 1.281 ^ 1 '' Intestine ElseIf tagnum = 9 Then rho = 1.03 Ears range = 2 / (1.287 + 1.262) '' Average soft tissue ElseIf tagnum = 10 Then rho = 1.03 Esophagus range = 2 / (1.287 + 1.262) '' Average soft tissue ElseIf tagnum = 11 Then rho = 1.03 External nose range = 2 / (1.287 + 1.262) '' Average soft tissue ElseIf tagnum = 12 Then rho = 1.058 Eyeballs range = 1.281 ^ 1 '' Organ ElseIf tagnum = 13 Then rho = 1.058 Gall bladder wall range = 1.281 ^ 1 '' Organ ElseIf tagnum = 14 Then rho = 1.058 Gall bladder contents range = 1.281 ^ 1 '' Organ ElseIf tagnum = 15 Then rho = 1.058 Heart wall range = 1.281 ^ 1 '' Organ ElseIf tagnum = 16 Then rho = 1.058 Heart contents range = 1.281 ^ 1 '' Organ

PAGE 346

346 ElseIf tagnum = 17 Then rho = 1.058 Kidney cortex (L) range = 1.281 ^ 1 '' Organ ElseIf tagnum = 18 Then rho = 1.058 Kidney cortex (R) range = 1.281 ^ 1 '' Organ ElseIf tagnum = 19 Then rho = 1.058 Kidney medulla (L) range = 1.281 ^ 1 '' Organ ElseIf tagnum = 20 Then rho = 1.058 Kidney medulla (R) range = 1.281 ^ 1 '' Organ ElseIf tagnum = 21 Then rho = 1.058 Kid ney pelvis (L) range = 1.281 ^ 1 '' Organ ElseIf tagnum = 22 Then rho = 1.058 Kidney pelvis (R) range = 1.281 ^ 1 '' Organ ElseIf tagnum = 23 Then rho = 1.03 LaryN(0) range = 2 / (1.287 + 1.262) '' Average soft tissue ElseIf tagnum = 24 Then rho = 1.05 8 Lens range = 1.281 ^ 1 '' Organ ElseIf tagnum = 25 Then rho = 1.058 Liver range = 1.281 ^ 1 '' Organ ElseIf tagnum = 26 Then rho = 0.257 Lung (L) range = 1.281 ^ 1 '' Lung ElseIf tagnum = 27 Then rho = 0.33 Lung (R) range = 1.281 ^ 1 '' Lung ElseIf tagnum = 28 Then rho = 1.03 Nasal layer (A) range = 2 / (1.287 + 1.262) '' Average soft tissu e ElseIf tagnum = 29 Then rho = 1.03 Nasal layer (P) range = 2 / (1.287 + 1.262) '' Average soft tissue ElseIf tagnum = 30 Then rho = 1.03 Oral cavity layer range = 2 / (1.287 + 1.262) '' Average soft tissue

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347 ElseIf tagnum = 31 Then rho = 0 ## EMPTY TAG ## rang e = 2 / (1.287 + 1.262) '' Average soft tissue ElseIf tagnum = 32 Then rho = 1.058 Pancreas range = 1.281 ^ 1 '' Organ ElseIf tagnum = 33 Then rho = 1.058 Penis range = 1.281 ^ 1 '' Organ ElseIf tagnum = 34 Then rho = 1.03 Ph aryN(0) range = 2 / (1.287 + 1.262) '' Average soft tissue ElseIf tagnum = 35 Then rho = 1.03 Pituitary range = 2 / (1.287 + 1.262) '' Average so ft tissue ElseIf tagnum = 36 Then rho = 1.03 Prostate range = 2 / (1.287 + 1.262) '' Average soft tissue ElseIf tagnum = 37 Then rho = 0.451 Rectosigmoid wall range = 1.281 ^ 1 '' Intestine ElseIf tagnum = 38 Then rho = 0.451 Rectosigmoid contents range = 1.281 ^ 1 '' Intestine ElseIf tagnum = 39 Then rho = 1.03 Salivary glands (parotid) range = 2 / (1.287 + 1.262) '' Average soft tissue ElseIf tagnum = 40 Then rho = 1.03 Scrotum range = 2 / (1.287 + 1.262) '' Average soft tissue ElseIf tagnum = 41 Then rho = 0.45 1 Small intestines wall range = 1.281 ^ 1 '' Intestine ElseIf tagnum = 42 Then rho = 0.451 Small intestines contents range = 1 .281 ^ 1 '' Intestine ElseIf tagnum = 43 Then rho = 1.03 Skin range = 2 / (1.287 + 1.262) '' Average soft tissue ElseIf tagnum = 44 Then rho = 1.058 Spinal cord

PAGE 348

348 range = 1.281 ^ 1 '' Organ ElseIf tagnum = 45 Then rho = 1.058 Spleen range = 1.281 ^ 1 '' Organ ElseIf tagnum = 46 Then rho = 1.058 Stomach wall range = 1.281 ^ 1 '' Organ ElseIf tagnum = 47 Then rho = 1.058 Stomach contents range = 1.281 ^ 1 '' Organ ElseIf tagnum = 48 Then rho = 1.058 Testes ran ge = 1.281 ^ 1 '' Organ ElseIf tagnum = 49 Then rho = 1.03 Thymus range = 2 / (1.287 + 1.262) '' Average soft tissue ElseIf tagnum = 50 Th en rho = 1.058 Thyroid range = 1.281 ^ 1 '' Organ ElseIf tagnum = 51 Then rho = 1.06 Tongue range = 1. 287 ^ 1 '' Muscle ElseIf tagnum = 52 Then rho = 1.03 Tonsil range = 2 / (1.287 + 1.262) '' Average soft tissue ElseIf tagnum = 53 Then rho = 1.03 Trachea range = 2 / (1.287 + 1.262) '' Average soft tissue ElseIf tagnum = 54 Then rho = 1.058 Urinary bladder wall range = 1.281 ^ 1 '' Organ ElseIf tagnum = 55 Then rho = 1.058 Urinary bladder contents range = 1.281 ^ 1 '' Organ ElseIf tagnum = 56 Then rho = 0 ## EMPTY TAG ## range = 0 ElseIf tagnum = 57 Then rho = 0.00120484 Air rang e = 1.136 ^ 1 '' ICRU Dry Air

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349 ElseIf tagnum = 58 Then rho = 0.451 Left colon wall range = 1.281 ^ 1 '' Intestine ElseIf tagnum = 59 Then rho = 0.451 Left colon contents range = 1.281 ^ 1 '' Intestine ElseIf tagnum = 60 Then rho = 1.03 Salivary glands (s ubmaxillary) range = 2 / (1.287 + 1.262) '' Average soft tissue ElseIf tagnum = 61 Then rho = 1.03 Salivary glands (sublingual) range = 2 / (1.287 + 1.262) '' Average soft tissue ElseIf tagnum = 128 Then rho = 1.03 Costal cartilage (ribs) range = 2 / (1.287 + 1.262) '' A verage soft tissue ElseIf tagnum = 129 Then rho = 1.03 Cervical discs range = 2 / (1.287 + 1.262) '' Average soft tissue ElseIf tagnum = 130 Then rho = 1.03 Thoracic discs range = 2 / (1.287 + 1.262) '' Average soft tissue ElseIf tagnum = 131 Then rho = 1.03 Lumbar discs range = 2 / (1.287 + 1.262) '' Average soft tissue ElseIf tagnum >= 151 And tagnum <= 188 Then rho = 1.75 Cortical bone (all bone sites) range = 1.202 ^ 1 '' Bone ElseIf tagnum = 189 Then rho = 1.75 Teeth range = 1.202 ^ 1 '' Bone ElseIf tagnum >= 201 And tagnum <= 234 Then rho = 1.499 Spongiosa (all bone sites) range = 1.247 ^ 1 '' Skeleton End If range_Al = 1.0 range_H2O = 1.299 ^ 1 ElseIf gender = 3 Then Use CAM/CAF densities and organ tags If tagnum = 1 Or tagnum = 11 Or tagnum = 21 Or tagnum = 0 Then rho = 0 Void

PAGE 350

350 range = 1 ElseI f tagnum = 2 Then rho = 0.257 Lung range = 1.281 ^ 1 ElseIf tagnum = 3 Or tagnum = 13 Or tagnum = 23 Or tagnum = 33 Or tagnum = 43 Or tagnum = 53 Or tagnum = 63 Or tagnum = 73 Or tagnu m = 83 Or tagnum = 93 Or tagnum = 103 Or tagnum = 113 Then rho = 1.058 Organ range = 1.281 ^ 1 ElseIf tagnum = 4 Then rho = 0.451 Intestine range = 1.281 ^ 1 ElseIf tagnum = 5 Then rho = 1.06 Muscle range = 1.287 ^ 1 ElseIf tagnum = 6 Then rho = 1.75 Bone range = 1.202 ^ 1 ElseIf tagnum = 7 Or tagnum = 17 Then rho = 0.918 Marrow (fat) range = 1.348 ^ 1 ElseIf tagnum = 8 Or tagnum = 18 Or tag num = 207 Or tagnum = 209 Or tagnum = 213 Or tagnum = 215 Or tagnum = 212 Or tagnum = 239 Or tagnum = 14 Or tagnum = 214 Or tagnum = 211 Or tagnum = 19 Or tagnum = 210 Or tagnum = 208 Then rho = 1.5 Skeleton (spongiosa) range = 1.247 ^ 1 ElseIf tagnum = 9 Then rho = 1 Tissue range = 1.262 ^ 1 ElseIf tagnum = 99 Then rho = 1.1 Skin range = 2.211 / 2.9047 Tissue End If range_Al = 1.0 range_H2O = 1.299 ^ 1 ElseIf gender = 4 Then 'Use UFHADF densities If tagnum = 0 Then rho = 0 range = 1 ElseIf tagnum = 1 Then rho = 1.02 Residual soft tissue

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351 range = 2.1949 '' Average soft tissue ElseIf tagnum = 2 Then rho = 1.02 Adrenal (L) range = 2.1949 '' Average soft tissue ElseIf tagnum = 3 Then rho = 1.02 Adrenal (R) range = 2.1949 '' Average soft tissue ElseIf tagnum = 4 Then rho = 1.04 Brain range = 2.1965 '' Brain ElseIf tagnum = 5 Then rho = 0.94 Breast range = 2.1581 '' Breast ElseIf tagnum = 6 Then rho = 1.07 Bro nchi range = 0.5 (2.1949 + 2.2363) '' 50% average soft tissue, 50% cartilage (linear interpolation) ElseIf tagnum = 7 Then rho = 1.03 Right colon wall range = 2.3021 '' GI tract ElseIf tagnum = 8 Then rho = 1.02 Right colon contents range = 2.1949 '' Average soft tissue ElseIf tagnum = 9 Then rho = 1.1 Ears range = 2.2363 '' Cartilage ElseIf tagnum = 10 Then rho = 1.03 Esophagus range = 2.3021 '' GI tract ElseIf tagnum = 11 Then rho = 1.05 External nose range = 2 / 3 2.1949 + 1 / 3 2.2363 '' 67 % average soft tissue, 33% cartilage (linear interpolation) ElseIf tagnum = 12 Then rho = 1.02 Eyeballs range = 2.1949 '' Average soft tissue ElseIf tagnum = 13 Then rho = 1.02 Gall bladder wall range = 2.1949 '' Average soft tissue ElseIf tagnum = 14 Then rho = 1.02 Gall bladder contents range = 2.1949 '' Average soft tissue

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352 ElseIf tagnum = 15 Then rho = 1.05 Heart wall range = 2.204 '' Heart ElseIf tagnum = 16 Then rho = 1.06 Heart contents range = 2.2112 '' Blood ElseIf tagnum = 17 Then rho = 1.05 Kidney cortex (L) range = 2.2071 '' Kidney ElseIf tagnum = 18 Then rho = 1.05 Kidney cortex (R) range = 2.2071 '' Kidney ElseIf tagnum = 19 Then rho = 1.05 Kidney medulla (L) range = 2.2071 '' Kidney ElseIf tagnum = 20 Then rho = 1.05 Kidney medulla (R) range = 2.2071 '' Kidney ElseIf tagnum = 21 Then rho = 1.05 Kidney pelvis (L) range = 2.2071 '' Kidney ElseIf tagnum = 22 Then rho = 1.05 Kidney pelvis (R) range = 2.2071 '' Kidney Els eIf tagnum = 23 Then rho = 1.07 Larynx range = 0.5 (2.1949 + 2.2363) '' 50% average soft tissue, 50% cartilage (linear interpolation) ElseIf tagnum = 24 Then rho = 1.07 Lens range = 2.2213 '' Eye lens ElseIf tagnum = 25 Then rho = 1.06 Liver range = 2.2112 '' L iver ElseIf tagnum = 26 Then rho = 0.34 Lung (L) range = 2.2092 '' Lung ElseIf tagnum = 27 Then rho = 0.34 Lung (R) range = 2.2092 '' Lung ElseIf tagnum = 28 Then

PAGE 353

353 rho = 1.02 Nasal layer (A) range = 2.1949 '' Average soft tissue ElseIf tagnum = 29 Then rho = 1.02 Nasal layer (P) range = 2.1949 '' Average soft tissue ElseIf tagnum = 30 Then rho = 1.02 Oral cavity layer range = 2.1949 '' Average soft tissue ElseIf tagnum = 31 Then rho = 1.05 Ovaries range = 2.204 Ovary ElseIf tagnum = 32 Then rho = 1.02 Pancreas range = 2.1966 '' Pancreas ElseIf tagnum = 33 Then rho = 0 ## EMPTY TAG ## range = 1 ElseIf tagnum = 34 Then rho = 1.03 Pharynx range = 2.1949 '' Average soft tissue ElseIf tagnum = 35 Then rho = 1.03 Pituitary range = 2.1949 '' Average soft tissue ElseIf tagnum = 36 Then rho = 0 ## EMPTY TAG ## range = 1 ElseIf tagnum = 37 Then rho = 1.03 Rectosigmoid wall range = 2.1991 '' GI tract ElseIf tagnum = 38 Then rho = 1.02 Rectosigmoid contents range = 2.1949 '' Average soft tissue ElseIf tagnum = 39 Then rho = 1.02 Salivary glands (parotid) range = 2.1949 '' Average soft tissue ElseIf tagnum = 40 Then rho = 0 ## EMPTY TAG ## range = 1 ElseIf tagnum = 41 Then rho = 1.03 Small intestines wall range = 2.1991 '' GI tract

PAGE 354

354 ElseIf tagnum = 42 Then rho = 0.52 Small intestines contents range = 2.1949 '' Average soft tissue ElseIf tagnum = 43 Then rho = 1.1 Skin range = 2.211 '' Skin ElseIf tagnum = 44 Then rho = 1.04 Spinal cord range = 2.1965 '' Brain ElseIf tagnu m = 45 Then rho = 1.06 Spleen range = 2.209 '' Spleen ElseIf tagnum = 46 Then rho = 1.03 Stomach wall r ange = 2.1991 '' GI tract ElseIf tagnum = 47 Then rho = 0.52 Stomach contents range = 2.1949 '' Average soft tissue ElseIf tagnum = 48 Then rho = 0 '## EMPTY TAG## range = 1 ElseIf tagnum = 49 Then rho = 1.03 Thymus range = 2.1949 '' Average soft tissue ElseIf tagnum = 50 Then rho = 1.05 Thyroid range = 2.205 '' Thyroid ElseIf tagnum = 51 Then rho = 1.05 Tongue range = 2.2103 '' Muscle ElseIf tagnum = 52 Then rho = 1.02 Tonsil range = 2.1949 '' Average soft tissue ElseIf tagnum = 53 Then rho = 1.07 Trachea range = 0.5 (2.1949 + 2.2363) '' 50% average soft tissue, 50% cartilage (linear interpolation) ElseIf tagnum = 54 Then rho = 1.04 Urinary bladder wall range = 2.2048 '' Urinary bladder ElseIf tagnum = 55 Then rho = 1.01 Urinary bladder contents

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355 range = 2.189 '' Water ElseIf tagnum = 56 Then rho = 1.05 Uterus range = 2.2103 '' Muscle ElseIf tagnum = 57 Then rho = 0.00120484 Air range = 2.5374 '' ICRU Dry Air ElseIf tagnum = 58 Then rho = 1.03 Left colon wall range = 2.1991 '' GI tract ElseIf tagnum = 59 Then rho = 1.08 Left colon contents range = 2.1949 '' Average soft tissue ElseIf tagnum = 60 Then rho = 1.03 Salivary glands (submaxillary) range = 2.1949 '' Average soft tissue ElseIf tagnum = 61 Then rho = 1.03 Salivary glands (sublingual) range = 2.1949 '' Average soft tissue ElseIf tagnum = 128 Then rho = 1.1 Costal cartilage (ribs) range = 2.2363 '' Cartilage ElseIf tagnum = 129 Then rho = 1.1 Cervical discs range = 2.2363 '' Cartilage ElseIf tagnum = 130 Then rho = 1.1 Thoracic discs range = 2.2363 '' Cartilage ElseIf tagnum = 131 Then rho = 1.1 Lumbar discs range = 2.2363 '' Cartilage ElseIf tagnum >= 151 And tagnum <= 188 Then rho = 1.9 Cortical bone (all bone sites) range = 2.5042 '' ICRP Cortical Bone ElseIf tagnum = 189 Then rho = 3.0 Teeth range = 2.595 '' Teeth ElseIf tagnum = 201 Then

PAGE 356

356 rho = 1.36 Cranium spongiosa range = 2.3299 '' ElseIf tagnum = 202 Then rho = 1.08 Mandible spongiosa range = 2.2 '' ElseIf tagnum = 207 Then rho = 1.17 Cervical vertebra spongiosa range = 2.2547 '' ElseIf tagnum = 208 Then rho = 1.1 Thoracic vertebra spongiosa range = 2.2127 '' ElseIf tagnum = 209 Then rho = 1.1 Lumbar vertebra spongiosa range = 2.2337 '' ElseIf tagnum = 205 Then rho = 1.09 Sternum spongiosa range = 2.2052 '' ElseIf tagnum = 206 Then rho = 1.11 Rib spongiosa range = 2.2366 '' ElseIf tagnum = 203 Then rho = 1.13 Scapula spongiosa range = 2.2433 '' ElseIf tagnum = 204 Then rho = 1.1 Clavicle spongiosa range = 2.2152 '' ElseIf tagnum = 211 Then rho = 1.09 Os coxa spongiosa range = 2.2175 '' ElseIf tagnum = 210 Then rho = 1.12 Sacrum spongiosa range = 2.2242 '' ElseIf tagnum = 224 Then rho = 1.08 Proximal humerus spongiosa range = 2.2016 '' ElseIf tagnum = 225 Then rho = 0.99 Upper shaft humerus (medullary) range = 2.1621 '' ElseIf tagnum = 226 Then rho = 0.98 Lower shaft humerus (medullary) range = 2.1485 ''

PAGE 357

357 ElseIf tagnum = 227 Then rho = 1.12 Dis tal humerus spongiosa range = 2.2174 '' ElseIf tagnum = 228 Then rho = 1.06 Proximal radius spongiosa range = 2.1621 '' ElseIf tagnum = 229 Then rho = 0.98 Shaft radius (medullary) range = 2.1485 '' ElseIf tagnum = 230 Then rho = 1.08 Distal radius spongiosa range = 2.2176 '' ElseIf tagnum = 231 Then rho = 1.13 Proximal ulna spongiosa range = 2.2202 '' ElseIf tagnum = 232 Then rho = 0.98 Shaft ulna (medullary) range = 2.1485 '' ElseIf tagnum = 233 Then rho = 1.11 Distal ulna spongiosa range = 2.21 '' ElseIf tagnum = 234 Then rho = 1.12 Wrist and hand range = 2.2174 '' ElseIf tagnum = 212 Then rho = 1.13 Proximal femur spongiosa range = 2.2227 '' ElseIf tagnum = 213 Then rho = 0.99 U pper shaft femur (medullary) range = 2.1621 '' ElseIf tagnum = 214 Then rho = 0.98 Lower shaft femur (medullary) range = 2.1485 '' ElseIf tagnum = 215 Then rho = 1.11 Distal femur spongiosa range = 2.2262 '' ElseIf tagnum = 222 Then rho = 1.11 Patella range = 2.2262 '' ElseIf tagnum = 216 Then rho = 1.08 Proximal tibia spongiosa range = 2.2156 ''

PAGE 358

358 ElseIf tagnum = 217 Then rho = 0.98 Shaft tibia (medullary) range = 2.1485 '' ElseIf tagnum = 218 Then rho = 1.09 Distal tibia spongiosa range = 2.2189 '' ElseIf tagnum = 219 Then rho = 1.05 Proximal fibula spongiosa r ange = 2.1895 '' ElseIf tagnum = 220 Then rho = 0.98 Shaft fibula (medullary) range = 2.1485 '' ElseIf tagnum = 221 Then rho = 1.11 Distal fibula spongiosa range = 2.2278 '' ElseIf tagnum = 223 Then rho = 1.11 Ankle and foot range = 2.2262 '' End If range_Al = 2.9047 range_H2O = 2.189 ElseIf gender = 6 Then Use micro gravity bone densities (all other densities the same) If tagnum = 0 Then rho = 0 range = 1 ElseIf tagnum = 1 Then rho = 1.02 Residual soft tissue range = 2.1949 Average soft tissue ElseIf tagnum = 2 Then rho = 1.02 Adrenal (L) range = 2.1949 '' Average soft tissue ElseIf tagnum = 3 Then rho = 1.02 Adrenal (R) range = 2.1949 '' Average soft tissue ElseIf tagnum = 4 Then rho = 1.04 Brain range = 2.1965 '' Brain ElseIf tagnum = 5 Then rho = 0.94 Breast

PAGE 359

359 range = 2.1581 '' Breast ElseIf tagnum = 6 Then rho = 1.07 Bronchi range = 0.5 (2.1949 + 2.2363) '' 50% average soft tissue, 50% cartilage (linear interpolation) ElseIf tagnum = 7 Then rho = 1.03 Right colon wall range = 2.3021 '' GI tract ElseIf tagnum = 8 Then rho = 1.02 Right colon contents range = 2.1 949 '' Average soft tissue ElseIf tagnum = 9 Then rho = 1.1 Ears range = 2.2363 '' Cartilage ElseIf tagnum = 10 Then rho = 1.03 Esophagus range = 2.3021 '' GI tract ElseIf tagnum = 11 Then rho = 1.05 External nose range = 2 / 3 2.1949 + 1 / 3 2.2363 '' 67% average soft tissue, 33% cartilage (linear interpolation) ElseIf tagnum = 12 Then rho = 1.02 Eyeballs range = 2.1949 '' Average soft tissue ElseIf tagnum = 13 Then rho = 1.02 Gall bladder wall range = 2.1949 '' Average soft tissue ElseIf tagnum = 14 Then rho = 1.02 Gall bladder contents range = 2.1949 '' Average soft tissue ElseIf tagnum = 15 Then rho = 1.05 Heart wall range = 2.204 '' Heart ElseIf tagnum = 16 Then rho = 1.06 Heart contents range = 2.2112 '' Blood ElseIf tagnum = 17 Then rho = 1.05 Kidney cortex (L) range = 2.2071 '' Kidney ElseIf tagnum = 18 Then rho = 1.05 Kidney cortex (R) range = 2.2071 '' Kidney

PAGE 360

360 ElseIf tagnum = 19 Then rho = 1.05 Kidney medulla (L) range = 2.2071 '' Kidney ElseIf tagnum = 20 Then rho = 1.05 Kidney medulla (R) range = 2.2071 '' Kidney ElseIf tagnum = 21 Th en rho = 1.05 Kidney pelvis (L) range = 2.2071 '' Kidney ElseIf tagnum = 22 Then rho = 1.05 Kidney pelvis (R) range = 2.2071 '' Kidney ElseIf tagnum = 23 Then rho = 1.07 Larynx range = 0.5 (2.1949 + 2.2363) '' 50% average soft tissue, 50% cartilage (linear inte rpolation) ElseIf tagnum = 24 Then rho = 1.07 Lens range = 2.2213 '' Eye lens ElseIf tagnum = 25 Then rho = 1.06 Liver range = 2.2112 '' Liver ElseIf tagnum = 26 Then rho = 0.34 Lung (L) range = 2.2092 '' Lung ElseIf tagnum = 27 Then rho = 0.34 Lung (R) range = 2.2092 '' Lung ElseIf tagnum = 28 Then rho = 1.02 Nasal layer (A) range = 2.1949 '' Average soft tissue ElseIf tagnum = 29 Then rho = 1.02 Nasal layer (P) range = 2.1949 '' Average s oft tissue ElseIf tagnum = 30 Then rho = 1.02 Oral cavity layer range = 2.1949 '' Average soft tissue ElseIf tagnum = 31 Then rho = 1.05 Ovaries range = 2.204 Ovary ElseIf tagnum = 32 Then

PAGE 361

361 rho = 1.02 Pancreas range = 2.1966 Pancreas ElseIf tagnum = 33 Then rho = 0 ## EMPTY TAG ## range = 1 ElseIf tagnum = 34 Then rho = 1.03 Pharynx range = 2.1949 '' Average soft tissue ElseIf tagnum = 35 Then rho = 1.03 Pituitary range = 2.1949 '' Average soft tissue ElseIf tagnum = 36 Then rho = 0 ## EMPTY TAG ## range = 1 ElseIf tagnum = 37 Then rho = 1.03 Rectosigmoid wall range = 2.1991 '' GI tract ElseIf tagnum = 38 Then rho = 1.02 Rectosigmoid contents range = 2.1949 '' Average soft tissue ElseIf tagnum = 39 Then rho = 1.02 Salivary glands (parotid) range = 2.1949 '' Average soft tissue ElseIf tagnum = 40 Then rho = 0 ## EMPTY TAG ## range = 1 ElseIf tagnum = 41 Then rho = 1.03 Small intestines wall range = 2.1991 '' GI tract ElseIf tagnum = 42 Then rho = 0.52 Small intestines contents range = 2.1949 '' Average soft tissue ElseIf tagnum = 43 Then rho = 1.1 Skin range = 2.211 '' Skin ElseIf tagnum = 44 Then rho = 1.04 Spinal cord range = 2.1965 '' Brain ElseIf tagnum = 45 Then rho = 1.06 Spleen range = 2.209 '' Spleen

PAGE 362

362 ElseIf tagnum = 46 Then rho = 1.03 Stomach wall range = 2.1991 '' GI tract ElseIf tagnum = 47 Then rho = 0.52 Stomach contents range = 2.1949 '' Average soft tissue ElseIf tagnum = 48 Then rho = 0 '## EMPTY TAG## range = 1 ElseIf tagnum = 49 T hen rho = 1.03 Thymus range = 2.1949 '' Average soft tissue ElseIf tagnum = 50 Then rho = 1.05 Thyroid range = 2.205 '' Thyroid ElseIf tagnum = 51 Then rho = 1.05 Tongue range = 2.2103 '' Muscle ElseIf tagnum = 52 Then rho = 1.02 Tonsil range = 2.1949 '' Average soft tissue ElseIf tagnum = 53 Then rho = 1.07 Trachea range = 0.5 (2.1 949 + 2.2363) '' 50% average soft tissue, 50% cartilage (linear interpolation) ElseIf tagnum = 54 Then rho = 1.04 Urinary bladder wall range = 2.2048 '' Urinary bladder ElseIf tagnum = 55 Then rho = 1.01 Urinary bladder contents range = 2.189 '' Water ElseIf tagnum = 56 Then rho = 1.05 Uterus range = 2.2103 '' Muscle ElseIf tagnum = 57 Then rho = 0.00120484 Air range = 2.5374 '' ICRU Dry Air ElseIf tagnum = 58 Then rho = 1.03 Left colon wall range = 2.1991 '' GI tract E lseIf tagnum = 59 Then

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363 rho = 1.08 Left colon contents range = 2.1949 '' Average soft tissue ElseIf tagnum = 60 Then rho = 1.03 Salivary glands (submaxillary) range = 2.1949 '' Average soft tissue ElseIf tagnum = 61 Then rho = 1.03 Salivary glands (sublingual) range = 2.1949 '' Average soft tissue ElseIf tagnum = 128 Then rho = 1.1 Costal cartilage (ribs) range = 2.2363 '' Cartilage ElseIf tagnum = 129 Then rho = 1.1 Cervical discs range = 2.2363 '' Cartilage ElseIf tagnum = 130 Then rho = 1.1 Thoracic discs range = 2.2363 '' Cartilage ElseIf tagnum = 131 Then rho = 1.1 Lumbar discs range = 2.2363 '' Cartilag e ElseIf tagnum >= 151 And tagnum <= 188 Then rho = 1.9 Cortical bone (all bone sites) range = 2.5042 '' ICRP Cortical Bone ElseIf tagnum = 189 Then rho = 3.0 Teeth range = 2.595 '' Teeth ElseIf tagnum = 201 Then rho = 1.36 Cranium spongiosa range = 2.3299 '' ElseIf tagnum = 202 Then rho = 1.08 Mandible spongiosa range = 2.2 '' ElseIf tagnum = 207 Then rho = 1.14 Cervical vertebra spongiosa range = 2.2547 '' ElseIf tagnum = 208 Then rho = 1.08 Thoracic vertebra spong iosa range = 2.2127 '' ElseIf tagnum = 209 Then

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364 rho = 1.09 Lumbar vertebra spongiosa range = 2.2337 '' El seIf tagnum = 205 Then rho = 1.09 Sternum spongiosa range = 2.2052 '' ElseIf tagnum = 206 Then rho = 1.11 Rib spongiosa range = 2.2366 '' ElseIf tagnum = 203 Then rho = 1.13 Scapula spongiosa range = 2.2433 '' ElseIf tagnum = 204 Then rho = 1.1 Clavicle spongiosa range = 2.2152 '' ElseIf tagnum = 211 Then rho = 1.07 Os coxa spongiosa range = 2.2175 '' ElseIf tagnum = 210 Then rho = 1.09 Sacrum spongiosa range = 2.2242 '' ElseIf tagnum = 224 Then rho = 1.08 Proximal humerus spongiosa range = 2.2016 '' ElseIf tagnum = 225 Then rho = 0.99 Upper s haft humerus (medullary) range = 2.1621 '' ElseIf tagnum = 226 Then rho = 0.98 Lower shaft humerus (medullary) range = 2.1485 '' ElseIf tagnum = 227 Then rho = 1.12 Distal humerus spongiosa range = 2.2174 '' ElseIf tagnum = 228 Then rho = 1.06 Proximal radius spongiosa range = 2.1621 '' ElseIf tagnum = 229 Then rho = 0.98 Shaft radius (medullary) range = 2.1485 '' ElseIf tagnum = 230 Then rho = 1.08 Distal radius spongiosa range = 2.2176 ''

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365 ElseIf tagnum = 231 Then rho = 1.13 Proximal ulna spongiosa range = 2.2202 '' ElseIf tagnum = 232 Then rho = 0.98 Shaft ulna (medullary) range = 2.1485 '' ElseIf tagnum = 233 Then rho = 1.11 Distal ulna spongiosa range = 2.21 '' ElseIf tagnum = 234 Then rho = 1.12 Wrist and hand range = 2.2174 '' ElseIf tagnum = 212 Then rho = 1.1 Proximal femur spongiosa range = 2.2227 '' ElseIf tagnum = 213 Then rho = 0.98 Upper shaft femur (medullary) range = 2.1621 '' El seIf tagnum = 214 Then rho = 0.98 Lower shaft femur (medullary) range = 2.1485 '' ElseIf tagnum = 215 Then rho = 1.11 Distal femur spongiosa range = 2.2262 '' ElseIf tagnum = 222 Then rho = 1.11 Patella range = 2.2262 '' ElseIf tag num = 216 Then rho = 1.08 Proximal tibia spongiosa range = 2.2156 '' ElseIf tagnum = 217 Then rho = 0.98 Shaft tibia (medulla ry) range = 2.1485 '' ElseIf tagnum = 218 Then rho = 1.09 Distal tibia spongiosa range = 2.2189 '' ElseIf tagnum = 219 Then rho = 1.05 Proximal fibula spongiosa range = 2.1895 '' ElseIf tagnum = 220 Then rho = 0.98 Shaft fibula (medullary) range = 2.1485 ''

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366 ElseIf tagnum = 221 Then rho = 1.11 Distal fibula spongiosa range = 2.2278 '' ElseIf tagnum = 223 Then rho = 1.11 Ankle and foot range = 2.2262 '' End If range_Al = 2.9047 ra nge_H2O = 2.189 ElseIf gender = 0 Then Use unit density and water interaction information If tagnum = 0 Then rho = 0 range = 1 ElseIf tagnum > = 1 And tagnum <= 56 Then rho = 1.0 range = 1.299 ^ 1 ElseIf tagnum = 57 Then rho = 0.00120484 Air range = 1.136 ^ 1 '' ICRU Dry Air ElseIf tagnum >= 58 And tagnum <= 234 Then rho = 1.0 range = 1.299 ^ 1 End If range_Al = 1.0 range_H2O = 1.299 ^ 1 End If If a_min = 1 Then This is the case where the dose point lies on a voxel boundary, and there is no remainder distance If i_first(0) = i_last(0) And i_first(1) = i_last(1) And i_first(2) = i _last(2) Then Case of identical entrance and exit voxels d12(src, dose) = Math.Sqrt((x_first(0) p2c(dose, 0)) ^ 2 + (x_first(1) p2c(dose, 1)) ^ 2 + (x_first(2) p2c(dose, 2)) ^ 2) / radius rho range ^ 1 Else Case of different entrance and exit voxels d12(src, dose) = d12(src, dose) + Math.Sqrt((p2c(dose, 0) x_next(0)) ^ 2 + (p2c(dose, 1) x_next(1)) ^ 2 + (p2c(dose, 2) x_next(2)) ^ 2) / radius rho range ^ 1 End If Else a_rest = 1 a_store

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367 For k = 0 To 2 x_bound(k) = p1(src, k) + a_store (p2c(dose, k) p1(src, k)) Next d12(src, dose) = d12(src, dose) + a_rest rho (range ^ 1) End If d12(src, dose) = d12(src, dose) radius range_H2O Console.WriteLine(d12(src, dose)) Next Next Write time statistics to screen Dim traceend As Double = Timer Console.WriteLine ("Ray tracing took & (traceend tracestart) & "seconds to complete.") Console.WriteLine(" ") Write angles, direct ion cosines, and resulting radiological path lengths to Excel spreadsheet Dim excelfile As String Dim oExcel As Object Dim oBook As Object Dim oSheet As Object Dim ray As Integer = 0 Console.WriteLine ("***** STEP 6: WRITE RESULTS TO EXCEL *****") '' Start a new workbook in Excel oExcel = CreateObject("Excel.Application") oBook = oExcel.Workbooks.Add '' Record headers oSheet = oBook.Worksheets(1) oSheet.Range("A1").Value = "Theta (radians)" oSheet.Range("B1").Value = "Phi (radians)" oSheet.Range("C1").Value = "DirCosine Alpha" oSheet.Range("D1").Value = "DirCosine Beta" oSheet.Range("E1").Value = "DirCosine Gamma" oSheet.Range("F1").Value = "H2O Path Length" '' Calculate corresponding angles Dim theta(UBound(dircos, 1)) As Double Dim phee(UBound(dircos, 1)) As Double

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368 For ray = 0 To UBound(dircos, 1) theta(ray) = Math.Acos(dircos(ray, 2)) If dircos(ray, 0) >= 0 And dircos(ray, 1) >= 0 Then phee(ray) = Math.Atan(dircos(ray, 1) / dircos(ray, 0)) ElseIf dircos(ray, 0) < 0 And dircos(ray, 1) >= 0 Then phee(ray) = Math.PI Math.Atan(dircos(ray, 1) / Math.Abs(dircos(ray, 0))) ElseIf dircos(ray, 0) < 0 And dircos(ray, 1) < 0 Then phee(ray) = Math.PI + Math.Atan(Math.Abs(dircos(ray, 1)) / Math.Abs(dircos(ray, 0)) ) ElseIf dircos(ray, 0) >= 0 And dircos(ray, 1) < 0 Then phee(ray) = 2 Math.PI Math.Atan(Math.Abs(dircos(ray, 1)) / dircos(ray, 0)) End If Next '' Transfer arrays to worksheet For ray = 0 To UBound(theta) oSheet.Range("A" & ray + 2).Value = theta(ray) oSheet.Range("B" & ray + 2).Value = phee(ray) oSheet.Range("C" & ray + 2).Value = dircos(ray, 0) oSheet.Range("D" & ray + 2).Value = dircos(ra y, 1) oSheet.Range("E" & ray + 2).Value = dircos(ray, 2) Next Dim p2w(UBound(p2c, 2), UBound(p2c, 1)) As Single For k = 0 To UBound(p2c, 2) For dose = 0 To UBound(p2c, 1) p2w(k, dose) = p2c( dose, k) Next Next oSheet.Range("F2").Resize(UBound(d12, 1) + 1, UBound(d12, 2) + 1) = d12 oSheet = oBook.Worksheets(2) oSheet.Range("A1").Resize(UBound(p2w, 1) + 1, UBound(p2w, 2) + 1) = p2w '' Save workbook and quit Excel Console.WriteLine ("Input the name of the Excel file without extension:") excelfile = Console.ReadLine() oBook.SaveAs("E: \ NASA GSRP \ Ray Trace \ Results \ & excelfile & ".xls") oSheet = Nothing oBook = Nothing oExcel.Quit() oExcel = Nothing GC.Collect() '' Notify user of sucessful file creation

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369 Console.WriteLine ("Data successfully written to Excel file! Would you like to ray trace another organ? (1 = Yes, 2 = No)") Dim input As Integer input = Console.ReadLine() If input = 1 Then Erase p2 Erase p2c Erase p2w Erase theta Erase phee Erase dircos Erase p1 Erase d12 GoTo doserep End If End Sub End Module

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370 APPENDIX D INITIAL BODY SELF SHIELDING DISTRIBUTI ONS Figure D 1 BFO initial body se lf shielding distributions using 1000 randomly selected points Figure D 2 Skin initial body self shielding distributions using 1000 radomly selected points

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371 Figure D 3 Small intestines initial body self shielding distributions using 500 radomly selected points Figure D 4 Muscle initial body self shielding distributions using 1000 radomly selected points

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372 Figure D 5 Right eye lens initial body s elf shielding distributions Figure D 6 Left eye lens initial body self shielding distributions

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373 Figure D 7 Right eyeball initial body self shielding distributions Figure D 8 Left eyeball initial body self shielding distributions

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374 Figure D 9 Anterior stomach initial body self shielding distributions Figure D 10 Posterior stomach initial body self shielding distributi ons

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375 Figure D 11 Ascending colon initial body self shielding distributions Figure D 12 Transverse colon initial body self shielding distributions

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376 Figure D 13 Descending colon initial body self shielding distributions Figure D 14 Rectosigmoid colon initial body self shielding distributions

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377 Figure D 15 Left liver initial body self shielding distributions Figure D 16 Right liver initial body self shielding distributions

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378 Figure D 17 Right upper mid lung initial body self shielding distributions Figure D 18 Left upper mid lung initial body self shielding distributions

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379 Figure D 19 Right middle anterior lung initial body self shielding distributions Figure D 20 Right middle mid lung initial body self shielding distributions

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380 Figure D 21 Right middle posterior lung initial body self shielding distributions Figure D 22 Left middle anterior lung initial body self shielding distributions

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381 Figure D 23 Left middle mid lung initial body self shielding distributions Figure D 24 Left middle posterior lung initial body self shielding distributions

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382 Figure D 25 Right base anterior lung initial body s elf shielding distributions Figure D 26 Right base posterior lung initial body self shielding distributions

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383 Figure D 27 Left base anterior lung initial body self shielding distributions Figure D 28 Left base posterior lung initial body self shielding distributions

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384 Figure D 29 Esophagus initial body self shielding distributions Figure D 30 Bladder initial body self shielding distributions

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385 Figure D 31 Left thyroid initial body self shielding distributions Figure D 32 Right thyroid initial body self shielding distributions

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386 Figure D 33 Anterior brain initial body self shielding distributions Figure D 34 Mid brain initial body self shielding distributions

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387 Figure D 35 Posterior brain initial body self shielding distributions Fig ure D 36 Left parotid initial body self shielding distributions

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388 Figure D 37 Right parotid initial body self shielding distributions Figure D 38 Left adrenal initial body s elf shielding distributions

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389 Figure D 39 Right adrenal initial body self shielding distributions Figure D 40 ET region initial body self shielding distributions

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390 Figure D 41 Gallbladder initial body self shielding distributions Figure D 42 Heart initial body self shielding distributions

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391 Figure D 43 Left kidney initial body self shielding distributions Figure D 44 Right kidney initial body self shielding distributions

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392 Figure D 45 Lateral pancreas initial body self shielding distributions Figure D 46 Mid pancreas initial body self shielding distributions

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393 Figure D 47 Medial pancreas initial body self shielding distributions Figure D 48 Spleen initial body self shielding distributions

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394 Figure D 49 Left thymus initial body self shielding distributions Figure D 50 Right thymus initial body self shielding distributions

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395 Figure D 51 Oral mucosa initial body self shielding distributions Figure D 52 Left testis initial body self shielding distributions

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396 Figure D 53 Right testis initial body self shielding distributions Figure D 54 Prostate initial body self shieldin g distributions

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397 Figure D 55 Left ovary initial body self shielding distributions Figure D 56 Right ovary initial body self shielding distributions

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398 Figure D 57 Uterus initial body self shielding distributions Figure D 58 Left breast initial body self shielding distributions

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399 Figure D 59 Right breast initial body self shielding distributions

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400 APPENDIX E INITIAL ORGAN DOSE E QUIVALENTS Table E 1. Trapped proton organ dose equivalent rates (mSv d 1 ) with suit shielding Organ CAM M5 M50 M95 CAF F5 F50 F95 BFO 0.50 0.48 0.46 0.44 0.53 0.55 0.53 0.50 Skin 0.93 0.97 0.94 0.94 1.01 1.01 0.99 0.98 Small Intestine 0.49 0.43 0.38 0.35 0.52 0.47 0.45 0.42 Muscle 0.62 0.61 0.58 0.55 0.65 0.66 0.63 0.61 R Eye Lens 0.92 0.90 0.85 0.83 0.95 1.08 0.94 1.01 L Eye Lens 0.93 0.90 0.85 0.83 0.96 1.06 0.94 0.98 R Eyeball 0.63 0.64 0.64 0.62 0.66 0.68 0.66 0.65 L Eyeball 0.64 0.64 0.64 0.62 0.67 0.67 0.66 0.64 Anterior Stomach 0.46 0.45 0.42 0.41 0.49 0.55 0.57 0.50 Posterior Stomach 0.38 0.36 0.35 0.31 0.41 0.46 0.44 0.43 Ascending Colon 0.52 0.46 0.44 0.39 0.55 0.49 0.46 0.43 Transverse Colon 0.54 0.67 0.64 0.65 0.57 0.72 0.69 0.68 Descending Colon 0.54 0.45 0.41 0.37 0.57 0.48 0.46 0.43 Rectosigmoid Colon 0.45 0.39 0.33 0.31 0.48 0.42 0.37 0.35 L Liver 0.37 0.35 0.33 0.33 0.40 0.44 0.43 0.39 R Liver 0.38 0.37 0.35 0.31 0.41 0.42 0.40 0.38 R Upper Mid Lung 0.53 0.53 0.51 0.50 0.56 0.59 0.56 0.54 L Upper Mid Lung 0.54 0.52 0.51 0.49 0.57 0.59 0.57 0.55 R Middle Anterior Lung 0.58 0.50 0.48 0.48 0.61 0.58 0.57 0.53 R Middle Mid Lung 0.52 0.53 0.50 0.48 0.56 0.57 0.56 0.52 R Middle Posterior Lung 0.54 0.51 0.49 0.48 0.58 0.55 0.53 0.50 L Middle Anterior Lung 0.58 0.50 0.49 0.49 0.61 0.59 0.60 0.54 L Middle Mid Lung 0.53 0.51 0.49 0.47 0.57 0.56 0.55 0.51 L Middle Posterior Lung 0.55 0.49 0.48 0.46 0.58 0.54 0.52 0.50 R Base Anterior Lung 0.52 0.51 0.46 0.44 0.55 0.55 0.56 0.50 R Base Posterior Lung 0.53 0.48 0.47 0.44 0.56 0.54 0.52 0.48 L Base Anterior Lung 0.52 0.52 0.50 0.47 0.55 0.56 0.56 0.50 L Base Posterior Lung 0.53 0.50 0.50 0.49 0.56 0.53 0.51 0.47 Esophagus 0.44 0.37 0.35 0.33 0.47 0.44 0.41 0.39 Bladder 0.35 0.35 0.30 0.28 0.38 0.40 0.39 0.37 L Thyroid 0.76 0.54 0.51 0.50 0.79 0.63 0.60 0.56 R Thyroid 0.76 0.55 0.52 0.52 0.79 0.66 0.61 0.56 Anterior Brain 0.54 0.52 0.50 0.48 0.57 0.55 0.53 0.50 Mid Brain 0.53 0.51 0.49 0.47 0.56 0.54 0.52 0.49 Posterior Brain 0.62 0.61 0.58 0.56 0.66 0.64 0.59 0.59 L Parotid 0.67 0.68 0.65 0.64 0.70 0.67 0.68 0.66

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401 Table E 1. Continued Organ CAM M5 M50 M95 CAF F5 F50 F95 R Parotid 0.67 0.66 0.65 0.62 0.70 0.69 0.66 0.66 L Adrenal 0.42 0.34 0.33 0.30 0.45 0.42 0.39 0.37 R Adrenal 0.40 0.34 0.34 0.30 0.43 0.43 0.40 0.38 ET Region 0.81 0.59 0.55 0.56 0.84 0.61 0.59 0.54 Gallbladder 0.46 0.37 0.34 0.31 0.49 0.43 0.42 0.38 Heart 0.41 0.36 0.35 0.34 0.45 0.44 0.44 0.40 L Kidney 0.41 0.37 0.36 0.33 0.44 0.52 0.48 0.46 R Kidney 0.41 0.39 0.38 0.35 0.44 0.56 0.52 0.46 Lateral Pancreas 0.35 0.38 0.35 0.31 0.38 0.45 0.42 0.40 Mid Pancreas 0.36 0.34 0.31 0.28 0.40 0.40 0.38 0.35 Medial Pancreas 0.40 0.33 0.30 0.27 0.43 0.40 0.37 0.36 Spleen 0.41 0.40 0.41 0.38 0.44 0.54 0.49 0.47 L Thymus 0.60 0.44 0.41 0.40 0.63 0.52 0.49 0.47 R Thymus 0.60 0.43 0.42 0.42 0.63 0.52 0.49 0.47 Oral mucosa 0.60 0.50 0.48 0.46 0.63 0.54 0.51 0.49 L Testis 0.58 0.57 0.56 0.56 N/A N/A N/A N/A R Testis 0.58 0.57 0.56 0.56 N/A N/A N/A N/A Prostate 0.36 0.38 0.33 0.32 N/A N/A N/A N/A L Ovary N/A N/A N/A N/A 0.43 0.41 0.40 0.38 R Ovary N/A N/A N/A N/A 0.43 0.41 0.41 0.38 Uterus N/A N/A N/A N/A 0.38 0.39 0.37 0.35 L Breast N/A N/A N/A N/A 0.69 0.76 0.69 0.68 R Breast N/A N/A N/A N/A 0.69 0.76 0.71 0.71 Table E 2. GCR organ dose equivalent rates (mSv d 1 ) with suit shielding Organ CAM M5 M50 M95 CAF F5 F50 F95 BFO 1.85 1.82 1.78 1.74 1.91 1.95 1.91 1.85 Skin 2.45 2.51 2.47 2.45 2.58 2.58 2.54 2.52 Small Intestine 1.84 1.72 1.63 1.58 1.90 1.81 1.77 1.71 Muscle 2.07 2.05 1.99 1.95 2.12 2.13 2.08 2.05 R Eye Lens 2.55 2.50 2.44 2.40 2.59 2.65 2.55 2.59 L Eye Lens 2.57 2.49 2.44 2.40 2.61 2.63 2.55 2.57 R Eyeball 2.11 2.13 2.12 2.09 2.17 2.20 2.16 2.14 L Eyeball 2.12 2.13 2.12 2.09 2.18 2.19 2.16 2.13 Anterior Stomach 1.78 1.77 1.70 1.69 1.84 1.96 1.99 1.87 Posterior Stomach 1.62 1.59 1.56 1.50 1.68 1.78 1.75 1.72 Ascending Colon 1.91 1.79 1.74 1.65 1.96 1.84 1.79 1.72 Transverse Colon 1.93 2.15 2.09 2.11 1.99 2.22 2.17 2.16 Descending Colon 1.94 1.76 1.69 1.62 2.00 1.81 1.79 1.73

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402 Table E 2. Continued Organ CAM M5 M50 M95 CAF F5 F50 F95 Rectosigmoid Colon 1.76 1.65 1.53 1.49 1.82 1.70 1.61 1.57 L Liver 1.60 1.58 1.54 1.52 1.65 1.73 1.73 1.65 R Liver 1.62 1.62 1.56 1.50 1.68 1.71 1.66 1.63 R Upper Mid Lung 1.91 1.91 1.88 1.85 1.97 2.03 1.98 1.93 L Upper Mid Lung 1.94 1.89 1.87 1.84 2.00 2.03 1.99 1.95 R Middle Anterior Lung 2.01 1.86 1.82 1.82 2.07 2.01 2.00 1.92 R Middle Mid Lung 1.90 1.92 1.86 1.83 1.97 2.00 1.98 1.90 R Middle Posterior Lung 1.94 1.87 1.85 1.82 2.01 1.96 1.92 1.86 L Middle Anterior Lung 2.01 1.86 1.84 1.83 2.07 2.03 2.04 1.94 L Middle Mid Lung 1.93 1.87 1.84 1.81 1.99 1.97 1.96 1.88 L Middle Posterior Lung 1.95 1.83 1.82 1.78 2.01 1.94 1.90 1.86 R Base Anterior Lung 1.89 1.87 1.78 1.75 1.95 1.96 1.97 1.85 R Base Posterior Lung 1.92 1.82 1.80 1.75 1.98 1.93 1.89 1.81 L Base Anterior Lung 1.90 1.90 1.85 1.81 1.96 1.98 1.97 1.86 L Base Posterior Lung 1.92 1.85 1.86 1.83 1.98 1.91 1.87 1.80 Esophagus 1.74 1.60 1.57 1.53 1.80 1.74 1.68 1.64 Bladder 1.56 1.58 1.48 1.44 1.62 1.67 1.64 1.60 L Thyroid 2.31 1.93 1.88 1.87 2.35 2.10 2.04 1.97 R Thyroid 2.31 1.95 1.89 1.89 2.35 2.14 2.05 1.97 Anterior Brain 1.93 1.89 1.85 1.81 2.00 1.96 1.91 1.86 Mid Brain 1.91 1.88 1.83 1.80 1.97 1.94 1.89 1.84 Posterior Brain 2.10 2.07 2.01 1.97 2.16 2.13 2.03 2.04 L Parotid 2.17 2.18 2.14 2.11 2.22 2.17 2.19 2.14 R Parotid 2.17 2.16 2.14 2.09 2.22 2.20 2.16 2.14 L Adrenal 1.70 1.55 1.54 1.48 1.75 1.70 1.64 1.61 R Adrenal 1.67 1.56 1.54 1.48 1.73 1.72 1.66 1.62 ET Region 2.38 2.02 1.95 1.97 2.43 2.08 2.04 1.95 Gallbladder 1.78 1.62 1.55 1.49 1.83 1.72 1.71 1.62 Heart 1.69 1.59 1.57 1.55 1.75 1.75 1.75 1.66 L Kidney 1.68 1.62 1.60 1.53 1.74 1.90 1.82 1.79 R Kidney 1.69 1.65 1.63 1.57 1.75 1.97 1.90 1.79 Lateral Pancreas 1.56 1.63 1.57 1.50 1.62 1.76 1.70 1.66 Mid Pancreas 1.59 1.55 1.50 1.44 1.65 1.66 1.62 1.57 Medial Pancreas 1.66 1.53 1.48 1.42 1.72 1.66 1.61 1.58 Spleen 1.69 1.66 1.68 1.63 1.75 1.93 1.85 1.80 L Thymus 2.06 1.73 1.69 1.67 2.12 1.89 1.84 1.80 R Thymus 2.05 1.71 1.71 1.70 2.10 1.89 1.84 1.79 Oral mucosa 2.05 1.86 1.83 1.79 2.11 1.93 1.87 1.84 L Testis 2.00 1.99 1.96 1.96 N/A N/A N/A N/A

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403 Table E 2. Continued Organ CAM M5 M50 M95 CAF F5 F50 F95 R Testis 2.00 1.99 1.96 1.96 N/A N/A N/A N/A Prostate 1.58 1.64 1.54 1.52 N/A N/A N/A N/A L Ovary N/A N/A N/A N/A 1.73 1.68 1.67 1.63 R Ovary N/A N/A N/A N/A 1.73 1.69 1.68 1.62 Uterus N/A N/A N/A N/A 1.62 1.65 1.61 1.56 L Breast N/A N/A N/A N/A 2.22 2.34 2.23 2.21 R Breast N/A N/A N/A N/A 2.22 2.34 2.26 2.25 Table E 3. February 1956 SPE organ dose equivalents (Sv) with suit shielding Organ CAM M5 M50 M95 CAF F5 F50 F95 BFO 0.56 0.56 0.54 0.53 0.59 0.64 0.63 0.58 Skin 2.52 2.65 2.61 2.62 2.61 2.74 2.69 2.70 Small Intestine 0.53 0.48 0.43 0.41 0.56 0.52 0.50 0.48 Muscle 0.88 0.86 0.80 0.77 0.93 0.92 0.86 0.86 R Eye Lens 1.97 1.96 1.68 1.60 2.06 3.09 2.19 2.73 L Eye Lens 2.04 1.95 1.68 1.60 2.13 2.98 2.19 2.53 R Eyeball 0.66 0.72 0.73 0.71 0.70 0.77 0.75 0.75 L Eyeball 0.67 0.72 0.73 0.71 0.72 0.75 0.76 0.73 Anterior Stomach 0.51 0.50 0.46 0.46 0.53 0.62 0.65 0.55 Posterior Stomach 0.41 0.40 0.40 0.38 0.43 0.47 0.46 0.45 Ascending Colon 0.58 0.49 0.47 0.43 0.61 0.51 0.49 0.46 Transverse Colon 0.59 1.09 1.04 1.12 0.62 1.28 1.25 1.15 Descending Colon 0.59 0.47 0.44 0.42 0.63 0.50 0.49 0.46 Rectosigmoid Colon 0.48 0.43 0.39 0.38 0.50 0.44 0.41 0.40 L Liver 0.41 0.40 0.39 0.39 0.43 0.46 0.47 0.43 R Liver 0.41 0.41 0.40 0.38 0.43 0.44 0.42 0.42 R Upper Mid Lung 0.53 0.52 0.50 0.50 0.56 0.60 0.56 0.54 L Upper Mid Lung 0.54 0.51 0.50 0.49 0.57 0.60 0.57 0.56 R Middle Anterior Lung 0.62 0.50 0.49 0.50 0.66 0.59 0.62 0.56 R Middle Mid Lung 0.51 0.52 0.49 0.48 0.54 0.56 0.55 0.52 R Middle Posterior Lung 0.55 0.50 0.49 0.48 0.58 0.53 0.52 0.49 L Middle Anterior Lung 0.60 0.50 0.50 0.51 0.64 0.62 0.67 0.59 L Middle Mid Lung 0.53 0.50 0.49 0.48 0.56 0.54 0.54 0.51 L Middle Posterior Lung 0.55 0.49 0.48 0.47 0.58 0.53 0.51 0.50 R Base Anterior Lung 0.54 0.54 0.48 0.48 0.57 0.55 0.57 0.50 R Base Posterior Lung 0.54 0.49 0.49 0.47 0.57 0.53 0.52 0.48 L Base Anterior Lung 0.54 0.55 0.52 0.50 0.57 0.56 0.57 0.50 L Base Posterior Lung 0.54 0.50 0.52 0.53 0.57 0.52 0.50 0.48 Esophagus 0.44 0.40 0.39 0.38 0.47 0.44 0.43 0.42

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404 Table E 3. Continued Organ CAM M5 M50 M95 CAF F5 F50 F95 Bladder 0.40 0.40 0.37 0.36 0.42 0.43 0.42 0.41 L Thyroid 1.36 0.60 0.55 0.55 1.44 0.84 0.75 0.63 R Thyroid 1.36 0.64 0.58 0.59 1.44 0.93 0.77 0.63 Anterior Brain 0.50 0.49 0.47 0.46 0.53 0.52 0.50 0.48 Mid Brain 0.49 0.48 0.47 0.46 0.52 0.50 0.49 0.47 Posterior Brain 0.62 0.61 0.57 0.55 0.66 0.64 0.57 0.59 L Parotid 0.85 0.92 0.85 0.83 0.90 0.85 0.94 0.88 R Parotid 0.84 0.87 0.85 0.79 0.90 0.91 0.86 0.87 L Adrenal 0.45 0.39 0.39 0.37 0.47 0.44 0.42 0.41 R Adrenal 0.44 0.40 0.39 0.37 0.46 0.45 0.43 0.42 ET Region 1.55 0.73 0.64 0.68 1.63 0.73 0.70 0.58 Gallbladder 0.50 0.42 0.39 0.38 0.53 0.45 0.46 0.42 Heart 0.44 0.40 0.40 0.39 0.46 0.45 0.46 0.43 L Kidney 0.44 0.42 0.42 0.39 0.46 0.59 0.52 0.51 R Kidney 0.44 0.43 0.43 0.41 0.46 0.66 0.61 0.51 Lateral Pancreas 0.40 0.42 0.40 0.38 0.41 0.47 0.44 0.43 Mid Pancreas 0.41 0.39 0.38 0.36 0.43 0.43 0.41 0.40 Medial Pancreas 0.43 0.39 0.37 0.36 0.45 0.43 0.41 0.40 Spleen 0.44 0.43 0.45 0.43 0.46 0.62 0.53 0.50 L Thymus 0.68 0.45 0.43 0.43 0.73 0.52 0.49 0.48 R Thymus 0.68 0.44 0.44 0.44 0.73 0.52 0.49 0.47 Oral mucosa 0.59 0.49 0.48 0.46 0.63 0.52 0.49 0.48 L Testis 0.86 0.75 0.81 0.83 N/A N/A N/A N/A R Testis 0.87 0.77 0.82 0.83 N/A N/A N/A N/A Prostate 0.44 0.42 0.39 0.39 N/A N/A N/A N/A L Ovary N/A N/A N/A N/A 0.45 0.43 0.44 0.43 R Ovary N/A N/A N/A N/A 0.45 0.44 0.44 0.42 Uterus N/A N/A N/A N/A 0.42 0.42 0.41 0.40 L Breast N/A N/A N/A N/A 0.90 1.13 0.89 0.86 R Breast N/A N/A N/A N/A 0.90 1.10 0.91 0.93 Table E 4. October 1989 SPE organ dose equivalents (Sv) with suit shielding Organ CAM M5 M50 M95 CAF F5 F50 F95 BFO 1.11 1.13 1.08 1.05 1.25 1.54 1.47 1.22 Skin 13.46 14.33 14.08 14.21 14.15 14.87 14.54 14.67 Small Intestine 1.00 0.75 0.54 0.47 1.11 0.90 0.84 0.73 Muscle 2.85 2.75 2.45 2.29 3.11 3.01 2.70 2.74 R Eye Lens 9.20 9.19 7.37 6.88 9.76 17.27 10.63 14.49 L Eye Lens 9.65 9.19 7.34 6.87 10.23 16.54 10.66 13.13

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405 Table E 4. Continued Organ CAM M5 M50 M95 CAF F5 F50 F95 R Eyeball 1.56 1.86 1.94 1.83 1.77 2.13 2.05 2.04 L Eyeball 1.63 1.86 1.94 1.83 1.84 2.03 2.05 1.92 Anterior Stomach 0.87 0.86 0.66 0.69 0.99 1.39 1.57 1.10 Posterior Stomach 0.41 0.38 0.36 0.30 0.48 0.68 0.62 0.59 Ascending Colon 1.20 0.79 0.71 0.54 1.36 0.89 0.79 0.63 Transverse Colon 1.25 3.91 3.70 4.14 1.42 4.98 4.86 4.24 Descending Colon 1.27 0.70 0.59 0.49 1.44 0.80 0.78 0.65 Rectosigmoid Colon 0.72 0.52 0.33 0.30 0.83 0.51 0.40 0.36 L Liver 0.40 0.38 0.35 0.35 0.46 0.61 0.68 0.51 R Liver 0.42 0.42 0.35 0.29 0.49 0.52 0.45 0.45 R Upper Mid Lung 0.93 0.88 0.82 0.79 1.07 1.25 1.08 1.01 L Upper Mid Lung 0.99 0.84 0.81 0.77 1.14 1.26 1.14 1.07 R Middle Anterior Lung 1.38 0.82 0.77 0.83 1.56 1.24 1.39 1.12 R Middle Mid Lung 0.87 0.88 0.76 0.72 0.99 1.05 1.03 0.88 R Middle Posterior Lung 1.03 0.80 0.75 0.71 1.18 0.92 0.86 0.76 L Middle Anterior Lung 1.31 0.81 0.81 0.89 1.49 1.36 1.65 1.24 L Middle Mid Lung 0.93 0.79 0.73 0.70 1.07 0.96 1.00 0.83 L Middle Posterior Lung 1.05 0.73 0.71 0.66 1.19 0.93 0.85 0.80 R Base Anterior Lung 1.01 1.02 0.76 0.74 1.16 1.03 1.14 0.81 R Base Posterior Lung 0.98 0.78 0.79 0.72 1.13 0.95 0.90 0.73 L Base Anterior Lung 1.01 1.05 0.90 0.82 1.16 1.08 1.15 0.82 L Base Posterior Lung 0.99 0.83 0.94 0.97 1.13 0.87 0.81 0.70 Esophagus 0.54 0.36 0.33 0.30 0.63 0.52 0.45 0.41 Bladder 0.36 0.36 0.26 0.23 0.43 0.46 0.46 0.42 L Thyroid 5.45 1.32 1.10 1.12 5.87 2.52 2.07 1.48 R Thyroid 5.45 1.54 1.21 1.31 5.87 3.05 2.18 1.49 Anterior Brain 0.79 0.73 0.65 0.60 0.91 0.85 0.76 0.68 Mid Brain 0.74 0.68 0.62 0.58 0.85 0.79 0.72 0.63 Posterior Brain 1.37 1.30 1.14 1.05 1.56 1.45 1.11 1.21 L Parotid 2.53 2.90 2.58 2.49 2.81 2.52 3.04 2.74 R Parotid 2.51 2.65 2.58 2.28 2.78 2.83 2.57 2.68 L Adrenal 0.58 0.33 0.34 0.28 0.67 0.55 0.46 0.43 R Adrenal 0.54 0.35 0.36 0.29 0.63 0.60 0.51 0.45 ET Region 6.56 1.99 1.50 1.73 7.02 1.92 1.78 1.21 Gallbladder 0.83 0.44 0.35 0.30 0.94 0.57 0.62 0.45 Heart 0.51 0.37 0.36 0.35 0.60 0.57 0.63 0.48 L Kidney 0.55 0.48 0.47 0.37 0.64 1.28 0.94 0.92 R Kidney 0.54 0.54 0.54 0.45 0.63 1.62 1.37 0.90 Lateral Pancreas 0.34 0.46 0.38 0.30 0.40 0.65 0.55 0.49

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406 Table E 4. Continued Organ CAM M5 M50 M95 CAF F5 F50 F95 Mid Pancreas 0.38 0.33 0.29 0.23 0.45 0.45 0.40 0.35 Medial Pancreas 0.50 0.30 0.26 0.21 0.58 0.45 0.38 0.36 Spleen 0.55 0.51 0.63 0.57 0.63 1.41 0.97 0.86 L Thymus 1.71 0.57 0.52 0.51 1.92 0.88 0.76 0.70 R Thymus 1.72 0.55 0.56 0.57 1.93 0.88 0.76 0.68 Oral mucosa 1.23 0.76 0.70 0.64 1.40 0.86 0.75 0.70 L Testis 2.70 2.09 2.46 2.57 N/A N/A N/A N/A R Testis 2.71 2.20 2.46 2.57 N/A N/A N/A N/A Prostate 0.55 0.49 0.37 0.36 N/A N/A N/A N/A L Ovary N/A N/A N/A N/A 0.55 0.50 0.52 0.49 R Ovary N/A N/A N/A N/A 0.55 0.51 0.53 0.47 Uterus N/A N/A N/A N/A 0.43 0.42 0.40 0.35 L Breast N/A N/A N/A N/A 2.79 3.98 2.77 2.62 R Breast N/A N/A N/A N/A 2.79 3.87 2.85 2.96 Table E 5. August 1972 SPE organ dose equivalents (Sv) with suit shielding Organ CAM M5 M50 M95 CAF F5 F50 F95 BFO 1.83 1.86 1.77 1.71 2.08 2.59 2.46 2.03 Skin 18.09 19.16 18.85 18.97 18.86 19.95 19.51 19.61 Small Intestine 1.62 1.17 0.80 0.67 1.87 1.43 1.33 1.13 Muscle 4.71 4.51 4.04 3.78 5.13 4.98 4.48 4.49 R Eye Lens 13.92 13.81 11.64 10.94 14.64 22.71 15.75 19.97 L Eye Lens 14.57 13.79 11.61 10.92 15.30 21.76 15.78 18.41 R Eyeball 2.70 3.25 3.40 3.20 3.08 3.74 3.58 3.56 L Eyeball 2.83 3.25 3.40 3.20 3.22 3.56 3.59 3.35 Anterior Stomach 1.42 1.41 1.02 1.09 1.64 2.41 2.75 1.87 Posterior Stomach 0.51 0.47 0.45 0.34 0.63 1.01 0.90 0.85 Ascending Colon 2.04 1.25 1.11 0.79 2.33 1.44 1.26 0.95 Transverse Colon 2.14 6.71 6.36 7.06 2.44 8.24 8.05 7.22 Descending Colon 2.17 1.07 0.87 0.70 2.48 1.26 1.22 0.98 Rectosigmoid Colon 1.11 0.74 0.40 0.36 1.31 0.69 0.49 0.43 L Liver 0.50 0.48 0.42 0.45 0.61 0.89 1.04 0.73 R Liver 0.53 0.54 0.42 0.32 0.65 0.71 0.58 0.59 R Upper Mid Lung 1.49 1.38 1.27 1.22 1.75 2.09 1.77 1.64 L Upper Mid Lung 1.61 1.29 1.26 1.17 1.88 2.11 1.88 1.76 R Middle Anterior Lung 2.37 1.28 1.18 1.31 2.70 2.08 2.37 1.85 R Middle Mid Lung 1.35 1.37 1.15 1.08 1.59 1.69 1.67 1.38 R Middle Posterior Lung 1.69 1.23 1.14 1.07 1.96 1.44 1.33 1.14 L Middle Anterior Lung 2.24 1.26 1.26 1.44 2.57 2.32 2.86 2.10

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407 Table E 5. Continued Organ CAM M5 M50 M95 CAF F5 F50 F95 L Middle Mid Lung 1.48 1.19 1.09 1.05 1.74 1.53 1.61 1.29 L Middle Posterior Lung 1.71 1.09 1.06 0.97 1.99 1.47 1.32 1.22 R Base Anterior Lung 1.67 1.70 1.20 1.16 1.94 1.68 1.91 1.26 R Base Posterior Lung 1.60 1.21 1.24 1.11 1.87 1.51 1.42 1.11 L Base Anterior Lung 1.67 1.74 1.45 1.31 1.94 1.78 1.92 1.27 L Base Posterior Lung 1.62 1.29 1.52 1.60 1.89 1.35 1.24 1.05 Esophagus 0.73 0.41 0.37 0.32 0.89 0.68 0.55 0.50 Bladder 0.45 0.44 0.27 0.23 0.55 0.60 0.62 0.56 L Thyroid 8.98 2.27 1.84 1.89 9.58 4.36 3.60 2.57 R Thyroid 8.98 2.67 2.06 2.26 9.58 5.20 3.79 2.59 Anterior Brain 1.16 1.06 0.91 0.81 1.39 1.28 1.11 0.97 Mid Brain 1.06 0.96 0.85 0.78 1.28 1.15 1.03 0.87 Posterior Brain 2.33 2.19 1.88 1.71 2.69 2.49 1.82 2.02 L Parotid 4.45 5.09 4.55 4.40 4.92 4.42 5.26 4.77 R Parotid 4.41 4.67 4.55 4.02 4.88 4.93 4.51 4.68 L Adrenal 0.85 0.39 0.42 0.32 1.02 0.77 0.61 0.57 R Adrenal 0.77 0.42 0.45 0.34 0.93 0.86 0.70 0.60 ET Region 10.51 3.46 2.60 3.03 11.16 3.39 3.12 2.05 Gallbladder 1.33 0.60 0.43 0.34 1.54 0.81 0.92 0.60 Heart 0.70 0.45 0.44 0.44 0.85 0.79 0.93 0.65 L Kidney 0.80 0.67 0.67 0.50 0.96 2.21 1.56 1.52 R Kidney 0.76 0.79 0.80 0.65 0.92 2.85 2.38 1.49 Lateral Pancreas 0.38 0.61 0.47 0.34 0.48 0.95 0.77 0.68 Mid Pancreas 0.47 0.37 0.31 0.23 0.58 0.57 0.50 0.42 Medial Pancreas 0.68 0.33 0.27 0.20 0.83 0.57 0.46 0.44 Spleen 0.78 0.71 0.98 0.86 0.93 2.41 1.60 1.39 L Thymus 2.98 0.80 0.71 0.70 3.36 1.39 1.16 1.05 R Thymus 3.00 0.77 0.79 0.82 3.38 1.37 1.16 1.02 Oral mucosa 2.06 1.13 1.02 0.91 2.39 1.33 1.12 1.03 L Testis 4.73 3.71 4.33 4.56 N/A N/A N/A N/A R Testis 4.76 3.91 4.35 4.56 N/A N/A N/A N/A Prostate 0.80 0.68 0.48 0.48 N/A N/A N/A N/A L Ovary N/A N/A N/A N/A 0.76 0.67 0.74 0.70 R Ovary N/A N/A N/A N/A 0.76 0.68 0.74 0.64 Uterus N/A N/A N/A N/A 0.55 0.52 0.49 0.42 L Breast N/A N/A N/A N/A 5.02 7.01 4.98 4.71 R Breast N/A N/A N/A N/A 5.02 6.82 5.12 5.30

PAGE 408

408 Table E 6. Trapped proton organ dose equivalent rates (mSv d 1 ) with PV shielding Organ CAM M5 M50 M95 CAF F5 F50 F95 BFO 0.45 0.44 0.42 0.40 0.48 0.50 0.48 0.45 Skin 0.76 0.78 0.76 0.76 0.82 0.82 0.80 0.79 Small Intestine 0.45 0.39 0.35 0.32 0.47 0.43 0.41 0.39 Muscle 0.55 0.54 0.51 0.49 0.57 0.58 0.56 0.54 R Eye Lens 0.78 0.76 0.73 0.71 0.80 0.86 0.78 0.82 L Eye Lens 0.79 0.76 0.73 0.71 0.81 0.85 0.78 0.80 R Eyeball 0.57 0.58 0.57 0.56 0.60 0.61 0.59 0.58 L Eyeball 0.57 0.58 0.57 0.56 0.60 0.60 0.59 0.58 Anterior Stomach 0.42 0.41 0.38 0.37 0.44 0.50 0.51 0.46 Posterior Stomach 0.35 0.33 0.32 0.29 0.37 0.42 0.40 0.39 Ascending Colon 0.47 0.42 0.40 0.36 0.50 0.44 0.42 0.39 Transverse Colon 0.49 0.59 0.56 0.56 0.51 0.62 0.60 0.59 Descending Colon 0.49 0.41 0.38 0.34 0.52 0.43 0.42 0.39 Rectosigmoid Colon 0.41 0.36 0.30 0.28 0.44 0.38 0.34 0.32 L Liver 0.34 0.33 0.31 0.30 0.36 0.40 0.40 0.36 R Liver 0.35 0.34 0.32 0.29 0.37 0.39 0.36 0.35 R Upper Mid Lung 0.48 0.48 0.46 0.45 0.51 0.53 0.51 0.49 L Upper Mid Lung 0.49 0.47 0.46 0.45 0.52 0.54 0.52 0.50 R Middle Anterior Lung 0.52 0.46 0.44 0.43 0.55 0.53 0.52 0.48 R Middle Mid Lung 0.48 0.48 0.46 0.44 0.51 0.52 0.51 0.48 R Middle Posterior Lung 0.49 0.46 0.45 0.44 0.52 0.50 0.48 0.46 L Middle Anterior Lung 0.52 0.46 0.45 0.44 0.55 0.53 0.54 0.49 L Middle Mid Lung 0.49 0.46 0.45 0.43 0.51 0.51 0.50 0.47 L Middle Posterior Lung 0.50 0.44 0.44 0.42 0.53 0.49 0.47 0.46 R Base Anterior Lung 0.47 0.46 0.42 0.40 0.50 0.50 0.51 0.45 R Base Posterior Lung 0.48 0.44 0.42 0.40 0.51 0.49 0.47 0.43 L Base Anterior Lung 0.47 0.47 0.45 0.43 0.50 0.51 0.51 0.46 L Base Posterior Lung 0.48 0.45 0.45 0.44 0.51 0.48 0.46 0.43 Esophagus 0.40 0.34 0.32 0.30 0.43 0.40 0.37 0.36 Bladder 0.32 0.32 0.28 0.26 0.35 0.37 0.36 0.34 L Thyroid 0.66 0.49 0.46 0.46 0.68 0.56 0.53 0.50 R Thyroid 0.66 0.50 0.47 0.47 0.68 0.58 0.54 0.50 Anterior Brain 0.49 0.47 0.45 0.43 0.52 0.50 0.48 0.46 Mid Brain 0.48 0.47 0.45 0.43 0.51 0.49 0.47 0.45 Posterior Brain 0.57 0.55 0.53 0.51 0.59 0.58 0.53 0.54 L Parotid 0.59 0.60 0.58 0.57 0.62 0.60 0.60 0.58 R Parotid 0.59 0.59 0.58 0.55 0.62 0.61 0.59 0.58 L Adrenal 0.38 0.31 0.31 0.28 0.41 0.39 0.36 0.34 R Adrenal 0.37 0.32 0.31 0.28 0.40 0.39 0.37 0.34

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409 Table E 6. Continued Organ CAM M5 M50 M95 CAF F5 F50 F95 ET Region 0.70 0.53 0.49 0.50 0.72 0.55 0.53 0.49 Gallbladder 0.42 0.34 0.31 0.28 0.44 0.39 0.39 0.35 Heart 0.38 0.33 0.32 0.31 0.41 0.41 0.41 0.36 L Kidney 0.37 0.34 0.33 0.30 0.40 0.47 0.43 0.42 R Kidney 0.38 0.36 0.35 0.32 0.40 0.50 0.47 0.42 Lateral Pancreas 0.32 0.35 0.32 0.29 0.35 0.41 0.38 0.36 Mid Pancreas 0.33 0.31 0.29 0.26 0.36 0.37 0.35 0.33 Medial Pancreas 0.37 0.30 0.28 0.25 0.39 0.37 0.34 0.33 Spleen 0.38 0.37 0.37 0.35 0.40 0.49 0.45 0.42 L Thymus 0.54 0.40 0.38 0.37 0.57 0.47 0.45 0.43 R Thymus 0.54 0.39 0.39 0.38 0.57 0.47 0.45 0.43 Oral mucosa 0.54 0.46 0.44 0.42 0.57 0.49 0.46 0.45 L Testis 0.51 0.51 0.49 0.49 N/A N/A N/A N/A R Testis 0.52 0.51 0.50 0.49 N/A N/A N/A N/A Prostate 0.33 0.35 0.31 0.29 N/A N/A N/A N/A L Ovary N/A N/A N/A N/A 0.40 0.38 0.37 0.35 R Ovary N/A N/A N/A N/A 0.40 0.38 0.37 0.35 Uterus N/A N/A N/A N/A 0.35 0.36 0.34 0.32 L Breast N/A N/A N/A N/A 0.62 0.67 0.62 0.61 R Breast N/A N/A N/A N/A 0.62 0.67 0.63 0.63 Table E 7. GCR organ dose equivalent rates (mSv d 1 ) with PV shielding Organ CAM M5 M50 M95 CAF F5 F50 F95 BFO 1.78 1.75 1.72 1.68 1.83 1.87 1.84 1.78 Skin 2.32 2.37 2.34 2.32 2.44 2.44 2.40 2.38 Small Intestine 1.77 1.66 1.59 1.53 1.83 1.74 1.71 1.66 Muscle 1.98 1.96 1.91 1.87 2.02 2.04 1.99 1.96 R Eye Lens 2.41 2.36 2.31 2.28 2.44 2.50 2.41 2.45 L Eye Lens 2.42 2.36 2.31 2.28 2.46 2.48 2.41 2.43 R Eyeball 2.01 2.03 2.02 1.99 2.07 2.10 2.06 2.04 L Eyeball 2.02 2.03 2.03 1.99 2.08 2.09 2.06 2.03 Anterior Stomach 1.72 1.71 1.65 1.64 1.77 1.88 1.91 1.80 Posterior Stomach 1.57 1.55 1.52 1.47 1.63 1.72 1.69 1.66 Ascending Colon 1.83 1.73 1.68 1.60 1.88 1.77 1.73 1.66 Transverse Colon 1.86 2.05 2.00 2.01 1.91 2.11 2.07 2.05 Descending Colon 1.86 1.70 1.64 1.58 1.91 1.75 1.73 1.67 Rectosigmoid Colon 1.70 1.61 1.50 1.46 1.76 1.64 1.57 1.53 L Liver 1.55 1.54 1.50 1.49 1.61 1.68 1.68 1.60 R Liver 1.58 1.57 1.52 1.46 1.63 1.65 1.61 1.59

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410 Table E 7. Continued Organ CAM M5 M50 M95 CAF F5 F50 F95 R Upper Mid Lung 1.84 1.84 1.81 1.79 1.89 1.94 1.90 1.86 L Upper Mid Lung 1.86 1.82 1.80 1.77 1.92 1.95 1.91 1.87 R Middle Anterior Lung 1.92 1.79 1.76 1.75 1.98 1.93 1.91 1.85 R Middle Mid Lung 1.83 1.84 1.79 1.76 1.89 1.92 1.90 1.83 R Middle Posterior Lung 1.87 1.80 1.78 1.75 1.92 1.88 1.84 1.79 L Middle Anterior Lung 1.93 1.79 1.78 1.77 1.98 1.94 1.96 1.87 L Middle Mid Lung 1.85 1.81 1.78 1.75 1.91 1.89 1.88 1.81 L Middle Posterior Lung 1.87 1.77 1.76 1.72 1.93 1.86 1.83 1.79 R Base Anterior Lung 1.82 1.80 1.72 1.70 1.87 1.89 1.89 1.78 R Base Posterior Lung 1.84 1.75 1.73 1.69 1.90 1.86 1.82 1.75 L Base Anterior Lung 1.83 1.83 1.78 1.74 1.88 1.90 1.89 1.80 L Base Posterior Lung 1.85 1.78 1.79 1.77 1.90 1.83 1.80 1.74 Esophagus 1.68 1.56 1.53 1.49 1.74 1.68 1.63 1.59 Bladder 1.52 1.53 1.44 1.41 1.58 1.62 1.60 1.56 L Thyroid 2.19 1.85 1.81 1.80 2.23 2.01 1.95 1.89 R Thyroid 2.19 1.88 1.82 1.82 2.23 2.04 1.96 1.89 Anterior Brain 1.86 1.82 1.78 1.75 1.92 1.88 1.84 1.80 Mid Brain 1.83 1.81 1.77 1.74 1.90 1.86 1.82 1.78 Posterior Brain 2.01 1.98 1.93 1.90 2.06 2.04 1.94 1.95 L Parotid 2.07 2.08 2.04 2.01 2.12 2.07 2.08 2.04 R Parotid 2.06 2.06 2.04 1.99 2.11 2.10 2.06 2.04 L Adrenal 1.64 1.51 1.50 1.44 1.70 1.65 1.60 1.57 R Adrenal 1.62 1.52 1.50 1.45 1.67 1.67 1.61 1.57 ET Region 2.26 1.94 1.87 1.89 2.30 1.98 1.95 1.87 Gallbladder 1.72 1.57 1.51 1.46 1.77 1.66 1.66 1.58 Heart 1.64 1.55 1.53 1.51 1.70 1.69 1.69 1.61 L Kidney 1.63 1.57 1.55 1.49 1.68 1.83 1.75 1.73 R Kidney 1.64 1.60 1.59 1.53 1.69 1.88 1.83 1.73 Lateral Pancreas 1.53 1.59 1.53 1.47 1.58 1.70 1.65 1.61 Mid Pancreas 1.55 1.51 1.47 1.41 1.60 1.62 1.57 1.53 Medial Pancreas 1.61 1.49 1.44 1.39 1.67 1.62 1.57 1.54 Spleen 1.63 1.61 1.63 1.58 1.69 1.86 1.78 1.73 L Thymus 1.97 1.68 1.64 1.62 2.02 1.82 1.77 1.74 R Thymus 1.96 1.66 1.66 1.65 2.01 1.82 1.78 1.73 Oral mucosa 1.96 1.79 1.76 1.73 2.02 1.85 1.80 1.78 L Testis 1.91 1.90 1.87 1.88 N/A N/A N/A N/A R Testis 1.91 1.91 1.88 1.88 N/A N/A N/A N/A Prostate 1.54 1.59 1.50 1.48 N/A N/A N/A N/A L Ovary N/A N/A N/A N/A 1.67 1.63 1.62 1.59

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411 Table E 7. Continued Organ CAM M5 M50 M95 CAF F5 F50 F95 R Ovary N/A N/A N/A N/A 1.67 1.64 1.63 1.58 Uterus N/A N/A N/A N/A 1.58 1.60 1.57 1.52 L Breast N/A N/A N/A N/A 2.11 2.22 2.12 2.10 R Breast N/A N/A N/A N/A 2.11 2.21 2.14 2.14 Table E 8. February 1956 SPE organ dose equivalents (Sv) with PV shielding Organ CAM M5 M50 M95 CAF F5 F50 F95 BFO 0.49 0.49 0.48 0.47 0.51 0.54 0.53 0.50 Skin 1.27 1.33 1.31 1.31 1.31 1.37 1.35 1.35 Small Intestine 0.48 0.44 0.41 0.39 0.50 0.47 0.45 0.44 Muscle 0.66 0.64 0.61 0.59 0.68 0.68 0.65 0.64 R Eye Lens 1.14 1.12 1.03 0.99 1.18 1.50 1.22 1.39 L Eye Lens 1.17 1.12 1.03 0.99 1.21 1.45 1.22 1.32 R Eyeball 0.57 0.60 0.60 0.59 0.60 0.63 0.62 0.62 L Eyeball 0.58 0.60 0.60 0.59 0.60 0.62 0.62 0.60 Anterior Stomach 0.46 0.46 0.43 0.42 0.48 0.53 0.55 0.49 Posterior Stomach 0.40 0.39 0.38 0.37 0.41 0.44 0.43 0.42 Ascending Colon 0.51 0.45 0.43 0.41 0.53 0.47 0.45 0.43 Transverse Colon 0.52 0.77 0.74 0.77 0.54 0.85 0.83 0.79 Descending Colon 0.52 0.44 0.42 0.40 0.54 0.46 0.45 0.43 Rectosigmoid Colon 0.44 0.41 0.37 0.36 0.46 0.42 0.39 0.38 L Liver 0.39 0.39 0.38 0.37 0.41 0.43 0.44 0.41 R Liver 0.40 0.40 0.38 0.37 0.41 0.42 0.41 0.40 R Upper Mid Lung 0.48 0.48 0.47 0.46 0.50 0.53 0.51 0.49 L Upper Mid Lung 0.49 0.47 0.47 0.46 0.51 0.53 0.51 0.50 R Middle Anterior Lung 0.54 0.46 0.45 0.46 0.56 0.53 0.54 0.50 R Middle Mid Lung 0.47 0.48 0.46 0.45 0.50 0.51 0.50 0.48 R Middle Posterior Lung 0.50 0.47 0.46 0.45 0.52 0.49 0.48 0.46 L Middle Anterior Lung 0.53 0.46 0.46 0.47 0.56 0.54 0.57 0.52 L Middle Mid Lung 0.48 0.46 0.45 0.45 0.50 0.49 0.50 0.47 L Middle Posterior Lung 0.50 0.45 0.45 0.44 0.52 0.49 0.47 0.46 R Base Anterior Lung 0.49 0.49 0.45 0.44 0.51 0.50 0.51 0.46 R Base Posterior Lung 0.49 0.46 0.45 0.44 0.51 0.49 0.48 0.45 L Base Anterior Lung 0.49 0.49 0.47 0.46 0.51 0.51 0.51 0.46 L Base Posterior Lung 0.49 0.46 0.48 0.47 0.51 0.48 0.47 0.45 Esophagus 0.42 0.39 0.38 0.37 0.44 0.42 0.41 0.40 Bladder 0.38 0.38 0.36 0.35 0.40 0.41 0.40 0.39 L Thyroid 0.90 0.52 0.49 0.49 0.93 0.65 0.60 0.54 R Thyroid 0.90 0.54 0.50 0.51 0.93 0.70 0.62 0.54

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412 Table E 8. Continued Anterior Brain 0.47 0.46 0.45 0.44 0.49 0.48 0.47 0.45 Mid Brain 0.46 0.45 0.44 0.44 0.48 0.47 0.46 0.45 Posterior Brain 0.55 0.54 0.51 0.50 0.57 0.56 0.51 0.53 L Parotid 0.66 0.70 0.67 0.65 0.70 0.67 0.71 0.68 R Parotid 0.66 0.67 0.66 0.63 0.69 0.70 0.67 0.67 L Adrenal 0.42 0.38 0.38 0.36 0.44 0.42 0.40 0.40 R Adrenal 0.41 0.38 0.38 0.36 0.43 0.43 0.41 0.40 ET Region 0.97 0.59 0.54 0.56 1.01 0.60 0.58 0.51 Gallbladder 0.45 0.40 0.38 0.36 0.47 0.42 0.43 0.40 Heart 0.41 0.39 0.38 0.38 0.43 0.43 0.43 0.41 L Kidney 0.42 0.40 0.39 0.37 0.43 0.51 0.47 0.46 R Kidney 0.42 0.41 0.40 0.39 0.43 0.56 0.52 0.46 Lateral Pancreas 0.38 0.40 0.38 0.36 0.40 0.44 0.42 0.41 Mid Pancreas 0.39 0.38 0.37 0.35 0.41 0.41 0.40 0.39 Medial Pancreas 0.41 0.37 0.36 0.35 0.43 0.41 0.39 0.39 Spleen 0.42 0.41 0.42 0.41 0.43 0.53 0.48 0.46 L Thymus 0.58 0.42 0.41 0.41 0.60 0.47 0.46 0.44 R Thymus 0.58 0.42 0.42 0.42 0.60 0.47 0.46 0.44 Oral mucosa 0.53 0.46 0.45 0.43 0.55 0.48 0.46 0.45 L Testis 0.65 0.60 0.63 0.64 N/A N/A N/A N/A R Testis 0.65 0.61 0.63 0.64 N/A N/A N/A N/A Prostate 0.40 0.40 0.38 0.37 N/A N/A N/A N/A L Ovary N/A N/A N/A N/A 0.42 0.41 0.41 0.40 R Ovary N/A N/A N/A N/A 0.42 0.42 0.41 0.40 Uterus N/A N/A N/A N/A 0.40 0.40 0.39 0.38 L Breast N/A N/A N/A N/A 0.70 0.81 0.70 0.68 R Breast N/A N/A N/A N/A 0.70 0.80 0.71 0.71 Table E 9. October 1989 SPE organ dose equivalents (Sv) with PV shielding Organ CAM M5 M50 M95 CAF F5 F50 F95 BFO 0.78 0.78 0.74 0.71 0.87 1.02 0.97 0.84 Skin 4.90 5.18 5.09 5.11 5.09 5.40 5.28 5.29 Small Intestine 0.73 0.56 0.43 0.37 0.81 0.66 0.62 0.55 Muscle 1.62 1.55 1.41 1.33 1.74 1.71 1.56 1.55 R Eye Lens 4.07 4.02 3.50 3.32 4.26 6.05 4.50 5.46 L Eye Lens 4.24 4.01 3.49 3.31 4.43 5.82 4.51 5.09 R Eyeball 1.12 1.27 1.31 1.24 1.24 1.43 1.37 1.36 L Eyeball 1.16 1.27 1.31 1.24 1.29 1.38 1.37 1.30 Anterior Stomach 0.65 0.65 0.51 0.53 0.73 0.98 1.09 0.81 Posterior Stomach 0.34 0.32 0.30 0.25 0.39 0.54 0.49 0.47

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413 Table E 9. Continued Organ CAM M5 M50 M95 CAF F5 F50 F95 Ascending Colon 0.87 0.61 0.55 0.43 0.97 0.68 0.61 0.50 Transverse Colon 0.90 2.18 2.07 2.25 1.01 2.59 2.51 2.31 Descending Colon 0.91 0.55 0.47 0.39 1.02 0.62 0.60 0.51 Rectosigmoid Colon 0.56 0.42 0.28 0.25 0.63 0.42 0.33 0.30 L Liver 0.33 0.32 0.29 0.29 0.38 0.48 0.53 0.41 R Liver 0.34 0.34 0.29 0.24 0.40 0.43 0.37 0.37 R Upper Mid Lung 0.72 0.69 0.64 0.62 0.81 0.92 0.82 0.76 L Upper Mid Lung 0.76 0.65 0.64 0.60 0.86 0.93 0.85 0.81 R Middle Anterior Lung 0.99 0.64 0.60 0.63 1.11 0.91 0.99 0.82 R Middle Mid Lung 0.67 0.69 0.61 0.57 0.77 0.80 0.79 0.68 R Middle Posterior Lung 0.78 0.63 0.60 0.57 0.88 0.72 0.68 0.60 L Middle Anterior Lung 0.96 0.64 0.63 0.68 1.07 0.99 1.14 0.89 L Middle Mid Lung 0.72 0.62 0.58 0.56 0.81 0.75 0.77 0.65 L Middle Posterior Lung 0.79 0.58 0.57 0.52 0.89 0.72 0.66 0.62 R Base Anterior Lung 0.76 0.76 0.59 0.57 0.85 0.79 0.85 0.63 R Base Posterior Lung 0.75 0.60 0.60 0.55 0.85 0.73 0.69 0.58 L Base Anterior Lung 0.76 0.78 0.68 0.63 0.86 0.82 0.86 0.64 L Base Posterior Lung 0.76 0.64 0.71 0.72 0.85 0.68 0.63 0.56 Esophagus 0.44 0.30 0.28 0.25 0.51 0.43 0.37 0.34 Bladder 0.30 0.30 0.22 0.20 0.35 0.38 0.38 0.35 L Thyroid 2.80 0.94 0.80 0.81 2.97 1.55 1.33 1.03 R Thyroid 2.80 1.05 0.87 0.92 2.97 1.78 1.38 1.04 Anterior Brain 0.63 0.59 0.53 0.49 0.72 0.67 0.61 0.55 Mid Brain 0.59 0.55 0.51 0.48 0.68 0.63 0.58 0.52 Posterior Brain 1.02 0.97 0.86 0.80 1.14 1.07 0.85 0.91 L Parotid 1.61 1.78 1.62 1.57 1.75 1.60 1.82 1.68 R Parotid 1.60 1.66 1.62 1.46 1.74 1.74 1.62 1.65 L Adrenal 0.46 0.28 0.29 0.24 0.53 0.44 0.37 0.35 R Adrenal 0.43 0.29 0.30 0.25 0.49 0.47 0.41 0.37 ET Region 3.21 1.29 1.03 1.15 3.38 1.29 1.20 0.88 Gallbladder 0.62 0.36 0.29 0.25 0.70 0.46 0.49 0.36 Heart 0.42 0.31 0.30 0.29 0.48 0.46 0.50 0.39 L Kidney 0.44 0.39 0.38 0.31 0.51 0.91 0.70 0.68 R Kidney 0.43 0.43 0.43 0.36 0.50 1.11 0.96 0.68 Lateral Pancreas 0.28 0.37 0.31 0.25 0.33 0.51 0.44 0.40 Mid Pancreas 0.32 0.27 0.24 0.20 0.37 0.37 0.33 0.30 Medial Pancreas 0.40 0.26 0.22 0.18 0.46 0.37 0.32 0.30 Spleen 0.44 0.41 0.49 0.44 0.50 0.97 0.72 0.65 L Thymus 1.18 0.46 0.42 0.41 1.30 0.68 0.60 0.55

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414 Table E 9. Continued Organ CAM M5 M50 M95 CAF F5 F50 F95 R Thymus 1.18 0.44 0.45 0.46 1.30 0.68 0.60 0.54 Oral mucosa 0.92 0.60 0.56 0.51 1.04 0.68 0.60 0.56 L Testis 1.61 1.35 1.50 1.56 N/A N/A N/A N/A R Testis 1.62 1.40 1.50 1.56 N/A N/A N/A N/A Prostate 0.40 0.39 0.30 0.30 N/A N/A N/A N/A L Ovary N/A N/A N/A N/A 0.45 0.41 0.42 0.40 R Ovary N/A N/A N/A N/A 0.45 0.41 0.42 0.38 Uterus N/A N/A N/A N/A 0.35 0.35 0.33 0.29 L Breast N/A N/A N/A N/A 1.79 2.35 1.78 1.70 R Breast N/A N/A N/A N/A 1.79 2.29 1.83 1.87 Table E 10. August 1972 SPE organ dose equivalents (Sv) with PV shielding Organ CAM M5 M50 M95 CAF F5 F50 F95 BFO 1.23 1.23 1.17 1.13 1.39 1.68 1.59 1.34 Skin 8.25 8.70 8.56 8.58 8.54 9.09 8.88 8.89 Small Intestine 1.12 0.81 0.58 0.49 1.28 0.98 0.92 0.79 Muscle 2.78 2.66 2.40 2.26 3.01 2.94 2.67 2.64 R Eye Lens 7.09 6.97 6.16 5.83 7.40 10.12 7.79 9.25 L Eye Lens 7.39 6.96 6.14 5.82 7.70 9.73 7.81 8.68 R Eyeball 1.84 2.15 2.23 2.10 2.07 2.44 2.34 2.32 L Eyeball 1.92 2.15 2.23 2.10 2.16 2.34 2.34 2.20 Anterior Stomach 1.00 0.99 0.74 0.78 1.14 1.63 1.84 1.29 Posterior Stomach 0.40 0.36 0.34 0.26 0.48 0.74 0.67 0.63 Ascending Colon 1.39 0.90 0.80 0.59 1.58 1.02 0.90 0.70 Transverse Colon 1.46 3.91 3.71 4.04 1.65 4.59 4.47 4.14 Descending Colon 1.48 0.78 0.64 0.52 1.67 0.91 0.88 0.72 Rectosigmoid Colon 0.80 0.55 0.31 0.28 0.94 0.52 0.37 0.33 L Liver 0.38 0.37 0.33 0.34 0.46 0.65 0.75 0.54 R Liver 0.40 0.41 0.32 0.25 0.49 0.54 0.45 0.45 R Upper Mid Lung 1.07 1.00 0.93 0.89 1.25 1.46 1.26 1.17 L Upper Mid Lung 1.15 0.94 0.92 0.86 1.34 1.48 1.33 1.25 R Middle Anterior Lung 1.62 0.93 0.86 0.94 1.83 1.45 1.60 1.28 R Middle Mid Lung 0.98 1.00 0.85 0.80 1.15 1.22 1.20 1.00 R Middle Posterior Lung 1.20 0.90 0.84 0.79 1.38 1.05 0.98 0.84 L Middle Anterior Lung 1.55 0.92 0.92 1.02 1.76 1.60 1.90 1.44 L Middle Mid Lung 1.07 0.88 0.81 0.78 1.24 1.11 1.15 0.94 L Middle Posterior Lung 1.22 0.80 0.79 0.72 1.40 1.07 0.96 0.89 R Base Anterior Lung 1.17 1.19 0.87 0.84 1.35 1.20 1.34 0.92 R Base Posterior Lung 1.15 0.88 0.89 0.80 1.33 1.09 1.02 0.81

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415 Table E 10. Continued Organ CAM M5 M50 M95 CAF F5 F50 F95 L Base Anterior Lung 1.18 1.21 1.03 0.94 1.36 1.27 1.34 0.93 L Base Posterior Lung 1.16 0.94 1.08 1.11 1.34 0.98 0.91 0.77 Esophagus 0.56 0.32 0.29 0.25 0.67 0.52 0.43 0.39 Bladder 0.34 0.34 0.21 0.18 0.41 0.46 0.47 0.42 L Thyroid 4.97 1.53 1.27 1.30 5.26 2.69 2.28 1.71 R Thyroid 4.97 1.76 1.40 1.52 5.26 3.10 2.39 1.73 Anterior Brain 0.86 0.79 0.69 0.61 1.03 0.95 0.83 0.73 Mid Brain 0.80 0.73 0.65 0.60 0.95 0.86 0.77 0.66 Posterior Brain 1.63 1.54 1.33 1.22 1.86 1.74 1.30 1.43 L Parotid 2.80 3.14 2.85 2.76 3.07 2.78 3.19 2.94 R Parotid 2.78 2.91 2.85 2.55 3.05 3.05 2.82 2.90 L Adrenal 0.63 0.30 0.32 0.25 0.74 0.57 0.46 0.43 R Adrenal 0.57 0.32 0.34 0.27 0.68 0.64 0.53 0.45 ET Region 5.66 2.20 1.72 1.96 5.95 2.21 2.04 1.42 Gallbladder 0.94 0.45 0.33 0.27 1.08 0.60 0.67 0.45 Heart 0.53 0.35 0.34 0.34 0.63 0.59 0.68 0.49 L Kidney 0.59 0.50 0.50 0.37 0.70 1.50 1.10 1.06 R Kidney 0.57 0.58 0.59 0.48 0.68 1.88 1.60 1.05 Lateral Pancreas 0.30 0.46 0.36 0.27 0.37 0.70 0.58 0.51 Mid Pancreas 0.36 0.29 0.25 0.18 0.44 0.44 0.38 0.33 Medial Pancreas 0.51 0.26 0.21 0.16 0.62 0.44 0.36 0.34 Spleen 0.58 0.53 0.70 0.62 0.69 1.60 1.12 0.99 L Thymus 1.98 0.60 0.53 0.53 2.21 1.00 0.85 0.77 R Thymus 1.98 0.58 0.59 0.61 2.21 0.99 0.85 0.75 Oral mucosa 1.45 0.84 0.76 0.68 1.67 0.98 0.83 0.77 L Testis 2.87 2.36 2.65 2.79 N/A N/A N/A N/A R Testis 2.88 2.46 2.66 2.79 N/A N/A N/A N/A Prostate 0.55 0.51 0.36 0.36 N/A N/A N/A N/A L Ovary N/A N/A N/A N/A 0.57 0.50 0.55 0.52 R Ovary N/A N/A N/A N/A 0.57 0.52 0.55 0.48 Uterus N/A N/A N/A N/A 0.41 0.40 0.38 0.33 L Breast N/A N/A N/A N/A 3.18 4.22 3.17 3.02 R Breast N/A N/A N/A N/A 3.18 4.12 3.25 3.34 Table E 11. Trapped proton organ dose equivalent rates (mSv d 1 ) with shelter shielding Organ CAM M5 M50 M95 CAF F5 F50 F95 BFO 0.28 0.27 0.26 0.25 0.30 0.31 0.30 0.28 Skin 0.42 0.44 0.43 0.42 0.46 0.46 0.44 0.44

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416 Table E 11. Continued Organ CAM M5 M50 M95 CAF F5 F50 F95 Small Intestine 0.28 0.25 0.22 0.21 0.30 0.27 0.26 0.25 Muscle 0.33 0.33 0.31 0.30 0.35 0.35 0.34 0.33 R Eye Lens 0.44 0.43 0.42 0.41 0.45 0.47 0.44 0.45 L Eye Lens 0.45 0.43 0.42 0.41 0.46 0.47 0.44 0.45 R Eyeball 0.35 0.35 0.35 0.34 0.37 0.37 0.36 0.36 L Eyeball 0.35 0.35 0.35 0.34 0.37 0.37 0.36 0.35 Anterior Stomach 0.26 0.26 0.24 0.24 0.28 0.31 0.32 0.28 Posterior Stomach 0.22 0.22 0.21 0.19 0.24 0.27 0.26 0.25 Ascending Colon 0.30 0.27 0.25 0.23 0.31 0.28 0.27 0.25 Transverse Colon 0.30 0.35 0.33 0.33 0.32 0.37 0.35 0.35 Descending Colon 0.30 0.26 0.24 0.22 0.32 0.27 0.27 0.25 Rectosigmoid Colon 0.26 0.23 0.20 0.19 0.28 0.25 0.22 0.21 L Liver 0.22 0.21 0.20 0.20 0.24 0.26 0.25 0.23 R Liver 0.23 0.22 0.21 0.19 0.24 0.25 0.24 0.23 R Upper Mid Lung 0.30 0.30 0.29 0.29 0.32 0.33 0.32 0.31 L Upper Mid Lung 0.31 0.30 0.29 0.28 0.32 0.33 0.32 0.31 R Middle Anterior Lung 0.32 0.29 0.28 0.27 0.34 0.33 0.32 0.30 R Middle Mid Lung 0.30 0.30 0.29 0.28 0.32 0.33 0.32 0.30 R Middle Posterior Lung 0.31 0.29 0.28 0.28 0.32 0.31 0.30 0.29 L Middle Anterior Lung 0.32 0.29 0.28 0.28 0.34 0.33 0.33 0.31 L Middle Mid Lung 0.30 0.29 0.28 0.27 0.32 0.32 0.31 0.29 L Middle Posterior Lung 0.31 0.28 0.28 0.27 0.33 0.31 0.30 0.29 R Base Anterior Lung 0.29 0.29 0.26 0.26 0.31 0.31 0.31 0.29 R Base Posterior Lung 0.30 0.28 0.27 0.26 0.32 0.31 0.30 0.28 L Base Anterior Lung 0.30 0.30 0.28 0.27 0.31 0.32 0.32 0.29 L Base Posterior Lung 0.30 0.28 0.29 0.28 0.32 0.30 0.29 0.27 Esophagus 0.26 0.22 0.21 0.20 0.27 0.26 0.24 0.23 Bladder 0.21 0.21 0.18 0.17 0.23 0.24 0.23 0.22 L Thyroid 0.39 0.30 0.29 0.28 0.40 0.34 0.33 0.31 R Thyroid 0.39 0.31 0.29 0.29 0.40 0.35 0.33 0.31 Anterior Brain 0.31 0.30 0.29 0.28 0.33 0.32 0.30 0.29 Mid Brain 0.30 0.30 0.28 0.28 0.32 0.31 0.30 0.29 Posterior Brain 0.35 0.34 0.33 0.32 0.36 0.36 0.33 0.33 L Parotid 0.36 0.36 0.35 0.34 0.37 0.36 0.36 0.35 R Parotid 0.36 0.36 0.35 0.34 0.37 0.37 0.36 0.35 L Adrenal 0.24 0.21 0.20 0.18 0.26 0.25 0.23 0.22 R Adrenal 0.24 0.21 0.20 0.18 0.25 0.25 0.24 0.22 ET Region 0.41 0.32 0.31 0.31 0.42 0.34 0.33 0.31 Gallbladder 0.26 0.22 0.20 0.19 0.28 0.25 0.25 0.22

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417 Table E 11. Continued Organ CAM M5 M50 M95 CAF F5 F50 F95 Heart 0.24 0.22 0.21 0.20 0.26 0.26 0.26 0.24 L Kidney 0.24 0.22 0.21 0.19 0.26 0.29 0.27 0.26 R Kidney 0.24 0.23 0.22 0.20 0.26 0.31 0.29 0.27 Lateral Pancreas 0.21 0.23 0.21 0.19 0.23 0.26 0.25 0.23 Mid Pancreas 0.22 0.20 0.19 0.17 0.23 0.24 0.23 0.21 Medial Pancreas 0.24 0.20 0.18 0.17 0.25 0.24 0.22 0.21 Spleen 0.24 0.24 0.24 0.22 0.26 0.30 0.28 0.27 L Thymus 0.33 0.26 0.24 0.24 0.35 0.30 0.28 0.27 R Thymus 0.33 0.25 0.25 0.24 0.35 0.30 0.28 0.27 Oral mucosa 0.34 0.29 0.28 0.27 0.35 0.31 0.29 0.28 L Testis 0.31 0.31 0.30 0.30 N/A N/A N/A N/A R Testis 0.31 0.31 0.30 0.30 N/A N/A N/A N/A Prostate 0.21 0.23 0.20 0.19 N/A N/A N/A N/A L Ovary N/A N/A N/A N/A 0.25 0.24 0.24 0.23 R Ovary N/A N/A N/A N/A 0.25 0.24 0.24 0.22 Uterus N/A N/A N/A N/A 0.23 0.23 0.22 0.21 L Breast N/A N/A N/A N/A 0.37 0.40 0.37 0.37 R Breast N/A N/A N/A N/A 0.37 0.40 0.38 0.38 Table E 12. GCR organ dose equivalent rates (mSv d 1 ) with shelter shielding Organ CAM M5 M50 M95 CAF F5 F50 F95 BFO 1.53 1.51 1.49 1.47 1.56 1.58 1.56 1.53 Skin 1.84 1.87 1.85 1.84 1.91 1.91 1.89 1.88 Small Intestine 1.52 1.45 1.41 1.38 1.56 1.51 1.48 1.45 Muscle 1.64 1.63 1.60 1.58 1.67 1.68 1.65 1.63 R Eye Lens 1.89 1.87 1.84 1.82 1.92 1.95 1.89 1.92 L Eye Lens 1.90 1.87 1.84 1.82 1.92 1.94 1.89 1.90 R Eyeball 1.67 1.68 1.67 1.66 1.71 1.72 1.70 1.69 L Eyeball 1.68 1.68 1.68 1.66 1.71 1.71 1.70 1.68 Anterior Stomach 1.49 1.49 1.45 1.44 1.52 1.59 1.61 1.54 Posterior Stomach 1.40 1.39 1.37 1.34 1.44 1.50 1.47 1.46 Ascending Colon 1.56 1.50 1.47 1.42 1.59 1.52 1.50 1.46 Transverse Colon 1.57 1.68 1.65 1.65 1.61 1.72 1.69 1.68 Descending Colon 1.58 1.48 1.44 1.40 1.61 1.51 1.50 1.46 Rectosigmoid Colon 1.48 1.42 1.35 1.33 1.51 1.45 1.40 1.38 L Liver 1.39 1.38 1.36 1.35 1.42 1.47 1.47 1.42 R Liver 1.41 1.40 1.37 1.33 1.44 1.45 1.43 1.41 R Upper Mid Lung 1.56 1.57 1.55 1.53 1.60 1.63 1.60 1.58 L Upper Mid Lung 1.58 1.55 1.54 1.53 1.61 1.63 1.61 1.59

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418 Table E 12. Continued Organ CAM M5 M50 M95 CAF F5 F50 F95 R Middle Anterior Lung 1.62 1.54 1.52 1.51 1.65 1.62 1.61 1.57 R Middle Mid Lung 1.56 1.57 1.54 1.52 1.60 1.62 1.60 1.56 R Middle Posterior Lung 1.58 1.55 1.53 1.51 1.62 1.59 1.57 1.54 L Middle Anterior Lung 1.62 1.54 1.53 1.52 1.65 1.63 1.63 1.58 L Middle Mid Lung 1.57 1.55 1.53 1.51 1.61 1.60 1.59 1.55 L Middle Posterior Lung 1.59 1.52 1.52 1.49 1.62 1.58 1.56 1.54 R Base Anterior Lung 1.55 1.54 1.49 1.48 1.59 1.60 1.60 1.53 R Base Posterior Lung 1.57 1.51 1.50 1.47 1.60 1.58 1.56 1.51 L Base Anterior Lung 1.56 1.56 1.53 1.51 1.59 1.60 1.60 1.54 L Base Posterior Lung 1.57 1.53 1.53 1.52 1.60 1.57 1.54 1.51 Esophagus 1.47 1.39 1.37 1.35 1.51 1.47 1.44 1.42 Bladder 1.37 1.38 1.32 1.30 1.41 1.43 1.42 1.39 L Thyroid 1.76 1.57 1.54 1.54 1.79 1.66 1.63 1.59 R Thyroid 1.76 1.58 1.55 1.55 1.79 1.68 1.63 1.59 Anterior Brain 1.58 1.56 1.54 1.51 1.62 1.60 1.57 1.54 Mid Brain 1.57 1.55 1.53 1.51 1.61 1.59 1.56 1.53 Posterior Brain 1.67 1.65 1.62 1.60 1.70 1.69 1.63 1.64 L Parotid 1.70 1.70 1.68 1.66 1.73 1.70 1.71 1.68 R Parotid 1.70 1.69 1.68 1.65 1.73 1.72 1.69 1.68 L Adrenal 1.45 1.37 1.36 1.32 1.48 1.45 1.42 1.40 R Adrenal 1.43 1.37 1.36 1.32 1.46 1.46 1.43 1.40 ET Region 1.80 1.62 1.58 1.59 1.83 1.65 1.63 1.58 Gallbladder 1.49 1.40 1.36 1.33 1.52 1.46 1.45 1.40 Heart 1.45 1.39 1.38 1.36 1.48 1.48 1.48 1.43 L Kidney 1.44 1.40 1.39 1.35 1.47 1.56 1.51 1.49 R Kidney 1.44 1.42 1.41 1.37 1.48 1.59 1.55 1.50 Lateral Pancreas 1.37 1.41 1.38 1.33 1.41 1.48 1.45 1.43 Mid Pancreas 1.39 1.36 1.34 1.30 1.42 1.43 1.40 1.38 Medial Pancreas 1.43 1.35 1.32 1.29 1.46 1.43 1.40 1.38 Spleen 1.44 1.43 1.43 1.40 1.47 1.57 1.53 1.50 L Thymus 1.64 1.47 1.44 1.43 1.67 1.56 1.53 1.50 R Thymus 1.63 1.46 1.46 1.45 1.67 1.56 1.53 1.50 Oral mucosa 1.64 1.54 1.52 1.50 1.67 1.58 1.55 1.53 L Testis 1.60 1.59 1.58 1.57 N/A N/A N/A N/A R Testis 1.60 1.60 1.58 1.57 N/A N/A N/A N/A Prostate 1.38 1.41 1.36 1.34 N/A N/A N/A N/A L Ovary N/A N/A N/A N/A 1.47 1.44 1.43 1.41 R Ovary N/A N/A N/A N/A 1.47 1.44 1.44 1.41 Uterus N/A N/A N/A N/A 1.41 1.42 1.40 1.37

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419 Table E 12. Continued Organ CAM M5 M50 M95 CAF F5 F50 F95 L Breast N/A N/A N/A N/A 1.72 1.78 1.73 1.72 R Breast N/A N/A N/A N/A 1.72 1.78 1.74 1.74 Table E 13. February 1956 SPE organ dose equivalents (Sv) with shelter shielding Organ CAM M5 M50 M95 CAF F5 F50 F95 BFO 0.36 0.36 0.35 0.35 0.37 0.38 0.37 0.36 Skin 0.44 0.45 0.45 0.44 0.45 0.46 0.46 0.45 Small Intestine 0.36 0.35 0.33 0.32 0.37 0.36 0.35 0.35 Muscle 0.39 0.39 0.38 0.37 0.40 0.40 0.40 0.39 R Eye Lens 0.45 0.45 0.44 0.44 0.46 0.48 0.45 0.46 L Eye Lens 0.46 0.45 0.44 0.44 0.46 0.47 0.45 0.46 R Eyeball 0.40 0.40 0.40 0.39 0.41 0.41 0.41 0.40 L Eyeball 0.40 0.40 0.40 0.39 0.41 0.41 0.41 0.40 Anterior Stomach 0.35 0.35 0.34 0.34 0.36 0.38 0.38 0.36 Posterior Stomach 0.34 0.33 0.33 0.32 0.35 0.36 0.35 0.35 Ascending Colon 0.37 0.36 0.35 0.33 0.38 0.36 0.36 0.35 Transverse Colon 0.37 0.40 0.39 0.39 0.38 0.41 0.41 0.40 Descending Colon 0.38 0.35 0.34 0.33 0.38 0.36 0.36 0.35 Rectosigmoid Colon 0.35 0.34 0.32 0.31 0.36 0.35 0.34 0.33 L Liver 0.33 0.33 0.32 0.32 0.34 0.35 0.35 0.34 R Liver 0.34 0.34 0.33 0.32 0.35 0.35 0.34 0.34 R Upper Mid Lung 0.37 0.37 0.37 0.37 0.38 0.39 0.38 0.38 L Upper Mid Lung 0.38 0.37 0.37 0.36 0.38 0.39 0.38 0.38 R Middle Anterior Lung 0.39 0.37 0.36 0.36 0.39 0.39 0.38 0.37 R Middle Mid Lung 0.37 0.38 0.37 0.36 0.38 0.39 0.38 0.37 R Middle Posterior Lung 0.38 0.37 0.37 0.36 0.39 0.38 0.38 0.37 L Middle Anterior Lung 0.39 0.37 0.36 0.36 0.39 0.39 0.39 0.38 L Middle Mid Lung 0.38 0.37 0.37 0.36 0.38 0.38 0.38 0.37 L Middle Posterior Lung 0.38 0.37 0.36 0.36 0.39 0.38 0.37 0.37 R Base Anterior Lung 0.37 0.37 0.35 0.35 0.38 0.38 0.38 0.37 R Base Posterior Lung 0.37 0.36 0.36 0.35 0.38 0.38 0.37 0.36 L Base Anterior Lung 0.37 0.37 0.36 0.36 0.38 0.38 0.38 0.37 L Base Posterior Lung 0.37 0.37 0.37 0.36 0.38 0.38 0.37 0.36 Esophagus 0.35 0.34 0.33 0.32 0.36 0.35 0.35 0.34 Bladder 0.33 0.33 0.31 0.31 0.34 0.34 0.34 0.33 L Thyroid 0.42 0.37 0.37 0.36 0.43 0.40 0.39 0.38 R Thyroid 0.42 0.38 0.37 0.37 0.43 0.40 0.39 0.38 Anterior Brain 0.38 0.37 0.37 0.36 0.39 0.38 0.38 0.37 Mid Brain 0.38 0.37 0.37 0.36 0.38 0.38 0.37 0.37

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420 Table E 13. Continued Organ CAM M5 M50 M95 CAF F5 F50 F95 Posterior Brain 0.40 0.39 0.39 0.38 0.41 0.40 0.39 0.39 L Parotid 0.41 0.41 0.40 0.40 0.41 0.41 0.41 0.40 R Parotid 0.41 0.41 0.40 0.39 0.41 0.41 0.41 0.40 L Adrenal 0.34 0.33 0.32 0.31 0.35 0.35 0.34 0.33 R Adrenal 0.34 0.33 0.32 0.31 0.35 0.35 0.34 0.33 ET Region 0.43 0.39 0.38 0.38 0.44 0.39 0.39 0.38 Gallbladder 0.35 0.33 0.32 0.31 0.36 0.35 0.35 0.34 Heart 0.35 0.33 0.33 0.32 0.35 0.35 0.35 0.34 L Kidney 0.34 0.33 0.33 0.32 0.35 0.37 0.36 0.35 R Kidney 0.34 0.34 0.33 0.32 0.35 0.38 0.37 0.35 Lateral Pancreas 0.33 0.34 0.33 0.32 0.34 0.36 0.35 0.34 Mid Pancreas 0.33 0.33 0.32 0.31 0.34 0.35 0.34 0.33 Medial Pancreas 0.34 0.32 0.32 0.31 0.35 0.34 0.34 0.33 Spleen 0.34 0.34 0.34 0.33 0.35 0.38 0.37 0.36 L Thymus 0.39 0.35 0.34 0.34 0.40 0.37 0.36 0.36 R Thymus 0.39 0.35 0.35 0.34 0.40 0.37 0.36 0.36 Oral mucosa 0.39 0.37 0.36 0.36 0.40 0.38 0.37 0.37 L Testis 0.38 0.38 0.38 0.37 N/A N/A N/A N/A R Testis 0.38 0.38 0.38 0.37 N/A N/A N/A N/A Prostate 0.33 0.34 0.32 0.32 N/A N/A N/A N/A L Ovary N/A N/A N/A N/A 0.35 0.35 0.34 0.34 R Ovary N/A N/A N/A N/A 0.35 0.35 0.34 0.34 Uterus N/A N/A N/A N/A 0.34 0.34 0.34 0.33 L Breast N/A N/A N/A N/A 0.41 0.43 0.41 0.41 R Breast N/A N/A N/A N/A 0.41 0.43 0.42 0.41 Table E 14. October 1989 SPE organ dose equivalents (Sv) with shelter shielding Organ CAM M5 M50 M95 CAF F5 F50 F95 BFO 0.24 0.24 0.22 0.21 0.26 0.29 0.27 0.25 Skin 0.61 0.63 0.62 0.61 0.62 0.66 0.65 0.64 Small Intestine 0.24 0.19 0.16 0.15 0.26 0.22 0.21 0.19 Muscle 0.35 0.35 0.32 0.31 0.38 0.38 0.35 0.34 R Eye Lens 0.61 0.59 0.55 0.54 0.63 0.71 0.62 0.67 L Eye Lens 0.62 0.59 0.55 0.53 0.64 0.69 0.62 0.65 R Eyeball 0.33 0.35 0.35 0.34 0.36 0.38 0.37 0.36 L Eyeball 0.34 0.35 0.35 0.34 0.37 0.37 0.37 0.35 Anterior Stomach 0.22 0.22 0.19 0.19 0.24 0.29 0.31 0.25 Posterior Stomach 0.15 0.14 0.13 0.12 0.17 0.21 0.19 0.18 Ascending Colon 0.27 0.22 0.20 0.17 0.29 0.23 0.22 0.19

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421 Table E 14. Continued Organ CAM M5 M50 M95 CAF F5 F50 F95 Transverse Colon 0.28 0.42 0.40 0.41 0.30 0.45 0.44 0.43 Descending Colon 0.28 0.20 0.18 0.16 0.30 0.22 0.22 0.19 Rectosigmoid Colon 0.20 0.17 0.13 0.12 0.22 0.17 0.15 0.13 L Liver 0.14 0.14 0.13 0.13 0.16 0.19 0.19 0.16 R Liver 0.15 0.15 0.13 0.11 0.17 0.18 0.16 0.16 R Upper Mid Lung 0.25 0.25 0.24 0.23 0.27 0.30 0.28 0.26 L Upper Mid Lung 0.26 0.24 0.23 0.22 0.29 0.30 0.28 0.27 R Middle Anterior Lung 0.30 0.23 0.22 0.22 0.32 0.29 0.30 0.26 R Middle Mid Lung 0.25 0.25 0.23 0.22 0.27 0.28 0.27 0.25 R Middle Posterior Lung 0.27 0.23 0.23 0.22 0.29 0.26 0.25 0.23 L Middle Anterior Lung 0.30 0.23 0.23 0.23 0.32 0.30 0.32 0.28 L Middle Mid Lung 0.26 0.23 0.22 0.21 0.28 0.27 0.27 0.24 L Middle Posterior Lung 0.27 0.22 0.22 0.20 0.29 0.26 0.24 0.23 R Base Anterior Lung 0.25 0.25 0.21 0.20 0.28 0.27 0.28 0.23 R Base Posterior Lung 0.26 0.22 0.22 0.20 0.28 0.26 0.24 0.22 L Base Anterior Lung 0.26 0.26 0.24 0.22 0.28 0.28 0.28 0.23 L Base Posterior Lung 0.26 0.23 0.24 0.24 0.28 0.25 0.23 0.21 Esophagus 0.18 0.14 0.13 0.12 0.21 0.18 0.16 0.15 Bladder 0.13 0.14 0.11 0.10 0.15 0.16 0.16 0.15 L Thyroid 0.49 0.28 0.25 0.25 0.51 0.36 0.33 0.29 R Thyroid 0.49 0.29 0.26 0.27 0.51 0.38 0.34 0.29 Anterior Brain 0.24 0.23 0.22 0.20 0.27 0.26 0.24 0.22 Mid Brain 0.24 0.22 0.21 0.20 0.26 0.25 0.23 0.21 Posterior Brain 0.32 0.31 0.29 0.27 0.35 0.34 0.29 0.30 L Parotid 0.39 0.40 0.38 0.37 0.41 0.38 0.40 0.38 R Parotid 0.38 0.39 0.38 0.36 0.41 0.40 0.38 0.38 L Adrenal 0.18 0.13 0.13 0.11 0.20 0.18 0.16 0.15 R Adrenal 0.17 0.13 0.13 0.11 0.19 0.19 0.17 0.15 ET Region 0.53 0.33 0.29 0.30 0.55 0.34 0.32 0.28 Gallbladder 0.21 0.15 0.13 0.11 0.23 0.18 0.19 0.15 Heart 0.17 0.14 0.14 0.13 0.19 0.19 0.19 0.16 L Kidney 0.18 0.16 0.15 0.13 0.19 0.27 0.23 0.22 R Kidney 0.18 0.17 0.16 0.14 0.19 0.30 0.28 0.22 Lateral Pancreas 0.13 0.16 0.14 0.12 0.15 0.20 0.18 0.17 Mid Pancreas 0.14 0.13 0.11 0.10 0.16 0.16 0.15 0.14 Medial Pancreas 0.17 0.12 0.11 0.09 0.18 0.16 0.14 0.14 Spleen 0.17 0.17 0.18 0.17 0.19 0.28 0.24 0.22 L Thymus 0.33 0.19 0.17 0.17 0.35 0.24 0.22 0.21 R Thymus 0.32 0.18 0.18 0.18 0.35 0.24 0.22 0.21

PAGE 422

422 Table E 14. Continued Organ CAM M5 M50 M95 CAF F5 F50 F95 Oral mucosa 0.30 0.23 0.22 0.20 0.33 0.25 0.23 0.22 L Testis 0.35 0.33 0.33 0.33 N/A N/A N/A N/A R Testis 0.35 0.33 0.33 0.33 N/A N/A N/A N/A Prostate 0.15 0.16 0.13 0.13 N/A N/A N/A N/A L Ovary N/A N/A N/A N/A 0.18 0.17 0.17 0.16 R Ovary N/A N/A N/A N/A 0.18 0.17 0.17 0.16 Uterus N/A N/A N/A N/A 0.15 0.15 0.15 0.13 L Breast N/A N/A N/A N/A 0.42 0.48 0.42 0.41 R Breast N/A N/A N/A N/A 0.42 0.48 0.43 0.43 Table E 15. August 1972 SPE organ dose equivalents (Sv) with shelter shielding Organ CAM M5 M50 M95 CAF F5 F50 F95 BFO 0.26 0.25 0.24 0.22 0.28 0.32 0.30 0.27 Skin 0.89 0.94 0.92 0.91 0.92 0.98 0.96 0.95 Small Intestine 0.24 0.19 0.15 0.13 0.27 0.22 0.21 0.18 Muscle 0.44 0.43 0.39 0.37 0.47 0.47 0.44 0.42 R Eye Lens 0.87 0.84 0.78 0.75 0.90 1.06 0.91 1.00 L Eye Lens 0.89 0.84 0.78 0.75 0.92 1.03 0.91 0.96 R Eyeball 0.38 0.41 0.42 0.40 0.41 0.46 0.43 0.43 L Eyeball 0.39 0.41 0.42 0.40 0.42 0.44 0.43 0.41 Anterior Stomach 0.22 0.22 0.18 0.19 0.25 0.33 0.36 0.27 Posterior Stomach 0.12 0.11 0.10 0.09 0.14 0.19 0.18 0.17 Ascending Colon 0.29 0.22 0.20 0.15 0.32 0.24 0.22 0.18 Transverse Colon 0.30 0.57 0.54 0.57 0.33 0.62 0.60 0.58 Descending Colon 0.31 0.20 0.17 0.14 0.34 0.22 0.21 0.18 Rectosigmoid Colon 0.20 0.15 0.10 0.09 0.22 0.15 0.11 0.10 L Liver 0.11 0.11 0.10 0.10 0.13 0.17 0.18 0.14 R Liver 0.12 0.12 0.10 0.08 0.14 0.15 0.13 0.13 R Upper Mid Lung 0.26 0.25 0.23 0.22 0.29 0.32 0.29 0.27 L Upper Mid Lung 0.27 0.23 0.23 0.22 0.30 0.32 0.30 0.28 R Middle Anterior Lung 0.33 0.23 0.21 0.22 0.37 0.32 0.33 0.28 R Middle Mid Lung 0.24 0.25 0.22 0.21 0.27 0.29 0.28 0.24 R Middle Posterior Lung 0.28 0.23 0.22 0.20 0.31 0.26 0.24 0.22 L Middle Anterior Lung 0.33 0.23 0.22 0.24 0.36 0.33 0.37 0.30 L Middle Mid Lung 0.26 0.22 0.21 0.20 0.29 0.27 0.27 0.23 L Middle Posterior Lung 0.28 0.21 0.20 0.19 0.31 0.26 0.24 0.22 R Base Anterior Lung 0.26 0.26 0.21 0.20 0.29 0.28 0.30 0.23 R Base Posterior Lung 0.27 0.21 0.21 0.19 0.30 0.26 0.25 0.21 L Base Anterior Lung 0.27 0.27 0.24 0.22 0.30 0.29 0.30 0.23

PAGE 423

423 Table E 15. Continued Organ CAM M5 M50 M95 CAF F5 F50 F95 L Base Posterior Lung 0.27 0.23 0.25 0.25 0.30 0.24 0.23 0.20 Esophagus 0.16 0.10 0.10 0.09 0.18 0.15 0.13 0.12 Bladder 0.10 0.11 0.07 0.06 0.12 0.13 0.13 0.12 L Thyroid 0.67 0.31 0.27 0.27 0.70 0.45 0.40 0.34 R Thyroid 0.67 0.34 0.29 0.30 0.70 0.49 0.41 0.34 Anterior Brain 0.23 0.21 0.19 0.18 0.26 0.25 0.22 0.20 Mid Brain 0.22 0.20 0.18 0.17 0.25 0.23 0.21 0.19 Posterior Brain 0.36 0.34 0.31 0.28 0.39 0.37 0.30 0.32 L Parotid 0.48 0.51 0.48 0.46 0.51 0.48 0.51 0.48 R Parotid 0.48 0.49 0.48 0.44 0.51 0.51 0.48 0.48 L Adrenal 0.16 0.10 0.10 0.08 0.19 0.16 0.13 0.12 R Adrenal 0.15 0.10 0.10 0.08 0.18 0.17 0.14 0.13 ET Region 0.74 0.39 0.33 0.36 0.77 0.41 0.38 0.30 Gallbladder 0.22 0.13 0.10 0.08 0.24 0.16 0.17 0.13 Heart 0.15 0.11 0.10 0.10 0.17 0.16 0.18 0.14 L Kidney 0.16 0.14 0.13 0.11 0.18 0.30 0.24 0.24 R Kidney 0.15 0.15 0.15 0.13 0.18 0.35 0.31 0.23 Lateral Pancreas 0.10 0.13 0.11 0.09 0.11 0.18 0.16 0.14 Mid Pancreas 0.11 0.09 0.08 0.06 0.13 0.13 0.12 0.10 Medial Pancreas 0.14 0.09 0.07 0.06 0.16 0.13 0.11 0.10 Spleen 0.16 0.15 0.17 0.15 0.18 0.31 0.25 0.23 L Thymus 0.38 0.16 0.15 0.15 0.41 0.24 0.21 0.20 R Thymus 0.38 0.16 0.16 0.16 0.41 0.24 0.22 0.19 Oral mucosa 0.33 0.22 0.20 0.18 0.36 0.25 0.22 0.20 L Testis 0.45 0.40 0.42 0.44 N/A N/A N/A N/A R Testis 0.45 0.41 0.42 0.44 N/A N/A N/A N/A Prostate 0.13 0.14 0.10 0.10 N/A N/A N/A N/A L Ovary N/A N/A N/A N/A 0.16 0.14 0.15 0.14 R Ovary N/A N/A N/A N/A 0.16 0.15 0.15 0.13 Uterus N/A N/A N/A N/A 0.12 0.12 0.11 0.10 L Breast N/A N/A N/A N/A 0.54 0.65 0.54 0.52 R Breast N/A N/A N/A N/A 0.54 0.64 0.55 0.56

PAGE 424

424 APPENDIX F EARTH BASED BODY SELF SHIELDING DISTRIBUTI ONS Figure F 1 Earth based eye lenses body self shielding distributions ( Bahadori et al. 2011 ) Figure F 2 Earth based BFO body self shielding distributions ( Bahadori et al. 2011 )

PAGE 425

425 Figure F 3 Earth based colon body self shielding distributions ( Bahadori et al. 2011 ) Figure F 4 Earth based lung body self shielding distributions ( Bahadori et al. 2011 )

PAGE 426

426 Figure F 5 Earth based stomach body self shielding distributions ( Bahadori et al. 2011 ) Figure F 6 Earth based breasts body self shielding distributions ( Bahadori et al. 2011 )

PAGE 427

427 Figure F 7 Earth based ovaries body self shielding distributions ( Bahadori et al. 2011 ) Figure F 8 Earth based testes body self shielding distributions ( Bahadori et al. 2011 )

PAGE 428

428 Figure F 9 Earth based bladder body self shielding distributions ( Bahadori et al. 2011 ) Figure F 10 Earth based esophagus body self shielding distributions ( Bahadori et al. 2011 )

PAGE 429

429 Figure F 11 Earth based liver body self shielding distributions ( Bahadori et al. 2011 ) Figure F 12 Earth based thyroid body self shielding distributions ( Bahadori et al. 2011 )

PAGE 430

430 Figure F 13 Earth based brain body self shielding distribu tions ( Bahadori et al. 2011 ) Figure F 14 Earth based salivary glands body self shielding distributions ( Bahadori et al. 2011 )

PAGE 431

431 Figure F 15 Earth based skin body self shielding distributions ( Bahadori et al. 2011 ) Figure F 16 Earth based adrenals bo dy self shielding distributions ( Bahadori et al. 2011 )

PAGE 432

432 Figure F 17 Earth based ET region body self shielding distributions ( Bahadori et al. 2011 ) Figure F 18 Earth based gallbladder body self shielding distributions ( Bahadori et al. 2011 )

PAGE 433

433 Figure F 19 Earth based heart body self shielding distributions ( Bahadori et al. 2011 ) Figure F 20 Earth based kidneys body self shielding distributions ( Bahadori et al. 2011 )

PAGE 434

434 Figure F 21 Earth based muscle body self shielding distributions ( Bahadori et al. 2011 ) Figure F 22 Earth based oral mucosa body self shielding distributions ( Bahadori et al. 2011 )

PAGE 435

435 Figure F 23 Earth based pancreas body self shielding distributions ( Bahadori et al. 2011 ) Figure F 24 Earth based prostate body self shielding distributions ( Bahadori et al. 2011 )

PAGE 436

436 Figure F 25 Earth based small intestines body self shielding distributions ( Bahadori et al. 2011 ) Figure F 26 Earth based spleen body self shielding distributions ( Bahadori et al. 2011 )

PAGE 437

437 Figure F 27 Earth based thymus body self shielding distributions ( Bahadori et al. 2011 ) Figure F 28 Earth based uterus body self shielding distributions ( Bahadori et al. 2011 )

PAGE 438

438 APPENDIX G EARTH BASED ORGAN DOSE EQUIVALEN T RESULTS Figure G 1 Male suit trapped proton Earth based organ dose equivalent rates ( Bahadori et al. 2011 ) Figure G 2 Female suit trapped proton Earth based organ dose equivalent rates ( Bahadori et al. 2011 )

PAGE 439

439 Figure G 3 Male suit GCR Earth based or gan dose equivalent rates ( Bahadori et al. 2011 ) Figure G 4 Female suit GCR Earth based organ dose equivalent rates ( Bahadori et al. 2011 )

PAGE 440

440 Figure G 5 Male suit February 1956 SPE Earth based organ dose equivalents ( Bahadori et al. 2011 ) Figure G 6 Female suit February 1956 SPE Earth based organ dose equivalents ( Bahadori et al. 2011 )

PAGE 441

441 Figure G 7 Male suit October 1989 SPE Earth based organ dose equivalents ( Bahadori et al. 2011 ) Figure G 8 Female suit October 1989 SPE Earth based organ dose equivalents ( Bahadori et al. 2011 )

PAGE 442

442 Figure G 9 Male suit August 1972 SPE Earth based organ dose equivalents ( Bahadori et al. 2011 ) Figure G 10 Female suit August 1972 SPE Earth based organ dose equivalents ( Bahadori et al. 2011 )

PAGE 443

443 Figure G 11 Male PV trapped proton Earth based organ dose equivalent rates ( Bahadori et al. 2011 ) Figure G 12 Female PV trapped proton Earth based organ dose equivalent rates ( Bahadori et al. 2011 )

PAGE 444

444 Figure G 13 Male PV GCR Earth based organ dose equivalent rates ( Bahadori et al. 2011 ) Figure G 14 Female PV GCR Earth based organ dose equivalent rates ( Bahadori et al. 2011 )

PAGE 445

445 Figure G 15 Male PV February 1956 SPE Earth based organ dose equivalents ( Bahadori et al. 2011 ) Figure G 16 Female PV February 1956 SPE Earth based organ dose equivalents ( Bahadori et al. 2011 )

PAGE 446

446 Figure G 17 Male PV October 1989 SPE Earth based organ dose equivalents ( Bahadori et al. 2011 ) Figure G 18 Female PV October 1989 SPE Earth based organ dose equivalents ( Bahadori et al. 2011 )

PAGE 447

447 Figure G 19 Male PV August 1972 SPE Earth based organ dose equivalents ( Bahadori et al. 2011 ) Figure G 20 Female PV August 1972 SPE Earth based organ dose equivalents ( Bahadori et al. 2011 )

PAGE 448

448 Figure G 21 Male shelter trapped p roton Earth based organ dose equivalent rates ( Bahadori et al. 2011 ) Figure G 22 Female shelter trapped proton Earth based organ dose equivalent rates ( Bahadori et al. 2011 )

PAGE 449

449 Figure G 23 Male shelter GCR Earth based organ dose equivalent rates ( Bahadori et al. 2011 ) Figure G 24 Female shelter GCR Earth based organ dose equivalent rates ( Bahadori et al. 2011 )

PAGE 450

450 Figure G 25 Male shelter February 1956 SPE E arth based organ dose equivalents ( Bahadori et al. 2011 ) Figure G 26 Female shelter February 1956 SPE Earth based organ dose equivalents ( Bahadori et al. 2011 )

PAGE 451

451 Figure G 27 Male shelter October 1989 SPE Earth based organ dose equivalents ( Bahadori et al. 2011 ) Figure G 28 Female shelter October 1989 SPE Earth based organ dose equivalents ( Bahadori et al. 2011 )

PAGE 452

452 Figure G 29 Male shelter August 1972 SPE Earth based organ dose equivalents ( Bahadori et al. 2011 ) Figure G 30 Female shelter August 1972 SPE Earth based organ dose equivalents ( Bahadori et al. 2011 )

PAGE 453

453 APPENDIX H EARTH BASED FRACTIONAL DIF FERENCE Figure H 1 Male suit trapped proton Earth based organ dose equivalent fractional difference ( Bahadori et al. 2011 ) Figure H 2 Female suit trapped proton Earth based organ dose equivalent fractional difference ( Bahadori et al. 201 1 )

PAGE 454

454 Figure H 3 Male suit GCR Earth based organ dose equivalent fractional difference ( Bahadori et al. 2011 ) Figure H 4 Female suit GCR Ea rth based organ dose equivalent fractional difference ( Bahadori et al. 2011 )

PAGE 455

455 Figure H 5 Male suit February 1956 SPE Earth based organ dose equivalent fractional ( Bahadori et al. 2011 ) Figure H 6 Female suit February 1956 SPE Earth based organ dose equivalent fractional difference ( Bahadori et al. 2011 )

PAGE 456

456 Figure H 7 Male suit October 1989 SPE Earth based organ dose equivalent fractional difference ( Bahadori et al. 2011 ) Figure H 8 Female suit October 1989 SPE Earth based organ dose equivalent fractional difference ( Bahadori et al. 2011 )

PAGE 457

457 Figure H 9 Male suit August 19 72 SPE Earth based organ dose equivalent fractional difference ( Bahadori et al. 2011 ) Figure H 10 Female suit August 1972 SPE Earth based organ dose equivalent fractional difference ( Bahadori et al. 2011 )

PAGE 458

458 Figure H 11 Male PV trapped proton Earth based organ dose equivalent fractional difference ( Bahadori et al. 2011 ) Figure H 12 Female PV trapped proton Earth based organ dose equivalent fractional difference ( Baha dori et al. 2011 )

PAGE 459

459 Figure H 13 Male PV GCR Earth based organ dose equivalent fractional difference ( Bahadori et al. 2011 ) Figure H 14 Female PV GCR Earth based organ dose equivalent fractional difference ( Bahadori et al. 2011 )

PAGE 460

460 Figure H 15 Male PV February 1956 SPE Earth based organ dose equivalent fra ctional difference ( Bahadori et al. 2011 ) Figure H 16 Female PV February 1956 SPE Earth based organ dose equivalent fractional difference ( Bahadori et al. 2011 )

PAGE 461

461 Figure H 17 Male PV October 1989 SPE Earth based organ dose equivalent fractional difference ( Bahadori et al. 2011 ) Figure H 18 Female PV October 1989 SPE Earth based organ dose equivalent fractional difference ( Bahadori et al. 2011 )

PAGE 462

462 Figure H 19 Male PV A ugust 1972 SPE Earth based organ dose equivalent fractional difference ( Bahadori et al. 2011 ) Figure H 20 Female PV August 1972 SPE Earth based organ dose equiv alent fractional difference ( Bahadori et al. 2011 )

PAGE 463

463 Figure H 21 Male shelter trapped proton Earth based organ dose equivalent fractional difference ( Bahadori et al. 2011 ) Figure H 22 Female shelter trapped proton Earth based organ dose equivalent fractional difference ( Bahado ri et al. 2011 )

PAGE 464

464 Figure H 23 Male shelter GCR Earth based organ dose equivalent fractional difference ( Bahadori et al. 2011 ) Figure H 24 Female shelter GCR Earth based organ dose equivalent fractional difference ( Bahadori et al. 2011 )

PAGE 465

465 Figure H 25 Male shelter February 1956 SPE Earth based organ dose equivalent fractional difference ( Bahadori et al. 2011 ) Figure H 26 Female shelter February 1956 SPE Earth based organ dose equivalent fractional difference ( Bahadori et al. 2011 )

PAGE 466

466 Figure H 27 Male shelter October 1989 SPE Earth based organ dose equivalent fractional difference ( Bahadori et al. 2011 ) Figure H 28 Female shelter October 1989 SPE Earth based organ dose equivalent fractional difference ( Bahadori et al. 2011 )

PAGE 467

467 Figure H 29 Male shelter August 1972 SPE Earth based organ dose equivalent fractional difference ( Bahadori et al. 2011 ) Figure H 30 Female shel ter August 1972 SPE organ dose equivalent fractional difference ( Bahadori et al. 2011 )

PAGE 468

468 APPENDIX I MICROGRAVITY BODY SE LF SHIELDING DISTRIBUTIONS Figure I 1 Microgravity eye lenses body self shielding distributions ( Bahadori et al. 2012 ) Figure I 2 Microgravity BFO body self shielding distributions ( Bahadori et al. 20 12 )

PAGE 469

469 Figure I 3 Microgravity colon body self shielding distributions ( Bahadori et al. 2012 ) Figure I 4 Microgravity lungs body self shielding distributions ( Bahadori et al. 2012 )

PAGE 470

470 Figure I 5 Microgravity stomach body self shielding distributions ( Bahadori et al. 2012 ) Figure I 6 Microgravity breasts body self shielding distributions ( Bahadori et al. 2012 )

PAGE 471

471 Figure I 7 Microgravity ovaries body self shielding distributions ( Bahadori et al. 2012 ) Figure I 8 Microgravity testes body self shielding distributions ( Bahadori et al. 2012 )

PAGE 472

472 Figure I 9 Microgravity bladder body self shielding distributions ( Bahadori et al. 2012 ) Figure I 10 Microgravity esophagus body se lf shielding distributions ( Bahadori et al. 2012 )

PAGE 473

473 Figure I 11 Microgravity liver body self shielding distributions ( Bahadori et al. 2012 ) Figure I 12 Microgravity thyroid body self shielding distributions ( Bahadori et al. 20 12 )

PAGE 474

474 Figure I 13 Microgravity brain body self shielding distributions ( Bahadori et al. 2012 ) Figure I 14 Microgravity salivary glands body self shielding distributions ( Bahadori et al. 2012 )

PAGE 475

4 75 Figure I 15 Microgravity skin body self shielding distributions ( Bahadori et al. 2012 ) Figure I 16 Microgravity adrenals body self shielding distributions ( Bahadori et al. 2012 )

PAGE 476

476 Figure I 17 Microgravity ET region body self shielding distributions ( Bahadori et al. 2012 ) Figure I 18 Microgravity gallbladder body self shielding distributions ( Bahadori et al. 2012 )

PAGE 477

477 Figure I 19 Microgravity heart body self shielding distributions ( Bahadori et al. 2012 ) Figure I 20 Microgravity kidneys body self shielding distributions ( Bahadori et al. 2012 )

PAGE 478

478 Figure I 21 Microgravity muscle body self shielding distributions ( Bahadori et al. 2012 ) Figure I 22 Microgravity oral mucosa body self shielding distributions

PAGE 479

479 Figure I 23 Microgravity pancreas body self shielding distributions ( Bahadori et al. 2012 ) Figure I 24 Microgravity prostate body self shielding distributions ( Bahadori et al. 2012 )

PAGE 480

480 Figure I 25 Microgravity small intestines body self shield ing distributions ( Bahadori et al. 2012 ) Figure I 26 Microgravity spleen body self shielding distributions ( Bahadori et al. 2012 )

PAGE 481

481 Figure I 27 Microgravity thymus body self shielding distributions ( Bahadori et al. 2012 ) Figure I 28 Microgravity uterus body self shielding distributions ( Bahadori et al. 2012 )

PAGE 482

482 APPENDIX J MICROGRAVITY ORGAN D OSE EQUIVALENT RESUL TS Figure J 1 Male suit trapped proton microgravity organ dose equivalent rates ( Bahadori et al. 2012 ) Figure J 2 Female suit trapped proton microgravity organ dose equivalent rates ( Bahadori et al. 2012 )

PAGE 483

483 Figure J 3 Male suit GCR microgravity organ dose equivalent r ates ( Bahadori et al. 2012 ) Figure J 4 Female suit GCR microgravity organ dose equivalent rates ( Bahadori et al. 2012 )

PAGE 484

484 Figure J 5 Male suit February 1956 SPE microgravity organ dose equivalents ( Bahadori et al. 2012 ) Figure J 6 Female suit February 1956 SPE microgravity organ dose equivalents ( Bahadori et al. 2012 )

PAGE 485

485 Figure J 7 Male suit October 1989 SPE microgravity organ dose equivalents ( Bahadori et al. 2012 ) Figure J 8 Female suit October 1989 SPE microgravity organ dose equivalents ( Bahadori et al. 2012 )

PAGE 486

486 Figure J 9 Male suit August 1972 SPE microgravity organ dose equivalents ( Bahadori et al. 2012 ) Figure J 10 Female suit August 1972 SPE microgravity organ dose equivalents ( Bahadori et al. 2012 )

PAGE 487

487 Figure J 11 Male PV trapped proton microgravity organ dose equivalent rates ( Bahadori et al. 2012 ) Figure J 12 Female P V trapped proton microgravity organ dose equivalent rates ( Bahadori et al. 2012 )

PAGE 488

488 Figure J 13 Male PV GCR microgravity organ dose equivalent rates ( Bahadori et al. 2012 ) Figure J 14 Female PV GCR microgravity organ dose equivalent rates ( Bahadori et al. 2012 )

PAGE 489

489 Figure J 15 Male PV February 1956 SPE microgravity organ dose equivalents ( Bahadori et al. 2012 ) Figure J 16 Female PV February 1956 SPE microgravity organ dose equivalents ( Bahadori et al. 2012 )

PAGE 490

490 Figure J 17 Male PV October 1989 SPE microgravity organ dose equivalents ( Bahadori et al. 2012 ) Figure J 18 Female PV October 1989 SPE microgravity organ dose equivalents ( Bahadori et al. 2012 )

PAGE 491

491 Figure J 19 Male PV August 1972 SPE microgravity organ dose equivalents ( Bahadori et al. 2012 ) Figure J 20 Female PV August 1972 SPE microgravity organ dose equivalents ( Bahadori et al. 2012 )

PAGE 492

492 Figure J 21 Male shelter trapped proton microgravity organ dose equivalent rates ( Bahadori et al. 2012 ) Figure J 22 Female shelter trapped proton microgravity organ dose equivalent rates ( Bahadori et al. 2012 )

PAGE 493

493 Figure J 23 Male shelter GCR microgravity organ dose equivalent rates ( Bahadori et al. 2012 ) Figure J 24 Female shelter GCR microgravity organ dose equivalent rates ( Bahadori et al. 2012 )

PAGE 494

494 Figure J 25 Male shelter February 1956 SPE microgravity or gan dose equivalents ( Bahadori et al. 2012 ) Figure J 26 Female sh elter February 1956 SPE microgravity organ dose equivalents ( Bahadori et al. 2012 )

PAGE 495

495 Figure J 27 Male shelter October 1989 SPE microgravity organ dose equivalents ( Bahadori et al. 2012 ) Figure J 28 Female shelter October 1989 SPE microgravity organ dose equivalents ( Bahadori et al. 2012 )

PAGE 496

496 Figure J 29 Male shelter August 1972 SPE microgravity organ dose equivalents ( Bahadori et al. 2012 ) Figure J 30 Female shelter August 1972 SPE microgravity organ dose equivalents ( Bahadori et al. 2012 )

PAGE 497

497 APPENDIX K MICROGRAVITY FRACTIO NAL DIFFERENCE (VS. 50 TH PCTL) Figure K 1 Male suit trapped proton microgravity organ dose equivalent fractional difference vs. 50 th PCTL ( Bahadori et al. 2012 ) Figure K 2 Female suit trapped proton microgravity organ dose equivalent fractional difference vs. 50 th PCTL ( Bahadori et al. 2012 )

PAGE 498

498 Figure K 3 Male suit GCR microgravity organ dose equivalent fractional difference vs. 50 th PCTL ( Bahadori et al. 2012 ) Figure K 4 Female suit GCR microgravity organ dose equivalent fractional difference vs. 50 th PCTL ( Bahadori et al. 2012 )

PAGE 499

499 Figure K 5 Male suit February 1956 SPE microgravity organ dose equivalent fractional difference vs. 50 th PCTL ( Ba hadori et al. 2012 ) Figure K 6 Female suit February 1956 SPE microgravity organ dose equivalent fractional difference vs. 50 th PCTL ( Bahadori et al. 2012 )

PAGE 500

500 Figure K 7 Male suit October 1989 SPE microgravity organ dose equivalent fractional difference vs. 50 th PCTL ( Bahadori et al. 2012 ) Figure K 8 Female suit October 1989 SPE microgravity organ dose equ ivalent fractional difference vs. 50 th PCTL ( Bahadori et al. 2012 )

PAGE 501

501 Figure K 9 Male suit August 1972 SPE microgravity organ dose equivalent fractional difference vs. 50 th PCTL ( Bahadori et al. 2012 ) Figure K 10 Female suit August 1972 SPE microgravity organ dose equivalent fractional difference vs. 50 th PCTL ( Bahadori et al. 2012 )

PAGE 502

502 Figure K 11 Male PV trapped proton microgravity organ dose equivalent fractional difference vs. 50 th PCTL ( Bahadori et al. 2012 ) Figure K 12 Female PV trapped proton micro gravity organ dose equivalent fractional difference vs. 50 th PCTL ( Bahadori et al. 2012 )

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503 Figure K 13 Male PV GCR microgravity organ dose equivalent fractional difference vs. 50 th PCTL ( Bahadori et al. 2012 ) Figure K 14 Female PV GCR microgravity organ dose equivalent fractional difference vs. 50 th PCTL ( Bahadori et al. 2012 )

PAGE 504

504 Figure K 15 Male PV February 1956 SPE microgravity organ dose equivalent fractional difference vs. 50 th PCTL ( Bahadori et al. 2012 ) Figure K 16 Female PV February 1956 SPE microgravity organ dose equivalent fractional difference vs. 50 th PCTL ( Bahadori et al. 2012 )

PAGE 505

505 Figure K 17 Male PV October 1989 SPE microgravity organ dose equivalent fractional difference vs. 50 th PCTL ( Bahadori et al. 2012 ) Figure K 18 Female PV October 1989 SPE microgravity organ dose equivalent fractional difference vs. 50 th PCTL ( Bahadori et al. 2012 )

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506 Figure K 19 Male PV August 1972 SPE microgravity organ dose equivalent fractional difference vs. 50 th P CTL ( Bahadori et al. 2012 ) Figure K 2 0 Female PV August 1972 SPE microgravity organ dose equivalent fractional difference vs. 50 th PCTL ( Bahadori et al. 2012 )

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507 Figure K 21 Male shelter trapped proton microgravity organ dose equivalent fractional difference vs. 50 th PCTL ( Bahadori et al. 2012 ) Figure K 22 Female shelter trapped proton microgravity organ dose equivalent fractional difference vs. 50 th PCTL ( Bahadori et al. 2012 )

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508 Figure K 23 Male shelter GCR microgravity organ dose equivalent fractional diffe rence vs. 50 th PCTL ( Bahadori et al. 2012 ) Figure K 24 Female shelter GCR microgravity organ dose equivalent fractional difference vs. 50 th PCTL ( Bahadori et a l. 2012 )

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509 Figure K 25 Male shelter February 1956 SPE microgravity organ dose equivalent fractional difference vs. 50 th PCTL ( Bahadori et al. 2012 ) Figure K 26 Female shelter February 1956 SPE microgravity organ dose equivalent fractional difference vs. 50 th PCTL ( Bahadori et al. 2012 )

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510 Figure K 27 Male shelter October 1989 SPE microgravity organ dose equivalent fractional difference vs. 50 th PCTL ( Bahadori et al. 2012 ) Figure K 28 Female shelter October 1989 SPE microgravity organ dose equivalent fractional difference vs. 50 th PCTL ( Bahadori et al. 2012 )

PAGE 511

511 Figure K 29 Male shelter August 1972 SPE microgravity organ dose equivalent fractional difference vs. 50 th PCTL ( Bahadori et al. 2012 ) Figure K 30 Female shelter August 1972 SPE microgravity organ dose equivalent fractional difference vs. 50 th PCTL ( Bahadori et al. 2012 )

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512 APPENDIX L MICROGRAVITY FRACTIO NAL DIFF ERENCE (VS. EARTH BASED) Figure L 1 Male suit trapped proton microgravity organ dose equivalent fractional difference vs. Earth based ( Bahadori et al. 2012 ) Figure L 2 Female suit trapped proton microgravity organ dose equivalent fractional difference vs. Earth based ( Bahadori et al. 2012 )

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513 Figure L 3 Male suit GCR microgravity organ dose equivalen t fractional difference vs. Earth based ( Bahadori et al. 2012 ) Figure L 4 Female suit GCR microgravity organ dose equivalent fractional difference vs. Earth based ( Bahadori et al. 2012 )

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514 Figure L 5 Male suit February 1956 SPE microgravity organ dose equivalent fractional difference vs. Earth based ( Bahadori et al. 2012 ) Figure L 6 Female suit February 1956 SPE microgravity organ dose equivalent fractional difference vs. Earth based ( Bahadori et al. 2012 )

PAGE 515

515 Figure L 7 Male suit October 1 989 SPE microgravity organ dose equivalent fractional difference vs. Earth based ( Bahadori et al. 2012 ) Figure L 8 Female suit October 1989 SPE microgravity organ dose equivalent fractional difference vs. Earth based ( Bahadori et al. 2012 )

PAGE 516

516 Figure L 9 Male suit August 1972 SPE microgravity organ dose equivalent fractional difference vs. Earth based ( Bahadori et al. 2012 ) Figure L 10 Female suit August 1972 SPE microgravity organ dose equivalent fractional difference vs. Earth based ( Bahadori et al. 2012 )

PAGE 517

517 Figure L 11 Male PV trapped proton microgravity organ dose equivalent fractional difference vs. Earth based ( Bahadori et al. 2012 ) Figure L 12 Female PV trapped proton microgravity organ dose equivalent fractional difference vs. Earth based ( Bahadori et al. 2012 )

PAGE 518

518 Figure L 13 Male PV GCR microgravity organ dose equivalent fractional difference vs. Earth based ( Bahadori et al. 2012 ) Figure L 14 Female PV GCR microgravity organ dose equivale nt fractional difference vs. Earth based ( Bahadori et al. 2012 )

PAGE 519

519 Figure L 15 Male PV February 1956 SPE microgravity organ dose equivalent fractional difference vs. Earth based ( Bahadori et al. 2012 ) Figure L 16 Female PV February 1956 SPE microgravity organ dose equivalent fractional difference vs. Earth based ( Bahadori et al. 2012 )

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520 Figure L 17 Male PV October 1989 SPE microgravity organ dose equivalent fractional difference vs. Earth based ( Bahadori et al. 2012 ) Figure L 18 Female PV October 1989 SPE microgravity organ dose equivalent fractional difference vs. Earth based ( Bahadori et al 2012 )

PAGE 521

521 Figure L 19 Male PV August 1972 SPE microgravity organ dose equivalent fractional difference vs. Earth based ( Bahadori et al. 2012 ) Figure L 20 Female PV August 1972 SPE microgravity organ dose equivalent fractional difference vs. Earth based ( Bahadori et al. 2012 )

PAGE 522

522 Figure L 21 Male shelter trapped proton microgravity organ dose equivalent fract ional difference vs. Earth based ( Bahadori et al. 2012 ) Figure L 22 Female shelter trapped proton microgravity organ dose equivalent fractional difference vs. Earth based ( Bahadori et al. 2012 )

PAGE 523

523 Figure L 23 Male shelter GCR microgravity organ dose equivalent fractional difference vs. Earth based ( Bahadori et al. 2012 ) Figure L 24 Female shelter GCR microgravity organ dose equivalent fractional difference vs. Earth based ( Bahadori et al. 2012 )

PAGE 524

524 Figure L 25 Male shelter February 1956 SPE microgravity or gan dose equivalent fractional difference vs. Earth based ( Bahadori et al. 2012 ) Figure L 26 Female shelter February 1956 SPE microgravity organ dose equivalent fractional difference vs. Earth based ( Bahadori et al. 2012 )

PAGE 525

525 Figure L 27 Male shelter October 1989 SPE microgravity organ dose equivalent fractional difference vs. Earth based ( Bahadori et al. 2012 ) Figure L 28 Female shelter October 1989 SPE microgravity organ dose equivalent fractional difference vs. Earth based ( Bahadori et al. 2012 )

PAGE 526

526 Figure L 29 Male shelter August 1972 SPE microgravity organ dose equivalent fractional difference vs. Earth based ( Bahadori et al. 2012 ) Figure L 30 Female shelter August 1972 SPE microgravity organ dose equivalent fractional difference vs. Earth based ( Bahadori et al. 2012 )

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527 APPENDIX M HZETRN MATLAB INTERP OLATION CODES Dosimetry Interpolation % Load body self shielding distributions and HZETRN2010 depth dose load UFHADF50.mat load UFHADM50.mat load HZETRN2010depthdose.mat % Environments env{1} = 'AUG1972_05' ; env{2} = 'AUG1972_10' ; env{3} = 'FEB1956_05' ; env{4} = 'FEB1956_10' ; env{5} = 'TRAPPED_2' ; env{6} = 'GCR_H_2' ; env{7} = 'GCR_He_2' ; env{8} = 'GCR_C_2' ; env{9} = 'GCR_O_2' ; env{10} = 'GCR_Mg_2' ; env{11} = 'GCR_Si_2' ; env{12} = 'GCR_Fe_2' ; env{13} = 'GCR_Grp1_2' ; env{14} = 'GCR_Grp2_2' ; env{15} = 'GCR_Grp3_2' ; % Male organs morg{1} = 'skin' ; morg{2} = 'BFO' ; morg{3} = 'muscle' ; morg{4} = 'lens' ; morg{5} = 'stomach' ; morg{6} = 'colon' ; morg{7} = 'liver' ; morg{8} = 'lung' ; morg{9} = 'esophagus' ; morg{10} = 'bladder' ; morg{11} = 'thyroid' ; morg{12} = 'brain' ; morg{13} = 'salivary' ; morg{14} = 'adrenals' ; morg{15} = 'ETregion' ; morg{16} = 'gallbladder' ; morg{17} = 'kidneys' ; morg{18} = 'pancreas' ; morg{19} = 'smallint' ; morg{20} = 'spleen' ; morg{21} = 'thymus' ; morg{22} = 'heart' ; morg{23} = 'oralmuc' ; morg{24} = 'prostate' ; morg{25} = 'testes' ; % Female organs

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528 forg = morg; forg{24} = 'br easts' ; forg{25} = 'ovaries' ; forg{26} = 'uterus' ; % Interpolate to get Dorg and Horg for male and female for i = 1:length(env) for j = 1:length(morg) temp_Dorg_interp = ... pchip(HZETRN2010depthdose.water_grid, ... HZETRN2010depthdose.(env{i}).D, ... UFHADM50.(morg{j})); temp_Dorg_interp( ... UFHADM50.(morg{j}) > HZETRN2010depthdose.water_grid(end)) = ... HZETRN2010depthdose.(env{i}).D(end); HZETRN2010resu lts.UFHADM50.(env{i}).(morg{j}).Dorg = ... mean(temp_Dorg_interp); temp_Horg_interp = ... pchip(HZETRN2010depthdose.water_grid, ... HZETRN2010depthdose.(env{i}).H, ... UFHADM50.(morg{j})); temp_ Horg_interp( ... UFHADM50.(morg{j}) > HZETRN2010depthdose.water_grid(end)) = ... HZETRN2010depthdose.(env{i}).H(end); HZETRN2010results.UFHADM50.(env{i}).(morg{j}).Horg = ... mean(temp_Horg_interp); end for j = 1:length(forg) temp_Dorg_interp = ... pchip(HZETRN2010depthdose.water_grid, ... HZETRN2010depthdose.(env{i}).D, ... UFHADF50.(forg{j})); temp_Dorg_interp( ... UFHADF50.(forg{j}) > HZETRN2 010depthdose.water_grid(end)) = ... HZETRN2010depthdose.(env{i}).D(end); HZETRN2010results.UFHADF50.(env{i}).(forg{j}).Dorg = ... mean(temp_Dorg_interp); temp_Horg_interp = ... pchip(HZETRN2010depthdose.water_grid, ... HZETRN2010depthdose.(env{i}).H, ... UFHADF50.(forg{j})); temp_Horg_interp( ... UFHADF50.(forg{j}) > HZETRN2010depthdose.water_grid(end)) = ... HZETRN 2010depthdose.(env{i}).H(end); HZETRN2010results.UFHADF50.(env{i}).(forg{j}).Horg = ... mean(temp_Horg_interp); end end Flux Interpolation % Load body self shielding distributions and HZETRN2010 fluences load UFHADF50.mat load UFHADM50.mat load HZETRN_dflux_raw_74.mat

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529 % Environment/shield combinations envshld{1} = 'AUG1972_05' ; envshld{2} = 'AUG1972_10' ; envshld{3} = 'FEB1956_05' ; envshld{4} = 'FEB1956_10' ; envshld{5} = 'TRAPPED_2' ; envshld{6} = 'GCR_H_2' ; envGCR{1} = 'GCR_H' ; envshld{7} = 'GCR_He_2' ; envGCR{2} = 'GCR_He' ; envshld{8} = 'GCR_C_2' ; envGCR{3} = 'GCR_C' ; envshld{9} = 'GCR_O_2' ; envGCR{4} = 'GCR_O' ; envshld{10} = 'GCR_Mg_2' ; envGCR{5} = 'GCR_Mg' ; envshld{11} = 'GCR_Si_2' ; envGCR{6} = 'GCR_Si' ; envshld{12} = 'GCR_Fe_2' ; envGCR{7} = 'GCR_Fe' ; envshld{13} = 'GCR_Grp1_2' ; envGCR{8} = 'GCR_Grp1' ; envshld{14} = 'GCR_Grp2_2' ; envGCR{9} = 'GCR_Grp2' ; envshld{15} = 'GCR_Grp3_2' ; envGCR{10} = 'GCR_Grp3' ; envshld{1} = 'GCR_H_2' ; envGCR{1} = 'GCR_H' ; envshld{2} = 'GCR_He _2' ; envGCR{2} = 'GCR_He' ; envshld{3} = 'GCR_Si_2' ; envGCR{3} = 'GCR_Si' ; envshld{1} = 'GCR_Si_2' ; envGCR{1} = 'GCR_Si' ; % Determine flux for appropriate vehicular shielding tempflux.(envshld{1}).flux = HZETRN_dflux_raw.AUG1972.flux(:,2:end, ... HZE TRN_dflux_raw.AUG1972.depth1 == 0.5); tempflux.(envshld{1}).energy = HZETRN_dflux_raw.AUG1972.flux(:,1,1); tempflux.(envshld{1}).waterdepth = HZETRN_dflux_raw.AUG1972.depth2( ... HZETRN_dflux_raw.AUG1972.depth1 == 0.5); tempflux.(envshld{2}).flux = HZETRN_dflux_raw.AUG1972.flux(:,2:end, ... HZETRN_dflux_raw.AUG1972.depth1 == 10.0); tempflux.(envshld{2}).energy = HZETRN_dflux_raw.AUG1972.flux(:,1,1); tempflux.(envshld{2}).waterdepth = HZETRN_dflux_raw.AUG1972.depth2( ... HZETRN_dflux_raw.AUG1972 .depth1 == 10.0); tempflux.(envshld{3}).flux = HZETRN_dflux_raw.FEB1956.flux(:,2:end, ... HZETRN_dflux_raw.FEB1956.depth1 == 0.5); tempflux.(envshld{3}).energy = HZETRN_dflux_raw.FEB1956.flux(:,1,1); tempflux.(envshld{3}).waterdepth = HZETRN_dflux_raw .FEB1956.depth2( ... HZETRN_dflux_raw.FEB1956.depth1 == 0.5); tempflux.(envshld{4}).flux = HZETRN_dflux_raw.FEB1956.flux(:,2:end, ... HZETRN_dflux_raw.FEB1956.depth1 == 10.0); tempflux.(envshld{4}).energy = HZETRN_dflux_raw.FEB1956.flux(:,1,1); tempflux.(envshld{4}).waterdepth = HZETRN_dflux_raw.FEB1956.depth2( ... HZETRN_dflux_raw.FEB1956.depth1 == 10.0); tempflux.(envshld{5}).flux = HZETRN_dflux_raw.TRAPPED.flux(:,2:end, ... HZETRN_dflux_raw.TRAPPED.depth1 == 2.0); tempflux.(envshld{5}) .energy = HZETRN_dflux_raw.TRAPPED.flux(:,1,1); tempflux.(envshld{5}).waterdepth = HZETRN_dflux_raw.TRAPPED.depth2( ... HZETRN_dflux_raw.TRAPPED.depth1 == 2.0); for i = 1:length(envGCR)

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530 tempflux.(envshld{5+i}).flux = ... HZETRN_dflux_raw.( envGCR{i}).flux(:,2:end, ... HZETRN_dflux_raw.(envGCR{i}).depth1 == 2.0); tempflux.(envshld{5+i}).energy = ... HZETRN_dflux_raw.(envGCR{i}).flux(:,1,1); tempflux.(envshld{5+i}).waterdepth = ... HZETRN_dflux_raw.(envGCR{i}).depth2( ... HZETRN_dflux_raw.(envGCR{i}).depth1 == 2.0); end for i = 1:length(envGCR) tempflux.(envshld{i}).flux = ... HZETRN_dflux_raw.(envGCR{i}).flux(:,2:end, ... HZETRN_dflux_raw.(envGCR{i}).depth1 == 2.0); tempflux.(envshld{i}).energy = ... HZETRN_dflux_raw.(envGCR{i}).flux(:,1,1); tempflux.(envshld{i}).waterdepth = ... HZETRN_dflux_raw.(envGCR{i}).depth2( ... HZETRN_dflux_r aw.(envGCR{i}).depth1 == 2.0); end % Male organs morg{1} = 'skin' ; morg{2} = 'BFO' ; morg{3} = 'muscle' ; morg{4} = 'lens' ; morg{5} = 'stomach' ; morg{6} = 'colon' ; morg{7} = 'liver' ; morg{8} = 'lung' ; morg{9} = 'esophagus' ; morg{10} = 'bladder' ; morg{11} = 'thyroid' ; morg{12} = 'brain' ; morg{13} = 'salivary' ; morg{14} = 'adrenals' ; morg{15} = 'ETregion' ; morg{16} = 'gallbladder' ; morg{17} = 'kidneys' ; morg{18} = 'pancreas' ; morg{19} = 'smallint' ; morg{20} = 'spleen' ; morg{21} = 'thymus' ; morg{22} = 'heart' ; morg{23} = 'oralmuc' ; morg{24} = 'prostate' ; morg{25} = 'testes' ; % Female organs forg = morg; forg{24} = 'breasts' ; forg{25} = 'ovaries' ; forg{26} = 'uterus' ; % Define ions

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531 A = [1.,1.,2.,3.,3.,4.,6.,7.,8.,9.,10.,10.,11.,12.,13.,14.,15.,16., ... 17.,18.,18.,19.,20.,21.,22.,23.,24.,25.,26.,27.,28.,29.,30.,31., ... 32.,33.,34.,36.,35.,37.,36.,38.,40.,39.,40.,41.,40.,42.,43.,44.,46., ... 48.,45.,46.,47.,48.,49.,50.,50.,51.,5 0.,52.,53.,54.,55.,54.,56.,57., ... 58.,59.,58.,60.,61.,62.]; Z = [0.,1.,1.,1.,2.,2.,3.,3.,4.,4.,4., 5., 5., 6., 6., 7., 7., 8., ... 8., 8., 9., 9., 10.,10.,10.,11.,12.,12.,12.,13.,14.,14.,14.,15., ... 16.,16.,16.,16.,17.,17.,18.,18.,18.,19.,19., 19.,20.,20.,20.,20.,20., ... 20.,21.,22.,22.,22.,22.,22.,23.,23.,24.,24.,24.,24.,25.,26.,26.,26., ... 26.,27.,28.,28.,28.,28.]; % Interpolate to get dphi/dE_org for male and female for i = 1:length(envshld) disp(envshld{i}); for j = 1:length(morg) disp(morg{j}); if i < 6 for k = 1:6 HZETRN2010_dflux.UFHADM50.(envshld{i}).(morg{j}).ion(k).energy = ... tempflux.(envshld{i}).energy; HZETRN2010_dflux.UFHA DM50.(envshld{i}).(morg{j}).ion(k).A = ... A(k); HZETRN2010_dflux.UFHADM50.(envshld{i}).(morg{j}).ion(k).Z = ... Z(k); for m = 1:length(tempflux.(envshld{i}).energy) if max(tempflux.(envshld{i}).flux(m,k,:)) <= 1e 17 HZETRN2010_dflux.UFHADM50.(envshld{i}).(morg{j}).ion(k).flux(m) = 1e 17; else temp_flux_interp = ... pchip( tempflux.(envshld{i}).waterdepth, ... tempflux.(envshld{i}).flux(m,k,:), ... UFHADM50.(morg{j})); temp_flux_interp( ... UFHADM50.(morg{j}) > ... tempflux.(envshld{i}).waterdepth(end)) = ... tempflux.(envshld{i}).flux(m,k,end); HZETRN2010_dflux.UFHADM50.(envshld{i}).(morg{j}).ion(k).flux(m) = ... mean(temp_flux_interp); end end end else for k = 1:length(A) HZETRN2010_dflux.UFHADM50.(envshld{i}).(morg{j}).ion(k).energy = ... tempflux.(envshld{i}).energy; HZETRN2010_dflux.UFHADM50.(envshld{i}).(morg{j}).ion(k).A = ... A(k); HZETRN2010_dflux.UFHADM50.(envshld{i}).(morg{j}).ion(k).Z = ... Z(k); for m = 1:length(tempflux.(envshld{i}).energy) if max(tempflux.(envshld{i}).flux(m,k,:)) <= 1e 17 HZETRN2010_dflux.UFHADM50.(envshld{i}).(morg{j}).ion(k).flux(m) = 1e 17;

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532 else temp_flux_interp = ... pchip(tempflux.(envshld{i}).waterdepth, ... tempflux.(envshld{i}).flux(m,k,:), ... UFHADM50.(morg{j})); temp_flux_interp( ... UFHADM50.(morg{j}) > ... tempflux.(envshld{i}).waterdepth(end)) = ... tempflux.(envshld{i}).flux(m,k,end); HZETRN2010_df lux.UFHADM50.(envshld{i}).(morg{j}).ion(k).flux(m) = ... mean(temp_flux_interp); end end end end end for j = 1:length(forg) disp(forg{j}); if i < 6 for k = 1:6 HZETRN2010_dflux.UFHADF50.(envshld{i}).(forg{j}).ion(k).energy = ... tempflux.(envshld{i}).energy; HZETRN2010_dflux.UFHADF50.(envshld{i}).(forg{j}).ion(k).A = ... A(k); HZETRN2010_dflux.UFHADF50.(envshld{i}).(forg{j}).ion(k).Z = ... Z(k); for m = 1:length(tempflux.(envshld{i}).energy) if max(tempflux.(envshld{i}).flux(m,k,:)) <= 1e 17 HZETRN2010_dflux.UFHADF50.(envshld{i}).(forg{j}).ion(k).flux(m) = 1e 17; else temp_flux_interp = ... pchip(tempflux.(envshld{i}).waterdepth, ... tempflux.(envshld{i}).flux(m,k,:), ... UFHADF50.(forg{j})); temp_flux_interp( ... UFHADF50.(forg{j}) > ... tempflux.(envshld{i}).waterdepth(end)) = ... tempflux.(envshld{i}).flux(m,k,end); HZETRN2010_dflux.UFHADF50.(envshld{i}).(forg{j}).ion(k).flux(m) = ... mean(temp_flux_interp); end end end else for k = 1:length(A) HZETRN2010_dflux.UFHADF50.(envshld{i}).(forg{j}).ion(k).energy = ... tempflux.(envshld{i}).energy; HZETRN2010_dflux.UFHADF50.(envshld{i}).(forg{j}).ion(k).A = ... A(k); HZETRN2010_dflux.UFHADF50.(envshld{i}).(forg{j}).ion(k).Z = ... Z(k); for m = 1:length(tempflux.(envshld{i}).energy)

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533 if max(tempflux.(envshld{i}).flux(m,k,:)) <= 1e 17 HZETRN2010_dflux.UFHADF50.(envshld{i}).(forg{j}).ion(k).flux(m) = 1e 17; else temp_flux_interp = ... pchip(tempflux.(envshld{i}).waterdepth, ... tempflux.(envshld{i}).flux(m,k,:), ... UFHADF50.(forg{j})); temp_flux_interp( ... UFHADF50.(forg{j}) > ... tempflux.(envshld{i}).waterdepth(end)) = ... tempflux.(envshld{i}).flux(m,k,end); HZETRN2010_df lux.UFHADF50.(envshld{i}).(forg{j}).ion(k).flux(m) = ... mean(temp_flux_interp); end end end end end end

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534 APPENDIX N EXAMPLE PHITS INPUT FILE [ T i t l e ] August 1972 SPE with UFHADM50 (0.5 g cm 2 Al) [ P a r a m e t e r s ] icntl = 0 $ Normal PHITS calculation maxcas = 1000000 $ Number of particles per batch maxbch = 3450 $ Number of batches (23 proc x 150) incut = 0 igcut = 0 rseed = 1 file(6) = phits.out $ Output filename file(7) = /home/abahador/phits230/xsdir file(14) = /home/abahador/phits230/data/trxcrd.dat emin(1) = 1.0E 3 $ Proton cutoff energy emin( 2) = 1.0E 10 $ Neutron cutoff energy dmax(2) = 20.0 $ Neutron max energy for ENDF emin(12) = 1.0 $ Electron cutoff energy emin(13) = 1.0 $ Positron cutoff energy emin(14) = 1.0E 3 $ Photon cutoff energy emin(15) = 1.0E 3 $ D cutoff energy (AMeV) emin(16) = 1.0E 3 $ T cutoff energy (AMeV) emin(17) = 1.0E 3 $ 3He cutoff energy (AMeV) emin(18) = 1.0E 3 $ Alpha cutoff energy (AMeV ) emin(19) = 1.0E 3 $ Nucleus cutoff energy (AMeV) ejamnu = 20.0 $ Use JAM above 20 MeV e mode = 1 $ Event generator mode ON dmax(12) = 1000.0 dmax(13) = 1000.0 dmax(14) = 1000.0 igamma = 1 ipngdr = 1 file(19) = /home/abahador/phits230/data/GDRxsec.inp itall = 1 $ Tally output after every batch ivoxel = 1 file(18) = /home/abahador/M50/M50.bin [ S o u r c e ] set: c1[ 0.5/2.7 ] set: c2[ 500.0 c1 ] c Define co nversion from MeV per cm3 per source to Sv g per cm3 set: c3[ 1.6022E 10 ] set: c4[ 1.848289242186554E+10 ] $ Total number of particles per cm2 set: c5[ pi 500.1 500.1 ] $ Total irradiation area set: c6[ c3 c4 c5 ] $ Calculate product of factors s type = 100 $ User defined source (usrsors.f) [ M a t e r i a l ] c $ Male average soft tissue (1.03 g cm 3) M1 1001.70c 10.5 6000.70c 25.6

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535 7014.70c 2.7 8016.70c 60.2 11023.70c 0.1 15031.70c 0.2 16032.70c 0.3 17035.70c 0.2 19039.70c 0.2 c $ Female average soft tissue (1.02 g cm 3) M2 1001.70c 10.6 6000.70c 31.5 7014.70c 2.4 8016.70c 54.7 11023.70c 0.1 15031.70c 0.2 16032.70c 0.2 17035.70c 0.1 19039.70c 0.2 c $ Blood (1.06 g cm 3) M3 1001.70c 10.2 6000.70c 11.0 7014.70c 3. 3 8016.70c 74.5 11023.70c 0.1 15031.70c 0.1 16032.70c 0.2 17035.70c 0.3 19039.70c 0.2 26056.70c 0.1 c $ Brain (1.04 g cm 3) M4 1001.70c 10.7 6000.70c 14.5 7014.70c 2.2 8016.70c 71.2 11023.70c 0.2 15031.70c 0.4 16032.70c 0.2 17035.70c 0.3 19039.70c 0.3 c $ Breast (0.96 g cm 3) M5 1001.70 c 11.5 6000.70c 38.7 8016.70c 49.8 c $ Eye Lens (1.07 g cm 3) M6 1001.70c 9.6 6000.70c 19.5 7014.70c 5.7 8016.70c 64.6 11023.70c 0.1 15031.70c 0.1 16 032.70c 0.3

PAGE 536

536 17035.70c 0.1 c $ GI Tract (1.03 g cm 3) M7 1001.70c 10.6 6000.70c 11.5 7014.70c 2.2 8016.70c 75.1 11023.70c 0.1 15031.70c 0.1 16032.70c 0.1 17035.70c 0.2 19039.70c 0.1 c $ Heart (1.05 g cm 3) M8 1001.70c 10.4 6000.70c 13.9 7014.70c 2.9 8016.70c 71.8 11023.70c 0.1 15031.70c 0.2 16032.70c 0. 2 17035.70c 0.2 19039.70c 0.3 c $ Kidney (1.05 g cm 3) M9 1001.70c 10.3 6000.70c 13.2 7014.70c 3.0 8016.70c 72.4 11023.70c 0.2 15031.70c 0.2 16032 .70c 0.2 17035.70c 0.2 19039.70c 0.2 20040.70c 0.1 c $ Liver (1.06 g cm 3) M10 1001.70c 10.2 6000.70c 13.9 7014.70c 3.0 8016.70c 71.6 11023.70c 0.2 15031.70c 0.3 16032.70c 0.3 17035.70c 0.2 19039.70c 0.3 c $ Lung (0.26 g cm 3) M11 1001.70c 10.3 6000.70c 10.5 7014.70c 3.1 8016.70c 74.9 11023.70c 0.2 15031.70c 0.2 16032.70c 0.3

PAGE 537

537 17035.70c 0.3 19039.70c 0.2 c $ Ovary (1.05 g cm 3) M12 1001.70c 10.5 6000.70c 9.3 7014.70c 2.4 8016.70c 76.8 11023.70c 0.2 15031.70c 0.2 16032.70c 0.2 17035.70c 0.2 19039.70c 0.2 c $ Pancreas (1.05 g cm 3) M13 1001.70c 10.6 6000.70c 16.9 7014.70c 2.2 8016.70c 69.4 11023.70c 0.2 15031.70c 0.2 16032.70c 0.1 17035.70c 0.2 19039.70c 0.2 c $ Skin (1.10 g cm 3) M14 1001.70c 10.0 6000.70c 20.4 7014.70c 4.2 8016.70c 64.5 11023.70c 0.2 15031.70c 0.1 16032.70c 0.2 17035.70c 0.3 19039.70c 0.1 c $ Spleen (1.06 g cm 3) M15 1001.70c 10.3 6000.70c 11.3 7014.70c 3.2 8016.70c 74.1 11023.70c 0.1 15031.70c 0.3 16032.70c 0.2 17035.70c 0.2 19039.70c 0.3 c $ Teeth (3.00 g cm 3) M16 1001.70c 2.2 6000.70c 9.5 7014.70c 2.9 8016.70c 42.1 12024.70c 0.7 15031.70c 13.7 20040.70c 28.9

PAGE 538

538 c $ Testes (1.04 g cm 3) M17 1001.70c 10.6 6000.70c 9.9 7014.70c 2.0 8016. 70c 76.6 11023.70c 0.2 15031.70c 0.1 16032.70c 0.2 17035.70c 0.2 19039.70c 0.2 c $ Thyroid (1.04 g cm 3) M18 1001.70c 10.4 6000.70c 11.9 7014.70c 2.4 8016.70c 74.5 11023.70c 0.2 15031.70c 0.1 16032.70c 0.1 17035.70c 0.2 19039.70c 0.1 53127.70c 0.1 c $ Muscle (1.05 g cm 3) M19 1001.70c 10.2 6000.70 c 14.3 7014.70c 3.4 8016.70c 71.0 11023.70c 0.1 15031.70c 0.2 16032.70c 0.3 17035.70c 0.1 19039.70c 0.4 c $ Urinary Bladder (1.04 g cm 3) M20 1001.70c 10.5 6000.70c 9.6 7014.70c 2.6 8016.70c 76.1 11023.70c 0.2 15031.70c 0.2 16032.70c 0.2 17035.70c 0.3 19039.70c 0.3 c $ Cartilage (1.10 g cm 3) M21 1001.70c 9.6 6000.70c 9.9 7014.70c 2.2 8016.70c 74.4 11023.70c 0.5 15031.70c 2.2 16032.70c 0.9 17035.70c 0.3

PAGE 539

539 c $ Cortical Bone (1.90 g cm 3) M22 1001.70c 3.5 6000.70c 16.0 7014.70c 4.2 8016.70c 44.5 11023.70c 0.3 12024.70c 0.2 15031.70c 9.5 16032.70c 0.3 20040.70c 21.5 c $ Inactive Marrow (0.98 g cm 3) M23 1 001.70c 11.5 6000.70c 64.4 7014.70c 0.7 8016.70c 23.1 11023.70c 0.1 15031.70c 0.1 16032.70c 0.1 c $ Spongiosa Cranium (1.36 g cm 3) M24 1001.70c 6.9 6000.70c 32.9 7014.70c 3.1 8016.70c 39.2 11023.70c 0.2 12024.70c 0.1 15031.70c 5.3 16032.70c 0.2 20040.70c 11.9 c $ Spongiosa Mandible (1.08 g cm 3) M 25 1001.70c 9.9 6000.70c 48.6 7014.70c 2.2 8016.70c 34.1 11023.70c 0.1 12024.70c 0.1 15031.70c 1.6 16032.70c 0.2 20040.70c 3.3 c $ Spongiosa CV (1.1 7 g cm 3) M26 1001.70c 8.7 6000.70c 38.4 7014.70c 3.1 8016.70c 40.3 11023.70c 0.2 12024.70c 0.2 15031.70c 2.8 16032.70c 0.2 20040.70c 6.1 c $ Spongiosa TV (1.10 g cm 3)

PAGE 540

540 M27 1001.70c 9.6 6000.70c 42.3 7014.70c 2.9 8016.70c 39.6 11023.70c 0.1 12024.70c 0.1 15031.70c 1.7 16032.70c 0.2 20040.70c 3.4 26056.70c 0.1 c $ Spongiosa LV (1.10 g cm 3) M28 1001.70c 9.5 6000.70c 41.9 7014.70c 2.9 8016.70c 39.6 11023.70c 0.1 12024.70c 0.1 15031.70c 1.8 16032.70c 0.2 20040.70c 3.7 26056.70c 0.1 c $ Spongiosa Sternum (1.09 g cm 3) M29 1001.70c 9.8 6000.70c 43.0 7014.70c 2.8 8016.70c 39.4 11023.70c 0.1 12 024.70c 0.1 15031.70c 1.5 16032.70c 0.2 20040.70c 3.0 26056.70c 0.1 c $ Spongiosa Ribs (1.11 g cm 3) M30 1001.70c 9.4 6000.70c 41.3 7014.70c 2.9 8016.70c 39 .8 11023.70c 0.1 12024.70c 0.1 15031.70c 1.9 16032.70c 0.2 20040.70c 4.1 26056.70c 0.1 c $ Spongiosa Scapulae (1.13 g cm 3) M31 1001.70c 9.2 6000.70c 44.8 7014.70c 2.4 8016.70c 35.3 11023.70c 0.1 12024.70c 0.1 15031.70c 2.5

PAGE 541

541 16032.70c 0.2 20040.70c 5.3 c $ Spongiosa Clavicles (1.10 g cm 3) M32 1001.70c 9.7 6000.70c 47.8 7014.70c 2.2 8016.70c 33.8 11023.70c 0.1 12024.70c 0.1 15031.70c 2.0 16032.70c 0.2 20040.70c 4.2 c $ Spongiosa Os Coxae (1.09 g cm 3) M33 1001.70c 9.7 6000.70c 46.1 7014.70c 2.4 8016.70c 36.0 11023.70c 0.1 12024.70c 0.1 15031.70c 1.7 16032.70c 0.2 20040.70c 3.6 c $ Spongiosa Sacrum (1.12 g cm 3) M34 1001.70c 9.4 6000.70c 41.2 7014.70c 2.9 8016.70c 39.8 11023.70c 0.1 12024.70c 0.1 15031.70c 2.0 16032.70c 0.2 20040.70c 4.2 26056.70c 0.1 c $ Spongiosa Humeri, Proximal (1.08 g cm 3) M35 1001.70c 9.9 6000.70c 50.5 7014.70c 1.9 8016.70c 32.0 11023.70c 0.1 12024.70c 0.1 15031.70c 1.7 16032.70c 0 .2 20040.70c 3.5 c $ Spongiosa Humeri, Upper (0.99 g cm 3) M36 1001.70c 11.2 6000.70c 57.4 7014.70c 1.4 8016.70c 29.5 11023.70c 0.1 12024.70c 0.1

PAGE 542

542 15031.70c 0.1 16032.70c 0.1 c $ Spongiosa Humeri, Lower (0.98 g cm 3) M37 1001.70c 11.5 6000.70c 63.2 7014.70c 0.8 8016.70c 24.3 11023.70c 0.1 15031.70c 0.1 16032.70c 0.1 c $ Spongiosa Humeri, Distal (1.12 g cm 3) M38 1001.70c 9.5 6000.70c 51.2 7014.70c 1.6 8016.70c 29.5 11023.70c 0.1 15031.70c 2.5 16032.70c 0.2 20040.70c 5.4 c $ Spo ngiosa Radii, Proximal (1.06 g cm 3) M39 1001.70c 10.2 6000.70c 55.8 7014.70c 1.3 8016.70c 27.5 11023.70c 0.1 15031.70c 1.6 16032.70c 0.1 20040.70c 3.3 c $ Spongiosa Radii, Shaft (0.98 g cm 3) M40 1001.70c 11.5 6000.70c 63.2 7014.70c 0.8 8016.70c 24.3 11023.70c 0.1 15031.70c 0.1 16032.70c 0.1 c $ Spongiosa Radii, Distal (1.08 g cm 3) M41 1001.70c 9.9 6000.70c 53.8 7014.70c 1.4 8016.70c 28.4 11023.70c 0.1 15031.70c 2.0 16032.70c 0.1 20040.70c 4.2 c $ Spongiosa Ulnae, Proximal (1.13 g cm 3) M42 1001.70c 9.4 6000.70c 50.6 7014.70c 1.7

PAGE 543

543 8016.70c 29.8 11023.70c 0.2 12024.70c 0.1 15031.70c 2.6 16032.70c 0.2 20040.70c 5.7 c $ Spongiosa Ulnae, Shaft (0.98 g cm 3) M43 1001.70c 11.5 6000.70c 63.2 7014.70c 0.8 8016.70c 24.3 11023.70c 0.1 15031.70c 0.1 16032.70c 0.1 c $ Spongiosa Ulnae, Distal (1.11 g cm 3) M4 4 1001.70c 9.6 6000.70c 52.1 7014.70c 1.6 8016.70c 29.1 11023.70c 0.1 15031.70c 2.3 16032.70c 0.2 20040.70c 5.0 c $ Spongiosa Wrists and Hands (1.12 g cm 3) M45 1001.70c 9.5 6000.70c 51.2 7014.70c 1.6 8016.70c 29.5 11023.70c 0.1 15031.70c 2.5 16032.70c 0.2 20040.70c 5.4 c $ Spongiosa Femora, Proximal (1.13 g cm 3) M46 1001.70c 9.3 6000.70c 47.1 7014.70c 2.1 8016.70c 33.3 11023.70c 0.1 12024.70c 0.1 15031.70c 2.4 16032.70c 0.2 20040.70c 5.3 c $ Spongiosa Femora, Up per Shaft (0.99 g cm 3) M47 1001.70c 11.2 6000.70c 57.4 7014.70c 1.4 8016.70c 29.5 11023.70c 0.1 12024.70c 0.1 15031.70c 0.1

PAGE 544

544 16032.70c 0.1 c $ Spongiosa Femora, Lower Shaft (0.98 g cm 3) M48 1001.70c 11.5 6000.70c 63.2 7014.70c 0.8 8016.70c 24.3 11023.70c 0.1 15031.70c 0.1 16032.70c 0.1 c $ Spongiosa Femora, Distal (1.11 g cm 3) M49 1001.70c 9.5 6000.70c 51.6 7014.70c 1.6 8016.70c 29.3 11023.70c 0.1 15031.70c 2.4 16032.70c 0.2 20040.70c 5.2 c $ Spongiosa Patellae (1.11 g cm 3) M50 1001 .70c 9.5 6000.70c 51.6 7014.70c 1.6 8016.70c 29.3 11023.70c 0.1 15031.70c 2.4 16032.70c 0.2 20040.70c 5.2 c $ Spongiosa Tibiae, Proximal (1.08 g cm 3) M51 1001.70c 9.9 6000.70c 53.8 7014.70c 1.4 8016.70c 28.3 11023.70c 0.1 15031.70c 1.9 16032.70c 0.1 20040.70c 4.2 c $ Spongiosa Tibiae, Shaft (0.98 g cm 3) M52 1001 .70c 11.5 6000.70c 63.2 7014.70c 0.8 8016.70c 24.3 11023.70c 0.1 15031.70c 0.1 16032.70c 0.1 c $ Spongiosa Tibiae, Distal (1.09 g cm 3) M53 1001.70c 9.8 6000.70 c 53.1 7014.70c 1.5 8016.70c 28.7

PAGE 545

545 11023.70c 0.1 15031.70c 2.1 16032.70c 0.1 20040.70c 4.5 c $ Spongiosa Fibulae, Proximal (1.05 g cm 3) M54 1001.70c 10.4 6000.70c 56.6 7014.70c 1.2 8016.70c 27.1 11023.70c 0.1 15031.70c 1.4 16032.70c 0.1 20040.70c 2.9 c $ Spongiosa Fibulae, Shaft (0.98 g cm 3) M55 1001.70c 11.5 6000.70c 63.2 7014.70c 0.8 8016.70c 24.3 11023.70c 0.1 15031.70c 0.1 16032.70c 0.1 c $ Spongiosa Fibulae, Distal (1.11 g cm 3) M56 1001.70c 9.5 6000.70c 51 .5 7014.70c 1.6 8016.70c 29.3 11023.70c 0.1 15031.70c 2.4 16032.70c 0.2 20040.70c 5.2 c $ Spongiosa Ankles and Feet (1.11 g cm 3) M57 1001.70c 9.5 6000.70c 51.6 7014.70c 1.6 8016.70c 29.3 11023.70c 0.1 15031.70c 2.4 16032.70c 0.2 20040.70c 5.2 c $ Aluminum M58 13027.70c 100.0 c $ Water M59 1001.70c 11.2 8016.70c 88. 8 c $ Larynx/Trachea (1.07 g cm 3) M60 1001.70c 9.6 6000.70c 9.9 7014.70c 2.2

PAGE 546

546 8016.70c 74.4 11023.70c 0.5 15031.70c 2.2 16032.70c 0.9 17035.70c 0.3 c $ Dry air n ear sea level (from NIST) M61 6000.70c 0.0124 7014.70c 75.5267 8016.70c 23.1781 18040.70c 1.2827 [ C e l l ] c 300 0 102 101 202 201 302 301 u=300 lat=1 fill=0:165 0:285 0:902 c infl: { /home/abahador/M50/M50.inp } c -------------------------------------------------c Organs/tissues and corresponding universe numbers c -------------------------------------------------99 0 3000 u=99 1 1 1.03 3000 u=1 vol=576 47.06 $ Residual Soft Tissue 2 1 1.03 3000 u=2 vol=7.12 $ Adrenal (L) 3 1 1.03 3000 u=3 vol=6.90 $ Adrenal (R) 4 4 1.04 3000 u=4 vol=1587.50 $ Brain 5 5 0.94 3000 u=5 vol=30.28 $ Brea st 6 60 1.065 3000 u=6 vol=15.06 $ Bronchi 7 7 1.03 3000 u=7 vol=151.82 $ Right Colon W 8 1 1.03 3000 u=8 vol=101.26 $ Right Colon C 9 21 1.10 3000 u=9 vol=7.96 $ Ears 10 7 1.03 3000 u=10 vol=40.19 $ Esophagus 11 1 1.05 3000 u=11 vol=6.86 $ External nose 12 1 1.03 3000 u=12 vol=16.38 $ Eye balls 13 1 1.03 3000 u=13 vol=10.11 $ Gall Bladder W 14 1 1.03 3000 u=14 vol =58.79 $ Gall Bladder C 15 8 1.05 3000 u=15 vol=327.84 $ Heart W 16 3 1.06 3000 u=16 vol=499.24 $ Heart C 17 9 1.05 3000 u=17 vol=112.75 $ Kidney cortex (L) 18 9 1.05 3000 u=18 vol=112.66 $ Kidney cortex (R) 19 9 1.05 3000 u=19 vol=40.52 $ Kidney medulla (L) 20 9 1.05 3000 u=20 vol=40.26 $ Kidney medulla (R) 21 9 1.05 3000 u=21 vol=8.15 $ Kidney pelvis (L) 22 9 1.05 3000 u=22 vol=8. 10 $ Kidney pelvis (R) 23 60 1.065 3000 u=23 vol=27.16 $ Larynx 24 6 1.07 3000 u=24 vol=0.54 $ Lens 25 10 1.06 3000 u=25 vol=1766.32 $ Liver 26 11 0.335 3000 u=26 vol=1602.70 $ Lung (L) 27 11 0 .335 3000 u=27 vol=2121.46 $ Lung (R) 28 1 1.03 3000 u=28 vol=2.13 $ Nasal layer (ant) 29 1 1.03 3000 u=29 vol=17.76 $ Nasal layer (post) 30 1 1.03 3000 u=30 vol=2.32 $ Oral cavity layer 32 13 1 .03 3000 u=32 vol=140.76 $ Pancreas 33 19 1.05 3000 u=33 vol=18.47 $ Penis 34 1 1.03 3000 u=34 vol=2.61 $ Pharynx 35 1 1.03 3000 u=35 vol=0.64 $ Pituitary Gland

PAGE 547

547 36 1 1.03 3000 u=36 vo l=17.21 $ Prostate 37 7 1.03 3000 u=37 vol=70.58 $ Rectosigmoid W 38 1 0.971 3000 u=38 vol=80.26 $ Rectosigmoid C 39 1 1.03 3000 u=39 vol=50.40 $ Salivary Glands (paro) 40 1 1.03 3000 u=40 vol= 31.38 $ Scrotum 41 7 1.03 3000 u=41 vol=641.61 $ SI W 42 1 0.44 3000 u=42 vol=830.34 $ SI C 43 14 1.10 3000 u=43 vol=4661.62 $ Skin 44 4 1.04 3000 u=44 vol=74.09 $ Spinal Cord 45 15 1.06 3 000 u=45 vol=147.04 $ Spleen 46 7 1.03 3000 u=46 vol=151.98 $ Stomach W 47 1 1.03 3000 u=47 vol=250.72 $ Stomach C 48 17 1.04 3000 u=48 vol=33.44 $ Testes 49 1 1.03 3000 u=49 vol=25.28 $ Thymus 50 18 1.05 3000 u=50 vol=19.68 $ Thyroid 51 19 1.05 3000 u=51 vol=71.53 $ Tongue 52 1 1.03 3000 u=52 vol=3.38 $ Tonsil 53 60 1.07 3000 u=53 vol=9.90 $ Trachea 54 20 1.04 3000 u= 54 vol=49.88 $ Urinary bladder W 55 59 1.01 3000 u=55 vol=208.05 $ Urinary bladder C 57 61 0.0012 3000 u=57 vol=97.55 $ Air (in body) 58 7 1.03 3000 u=58 vol=151.34 $ Left Colon W 59 1 0.663 3000 u=5 9 vol=55.95 $ Left Colon C 60 1 1.03 3000 u=60 vol=25.25 $ Salivary Glands 61 1 1.03 3000 u=61 vol=11.01 $ Salivary Glands 128 21 1.10 3000 u=128 vol=47.71 $ Costal cartilage 129 21 1.10 3000 u=129 vol=2.78 $ Cervical Discs 130 21 1.10 3000 u=130 vol=34.21 $ Thoracic Discs 131 21 1.10 3000 u=131 vol=28.45 $ Lumbar Discs 151 22 1.90 3000 u=151 vol=473.93 $ Cortical Bone 152 22 1.90 3000 u=152 vol= 23.55 $ Cortical Bone 153 22 1.90 3000 u=153 vol=182.02 $ Cortical Bone 154 22 1.90 3000 u=154 vol=25.70 $ Cortical Bone 155 22 1.90 3000 u=155 vol=20.31 $ Cortical Bone 156 22 1.90 3000 u=156 vol=119.94 $ Cortical Bone 157 22 1.90 3000 u=157 vol=30.98 $ Cortical Bone 158 22 1.90 3000 u=158 vol=77.41 $ Cortical Bone 159 22 1.90 3000 u=159 vol=65.35 $ Cortical Bone 160 22 1.90 3000 u=160 vol=53.66 $ Cor tical Bone 161 22 1.90 3000 u=161 vol=239.60 $ Cortical Bone 162 22 1.90 3000 u=162 vol=20.80 $ Cortical Bone 163 22 1.90 3000 u=163 vol=70.40 $ Cortical Bone 164 22 1.90 3000 u=164 vol=53.12 $ Cortical Bone 165 22 1.90 3000 u=165 vol=30.91 $ Cortical Bone 166 22 1.90 3000 u=166 vol=23.84 $ Cortical Bone 167 22 1.90 3000 u=167 vol=38.00 $ Cortical Bone 168 22 1.90 3000 u=168 vol=46.11 $ Cortical Bone 169 22 1.90 3000 u=169 vol=13.54 $ Cortical Bone 170 22 1.90 3000 u=170 vol=4.66 $ Cortical Bone 171 22 1.90 3000 u=171 vol=11.90 $ Cortical Bone 172 22 1.90 3000 u=172 vol=17.33 $ Cortical Bone 173 22 1.9 0 3000 u=173 vol=6.80 $ Cortical Bone 174 22 1.90 3000 u=174 vol=3.79 $ Cortical Bone 175 22 1.90 3000 u=175 vol=156.96 $ Cortical Bone 176 22 1.90 3000 u=176 vol=26.74 $ Cortical Bone

PAGE 548

548 177 22 1.90 300 0 u=177 vol=66.38 $ Cortical Bone 178 22 1.90 3000 u=178 vol=59.18 $ Cortical Bone 179 22 1.90 3000 u=179 vol=36.03 $ Cortical Bone 180 22 1.90 3000 u=180 vol=5.46 $ Cortical Bone 181 22 1.90 3000 u=1 81 vol=22.13 $ Cortical Bone 182 22 1.90 3000 u=182 vol=24.32 $ Cortical Bone 183 22 1.90 3000 u=183 vol=11.04 $ Cortical Bone 184 22 1.90 3000 u=184 vol=19.89 $ Cortical Bone 185 22 1.90 3000 u=185 vol =29.78 $ Cortical Bone 186 22 1.90 3000 u=186 vol=26.46 $ Cortical Bone 187 22 1.90 3000 u=187 vol=3.20 $ Cortical Bone 188 22 1.90 3000 u=188 vol=101.02 $ Cortical Bone 189 16 3.00 3000 u=189 vol=12.13 $ Teeth 201 24 1.36 3000 u=201 vol=304.80 $ Cranium 202 25 1.08 3000 u=202 vol=40.00 $ Mandible 203 31 1.13 3000 u=203 vol=349.74 $ Scapulae 204 32 1.10 3000 u=204 vol=38.74 $ Clavicles 205 29 1.09 3000 u=205 vol=47.54 $ Sternum 206 30 1.11 3000 u=206 vol=220.10 $ Ribs 207 26 1.17 3000 u=207 vol=58.04 $ Vertebrae C 208 27 1.10 3000 u=208 vol=228.24 $ Vertebrae T 209 28 1.10 3000 u=209 vol=257.82 $ Vertebrae L 210 34 1.12 3000 u=210 vol=167.37 $ Sacrum 211 33 1.09 3000 u=211 vol=724.41 $ Os Coxae 212 46 1.13 3000 u=212 vol=250.29 $ Femur proximal 213 47 0.99 3000 u=213 vol=132.88 $ Femur upper sha ft 214 48 0.98 3000 u=214 vol=101.82 $ Femur lower shaft 215 49 1.11 3000 u=215 vol=285.65 $ Femur distal 216 51 1.08 3000 u=216 vol=233.42 $ Tibiae proximal 217 52 0.98 3000 u=217 vol=152.32 $ Tibiae shaft 2 18 53 1.09 3000 u=218 vol=81.44 $ Tibiae distal 219 54 1.05 3000 u=219 vol=19.22 $ Fibulae proximal 220 55 0.98 3000 u=220 vol=12.40 $ Fibulae shaft 221 56 1.11 3000 u=221 vol=16.03 $ Fibulae distal 222 5 0 1.11 3000 u=222 vol=33.44 $ Patellae 223 57 1.11 3000 u=223 vol=374.18 $ Ankle+Feet 224 35 1.08 3000 u=224 vol=174.91 $ Humerus proximal 225 36 0.99 3000 u=225 vol=37.28 $ Humerus upper shaft 226 37 0.98 3000 u=226 vol=32.82 $ Humerus lower shaft 227 38 1.12 3000 u=227 vol=88.50 $ Humerus distal 228 39 1.06 3000 u=228 vol=14.64 $ Radii proximal 229 40 0.98 3000 u=229 vol=16.85 $ Radii shaft 230 41 1.08 3000 u=230 vol=26.21 $ Radii distal 231 42 1.13 3000 u=231 vol=47.28 $ Ulnae proximal 232 43 0.98 3000 u=232 vol=21.57 $ Ulnae shaft 233 44 1.11 3000 u=233 vol=9.68 $ Ulnae distal 234 45 1.12 3000 u=234 vol=58.46 $ Wrist+Hand c 1001 0 11 12 21 22 31 32 fill=300 $ Phantom Box 1002 0 3000 #1001 $ Vaccuum 1003 58 2.7 3000 3001 $ Spherical shell 1004 0 3001 3002 $ Outside of shell 1005 1 3002 $ *** GRAVEYARD *** [ S u r f a c e ]

PAGE 549

549 c Phantom Box 11 PX 16.6 12 PX 16.6 21 PY 28.6 22 PY 28.6 31 PZ 90.2 32 PZ 90.4 c Voxel Dime nsion 101 PX 0 102 PX 0.2 201 PY 0 202 PY 0.2 301 PZ 0 302 PZ 0.2 c Spherical Shell 3000 SO c2 3001 SO 500.0 3002 SO 1000.0 [ T T r a c k ] mesh = reg $ region mesh reg = 43 $ skin 207 $ CV spongiosa 204 $ clavicle spongiosa 201 $ cranium spongiosa 212 $ proximal fe mur spongiosa 213 $ femur upper shaft 224 $ proximal humerus spongiosa 225 $ humerus upper shaft 209 $ LV spongiosa 202 $ mandible spongiosa 211 $ pelvis spongiosa 206 $ rib spongiosa 210 $ sacrum spongiosa 203 $ scapula spo ngiosa 205 $ sternum spongiosa 208 $ TV spongiosa 24 $ eye lens 12 $ eye ball 46 $ stomach ( 7 58 37 ) $ colon 25 $ liver ( 26 27 ) $ lung 10 $ esophagus 54 $ bladder 50 $ thyroid 4 $ brain ( 39 60 61 ) $ salivary glands ( 2 3 ) $ adrenals ( 28 29 34 ) $ ET region (no larynx) 23 $ ET region (larynx) 13 $ gallbladder 15 $ heart ( 17 18 19 20 21 22 ) $ kidneys 1 $ muscle (RST)

PAGE 550

550 32 $ pancreas 41 $ small intestines 45 $ spleen 49 $ thymus 30 $ oral mucosa 48 $ testes 36 $ prostate c 5 $ breasts c 31 $ ovaries c 56 $ uterus unit = 2 $ Fluence [cm 2 MeV 1] file = M50_AUG1972_05_FZE_A.out axis = eng e type = 3 ne = 100 emin = 0.001 emax = 10000000.0 material = all factor = c6 part = 1H 2H 3H 3He 4He 6Li [ T T r a c k ] mesh = reg $ region mesh reg = 43 $ skin 207 $ CV spongiosa 204 $ clavicle spongiosa 201 $ cranium spongiosa 212 $ proximal femur spongiosa 213 $ femur upper shaft 224 $ proximal humerus spongiosa 225 $ humerus upper shaft 2 09 $ LV spongiosa 202 $ mandible spongiosa 211 $ pelvis spongiosa 206 $ rib spongiosa 210 $ sacrum spongiosa 203 $ scapula spongiosa 205 $ sternum spongiosa 208 $ TV spongiosa 24 $ eye lens 12 $ eye bal l 46 $ stomach ( 7 58 37 ) $ colon 25 $ liver ( 26 27 ) $ lung 10 $ esophagus 54 $ bladder 50 $ thyroid 4 $ brain ( 39 60 61 ) $ salivary glands ( 2 3 ) $ adrenals ( 28 29 34 ) $ ET region (no larynx) 23 $ ET region (larynx) 13 $ gallbladder 15 $ heart

PAGE 551

551 ( 17 18 19 20 21 22 ) $ kidney s 1 $ muscle (RST) 32 $ pancreas 41 $ small intestines 45 $ spleen 49 $ thymus 30 $ oral mucosa 48 $ testes 36 $ prostate c 5 $ breasts c 31 $ ovaries c 56 $ uterus unit = 2 $ Fluence [cm 2 MeV 1] file = M50_AUG1972_05_FZE_B.out axis = eng e type = 3 ne = 100 emin = 0.001 emax = 10000000.0 material = all factor = c6 part = 7 Li 8Be 9Be 10Be 10B 11B [ T T r a c k ] mesh = reg $ region mesh reg = 43 $ skin 207 $ CV spongiosa 204 $ clavicle spongiosa 201 $ cranium spongiosa 212 $ proximal femur spongiosa 213 $ femur upper shaft 224 $ proximal humerus spongiosa 225 $ humerus upper shaft 209 $ LV spongiosa 202 $ mandible spongiosa 211 $ pelvis spongiosa 206 $ rib spongiosa 210 $ sacrum spongiosa 203 $ scapula spongiosa 205 $ sternum spongiosa 208 $ TV spongiosa 24 $ eye lens 12 $ eye ball 46 $ stomach ( 7 58 37 ) $ colon 25 $ liver ( 26 27 ) $ lung 10 $ esophagus 54 $ bladder 50 $ thyroid 4 $ brain ( 39 60 61 ) $ salivary glands ( 2 3 ) $ adrenals ( 28 29 34 ) $ ET region (no larynx) 23 $ ET region (larynx)

PAGE 552

552 13 $ gallbladder 15 $ hea rt ( 17 18 19 20 21 22 ) $ kidneys 1 $ muscle (RST) 32 $ pancreas 41 $ small intestines 45 $ spleen 49 $ thymus 30 $ oral mucosa 48 $ testes 36 $ prostate c 5 $ breasts c 31 $ ovaries c 56 $ uterus unit = 2 $ Fluence [cm 2 MeV 1] file = M50_AUG1972_05_FZE_C.out axis = eng e type = 3 ne = 100 emin = 0.001 emax = 10000000.0 material = all factor = c6 part = 12C 13C 14N 15N 16O 17O [ T T r a c k ] mesh = reg $ region mesh reg = 43 $ skin 207 $ CV spongiosa 204 $ clavicle spongiosa 201 $ cranium spongiosa 212 $ proximal femur spongiosa 213 $ femur upper shaft 224 $ proximal humerus spongiosa 225 $ humerus upper shaft 209 $ LV spongiosa 202 $ mandible spongiosa 211 $ pelvis spon giosa 206 $ rib spongiosa 210 $ sacrum spongiosa 203 $ scapula spongiosa 205 $ sternum spongiosa 208 $ TV spongiosa 24 $ eye lens 12 $ eye ball 46 $ stomach ( 7 58 37 ) $ colon 25 $ liver ( 26 27 ) $ lung 10 $ esophagus 54 $ bladder 50 $ thyroid 4 $ brain ( 39 60 61 ) $ salivary glands ( 2 3 ) $ adrenals

PAGE 553

553 ( 28 29 34 ) $ ET region (no larynx) 23 $ ET region (larynx) 13 $ gallbladder 15 $ heart ( 17 18 19 20 21 22 ) $ kidneys 1 $ muscle (RST) 32 $ pancreas 41 $ small intestines 4 5 $ spleen 49 $ thymus 30 $ oral mucosa 48 $ testes 36 $ prostate c 5 $ breasts c 31 $ ovaries c 56 $ uterus unit = 2 $ Fluence [cm 2 MeV 1] file = M50_AUG1972_05_FZE_D.out axis = eng e type = 3 ne = 100 emin = 0.001 emax = 10000000.0 material = all factor = c6 part = 18F 19F 20Ne 21Ne 22Ne 23Na [ T T r a c k ] mesh = reg $ region mesh reg = 43 $ skin 207 $ CV spongiosa 204 $ clavicle spongiosa 201 $ cranium spongiosa 212 $ proximal femur spongiosa 213 $ femur upper shaft 224 $ proximal humerus spongiosa 225 $ humerus upper shaft 209 $ LV spongiosa 202 $ mandible spongios a 211 $ pelvis spongiosa 206 $ rib spongiosa 210 $ sacrum spongiosa 203 $ scapula spongiosa 205 $ sternum spongiosa 208 $ TV spongiosa 24 $ eye lens 12 $ eye ball 46 $ stomach ( 7 58 37 ) $ colon 25 $ liver ( 26 27 ) $ lung 10 $ esophagus 54 $ bladder 50 $ thyroid 4 $ brain

PAGE 554

554 ( 39 60 61 ) $ salivary glands ( 2 3 ) $ adrenals ( 28 29 34 ) $ ET region (no larynx) 23 $ ET region (larynx) 13 $ gallbladder 15 $ heart ( 17 18 19 20 21 22 ) $ kidneys 1 $ muscle (RST) 32 $ pancreas 41 $ small intestines 45 $ spleen 49 $ thymus 30 $ oral mucosa 48 $ testes 36 $ prostate c 5 $ breasts c 31 $ ovaries c 56 $ uterus unit = 2 $ Fluence [cm 2 MeV 1] file = M50_AUG1972_05_FZE_E.out axis = eng e type = 3 ne = 100 emin = 0.001 emax = 10000000.0 material = all factor = c6 part = 24Mg 25Mg 26Mg 27Al 28Si 29Si [ T T r a c k ] mesh = reg $ region mesh reg = 43 $ skin 207 $ CV spongiosa 204 $ clavicle spongiosa 201 $ cranium spongiosa 212 $ proximal femur spongiosa 213 $ femur upper shaft 224 $ proximal humerus spongiosa 225 $ humerus upper shaft 20 9 $ LV spongiosa 202 $ mandible spongiosa 211 $ pelvis spongiosa 206 $ rib spongiosa 210 $ sacrum spongiosa 203 $ scapula spongiosa 205 $ sternum spongiosa 208 $ TV spongiosa 24 $ eye lens 12 $ eye ball 46 $ stomach ( 7 58 37 ) $ colon 25 $ liver ( 26 27 ) $ lung 10 $ esophagus 54 $ bladder

PAGE 555

555 50 $ thyroid 4 $ brain ( 39 60 61 ) $ salivary glands ( 2 3 ) $ adrenals ( 28 29 34 ) $ ET region ( no larynx) 23 $ ET region (larynx) 13 $ gallbladder 15 $ heart ( 17 18 19 20 21 22 ) $ kidneys 1 $ muscle (RST) 32 $ pancreas 41 $ small intestines 45 $ spleen 49 $ thymus 3 0 $ oral mucosa 48 $ testes 36 $ prostate c 5 $ breasts c 31 $ ovaries c 56 $ uterus unit = 2 $ Fluence [cm 2 MeV 1] file = M50_AUG1972_05_FZE_F.out axis = eng e type = 3 ne = 100 emin = 0.001 emax = 10000000.0 material = all factor = c6 part = 30Si 31P 32S 33S 34S 36S [ T T r a c k ] mesh = reg $ region mesh reg = 43 $ skin 207 $ CV spongiosa 204 $ clavicle spongiosa 201 $ cranium spongiosa 212 $ proximal femur spongiosa 213 $ femur upper shaft 224 $ proximal humerus spongiosa 225 $ humerus upper shaft 209 $ LV spongiosa 202 $ mandible spongiosa 211 $ pelvis spongiosa 206 $ rib spongiosa 210 $ sacrum spongiosa 203 $ scapula spongiosa 205 $ sternum spongiosa 208 $ TV spongiosa 24 $ eye lens 12 $ eye ball 46 $ stomach ( 7 58 37 ) $ colon 25 $ liver ( 26 27 ) $ lung

PAGE 556

556 10 $ esophagus 54 $ bladder 50 $ thyroid 4 $ brain ( 39 60 61 ) $ salivary glands ( 2 3 ) $ ad renals ( 28 29 34 ) $ ET region (no larynx) 23 $ ET region (larynx) 13 $ gallbladder 15 $ heart ( 17 18 19 20 21 22 ) $ kidneys 1 $ muscle (RST) 32 $ pancreas 41 $ small intestines 45 $ spleen 49 $ thymus 30 $ oral mucosa 48 $ testes 36 $ prostate c 5 $ breasts c 31 $ ovaries c 56 $ uterus unit = 2 $ Fluence [cm 2 MeV 1] file = M50_AUG1972_05_FZE_G.out axis = eng e type = 3 ne = 100 emin = 0.001 emax = 10000000.0 material = all factor = c6 part = 35Cl 37Cl 36Ar 38Ar 40Ar 39K [ T T r a c k ] mesh = reg $ region mesh reg = 43 $ skin 207 $ CV spongiosa 204 $ clavicle spongiosa 201 $ cranium spongiosa 212 $ proximal femur spongiosa 213 $ femur upper shaft 224 $ proximal humerus spongiosa 225 $ humerus upper shaft 209 $ LV spongiosa 202 $ mandible spongiosa 211 $ pelvis spongiosa 206 $ rib spongiosa 210 $ sacrum spongiosa 203 $ scapula spongiosa 205 $ sternum spongiosa 208 $ TV spongiosa 24 $ eye lens 12 $ eye ball 46 $ stomach ( 7 58 37 ) $ colon

PAGE 557

557 25 $ liver ( 26 27 ) $ lung 10 $ esophagus 54 $ bladder 50 $ thyroid 4 $ brain ( 39 60 61 ) $ salivary glands ( 2 3 ) $ adrenals ( 28 29 34 ) $ ET region (no larynx) 23 $ ET region (larynx) 13 $ gallbladder 15 $ heart ( 17 18 19 20 21 22 ) $ kidneys 1 $ muscle (RST) 32 $ pancreas 41 $ small intestines 45 $ spleen 49 $ thymus 30 $ oral mucosa 48 $ testes 36 $ prostate c 5 $ breasts c 31 $ ovaries c 56 $ uterus unit = 2 $ Fluence [cm 2 MeV 1] file = M50_AUG1972_05_FZE_H.out axis = eng e type = 3 ne = 100 emin = 0.001 emax = 10000000.0 material = all factor = c6 part = 40K 41K 40Ca 42Ca 43Ca 44Ca [ T T r a c k ] mesh = reg $ region mesh reg = 43 $ skin 207 $ CV spongiosa 204 $ clavicle spongiosa 201 $ cranium spongiosa 212 $ proximal femur spongiosa 213 $ femur upper shaft 224 $ proximal humerus spongiosa 225 $ humerus upper shaft 209 $ LV spongiosa 202 $ mandible spongiosa 211 $ pelvis spongiosa 206 $ rib spongiosa 210 $ sacrum spongiosa 203 $ scapula spongiosa 205 $ sternum spongiosa 208 $ TV spongiosa 24 $ eye lens 12 $ eye ball

PAGE 558

558 46 $ stomach ( 7 58 37 ) $ colon 25 $ liver ( 26 27 ) $ lung 10 $ esophagus 54 $ bladder 50 $ thyroid 4 $ brain ( 39 60 61 ) $ salivary glands ( 2 3 ) $ adrenals ( 28 29 34 ) $ ET region (no larynx) 23 $ ET region (lar ynx) 13 $ gallbladder 15 $ heart ( 17 18 19 20 21 22 ) $ kidneys 1 $ muscle (RST) 32 $ pancreas 41 $ small intestines 45 $ spleen 49 $ thymus 30 $ oral mucosa 48 $ testes 36 $ prostate c 5 $ breasts c 31 $ ovaries c 56 $ uterus unit = 2 $ Fluence [cm 2 MeV 1] file = M50_AUG1972_05_ FZE_I.out axis = eng e type = 3 ne = 100 emin = 0.001 emax = 10000000.0 material = all factor = c6 part = 46Ca 48Ca 45Sc 46Ti 47Ti 48Ti [ T T r a c k ] mesh = reg $ region mesh reg = 43 $ skin 207 $ CV spongiosa 204 $ clavicle spongiosa 201 $ cranium spongiosa 212 $ proximal fem ur spongiosa 213 $ femur upper shaft 224 $ proximal humerus spongiosa 225 $ humerus upper shaft 209 $ LV spongiosa 202 $ mandible spongiosa 211 $ pelvis spongiosa 206 $ rib spongiosa 210 $ sacrum spongiosa 203 $ scapula spongiosa 205 $ sternum spongiosa 208 $ TV spongiosa

PAGE 559

559 24 $ eye lens 12 $ eye ball 46 $ stomach ( 7 58 37 ) $ colon 25 $ liver ( 26 27 ) $ lung 10 $ esophagus 54 $ bladder 50 $ thyroid 4 $ brain ( 39 60 61 ) $ salivary glands ( 2 3 ) $ adrenals ( 28 29 34 ) $ ET region (no larynx) 23 $ ET region (larynx) 13 $ gallbladder 15 $ heart ( 17 18 19 20 21 22 ) $ kidneys 1 $ muscle (RST) 32 $ pancreas 41 $ small intestines 45 $ spleen 49 $ thymus 30 $ oral mucosa 48 $ testes 36 $ prostate c 5 $ breasts c 31 $ ovaries c 56 $ uterus unit = 2 $ Fl uence [cm 2 MeV 1] file = M50_AUG1972_05_FZE_J.out axis = eng e type = 3 ne = 100 emin = 0.001 emax = 10000000.0 material = all factor = c6 part = 49Ti 50Ti 50V 51V 50Cr 52Cr [ T T r a c k ] mesh = reg $ region mesh reg = 43 $ skin 207 $ CV spongiosa 204 $ clavicle spongiosa 201 $ cranium spongiosa 212 $ proximal femur spongiosa 213 $ femur upper shaft 224 $ proximal humerus spongiosa 225 $ humerus upper shaft 209 $ LV spongiosa 202 $ mandible spongiosa 211 $ pelvis spongiosa 206 $ rib spongiosa 210 $ sac rum spongiosa 203 $ scapula spongiosa

PAGE 560

56 0 205 $ sternum spongiosa 208 $ TV spongiosa 24 $ eye lens 12 $ eye ball 46 $ stomach ( 7 58 37 ) $ colon 25 $ liver ( 26 27 ) $ lung 10 $ esophagus 54 $ bladder 50 $ thyroid 4 $ brain ( 39 60 61 ) $ salivary glands ( 2 3 ) $ adrenals ( 28 29 34 ) $ ET region (no larynx) 23 $ ET region (larynx) 13 $ gallbladder 15 $ heart ( 17 18 19 20 21 22 ) $ kidneys 1 $ muscle (RST) 32 $ pancreas 41 $ small intestines 45 $ spleen 49 $ thymus 30 $ oral mucosa 48 $ testes 36 $ prostate c 5 $ breasts c 31 $ ovaries c 56 $ uterus unit = 2 $ Fluence [cm 2 MeV 1] file = M50_AUG1972_05_FZE_K.out axis = eng e type = 3 ne = 100 emin = 0.001 emax = 10000000.0 material = all factor = c6 part = 53Cr 54Cr 55Mn 54Fe 56Fe 57Fe [ T T r a c k ] mesh = reg $ region mesh reg = 43 $ skin 207 $ CV spongiosa 204 $ clav icle spongiosa 201 $ cranium spongiosa 212 $ proximal femur spongiosa 213 $ femur upper shaft 224 $ proximal humerus spongiosa 225 $ humerus upper shaft 209 $ LV spongiosa 202 $ mandible spongiosa 211 $ pelvis spongiosa 206 $ rib spongiosa

PAGE 561

561 210 $ sacrum spongiosa 203 $ scapula spongiosa 205 $ sternum spongiosa 208 $ TV spongiosa 24 $ eye lens 12 $ eye ball 46 $ stomach ( 7 58 37 ) $ colon 25 $ liver ( 26 27 ) $ lung 10 $ esophagus 54 $ bladder 50 $ thyroid 4 $ brain ( 39 60 61 ) $ salivary glands ( 2 3 ) $ adrenals ( 28 29 34 ) $ ET region (no larynx) 23 $ ET region (larynx) 13 $ gallbladder 15 $ heart ( 17 18 1 9 20 21 22 ) $ kidneys 1 $ muscle (RST) 32 $ pancreas 41 $ small intestines 45 $ spleen 49 $ thymus 30 $ oral mucosa 48 $ testes 36 $ prostate c 5 $ breasts c 31 $ ovaries c 56 $ uterus unit = 2 $ Fluence [cm 2 MeV 1] file = M50_AUG1972_05_FZE_N.out axis = eng e type = 3 ne = 170 emin = 1e 10 emax = 10000000. 0 material = all factor = c6 part = neutron [ T T r a c k ] mesh = reg $ region mesh reg = 43 $ skin 207 $ CV spongiosa 204 $ clavicle spongiosa 201 $ cranium spongiosa 212 $ proximal femur spongiosa 213 $ femur upper shaft 224 $ proximal humerus s pongiosa 225 $ humerus upper shaft 209 $ LV spongiosa 202 $ mandible spongiosa

PAGE 562

562 211 $ pelvis spongiosa 206 $ rib spongiosa 210 $ sacrum spongiosa 203 $ scapula spongiosa 205 $ sternum spongiosa 208 $ TV spongiosa 24 $ eye lens 12 $ eye ball 46 $ stomach ( 7 58 37 ) $ colon 25 $ liver ( 26 27 ) $ lung 10 $ esophagus 54 $ bladder 50 $ thyroid 4 $ brain ( 39 60 61 ) $ saliv ary glands ( 2 3 ) $ adrenals ( 28 29 34 ) $ ET region (no larynx) 23 $ ET region (larynx) 13 $ gallbladder 15 $ heart ( 17 18 19 20 21 22 ) $ kidneys 1 $ muscle (RST) 32 $ pancreas 41 $ small intestines 45 $ splee n 49 $ thymus 30 $ oral mucosa 48 $ testes 36 $ prostate c 5 $ breasts c 31 $ ovaries c 56 $ uterus unit = 2 $ Fluence [cm 2 MeV 1] file = M50_AUG1972_05_FZE_elec.out axis = eng e type = 3 ne = 70 emin = 1.0 emax = 1000000 0.0 material = all factor = c6 part = electron [ T T r a c k ] mesh = reg $ region mesh reg = 43 $ skin 207 $ CV spongiosa 204 $ clavicle spongiosa 201 $ cranium spongiosa 212 $ proximal femur spongiosa 213 $ femur upper shaft 224 $ proximal humerus s pongiosa 225 $ humerus upper shaft

PAGE 563

563 209 $ LV spongiosa 202 $ mandible spongiosa 211 $ pelvis spongiosa 206 $ rib spongiosa 210 $ sacrum spongiosa 203 $ scapula spongiosa 205 $ sternum spongiosa 208 $ TV spongiosa 24 $ eye lens 12 $ eye ball 46 $ stomach ( 7 58 37 ) $ colon 25 $ liver ( 26 27 ) $ lung 10 $ esophagus 54 $ bladder 50 $ thyroid 4 $ brain ( 39 60 61 ) $ saliv ary glands ( 2 3 ) $ adrenals ( 28 29 34 ) $ ET region (no larynx) 23 $ ET region (larynx) 13 $ gallbladder 15 $ heart ( 17 18 19 20 21 22 ) $ kidneys 1 $ muscle (RST) 32 $ pancreas 41 $ small intestines 45 $ splee n 49 $ thymus 30 $ oral mucosa 48 $ testes 36 $ prostate c 5 $ breasts c 31 $ ovaries c 56 $ uterus unit = 2 $ Fluence [cm 2 MeV 1] file = M50_AUG1972_05_FZE_pos.out axis = eng e type = 3 ne = 70 emin = 1.0 emax = 10000000 .0 material = all factor = c6 part = positron [ T D e p o s i t ] mesh = reg $ region mesh reg = 43 $ skin 207 $ CV spongiosa 204 $ clavicle spongiosa 201 $ cranium spongiosa 212 $ proximal femur spongiosa 213 $ femur upper shaft

PAGE 564

564 224 $ proximal humerus spongiosa 225 $ humerus upper shaft 209 $ LV spongiosa 202 $ mandible spongiosa 211 $ pelvis spongiosa 206 $ rib spongiosa 210 $ sacrum spongiosa 203 $ scapula spongiosa 205 $ sternum spongiosa 208 $ TV spongiosa 24 $ eye lens 12 $ eye ball 46 $ stomach ( 7 58 37 ) $ colon 25 $ liver ( 26 27 ) $ lung 10 $ esophagus 54 $ bladder 50 $ thyroid 4 $ brain ( 39 60 61 ) $ saliv ary glands ( 2 3 ) $ adrenals ( 28 29 34 ) $ ET region (no larynx) 23 $ ET region (larynx) 13 $ gallbladder 15 $ heart ( 17 18 19 20 21 22 ) $ kidneys 1 $ muscle (RST) 32 $ pancreas 41 $ small intestines 45 $ splee n 49 $ thymus 30 $ oral mucosa 48 $ testes 36 $ prostate c 5 $ breasts c 31 $ ovaries c 56 $ uterus letmat = 59 $ LET in water dedxfnc = 1 output = dose unit = 1 $ Dose [MeV per cm3 per source] file = M50_ AUG1972_05_H.out axis = reg material = all factor = c6 [ T D e p o s i t ] mesh = reg $ region mesh reg = 43 $ skin 207 $ CV spongiosa 204 $ clavicle spongiosa 201 $ cranium spongiosa 212 $ proximal femur spongiosa 213 $ femur upper shaft

PAGE 565

565 224 $ proximal h umerus spongiosa 225 $ humerus upper shaft 209 $ LV spongiosa 202 $ mandible spongiosa 211 $ pelvis spongiosa 206 $ rib spongiosa 210 $ sacrum spongiosa 203 $ scapula spongiosa 205 $ sternum spongiosa 208 $ TV spongiosa 24 $ eye lens 12 $ eye ball 46 $ stomach ( 7 58 37 ) $ colon 25 $ liver ( 26 27 ) $ lung 10 $ esophagus 54 $ bladder 50 $ thyroid 4 $ brain ( 39 60 61 ) $ salivary glands ( 2 3 ) $ adrenals ( 28 29 34 ) $ ET region (no larynx) 23 $ ET region (larynx) 13 $ gallbladder 15 $ heart ( 17 18 19 20 21 22 ) $ kidneys 1 $ muscle (RST) 32 $ pancreas 41 $ small intestines 45 $ spleen 49 $ thymus 30 $ oral mucosa 48 $ testes 36 $ prostate c 5 $ breasts c 31 $ ovaries c 56 $ uterus letmat = 59 $ LET in water dedxfnc = 0 output = dose unit = 1 $ Dose [MeV per cm3 per source] file = M50_AUG1972_05_D.o ut axis = reg material = all factor = c6 [ T L E T ] mesh = reg $ region mesh reg = 43 $ skin 207 $ CV spongiosa 204 $ clavicle spongiosa 201 $ cranium spongiosa 212 $ proximal femur spongiosa 213 $ femur upper shaft

PAGE 566

566 224 $ proximal humerus spongiosa 225 $ humerus upper shaft 209 $ LV spongiosa 202 $ mandible spongiosa 211 $ pelvis spongiosa 206 $ rib spongiosa 210 $ sacrum spongiosa 203 $ scapula spongiosa 205 $ sternum spongiosa 208 $ TV spongiosa 24 $ eye lens 12 $ eye ball 46 $ stomach ( 7 58 37 ) $ colon 25 $ liver ( 26 27 ) $ lung 10 $ esophagus 54 $ bladder 50 $ thyroid 4 $ brain ( 39 60 61 ) $ salivary glands ( 2 3 ) $ adrenals ( 28 29 34 ) $ ET region (no larynx) 23 $ ET region (larynx) 13 $ gallbladder 15 $ heart ( 17 18 19 20 21 22 ) $ kidneys 1 $ muscle (RST) 32 $ pancreas 41 $ small intestines 45 $ spleen 49 $ thymus 30 $ oral mucosa 48 $ testes 36 $ prostate c 5 $ breasts c 31 $ ovaries c 56 $ uterus letmat = 59 $ LET in water l type = 3 nl = 50 lmin = 0.1 lmax = 10000 unit = 8 axis = let file = M50_AUG1972_05_LET.out factor = c6 [END]

PAGE 567

567 APPENDIX O PHITS USER SOURCE DE FINITION ************************************************************************ subroutine usrsors(x,y,z,u,v,w,e,wt,time,name,kf) sample subroutine for user defined source. variables : x, y, z : position of the source. u, v, w : unit vector of the particle direction. e : kinetic energy of particle (MeV). wt : weight of particle. time : initial time of particle. (ns) name : usually = 1, for Coulm b spread. kf : kf code of the particle. ---------------------------------------------------------------------* kf code table kf code: ityp : description 2212 : 1 : proton 2112 : 2 : neutron 211 : 3 : pion (+) 111 : 4 : pion (0) 211 : 5 : pion ( ) 13 : 6 : muon (+) 13 : 7 : muon ( ) 321 : 8 : kaon (+) 311 : 9 : kaon (0) 321 : 10 : kaon ( ) kf code of the other transport particles 12 : nu_e 14 : nu_mu 221 : eta 331 : eta' 311 : k0bar 2112 : nbar 2212 : pbar 3122 : Lanbda0 3222 : Sigma+ 3212 : Sigma0 3112 : Sigma 3322 : Xi0 3312 : Xi 3334 : Omega ---------------------------------------------------------------------*

PAGE 568

568 avai lable function for random number unirn(dummy) : uniform random number from 0 to 1 gaurn(dummy) : gaussian random number for exp( x**2 / 2 / sig**2 ) : sig = 1.0 ************************************************************************ parameter(max part=10) maximum particle number in one input file parameter(nebin=1000) number of energy bin implicit real*8 (a h,o z) common /sorcom1/ip235,iz235(maxpart),ia235(maxpart) common /sorcom2/eup235(0:nebin),rt235(maxpart,0:nebin) !0 for particle ratio data itatsuidx/0/ if(itatsuidx.eq.0) then read initial input file call getsor itatsuidx=1 endif R = 500.1 pai = acos( 1.0) costheta = 1.0 2.0*unirn(dummy) theta = acos(costheta) phi = 2.0*pai*unirn(dummy) rhop = R*sqrt(unirn(dummy)) psip = 2.0*pai*unirn(dummy) xpar = sin(phi)*cos(psip) + cos(theta)*cos(phi)*sin(psip) x = R*sin(theta)*cos (phi) + rhop*xpar ypar = cos(phi)*cos(psip) cos(theta)*sin(phi)*sin(psip) y = R*sin(theta)*sin(phi) rhop*ypar z = R*cos(theta) rhop*sin(theta)*sin(psip) u = sin(theta)*cos(phi) v = sin(the ta)*sin(phi) w = cos(theta) c Determine particle type tmp=unirn(dummy) do ip=1,ip235 if(tmp.le.rt235(ip,0)) goto 10 enddo 10 if(iz235(ip).ge.2) then kf = iz235(ip)*1000000 + ia235(ip) elseif(iz235(ip).eq.1) then kf = 2212 elseif (iz235(ip).eq.0) then kf = 2112 elseif(iz235(ip).eq. 1) then kf = 11 endif c Determine particle energy (MeV/A) tmp=unirn(dummy) do ie=1,nebin if(tmp.le.rt235(ip,ie)) goto 20

PAGE 569

569 enddo 20 e = eup235(ie 1)+(eup235(ie) eup235(ie 1))*unirn(dummy) wt = 1.0 time = 0.0 name = 1 nc1 = 0 nc2 = 0 nc3 = 0 ----------------------------------------------------------------------return end subroutine getsor parameter(maxpart=10) maximum particle number in one input file parameter(nebin=1000) number of energy bin implicit real*8 (a h,o z) common /sorcom1/ip235,iz235(maxpart),ia235(maxpart) common /sorcom2/eup235(0:nebin),rt 235(maxpart,0:nebin) !0 for particle ratio eup235(0)=1.0e 8 open(unit=222,file='getsor.inp',status='old') read(222,*) ip235 number of particle included in the file do ip=1,ip235 read(222,*) iz235(ip),ia235(ip),rt235(ip,0) do ie=1,nebin read(222,*) eup235(ie),rt235(ip,ie) enddo enddo return end

PAGE 570

570 APPENDIX P PHITS POST PROCESSING MATLAB CO DE Dosimetry Post Processing % Load data clear all load HZETRN2010results.mat ; load PHITS3Dresults.mat ; load organ_tally.mat ; load BFOdist.mat ; env{1} = 'AUG1972_05' ; env{2} = 'AUG1972_10' ; env{3} = 'FEB1956_05' ; env{4} = 'FEB1956_10' ; env{5} = 'TRAPPROT_2' ; env{6} = 'TRAPNEUT_2' ; env{7} = 'GCR_H_2' ; env{8} = 'GCR_He_2' ; env{9} = 'GCR_C_2' ; env{10} = 'GCR_O_2' ; env{11} = 'GCR_Mg_2' ; env{12} = 'GCR_Si_2' ; env{13} = 'GCR_Fe_2' ; env{14} = 'GCR_Rem1_2' ; env{15} = 'GCR_Rem2_2' ; env{16} = 'GCR_Rem3_2' ; HZETRNenv = env; HZETRNenv(6) = []; HZETRNenv{5} = 'TRAPPED_2' ; % Convert Gy cm^3 g^ 1 and Sv cm^3 g^ 1 to Gy and Sv for i = 1:length(env) jMD = size(PHITS3Dresults.UFHADM50.(env{i}).Dvol,2); PHITS3Dresults.UFHADM50.(env{i}).Dmass = zeros(length(M50_dens),jMD); jMH = size(PHITS3Dresults.UFHADM50.(env{i}).Hvol,2); PHITS3Dresults.UFHADM50.(env{i}).Hmass = zero s(length(M50_dens),jMH); jFD = size(PHITS3Dresults.UFHADF50.(env{i}).Dvol,2); PHITS3Dresults.UFHADF50.(env{i}).Dmass = zeros(length(F50_dens),jFD); jFH = size(PHITS3Dresults.UFHADF50.(env{i}).Hvol,2); PHITS3Dresults.UFHADF50.(env{i}).Hmass = zeros(length(F50_dens),jFH); for j = 1:jMD PHITS3Dresults.UFHADM50.(env{i}).Dmass(:,j) = ... PHITS3Dresults.UFHADM50.(env{i}).Dvol(:,j)./M50_dens; end for j = 1:jMH PHITS3Dresults.UFHADM50.(env{i}).Hmass(:,j) = ... PHITS3Dresults.UFHADM50.(env{i}).Hvol(:,j)./M50_dens; end for j = 1:jFD PHITS3Dresults.UFHADF50.(env{i}).Dmass(:,j) = ... PHITS3Dresults.UFHADF50.(env{i}).Dvol(:,j)./F50_dens; end for j = 1:jFH

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571 PHITS 3Dresults.UFHADF50.(env{i}).Hmass(:,j) = ... PHITS3Dresults.UFHADF50.(env{i}).Hvol(:,j)./F50_dens; end end % Assign results to structure morg{1} = 'skin' ; morg{2} = 'BFO' ; morg{3} = 'muscle' ; morg{4} = 'lens' ; morg{5} = 'stomach' ; morg{6} = 'colon' ; morg{7} = 'liver' ; morg{8} = 'lung' ; morg{9} = 'esophagus' ; morg{10} = 'bladder' ; morg{11} = 'thyroid' ; morg{12} = 'brain' ; morg{13} = 'salivary' ; morg{14} = 'adrenals' ; morg{15} = 'ETregion' ; morg{16} = 'gallbladder' ; morg{17} = 'kidneys' ; morg{18} = 'pancreas' ; morg{19} = 'smallint' ; morg{20} = 'spleen' ; morg{21} = 'thymus' ; morg{22} = 'heart' ; morg{23} = 'oralmuc' ; morg{24} = 'prostate' ; morg{25} = 'testes' ; forg = morg; forg{24} = 'breasts' ; forg{25} = 'ovaries' ; forg{26} = 'uterus' ; m_tally{1} = 'skin' ; m_tally{2} = 'CV' ; m_tally{3} = 'clavicles' ; m_tally{4} = 'cranium' ; m_tally{5} = 'femur_proximal' ; m_tally{6} = 'femur_upper' ; m_tally{7} = 'humerus_proximal' ; m_tally{8} = 'humerus_upper' ; m_tally{9} = 'LV' ; m_tally{10} = 'mandible' ; m_tally{11} = 'pelvis' ; m_tally{12} = 'ribs' ; m_tally{13} = 'sacrum' ; m_tally{14} = 'scapulae' ; m_tally{15} = 'sternum' ; m_tally{16} = 'TV' ; m_tally{17} = 'lens' ; m_tally{18} = 'eyeball' ;

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572 m_tally{19} = 'stomach' ; m_tally{20} = 'colon' ; m_tally{21} = 'liver' ; m_tally{22} = 'lung' ; m_tally{23} = 'esophagus' ; m_tally{24} = 'bladder' ; m_tally{25} = 'thyroid' ; m_tally{26} = 'brain' ; m_tally{27} = 'salivary' ; m_tally{28} = 'adrenals' ; m_tally{29} = 'ET_no_larynx' ; m_tally{30} = 'ET_la rynx' ; m_tally{31} = 'gallbladder' ; m_tally{32} = 'heart' ; m_tally{33} = 'kidneys' ; m_tally{34} = 'muscle' ; m_tally{35} = 'pancreas' ; m_tally{36} = 'smallint' ; m_tally{37} = 'spleen' ; m_tally{38} = 'thymus' ; m_tally{39} = 'oralmuc' ; m_tally{40} = 'testes' ; m_tally{41} = 'prostate' ; f_tally = m_tally; f_tally{40} = 'breasts' ; f_tally{41} = 'ovaries' ; f_tally{42} = 'uterus' ; % Calculate average and standard deviation and assign values to structure temp = struct(); temp.male = struct(); temp.female = struc t(); for i = 1:length(env) for j = 1:length(m_tally) temp.male.(env{i}).(m_tally{j}).D = ... PHITS3Dresults.UFHADM50.(env{i}).Dmass(j,:); temp.male.(env{i}).(m_tally{j}).H = ... PHITS3Dresults.UFHADM50.(env{i}).Hmass(j,:); end for j = 1:length(f_tally) temp.female.(env{i}).(f_tally{j}).D = ... PHITS3Dresults.UFHADF50.(env{i}).Dmass(j,:); temp.female.(env{i}).(f_tally{j}).H = ... PHITS3Dresults.UFHADF50.(env{i}).Hmass(j,:); end for j = 17:28 PHITS3Dresults.UFHADM50.(env{i}).(m_tally{j}).Davg = ... mean(temp.male.(env{i}).(m_tally{j}).D); PHITS3Dresults.UFHADM50.(env{i}).(m_tally{j}).Dstd = ... std(temp.male.(env{i}).(m_tally{j}).D)/ ... sqrt(length(temp.male.(env{i}).(m_tally{j}).D)); PHITS3Dresults.UFHADM50.(env{i}).(m_tally{j}).Havg = ... mean(temp.male.(env{i}).(m_tally{j}).H); PHITS3Dresults.UFHADM50.(env{i}).(m_tally{j}).Hstd = ...

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573 std(temp.male.(env{i}).(m_tally{j}).H)/ ... sqrt(length(temp.male.(env{i}).(m_tally{j}).H)); PHITS3Dresults.UFHADF50. (env{i}).(f_tally{j}).Davg = ... mean(temp.female.(env{i}).(f_tally{j}).D); PHITS3Dresults.UFHADF50.(env{i}).(f_tally{j}).Dstd = ... std(temp.female.(env{i}).(f_tally{j}).D)/ ... sqrt(length(temp.female.(env{i}).( f_tally{j}).D)); PHITS3Dresults.UFHADF50.(env{i}).(f_tally{j}).Havg = ... mean(temp.female.(env{i}).(f_tally{j}).H); PHITS3Dresults.UFHADF50.(env{i}).(f_tally{j}).Hstd = ... std(temp.female.(env{i}).(f_tally{j}).H)/ ... sqrt(length(temp.female.(env{i}).(f_tally{j}).H)); end for j = 31:length(m_tally) PHITS3Dresults.UFHADM50.(env{i}).(m_tally{j}).Davg = ... mean(temp.male.(env{i}).(m_tally{j}).D); PHITS3Dresults.U FHADM50.(env{i}).(m_tally{j}).Dstd = ... std(temp.male.(env{i}).(m_tally{j}).D)/ ... sqrt(length(temp.male.(env{i}).(m_tally{j}).D)); PHITS3Dresults.UFHADM50.(env{i}).(m_tally{j}).Havg = ... mean(temp.male.(env{i}).(m_tally{j}).H); PHITS3Dresults.UFHADM50.(env{i}).(m_tally{j}).Hstd = ... std(temp.male.(env{i}).(m_tally{j}).H)/ ... sqrt(length(temp.male.(env{i}).(m_tally{j}).H)); end for j = 31 :length(f_tally) PHITS3Dresults.UFHADF50.(env{i}).(f_tally{j}).Davg = ... mean(temp.female.(env{i}).(f_tally{j}).D); PHITS3Dresults.UFHADF50.(env{i}).(f_tally{j}).Dstd = ... std(temp.female.(env{i}).(f_tally{j}).D)/ .. sqrt(length(temp.female.(env{i}).(f_tally{j}).D)); PHITS3Dresults.UFHADF50.(env{i}).(f_tally{j}).Havg = ... mean(temp.female.(env{i}).(f_tally{j}).H); PHITS3Dresults.UFHADF50.(env{i}).(f_tally{j}).Hstd = ... std(temp.female.(env{i}).(f_tally{j}).H)/ ... sqrt(length(temp.female.(env{i}).(f_tally{j}).H)); end % Skin PHITS3Dresults.UFHADM50.(env{i}).(m_tally{1}).Davg = ... mean(temp.male.(env{i}).(m_tally{1}).D); PHITS3Dresults.UFHADM50.(env{i}).(m_tally{1}).Dstd = ... std(temp.male.(env{i}).(m_tally{1}).D)/ ... sqrt(length(temp.male.(env{i}).(m_tally{1}).D)); PHITS3Dresults.UFHADM50.(env{i}).(m_tally{1}).Havg = ... mean(temp.male.(env{i}).(m_tally{1}).H); PHITS3Dresults.UFHADM50.(env{i}).(m_tally{1}).Hstd = ... std(temp.male.(env{i}).(m_tally{1}).H)/ ... sqrt(length(temp.male.(env{i}).(m_tally{1}).H)); PHITS3Dresults.UFHADF50.(env{i}).( f_tally{1}).Davg = ... mean(temp.female.(env{i}).(f_tally{1}).D); PHITS3Dresults.UFHADF50.(env{i}).(f_tally{1}).Dstd = ... std(temp.female.(env{i}).(f_tally{1}).D)/ ... sqrt(length(temp.female.(env{i}).(f_tally{1}).D));

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574 PHITS 3Dresults.UFHADF50.(env{i}).(f_tally{1}).Havg = ... mean(temp.female.(env{i}).(f_tally{1}).H); PHITS3Dresults.UFHADF50.(env{i}).(f_tally{1}).Hstd = ... std(temp.female.(env{i}).(f_tally{1}).H)/ ... sqrt(length(temp.female.(env{i} ).(f_tally{1}).H)); % BFO sumBFOmaleD = zeros(1,length(temp.male.(env{i}).(m_tally{2}).D)); sumBFOmaleH = zeros(1,length(temp.male.(env{i}).(m_tally{2}).H)); sumBFOfemaleD = zeros(1,length(temp.female.(env{i}).(f_tally{2}).D)); sumBFOfemaleH = zeros(1,length(temp.female.(env{i}).(f_tally{2}).H)); for j = 2:16 sumBFOmaleD = sumBFOmaleD + ... BFOdist{strcmp(m_tally{j},BFOdist(:,1)),2}* ... temp.male.(env{i}).(m_tally{j}).D; sumBFOmaleH = sumBFOmaleH + ... BFOdist{strcmp(m_tally{j},BFOdist(:,1)),2}* ... temp.male.(env{i}).(m_tally{j}).H; sumBFOfemaleD = sumBFOfemaleD + ... BFOdist{strcmp(f_tally{j},BFOdist(:,1)),2}* ... temp.female.(env{i}).(f_tally{j}).D; sumBFOfemaleH = sumBFOfemaleH + ... BFOdist{strcmp(f_tally{j},BFOdist(:,1)),2}* ... temp.female.(env{i}).(f_tally{j}).H; end sumBFOmaleD = sumBFOmaleD./sum(cell2m at(BFOdist(:,2))); sumBFOmaleH = sumBFOmaleH./sum(cell2mat(BFOdist(:,2))); sumBFOfemaleD = sumBFOfemaleD./sum(cell2mat(BFOdist(:,2))); sumBFOfemaleH = sumBFOfemaleH./sum(cell2mat(BFOdist(:,2))); PHITS3Dresults.UFHADM50.(env{i}).BFO.Davg = m ean(sumBFOmaleD); PHITS3Dresults.UFHADM50.(env{i}).BFO.Dstd = std(sumBFOmaleD)/ ... sqrt(length(sumBFOmaleD)); PHITS3Dresults.UFHADM50.(env{i}).BFO.Havg = mean(sumBFOmaleH); PHITS3Dresults.UFHADM50.(env{i}).BFO.Hstd = std(sumBFOmaleH)/ .. sqrt(length(sumBFOmaleH)); PHITS3Dresults.UFHADF50.(env{i}).BFO.Davg = mean(sumBFOfemaleD); PHITS3Dresults.UFHADF50.(env{i}).BFO.Dstd = std(sumBFOfemaleD)/ ... sqrt(length(sumBFOfemaleD)); PHITS3Dresults.UFHADF50.(env{i}).BFO.Havg = mean(sumBFOfemaleH); PHITS3Dresults.UFHADF50.(env{i}).BFO.Hstd = std(sumBFOfemaleH)/ ... sqrt(length(sumBFOfemaleH)); % ET Region sumETmaleD = temp.male.(env{i}).(m_tally{29}).D* ... M50_vol(29)*M50_dens(29) + ... temp.male.(env{i}).(m_tally{30}).D* ... M50_vol(30)*M50_dens(30); sumETmaleH = temp.male.(env{i}).(m_tally{29}).H* ... M50_vol(29)*M50_dens(29) + ... temp.male.(env{i}).(m_tally{30}).H* ... M50_vol(30)*M50_dens(30); sumETfemaleD = temp.female.(env{i}).(f_tally{29}).D* ... F50_vol(29)*F50_dens(29) + ...

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575 temp.female.(env{i}).(f_tally{30}).D* ... F50_vol(30)*F50_den s(30); sumETfemaleH = temp.female.(env{i}).(f_tally{29}).H* ... F50_vol(29)*F50_dens(29) + ... temp.female.(env{i}).(f_tally{30}).H* ... F50_vol(30)*F50_dens(30); sumETmaleD = sumETmaleD./ ... (M50_vol(29)*M50_dens(29) + M50_vol(30)*M50_dens(30)); sumETmaleH = sumETmaleH./ ... (M50_vol(29)*M50_dens(29) + M50_vol(30)*M50_dens(30)); sumETfemaleD = sumETfemaleD./ ... (F50_vol(29)*F50_dens(29) + F50_vol(30)*F50_dens(30)); sumETfemaleH = sumETfemaleH./ ... (F50_vol(29)*F50_dens(29) + F50_vol(30)*F50_dens(30)); PHITS3Dresults.UFHADM50.(env{i}).ETregion.Davg = mean(sumETmaleD); PHITS3Dresults.UFHADM50.(env{i}).ETregion.Dstd = std(sumETmaleD)/ ... sqrt (length(sumETmaleD)); PHITS3Dresults.UFHADM50.(env{i}).ETregion.Havg = mean(sumETmaleH); PHITS3Dresults.UFHADM50.(env{i}).ETregion.Hstd = std(sumETmaleH)/ ... sqrt(length(sumETmaleH)); PHITS3Dresults.UFHADF50.(env{i}).ETregion.Davg = mean(sumETfemaleD); PHITS3Dresults.UFHADF50.(env{i}).ETregion.Dstd = std(sumETfemaleD)/ ... sqrt(length(sumETfemaleD)); PHITS3Dresults.UFHADF50.(env{i}).ETregion.Havg = mean(sumETfemaleH); PHITS3Dresults.UFHADF50.(env{i}).ETregion.Hstd = std(sumETfemaleH)/ ... sqrt(length(sumETfemaleH)); end for i = 1:length(morg) PHITS3Dresults.UFHADM50.TRAPPED_2.(morg{i}).Davg = ... PHITS3Dresults.UFHADM50.TRAPNEUT_2.(morg{i}).Dav g + ... PHITS3Dresults.UFHADM50.TRAPPROT_2.(morg{i}).Davg; PHITS3Dresults.UFHADM50.TRAPPED_2.(morg{i}).Havg = ... PHITS3Dresults.UFHADM50.TRAPNEUT_2.(morg{i}).Havg + ... PHITS3Dresults.UFHADM50.TRAPPROT_2.(morg{i}).Havg; PHI TS3Dresults.UFHADM50.TRAPPED_2.(morg{i}).Dstd = ... sqrt( ... PHITS3Dresults.UFHADM50.TRAPNEUT_2.(morg{i}).Dstd^2 + ... PHITS3Dresults.UFHADM50.TRAPPROT_2.(morg{i}).Dstd^2); PHITS3Dresults.UFHADM50.TRAPPED_2.(morg{i}).Hstd = ... sqrt( ... PHITS3Dresults.UFHADM50.TRAPNEUT_2.(morg{i}).Hstd^2 + ... PHITS3Dresults.UFHADM50.TRAPPROT_2.(morg{i}).Hstd^2); end for i = 1:length(forg) PHITS3Dresults.UFHADF50.TRAPPED_2.(forg{i}).Davg = ... PHITS3Dresults.UFHADF50.TRAPNEUT_2.(forg{i}).Davg + ... PHITS3Dresults.UFHADF50.TRAPPROT_2.(forg{i}).Davg; PHITS3Dresults.UFHADF50.TRAPPED_2.(forg{i}).Havg = ... PHITS3Dresults.UFHADF50.TRAPNEUT_2.(forg{i}).Havg + ... PHITS3Dresults.UFHADF50.TRAPPROT_2.(forg{i}).Havg; PHITS3Dresults.UFHADF50.TRAPPED_2.(forg{i}).Dstd = ... sqrt( ... PHITS3Dresults.UFHADF50.TRAPNEUT_2.(forg{i}).Dstd^2 + ... PHITS3Dresults.UFHADF50.TRAPPROT_2.(forg{i}).Ds td^2);

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576 PHITS3Dresults.UFHADF50.TRAPPED_2.(forg{i}).Hstd = ... sqrt( ... PHITS3Dresults.UFHADF50.TRAPNEUT_2.(forg{i}).Hstd^2 + ... PHITS3Dresults.UFHADF50.TRAPPROT_2.(forg{i}).Hstd^2); end Flux Post Processing % This script c alculates the average and standard deviation of the fluxes % for the PHITS runs. It also puts them in a structure for later access. load PHITS_dflux_raw.mat % Phantoms phantom{1} = 'M50' ; phantom{2} = 'F50' ; % Environments env{1} = 'AUG1972_05' ; env{2} = 'AUG1972_10' ; env{3} = 'FEB1956_05' ; env{4} = 'FEB1956_10' ; env{5} = 'TRAPNEUT_2' ; env{6} = 'TRAPPROT_2' ; env{7} = 'GCR_H_2' ; env{8} = 'GCR_He_2' ; env{9} = 'GCR_C_2' ; env{10} = 'GCR_O_2' ; env{11} = 'GCR_Mg_2' ; env{12} = 'GCR_Si_2' ; env{13} = 'GCR_Fe_2' ; env{14} = 'GCR_Rem1_2' ; env{15} = 'GCR_Rem2_2' ; env{16} = 'GCR_Rem3_2' ; HZETRNenv = env; HZETRNenv(6) = []; HZETRNenv{5} = 'TRAPPED_2' ; % Define number of trials for each environment numtrial(1) = 4; numtrial(2) = 6; numtrial(3) = 4; numtrial(4) = 4; numtrial(5) = 4; numtrial(6) = 8; numtrial(7:16) = 4; % Loop through phantoms and environments PHITS_dflux_struct = struct(); for i = 1:length(phantom) PHITS_dflux_struct.(phantom{i}) = struct(); for j = 1:length(env) PHITS_dflux_struct.(phantom{i}).(env{j}) = struct(); curr_struct_name = cell(numtrial(j),1); for k = 1:numtrial(j) curr_struct_name(k) = cellstr(strcat(phantom{i}, '_' ,env{j}, ...

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577 '_dflux_' ,num2str(k))); end curr_struct_name = genvarname(curr_struct_name); PHITS_dflux_struct.(phantom{i}).(env{j}) = ... eval(curr_struct_name{1}); for l = 1:length(PHITS_dflux_struct.(phantom{i}).(env{j})) for m = 1:leng th(PHITS_dflux_struct.(phantom{i}).(env{j})(l).ion) energy = PHITS_dflux_struct.(phantom{i}).(env{j})(l).ion(m).energy; A = PHITS_dflux_struct.(phantom{i}).(env{j})(l).ion(m).A; energy = energy/A^2; % This is to undo the erroneous conversion in the previous script PHITS_dflux_struct.(phantom{i}).(env{j})(l).ion(m).energy = energy; for n = 2:length(curr_struct_name) temp_trial = eval(curr_struct_name{n}); PHITS_dflux_struct.(phantom{i}).(env{j})(l).ion(m).flux(:,n) = ... temp_trial(l).ion(m).flux; end PHITS_dflux_struct.(phantom{i}).(env{j})(l).ion(m).avg_flux = ... mean(PHITS_dflux_struct.(phantom{i}).(env{j})(l).ion(m).flux,2); PHITS_dflux_struct.(phantom{i}).(env{j})(l).ion(m).std_flux = ... std(PHITS_dflux_struct.(phantom{i}).(env{j})(l).ion(m).flux,0,2)/sqrt(numtrial(j)); end end end end % Rearrange structure to match dosimetry results load organ_tally.mat ; load BFOdist.mat ; morg{1} = 'skin' ; morg{2} = 'BFO' ; morg{3} = 'muscle' ; morg{4} = 'lens' ; morg{5} = 'stomach' ; morg{6} = 'colon' ; morg{7} = 'liver' ; morg{8} = 'lung' ; morg{9} = 'esophagus' ; morg{10} = 'bladder' ; morg{11} = 'thyroid' ; morg{12} = 'brain' ; morg{13} = 'salivary' ; morg{14} = 'adrenals' ; morg{15} = 'ETregion' ; morg{16} = 'gallbladder' ; morg{17} = 'kidneys' ; morg{18} = 'pancreas' ; morg{19} = 'smallint' ; morg{20} = 'spleen' ; morg{21} = 'thymus' ; morg{22} = 'heart' ; morg{23} = 'oralmuc' ;

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578 morg{24} = 'prostate' ; morg{25} = 'testes' ; forg = morg; forg{24} = 'breasts' ; forg{25} = 'ovaries' ; forg{26} = 'uterus' ; m_tally{1} = 'skin' ; m_tally{2} = 'CV' ; m_tally{3} = 'clavicles' ; m_tally{4} = 'cranium' ; m_tally{5} = 'femur_proximal' ; m_tally{6} = 'femur_upper' ; m_tally{7} = 'humerus_proximal' ; m_tally{8} = 'humerus_upper' ; m_tally{9} = 'LV' ; m_tally{10} = 'mandible' ; m_tally{11} = 'pelvis' ; m_tally{12} = 'ribs' ; m_tally{13} = 'sacrum' ; m_tally{14} = 'scapulae' ; m_tally{15} = 'sternum' ; m_tally{16} = 'TV' ; m_tally{17} = 'lens' ; m_tally{18} = 'eyeball' ; m_tally{19} = 'stomach' ; m_tally{20} = 'colon' ; m_tally{21} = 'liver' ; m_tally{22} = 'lung' ; m_tally{23} = 'esophagus' ; m_tally{24} = 'bladder' ; m_tally{25} = 'thyroid' ; m_tally{26} = 'brain' ; m_tally{27} = 'salivary' ; m_tally{28} = 'adrenals' ; m_tally{29} = 'ET_no_larynx' ; m_tally{30} = 'ET_larynx' ; m_tally{31} = 'gallbladde r' ; m_tally{32} = 'heart' ; m_tally{33} = 'kidneys' ; m_tally{34} = 'muscle' ; m_tally{35} = 'pancreas' ; m_tally{36} = 'smallint' ; m_tally{37} = 'spleen' ; m_tally{38} = 'thymus' ; m_tally{39} = 'oralmuc' ; m_tally{40} = 'testes' ; m_tally{41} = 'prostate' ; f_tally = m_tally; f_tally{40} = 'breasts' ; f_tally{41} = 'ovaries' ; f_tally{42} = 'uterus' ; PHITS3D_dflux = struct(); PHITS3D_dflux.UFHADM50 = struct();

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579 PHITS3D_dflux.UFHADF50 = struct(); for i = 1:length(env) %Skin PHITS3D_dflux.UFHADM50.(env{i}).(m_tally{1}) = ... PHITS_dflux_struct.M50.(env{i})(1); PHITS3D_dflux.UFHADF50.(env{i}).(f_tally{1}) = ... PHITS_dflux_struct.F50.(env{i})(1); % Common organs for j = 17:28 PHITS3D_ dflux.UFHADM50.(env{i}).(m_tally{j}) = ... PHITS_dflux_struct.M50.(env{i})(j); PHITS3D_dflux.UFHADF50.(env{i}).(f_tally{j}) = ... PHITS_dflux_struct.F50.(env{i})(j); end % Male organs for j = 31:length(m_tally) PHITS3D_dflux.UFHADM50.(env{i}).(m_tally{j}) = ... PHITS_dflux_struct.M50.(env{i})(j); end % Female organs for j = 31:length(f_tally) PHITS3D_dflux.UFHADF50.(env{i}).(f_tally{j}) = ... PHITS_dflux_struct. F50.(env{i})(j); end % BFO for k = 1:length(PHITS_dflux_struct.M50.(env{i})(2).ion) sumBFOmale_dflux = zeros(size(PHITS_dflux_struct.M50.(env{i})(2).ion(k).flux)); sumBFOfemale_dflux = zeros(size(PHITS_dflux_struct.F50.(env{i})( 2).ion(k).flux)); for j = 2:16 sumBFOmale_dflux = sumBFOmale_dflux + ... BFOdist{strcmp(m_tally{j},BFOdist(:,1)),2}* ... PHITS_dflux_struct.M50.(env{i})(j).ion(k).flux; sumBFOfemale_dflux = sumBFOfemale_dflux + ... BFOdist{strcmp(f_tally{j},BFOdist(:,1)),2}* ... PHITS_dflux_struct.F50.(env{i})(j).ion(k).flux; end sumBFOmale_dflux = sumBFOmale_dflux./sum(cell2mat(BFOdist(:,2))); sumBFOfemale_dflux = sumBFOfemale_dflux./sum(cell2mat(BFOdist(:,2))); PHITS3D_dflux.UFHADM50.(env{i}).BFO.ion(k).flux = ... sumBFOmale_dflux; PHIT S3D_dflux.UFHADF50.(env{i}).BFO.ion(k).flux = ... sumBFOfemale_dflux; PHITS3D_dflux.UFHADM50.(env{i}).BFO.ion(k).avg_flux = ... mean(sumBFOmale_dflux,2); PHITS3D_dflux.UFHADF50.(env{i}).BFO.ion(k).avg_flux = ... mean(sumBFOfemale_dflux,2); PHITS3D_dflux.UFHADM50.(env{i}).BFO.ion(k).std_flux = ... std(sumBFOmale_dflux,0,2)/numtrial(i); PHITS3D_dflux.UFHADF50.(env{i}).BFO.ion(k).std_flux = ... std(sumBFOfemale_dflux,0, 2)/numtrial(i); PHITS3D_dflux.UFHADM50.(env{i}).BFO.ion(k).energy = ... PHITS_dflux_struct.M50.(env{i})(2).ion(k).energy; PHITS3D_dflux.UFHADF50.(env{i}).BFO.ion(k).energy = ...

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580 PHITS_dflux_struct.F50.(env{i})(2).ion (k).energy; PHITS3D_dflux.UFHADM50.(env{i}).BFO.ion(k).A = ... PHITS_dflux_struct.M50.(env{i})(2).ion(k).A; PHITS3D_dflux.UFHADF50.(env{i}).BFO.ion(k).A = ... PHITS_dflux_struct.F50.(env{i})(2).ion(k).A; PHITS3D_dflux.UFHADM50.(env{i}).BFO.ion(k).Z = ... PHITS_dflux_struct.M50.(env{i})(2).ion(k).Z; PHITS3D_dflux.UFHADF50.(env{i}).BFO.ion(k).Z = ... PHITS_dflux_struct.F50.(env{i})(2).ion(k).Z; end % ET region for k = 1:length(PHITS_dflux_struct.M50.(env{i})(2).ion) sumETmale_dflux = ... PHITS_dflux_struct.M50.(env{i})(29).ion(k).flux ... M50_vol(29) + ... PHITS_dflux_struct.M50.(env{i})(30).ion(k).flux ... M50_vol(30); sumETmale_dflux = sumETmale_dflux/(M50_vol(29) + M50_vol(30)); sumETfemale_dflux = ... PHITS_dflux_struct.F50.(env{i})(29).ion(k).flu x ... F50_vol(29) + ... PHITS_dflux_struct.F50.(env{i})(30).ion(k).flux ... F50_vol(30); sumETfemale_dflux = sumETfemale_dflux/(F50_vol(29) + F50_vol(30)); PHITS3D_dflux.UFHADM50.(env{i}).ETregion.ion (k).flux = ... sumETmale_dflux; PHITS3D_dflux.UFHADF50.(env{i}).ETregion.ion(k).flux = ... sumETfemale_dflux; PHITS3D_dflux.UFHADM50.(env{i}).ETregion.ion(k).avg_flux = ... mean(sumETmale_dflux,2); PHITS3D_dflux.UFHADF50.(env{i}).ETregion.ion(k).avg_flux = ... mean(sumETfemale_dflux,2); PHITS3D_dflux.UFHADM50.(env{i}).ETregion.ion(k).std_flux = ... std(sumETmale_dflux,0,2)/numtrial(i); PHITS3D_dflux.UFHADF50.(env{i}).ETregion.ion(k).std_flux = ... std(sumETfemale_dflux,0,2)/numtrial(i); PHITS3D_dflux.UFHADM50.(env{i}).ETregion.ion(k).energy = ... PHITS_dflux_struct.M50.(env{i})(29).ion(k).energy; PHITS3D_dflux.UFHADF50.(env{i}).ETregion.ion(k).energy = ... PHITS_dflux_struct.F50.(env{i})(29).ion(k).energy; PHITS3D_dflux.UFHADM50.(env{i}).ETregion.ion(k).A = ... PHITS_dflux_struct.M50.(env{i})(29).ion(k).A; PHITS3D_dflux.UFHADF50.(env{i}).ETregion.ion(k).A = ... PHITS_dflux_struct.F50.(env{i})(29).ion(k).A; PHITS3D_dflux.UFHADM50.(env{i}).ETregion.ion(k).Z = ... PHITS_dflux_struct.M50.(env{i})(29).ion(k).Z; PHITS3D_dflux.UFHADF50.(env{i}).ETregion.ion(k).Z = ... PHITS_dflux_struct.F50.(env{i})(29).ion(k).Z; end end

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581 APPENDIX Q US EPA REID MATLAB C ODE EPAExcessRisk.m %% Function Description % This function calculates the excess risk from a single instance of % radiation exposure using EPA 2011 methods. The calculated value is % unitless. The function takes in the age at exposure, gender, and organ % doses, and returns the REID and REIC for total cancer, solid cancer, an d % leukemia. All input and output variables are contained in a structure. %% Function Definition function ExcessRisk_io = EPAExcessRisk(ExcessRisk_io) %% Define variables from structure age_exp = ExcessRisk_io.AgeAtExposure; gender = ExcessRisk_io. Gender; d_stomach = ExcessRisk_io.StomachEquivalentDose; d_colon = ExcessRisk_io.ColonEquivalentDose; d_liver = ExcessRisk_io.LiverEquivalentDose; d_lung = ExcessRisk_io.LungEquivalentDose; d_breast = ExcessRisk_io.BreastEquivalentDose; d_prostate = Excess Risk_io.ProstateEquivalentDose; d_uterus = ExcessRisk_io.UterusEquivalentDose; d_ovary = ExcessRisk_io.OvaryEquivalentDose; d_bladder = ExcessRisk_io.BladderEquivalentDose; d_thyroid = ExcessRisk_io.ThyroidEquivalentDose; d_remainder = ExcessRisk_io.ColonE quivalentDose; d_leukemia = ExcessRisk_io.RBMEquivalentDose; d_skin = ExcessRisk_io.SkinEquivalentDose; d_bone = ExcessRisk_io.RBMEquivalentDose; d_kidney = ExcessRisk_io.KidneyEquivalentDose; %% Load cancer incidence and mortality background rates % Load background rate '.mat' file load( 'background_rates_EPA.mat' ); % Load lifetable '.mat' file load( 'lifetable_EPA.mat' ); switch gender case 'M' survival = lifetable.male; case 'F' survival = lifetable.female; end age_survival = lifetable.ages; % Age grid age_rates = background_rates.ages; switch gender

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582 case 'M' % Male incidence stomach_inc = background_rates.incidence.male.stomach; colon_inc = background_rates.incidence.male.colon; liver_in c = background_rates.incidence.male.liver; lung_inc = background_rates.incidence.male.lung; breast_inc = zeros(size(age_rates)); prostate_inc = background_rates.incidence.male.prostate; uterus_inc = zeros(size(age_rates)); ovary_inc = zeros(size(age_rates)); bladder_inc = background_rates.incidence.male.bladder; thyroid_inc = background_rates.incidence.male.thyroid; remainder_inc = background_rates.incidence.male.remainder; leukemia_in c = background_rates.incidence.male.leukemia; kidney_inc = background_rates.incidence.male.kidney; skin_inc = background_rates.incidence.male.skin; % Male mortality stomach_mort = background_rates.mortality.male.sto mach; colon_mort = background_rates.mortality.male.colon; liver_mort = background_rates.mortality.male.liver; lung_mort = background_rates.mortality.male.lung; breast_mort = zeros(size(age_rates)); prostate_mort = ba ckground_rates.mortality.male.prostate; uterus_mort = zeros(size(age_rates)); ovary_mort = zeros(size(age_rates)); bladder_mort = background_rates.mortality.male.bladder; thyroid_mort = 0.05*thyroid_inc; remainder_mo rt = background_rates.mortality.male.remainder; leukemia_mort = background_rates.mortality.male.leukemia; kidney_mort = background_rates.mortality.male.kidney; skin_mort = 0.0003*skin_inc; case 'F' % Female incidence stomach_inc = background_rates.incidence.female.stomach; colon_inc = background_rates.incidence.female.colon; liver_inc = background_rates.incidence.female.liver; lung_inc = background_rates.incidence.female.lung; breast_inc = background_rates.incidence.female.breast; prostate_inc = zeros(size(age_rates)); uterus_inc = background_rates.incidence.female.uterus; ovary_inc = background_rates.incidence.female.ovary; bladder_inc = background_rates.incidence.female.bladder; thyroid_inc = background_rates.incidence.female.thyroid; remainder_inc = background_rates.incidence.female.remainder; leukemia_inc = background_rates.incidence.female.leukemia; kidn ey_inc = background_rates.incidence.female.kidney; skin_inc = background_rates.incidence.female.skin; % Female mortality stomach_mort = background_rates.mortality.female.stomach; colon_mort = background_rates.mortality.fem ale.colon; liver_mort = background_rates.mortality.female.liver; lung_mort = background_rates.mortality.female.lung;

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583 breast_mort = background_rates.mortality.female.breast; prostate_mort = zeros(size(age_rates)); ute rus_mort = background_rates.mortality.female.uterus; ovary_mort = background_rates.mortality.female.ovary; bladder_mort = background_rates.mortality.female.bladder; thyroid_mort = 0.05*thyroid_inc; remainder_mort = backgroun d_rates.mortality.female.remainder; leukemia_mort = background_rates.mortality.female.leukemia; kidney_mort = background_rates.mortality.female.kidney; skin_mort = 0.0003*skin_inc; end %% Assign tissue specific transfer weight vT_stomach = transfer_weight( 'Stomach' ,ExcessRisk_io.mode); vT_colon = transfer_weight( 'Colon' ,ExcessRisk_io.mode); vT_liver = transfer_weight( 'Liver' ,ExcessRisk_io.mode); vT_lung = transfer_weight( 'Lung' ,ExcessRisk_io.mode); vT_breast = transfer_weight( 'B reast' ,ExcessRisk_io.mode); vT_prostate = transfer_weight( 'Prostate' ,ExcessRisk_io.mode); vT_uterus = transfer_weight( 'Uterus' ,ExcessRisk_io.mode); vT_ovary = transfer_weight( 'Ovary' ,ExcessRisk_io.mode); vT_bladder = transfer_weight( 'Bladder' ,ExcessRisk_io .mode); vT_thyroid = transfer_weight( 'Thyroid' ,ExcessRisk_io.mode); vT_remainder = transfer_weight( 'Remainder' ,ExcessRisk_io.mode); vT_leukemia = transfer_weight( 'Leukemia' ,ExcessRisk_io.mode); vT_kidney = transfer_weight( 'Kidney' ,ExcessRisk_io.mode); vT_s kin = transfer_weight( 'Skin' ,ExcessRisk_io.mode); vT_bone = transfer_weight( 'Bone' ,ExcessRisk_io.mode); %% Assign DDREF switch ExcessRisk_io.mode case 'EPA point' DDREF = 1.5; case 'EPA sample' DDREF = 1.5*lognrnd(log(1) log(1.35)^2/2,log(1.35),1,1); case 'No DDREF' DDREF = 1.0; end %% Calculate organ specific ERR and EAR EPA_age_att = age_rates; % Initialize organ ERR variables stomach_ERR = zeros(1,length(EPA_age_att))'; colon_ERR = zeros(1,length(EPA_age_att))'; liver_ERR = zeros(1,length(EPA_age_att))'; EPA_lung_ERR = zeros(1,length(EPA_age_att))'; breast_ERR = zeros(1,length(EPA_age_att))'; prostate_ERR = zeros(1,length(EPA_age_att))'; ute rus_ERR = zeros(1,length(EPA_age_att))'; ovary_ERR = zeros(1,length(EPA_age_att))'; bladder_ERR = zeros(1,length(EPA_age_att))'; thyroid_ERR = zeros(1,length(EPA_age_att))'; remainder_ERR = zeros(1,length(EPA_age_att))';

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584 leukemia_ERR = zeros(1,length(EPA_a ge_att))'; kidney_ERR = zeros(1,length(EPA_age_att))'; skin_ERR = zeros(1,length(EPA_age_att))'; bone_ERR = zeros(1,length(EPA_age_att))'; % Initialize organ ERR variables stomach_EAR = zeros(1,length(EPA_age_att))'; colon_EAR = zeros(1,length(EPA_age_att))'; liver_EAR = zeros(1,length(EPA_age_att))'; EPA_lung_EAR = zeros(1,length(EPA_age_att))'; breast_EAR = zeros(1,length(EPA_age_att))'; prostate_EAR = zeros(1,length(EPA_age_att))'; uterus_EAR = zeros(1,length(EPA_age_att))'; ovary_EAR = zeros(1,length(EPA_age_att))'; bladder_EAR = zeros(1,length(EPA_age_att))'; thyroid_EAR = zeros(1,length(EPA_age_att))'; remainder_EAR = zeros(1,length(EPA_age_att))'; leukemia_EAR = zeros(1,length(EPA_age_att))'; kidney_EAR = zeros(1,length(EP A_age_att))'; skin_EAR = zeros(1,length(EPA_age_att))'; bone_EAR = zeros(1,length(EPA_age_att))'; % Define latency period, in years lat_solid = 5; lat_leuk = 2; % Define latency smoothing based on TSE (for leukemia, this is included in % the expression for EAR and ERR) TSE = EPA_age_att age_exp; TSE_solid = zeros(length(EPA_age_att),1); TSE_solid(TSE < lat_solid 1) = 0; TSE_smooth = TSE(TSE >= lat_solid 1 & TSE <= lat_solid + 1); TSE_solid(TSE >= lat_solid 1 & TSE <= lat_solid + 1) = ... ((T SE_smooth 4).^2).*((TSE_smooth 4).^2 + (TSE_smooth 6).^2).^ 1; TSE_solid(TSE > lat_solid + 1) = 1; TSE_thyroid = zeros(length(EPA_age_att),1); % Organ ERR for i = 1:length(EPA_age_att) if EPA_age_att(i) >= age_exp stomach_ERR(i) = BEIR_ERR( 'Stomach' ,gender, ... d_stomach,age_exp,EPA_age_att(i)); colon_ERR(i) = BEIR_ERR( 'Colon' ,gender, ... d_colon,age_exp,EPA_age_att(i)); liver_ERR(i) = BEIR_ERR( 'Liver' ,gender, ... d_liver,age_exp,EPA_age_att(i)); EPA_lung_ERR(i) = BEIR_ERR( 'Lung' ,gender, ... d_lung,age_exp,EPA_age_att(i)); breast_ERR(i) = 0; prostate_ERR(i) = BEIR_ERR( 'Prostate' ,gender, ... d_prostate,age_exp,EPA_ag e_att(i)); uterus_ERR(i) = BEIR_ERR( 'Uterus' ,gender, ... d_uterus,age_exp,EPA_age_att(i)); ovary_ERR(i) = BEIR_ERR( 'Ovary' ,gender, ... d_ovary,age_exp,EPA_age_att(i));

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585 bladder_ERR(i) = BEIR_ERR( 'Bladder' ,gender, ... d_bladder,age_exp,EPA_age_att(i)); if TSE(i) < 5 thyroid_ERR(i) = 10.7 d_thyroid ... 0.2 exp( 0.083 ( age_exp 15 ) ) 0.0; elseif TSE(i) >= 5 && TSE(i) < 15 thyroid _ERR(i) = 10.7 d_thyroid ... 0.2 exp( 0.083 ( age_exp 15 ) ) 1.15; elseif TSE(i) >= 15 && TSE(i) < 20 thyroid_ERR(i) = 10.7 d_thyroid ... 0.2 exp( 0.083 ( age_exp 15 ) ) 1.9; elseif TSE(i) >= 20 && TSE(i) < 25 thyroid_ERR(i) = 10.7 d_thyroid ... 0.2 exp( 0.083 ( age_exp 15 ) ) 1.2; elseif TSE(i) >= 25 && TSE(i) < 30 thyroid_ERR(i) = 10.7 d_thyroid ... 0.2 exp( 0.083 ( age_exp 15 ) ) 1.6; elseif TSE(i) >= 30 thyroid_ERR(i) = 10.7 d_thyroid ... 0.2 exp( 0.083 ( age_exp 15 ) ) 0.47; end remainder_ERR(i) = BEIR_ERR( 'Remainder' ,gender, ... d_remainder,age_exp,EPA_age_att(i)); if TSE(i) <= lat_leuk leukemia_ERR(i) = 0; elseif TSE(i) > lat_leuk && TSE(i) <= lat_leuk + 3 leukemia_ERR(i) = BEIR_ERR( 'Leukemia' ,gender, ... d_leukemia,age_exp,age_exp + lat_leuk + 3); leukemia_ERR(i) = leukemia_ERR(i) ... leukemia_inc(EPA_age_att == age_exp + lat_leuk + 3) / ... leukemia_inc(EPA_age_att == age_exp + lat_leuk); elseif TSE(i) >= lat_leuk + 3 leukemia_ERR(i) = BEIR_ERR( 'Leukemia' ,gender, ... d_leukemia,age_exp,EPA_age_att(i)); end kidney_ERR(i) = BEIR_ERR( 'Remainder' ,gender, ... d_kidney,age_exp,EPA_age_att(i) ); skin_ERR(i) = 0.2 d_skin ( 0.88 ) ^ ( age_exp 7 ); bone_ERR(i) = 0; end end % Organ EAR for i = 1:length(EPA_age_att) if EPA_age_att(i) >= age_exp stomach_EAR(i) = BEIR_EAR( 'Stomach' ,gender, ... d_stomach,age_exp,EPA_age_att(i)); colon_EAR(i) = BEIR_EAR( 'Colon' ,gender, ... d_colon,age_exp,EPA_age_att(i)); liver_EAR(i) = BEIR_EAR( 'Liver' ,gender, ... d_liver,age_exp,EPA_age_att(i)); EPA_lung_ EAR(i) = BEIR_EAR( 'Lung' ,gender, ... d_lung,age_exp,EPA_age_att(i)); breast_EAR(i) = BEIR_EAR( 'Breast' ,gender, ... d_breast,age_exp,EPA_age_att(i));

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586 prostate_EAR(i) = BEIR_EAR( 'Prostate' ,gender, ... d_prosta te,age_exp,EPA_age_att(i)); uterus_EAR(i) = BEIR_EAR( 'Uterus' ,gender, ... d_uterus,age_exp,EPA_age_att(i)); ovary_EAR(i) = BEIR_EAR( 'Ovary' ,gender, ... d_ovary,age_exp,EPA_age_att(i)); bladder_EAR(i) = BEIR_EAR( 'Bladder' ,gender, ... d_bladder,age_exp,EPA_age_att(i)); thyroid_EAR(i) = 0; remainder_EAR(i) = BEIR_EAR( 'Remainder' ,gender, ... d_remainder,age_exp,EPA_age_att(i)); if TSE(i) <= 2 leukemia_EAR(i) = 0; elseif TSE(i) > lat_leuk && TSE(i) <= lat_leuk + 3 leukemia_EAR(i) = BEIR_EAR( 'Leukemia' ,gender, ... d_leukemia,age_exp,age_exp + lat_leuk + 3); elseif TSE(i) >= lat_leuk + 3 leukemia_EAR(i) = BEIR_EAR( 'Leukemia' ,gender, ... d_leukemia,age_exp,EPA_age_att(i)); end kidney_EAR(i) = kidney_inc(i) / remainder_inc(i) ... BEIR_EAR( 'Remainder' ,gender, ... d_kidney,age _exp,EPA_age_att(i)); skin_EAR(i) = 0; if EPA_age_att(i) > age_exp bone_EAR(i) = 0.1 1.2 d_bone 1.782e 3 ... exp( 0.0532 (age_exp 30)) ... (2*pi*0.612^2)^ 0.5 ... exp( (log(EPA_age_att(i) age_exp) log(12.72))^2/(2*0.612^2)) ... (EPA_age_att(i) age_exp)^ 1; end end end %% Calculate hazard function hazard = struct(); % Initialize incidence hazard hazard.incidence.stomach.EAR = zeros(length(EPA_age_att),1); hazard.incidence.stomach.ERR = zeros(length(EPA_age_att),1); hazard.incidence.colon.EAR = zeros(length(EPA_age_att),1); hazard.incidence.colon.ERR = zeros(length(EPA_age_att),1); hazard.incidence .liver.EAR = zeros(length(EPA_age_att),1); hazard.incidence.liver.ERR = zeros(length(EPA_age_att),1); hazard.incidence.lung.EAR = zeros(length(EPA_age_att),1); hazard.incidence.lung.ERR = zeros(length(EPA_age_att),1); hazard.incidence.breast.EAR = zeros(le ngth(EPA_age_att),1); hazard.incidence.breast.ERR = zeros(length(EPA_age_att),1); hazard.incidence.prostate.EAR = zeros(length(EPA_age_att),1); hazard.incidence.prostate.ERR = zeros(length(EPA_age_att),1); hazard.incidence.uterus.EAR = zeros(length(EPA_age _att),1); hazard.incidence.uterus.ERR = zeros(length(EPA_age_att),1); hazard.incidence.ovary.EAR = zeros(length(EPA_age_att),1);

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587 hazard.incidence.ovary.ERR = zeros(length(EPA_age_att),1); hazard.incidence.bladder.EAR = zeros(length(EPA_age_att),1); hazard. incidence.bladder.ERR = zeros(length(EPA_age_att),1); hazard.incidence.thyroid.EAR = zeros(length(EPA_age_att),1); hazard.incidence.thyroid.ERR = zeros(length(EPA_age_att),1); hazard.incidence.remainder.EAR = zeros(length(EPA_age_att),1); hazard.incidence.remainder.ERR = zeros(length(EPA_age_att),1); hazard.incidence.leukemia.EAR = zeros(length(EPA_age_att),1); hazard.incidence.leukemia.ERR = zeros(length(EPA_age_att),1); hazard.incidence.kidney.EAR = zeros(length(EPA_age_att),1); hazard.in cidence.kidney.ERR = zeros(length(EPA_age_att),1); hazard.incidence.skin.EAR = zeros(length(EPA_age_att),1); hazard.incidence.skin.ERR = zeros(length(EPA_age_att),1); hazard.incidence.bone.EAR = zeros(length(EPA_age_att),1); hazard.incidence.bone.ERR = zeros(length(EPA_age_att),1); % Initialize mortality hazard hazard.mortality.stomach.EAR = zeros(length(EPA_age_att),1); hazard.mortality.stomach.ERR = zeros(length(EPA_age_att),1); hazard.mortality.colon.EAR = zeros(length(EPA_age_att),1); hazard.mortal ity.colon.ERR = zeros(length(EPA_age_att),1); hazard.mortality.liver.EAR = zeros(length(EPA_age_att),1); hazard.mortality.liver.ERR = zeros(length(EPA_age_att),1); hazard.mortality.lung.EAR = zeros(length(EPA_age_att),1); hazard.mortality.lung.ERR = zeros( length(EPA_age_att),1); hazard.mortality.breast.EAR = zeros(length(EPA_age_att),1); hazard.mortality.breast.ERR = zeros(length(EPA_age_att),1); hazard.mortality.prostate.EAR = zeros(length(EPA_age_att),1); hazard.mortality.prostate.ERR = zeros(length(EPA_a ge_att),1); hazard.mortality.uterus.EAR = zeros(length(EPA_age_att),1); hazard.mortality.uterus.ERR = zeros(length(EPA_age_att),1); hazard.mortality.ovary.EAR = zeros(length(EPA_age_att),1); hazard.mortality.ovary.ERR = zeros(length(EPA_age_att),1); hazard .mortality.bladder.EAR = zeros(length(EPA_age_att),1); hazard.mortality.bladder.ERR = zeros(length(EPA_age_att),1); hazard.mortality.thyroid.EAR = zeros(length(EPA_age_att),1); hazard.mortality.thyroid.ERR = zeros(length(EPA_age_att),1); hazard.mortality.r emainder.EAR = zeros(length(EPA_age_att),1); hazard.mortality.remainder.ERR = zeros(length(EPA_age_att),1); hazard.mortality.leukemia.EAR = zeros(length(EPA_age_att),1); hazard.mortality.leukemia.ERR = zeros(length(EPA_age_att),1); hazard.mortality.kidney.EAR = zeros(length(EPA_age_att),1); hazard.mortality.kidney.ERR = zeros(length(EPA_age_att),1); hazard.mortality.skin.EAR = zeros(length(EPA_age_att),1); hazard.mortality.skin.ERR = zeros(length(EPA_age_att),1); hazard.mortality.bone.EAR = zeros(length(EPA_age_att),1); hazard.mortality.bone.ERR = zeros(length(EPA_age_att),1); % Calculate EAR incidence hazard hazard.incidence.stomach.EAR = 1e 4*stomach_EAR.*TSE_solid./DDREF; hazard.incidence.colon.EAR = 1e 4*colo n_EAR.*TSE_solid./DDREF; hazard.incidence.liver.EAR = 1e 4*liver_EAR.*TSE_solid./DDREF; hazard.incidence.lung.EAR = 1e 4*EPA_lung_EAR.*TSE_solid./DDREF; hazard.incidence.prostate.EAR = 1e 4*prostate_EAR.*TSE_solid./DDREF; hazard.incidence.uterus.EAR = 1e 4 *uterus_EAR.*TSE_solid./DDREF;

PAGE 588

588 hazard.incidence.ovary.EAR = 1e 4*ovary_EAR.*TSE_solid./DDREF; hazard.incidence.bladder.EAR = 1e 4*bladder_EAR.*TSE_solid./DDREF; hazard.incidence.thyroid.EAR = 1e 4*thyroid_EAR.*TSE_solid./DDREF; hazard.incidence.remainder.E AR = 1e 4*remainder_EAR.*TSE_solid./DDREF; hazard.incidence.kidney.EAR = 1e 4*kidney_EAR.*TSE_solid./DDREF; hazard.incidence.skin.EAR = 1e 4*skin_EAR.*TSE_solid; hazard.incidence.breast.EAR = 1e 4*breast_EAR.*TSE_solid./DDREF; hazard.incidence.leukemia.EAR = 1e 4*leukemia_EAR; hazard.incidence.bone.EAR = 1e 4*bone_EAR; % Calculate ERR incidence hazard hazard.incidence.stomach.ERR = stomach_ERR.*TSE_solid.*stomach_inc./DDREF; hazard.incidence.colon.ERR = colon_ERR.*TSE_solid.*colon_inc./DDREF; hazard.incid ence.liver.ERR = liver_ERR.*TSE_solid.*liver_inc./DDREF; hazard.incidence.lung.ERR = EPA_lung_ERR.*TSE_solid.*lung_inc./DDREF; hazard.incidence.prostate.ERR = prostate_ERR.*TSE_solid.* ... prostate_inc./DDREF; hazard.incidence.uterus.ERR = uterus_ERR.*TSE_solid.*uterus_inc./DDREF; hazard.incidence.ovary.ERR = ovary_ERR.*TSE_solid.*ovary_inc./DDREF; hazard.incidence.bladder.ERR = bladder_ERR.*TSE_solid.*bladder_inc./DDREF; hazard.incidence.thyroid.ERR = thyroid_ERR.*TSE_solid.*thyroid_inc./DD REF; hazard.incidence.remainder.ERR = remainder_ERR.*TSE_solid.* ... remainder_inc./DDREF; hazard.incidence.kidney.ERR = kidney_ERR.*TSE_solid.*kidney_inc./DDREF; hazard.incidence.skin.ERR = skin_ERR.*TSE_solid.*skin_inc; hazard.incidence.breast.ERR = breast_ERR.*TSE_solid.*breast_inc./DDREF; hazard.incidence.leukemia.ERR = leukemia_ERR.*leukemia_inc; % Calculate EAR mortality hazard hazard.mortality.stomach.EAR = 1e 4*stomach_EAR.*TSE_solid.* ... stomach_mort./stomach_inc./DDREF; hazard.mortality. colon.EAR = 1e 4*colon_EAR.*TSE_solid.* ... colon_mort./colon_inc./DDREF; hazard.mortality.liver.EAR = 1e 4*liver_EAR.*TSE_solid.* ... liver_mort./liver_inc./DDREF; hazard.mortality.lung.EAR = 1e 4*EPA_lung_EAR.*TSE_solid.* ... lung_mort./lung_inc ./DDREF; if strcmp(gender, 'M' ) hazard.mortality.prostate.EAR = 1e 4*prostate_EAR.*TSE_solid.* ... prostate_mort./prostate_inc./DDREF; end if strcmp(gender, 'F' ) hazard.mortality.uterus.EAR = 1e 4*uterus_EAR.*TSE_solid.* ... uterus_mort./uterus_inc./DDREF; hazard.mortality.ovary.EAR = 1e 4*ovary_EAR.*TSE_solid.* ... ovary_mort./ovary_inc./DDREF; end hazard.mortality.bladder.EAR = 1e 4*bladder_EAR.*TSE_solid.* ... bladder_mort./bladder_inc./DDREF; hazard.mortality.thyroid.EAR = 1e 4*thyroid_EAR.*TSE_solid.* ... thyroid_mort./thyroid_inc./DDREF; hazard.mortality.remainder.EAR = 1e 4*remainder_EAR.*TSE_solid.* ... remainder_mort./remainder_inc./DDREF; hazard.mortality.kidney.EAR = 1e 4*kidney_EA R.*TSE_solid.* ... kidney_mort./kidney_inc./DDREF;

PAGE 589

589 hazard.mortality.leukemia.EAR = ... 1e 4*leukemia_EAR.*leukemia_mort./leukemia_inc; hazard.mortality.bone.EAR = 0.35 bone_EAR; % Solve for breast cancer mortality hazard function Integral_hMR = zeros(length(EPA_age_att),1); for i = 1:length(EPA_age_att) aI = (age_exp:EPA_age_att(i))'; if isempty(aI) || length(aI) <= 1 Integral_hMR(i) = 0; else h = zeros(length(aI),1); h(aI < 20) = 0.778; h(aI >= 20 & aI < 35) = 0.778; h(aI >= 35 & aI < 40) = 0.835; h(aI >= 40 & aI < 45) = 0.880; h(aI >= 45 & aI < 50) = 0.895; h(aI >= 50 & aI < 55) = 0.895; h(aI >= 55 & aI < 60) = 0.896; h(aI >= 60 & aI < 65) = 0.901; h(aI >= 65 & aI < 70) = 0.910; h(aI >= 70 & aI < 75) = 0.918; h(aI >= 75 & aI < 80) = 0.914; h(aI >= 80 & aI < 85) = 0.907; h(aI >= 85) = 0.866; hM = 0.2 log(h(end)); % Added 6/20/12 h = 0.2 log (h); M = hazard.incidence.breast.EAR( ... find(EPA_age_att==age_exp):find(EPA_age_att==EPA_age_att(i))); R = exp( 1*(EPA_age_att(i) aI).*h); hMR = h.*M.*R; %hMR = hM.*M.*R; % Added 6/20/12 Integral_hMR( i) = trapz(aI,hMR); end end for i = 3:length(hazard.mortality.breast.EAR) if Integral_hMR(i) == 0 hazard.mortality.breast.EAR(i) = 0; else F = Integral_hMR(i); G = exp( trapz( ... EPA_age_att(1:i 1),hazard.mor tality.breast.EAR(1:i 1)) + ... 0.5*(EPA_age_att(i) EPA_age_att(i 1)) ... hazard.mortality.breast.EAR(i 1)); fMort = @(x) x.*exp( 0.5*(EPA_age_att(i) EPA_age_att(i 1))*x)* ... G F; hazard.mortality.breast.EAR(i) = fzero(fMort,1); end end % Calculate ERR mortality hazard hazard.mortality.stomach.ERR = stomach_ERR.*TSE_solid.*stomach_mort./DDREF; hazard.mortality.colon.ERR = colon_ERR.*TSE_solid.*colon_mort./DDREF; hazard.mortality.liver.ERR = liver_ERR.*TSE_solid.*liver_mort./DDREF; hazard.mortality.lung.ERR = EPA_lung_ERR.*TSE_solid.*lung_mort./DDREF;

PAGE 590

590 hazard.mortality.prostate.ERR = prostate_ERR.*TSE_solid.* ... prostate_mort./DDREF; hazard.mortality.uterus.ERR = uterus_ERR.*TSE_solid.*uterus_mort./DDREF; hazard.mortality.ovary.ERR = ovary_ERR.*TSE_solid.*ovary_mort./DDREF; hazard.mortality.bladder.ERR = bladder_ERR.*TSE_solid.* ... bladder_mort./DDREF; hazard.mortality.thyroid.ERR = thyroid_ERR.*TSE_solid.* .. thyroid_mort./DDREF; hazard.mortality.remainder.ERR = remainder_ERR.*TSE_solid.* ... remainder_mort./DDREF; hazard.mortality.kidney.ERR = kidney_ERR.*TSE_solid.*kidney_mort./DDREF; hazard.mortality.skin.ERR = skin_ERR.*TSE_solid.*skin_mort; hazard .mortality.breast.ERR = breast_ERR.*TSE_solid.*breast_mort./DDREF; hazard.mortality.leukemia.ERR = leukemia_ERR.*leukemia_mort; %% Calculate hazard function sum mort_hazard_sum = struct(); % Initialize organ specific hazard sum mort_hazard_sum.stomach.EAR = zeros(length(EPA_age_att),1); mort_hazard_sum.stomach.ERR = zeros(length(EPA_age_att),1); mort_hazard_sum.colon.EAR = zeros(length(EPA_age_att),1); mort_hazard_sum.colon.ERR = zeros(length(EPA_age_att),1); mort_hazard_sum.live r.EAR = zeros(length(EPA_age_att),1); mort_hazard_sum.liver.ERR = zeros(length(EPA_age_att),1); mort_hazard_sum.lung.EAR = zeros(length(EPA_age_att),1); mort_hazard_sum.lung.ERR = zeros(length(EPA_age_att),1); mort_hazard_sum.breast.EAR = zeros(length(EPA_age_att),1); mort_hazard_sum.breast.ERR = zeros(length(EPA_age_att),1); mort_hazard_sum.prostate.EAR = zeros(length(EPA_age_att),1); mort_hazard_sum.prostate.ERR = zeros(length(EPA_age_att),1); mort_hazard_sum.uterus.EAR = zeros(length(EPA _age_att),1); mort_hazard_sum.uterus.ERR = zeros(length(EPA_age_att),1); mort_hazard_sum.ovary.EAR = zeros(length(EPA_age_att),1); mort_hazard_sum.ovary.ERR = zeros(length(EPA_age_att),1); mort_hazard_sum.bladder.EAR = zeros(length(EPA_age_att),1); mort_ha zard_sum.bladder.ERR = zeros(length(EPA_age_att),1); mort_hazard_sum.thyroid.EAR = zeros(length(EPA_age_att),1); mort_hazard_sum.thyroid.ERR = zeros(length(EPA_age_att),1); mort_hazard_sum.remainder.EAR = zeros(length(EPA_age_att),1); mort_hazard_sum.remai nder.ERR = zeros(length(EPA_age_att),1); mort_hazard_sum.leukemia.EAR = zeros(length(EPA_age_att),1); mort_hazard_sum.leukemia.ERR = zeros(length(EPA_age_att),1); mort_hazard_sum.kidney.EAR = zeros(length(EPA_age_att),1); mort_hazard_sum.kidney.ERR = zeros(length(EPA_age_att),1); mort_hazard_sum.skin.EAR = zeros(length(EPA_age_att),1); mort_hazard_sum.skin.ERR = zeros(length(EPA_age_att),1); mort_hazard_sum.bone.EAR = zeros(length(EPA_age_att),1); mort_hazard_sum.bone.ERR = zeros(length(EPA_age_att),1) ; % Calculate organ specific hazard sum for i = 2:length(EPA_age_att) mort_hazard_sum.stomach.EAR(i) = ... trapz(EPA_age_att(1:i),hazard.mortality.stomach.EAR(1:i));

PAGE 591

591 mort_hazard_sum.stomach.ERR(i) = ... trapz(EPA_age_att(1:i),h azard.mortality.stomach.ERR(1:i)); mort_hazard_sum.colon.EAR(i) = ... trapz(EPA_age_att(1:i),hazard.mortality.colon.EAR(1:i)); mort_hazard_sum.colon.ERR(i) = ... trapz(EPA_age_att(1:i),hazard.mortality.colon.ERR(1:i)); mort_hazard_sum.liver.EAR(i) = ... trapz(EPA_age_att(1:i),hazard.mortality.liver.EAR(1:i)); mort_hazard_sum.liver.ERR(i) = ... trapz(EPA_age_att(1:i),hazard.mortality.liver.ERR(1:i)); mort_hazard_sum.lung.EAR(i) = ... tr apz(EPA_age_att(1:i),hazard.mortality.lung.EAR(1:i)); mort_hazard_sum.lung.ERR(i) = ... trapz(EPA_age_att(1:i),hazard.mortality.lung.ERR(1:i)); mort_hazard_sum.breast.EAR(i) = ... trapz(EPA_age_att(1:i),hazard.mortality.breast.EAR(1 :i)); mort_hazard_sum.breast.ERR(i) = ... trapz(EPA_age_att(1:i),hazard.mortality.breast.ERR(1:i)); mort_hazard_sum.prostate.EAR(i) = ... trapz(EPA_age_att(1:i),hazard.mortality.prostate.EAR(1:i)); mort_hazard_sum.prostate.ERR(i) = ... trapz(EPA_age_att(1:i),hazard.mortality.prostate.ERR(1:i)); mort_hazard_sum.uterus.EAR(i) = ... trapz(EPA_age_att(1:i),hazard.mortality.uterus.EAR(1:i)); mort_hazard_sum.uterus.ERR(i) = ... trapz(EPA_age_att(1:i),hazard.mortality.uterus.ERR(1:i)); mort_hazard_sum.ovary.EAR(i) = ... trapz(EPA_age_att(1:i),hazard.mortality.ovary.EAR(1:i)); mort_hazard_sum.ovary.ERR(i) = ... trapz(EPA_age_att(1:i),hazard.mortality .ovary.ERR(1:i)); mort_hazard_sum.bladder.EAR(i) = ... trapz(EPA_age_att(1:i),hazard.mortality.bladder.EAR(1:i)); mort_hazard_sum.bladder.ERR(i) = ... trapz(EPA_age_att(1:i),hazard.mortality.bladder.ERR(1:i)); mort_hazard_sum.thyroid.EAR(i) = ... trapz(EPA_age_att(1:i),hazard.mortality.thyroid.EAR(1:i)); mort_hazard_sum.thyroid.ERR(i) = ... trapz(EPA_age_att(1:i),hazard.mortality.thyroid.ERR(1:i)); mort_hazard_sum.remainder.EAR(i) = .. trapz(EPA_age_att(1:i),hazard.mortality.remainder.EAR(1:i)); mort_hazard_sum.remainder.ERR(i) = ... trapz(EPA_age_att(1:i),hazard.mortality.remainder.ERR(1:i)); mort_hazard_sum.leukemia.EAR(i) = ... trapz(EPA_age_att(1:i) ,hazard.mortality.leukemia.EAR(1:i)); mort_hazard_sum.leukemia.ERR(i) = ... trapz(EPA_age_att(1:i),hazard.mortality.leukemia.ERR(1:i)); mort_hazard_sum.kidney.EAR(i) = ... trapz(EPA_age_att(1:i),hazard.mortality.kidney.EAR(1:i)); mort_hazard_sum.kidney.ERR(i) = ... trapz(EPA_age_att(1:i),hazard.mortality.kidney.ERR(1:i)); mort_hazard_sum.skin.EAR(i) = ... trapz(EPA_age_att(1:i),hazard.mortality.skin.EAR(1:i)); mort_hazard_sum.skin.ERR(i) = ... tr apz(EPA_age_att(1:i),hazard.mortality.skin.ERR(1:i)); mort_hazard_sum.bone.EAR(i) = ...

PAGE 592

592 trapz(EPA_age_att(1:i),hazard.mortality.bone.EAR(1:i)); mort_hazard_sum.bone.ERR(i) = ... trapz(EPA_age_att(1:i),hazard.mortality.bone.ERR(1:i)) ; end % Calculate combined hazard sum mort_hazard_sum.stomach.combined = ... mort_hazard_sum.stomach.ERR vT_stomach + ... mort_hazard_sum.stomach.EAR (1 vT_stomach); mort_hazard_sum.colon.combined = ... mort_hazard_sum.colon.ERR vT_colon + ... mort_hazard_sum.colon.EAR (1 vT_colon); mort_hazard_sum.liver.combined = ... mort_hazard_sum.liver.ERR vT_liver + ... mort_hazard_sum.liver.EAR (1 vT_liver); mort_hazard_sum.lung.combined = ... mort_hazard_sum.lung.ERR vT_lung + ... mort_hazard_sum.lung.EAR (1 vT_lung); mort_hazard_sum.breast.combined = ... mort_hazard_sum.breast.ERR vT_breast + ... mort_hazard_sum.breast.EAR (1 vT_breast); mort_hazard_sum.prostate.combined = ... mort_hazard_sum.prostate.ERR vT_prostate + ... mort_hazard_sum.prostate.EAR (1 vT_prostate); mort_hazard_sum.uterus.combined = ... mort_hazard_sum.uterus.ERR vT_uterus + ... mort_hazard_sum.ut erus.EAR (1 vT_uterus); mort_hazard_sum.ovary.combined = ... mort_hazard_sum.ovary.ERR vT_ovary + ... mort_hazard_sum.ovary.EAR (1 vT_ovary); mort_hazard_sum.bladder.combined = ... mort_hazard_sum.bladder.ERR vT_bladder + ... mo rt_hazard_sum.bladder.EAR (1 vT_bladder); mort_hazard_sum.thyroid.combined = ... mort_hazard_sum.thyroid.ERR vT_thyroid + ... mort_hazard_sum.thyroid.EAR (1 vT_thyroid); mort_hazard_sum.remainder.combined = ... mort_hazard_sum.remainder.ERR vT_remainder + ... mort_hazard_sum.remainder.EAR (1 vT_remainder); mort_hazard_sum.leukemia.combined = ... mort_hazard_sum.leukemia.ERR vT_leukemia + ... mort_hazard_sum.leukemia.EAR (1 vT_leukemia) ; mort_hazard_sum.kidney.combined = ... mort_hazard_sum.kidney.ERR vT_kidney + ... mort_hazard_sum.kidney.EAR (1 vT_kidney); mort_hazard_sum.skin.combined = ... mort_hazard_sum.skin.ERR vT_skin + ... mort_hazard_sum.skin.EAR (1 vT_skin); mort_hazard_sum.bone.combined = ... mort_hazard_sum.bone.ERR vT_bone + ... mort_hazard_sum.bone.EAR (1 vT_bone); mort_hazard_sum.total = mort_hazard_sum.stomach.combined + ... mort_hazard_sum. colon.combined + ... mort_hazard_sum.liver.combined + ... mort_hazard_sum.lung.combined + ...

PAGE 593

593 mort_hazard_sum.breast.combined + ... mort_hazard_sum.prostate.combined + ... mort_hazard_sum.uterus.combined + ... mort_hazard_sum.ovary. combined + ... mort_hazard_sum.bladder.combined + ... mort_hazard_sum.thyroid.combined + ... mort_hazard_sum.remainder.combined + ... mort_hazard_sum.leukemia.combined + ... mort_hazard_sum.kidney.combined + ... mort_hazard_sum.skin.combined + ... mort_hazard_sum.bone.combined; %% Calculate REIC and REID risk = struct(); % Calculate organ specific REIC based on EAR and ERR risk.incidence.stomach.EAR = ... trapz(EPA_age_att,hazard.incidence.stomac h.EAR.* ... survival./survival(age_survival == age_exp).* ... exp( mort_hazard_sum.total)); risk.incidence.stomach.ERR = ... trapz(EPA_age_att,hazard.incidence.stomach.ERR.* ... survival./survival(age_survival == age_exp).* ... exp( mort_hazard_sum.total)); risk.incidence.colon.EAR = ... trapz(EPA_age_att,hazard.incidence.colon.EAR.* ... survival./survival(age_survival == age_exp).* ... exp( mort_hazard_sum.total)); risk.incidence.colon.ERR = ... trapz(EPA_age_a tt,hazard.incidence.colon.ERR.* ... survival./survival(age_survival == age_exp).* ... exp( mort_hazard_sum.total)); risk.incidence.liver.EAR = ... trapz(EPA_age_att,hazard.incidence.liver.EAR.* ... survival./survival(age_survival == age_exp).* ... exp( mort_hazard_sum.total)); risk.incidence.liver.ERR = ... trapz(EPA_age_att,hazard.incidence.liver.ERR.* ... survival./survival(age_survival == age_exp).* ... exp( mort_hazard_sum.total)); risk.incidence.lung.EAR = ... trapz(EPA_ag e_att,hazard.incidence.lung.EAR.* ... survival./survival(age_survival == age_exp).* ... exp( mort_hazard_sum.total)); risk.incidence.lung.ERR = ... trapz(EPA_age_att,hazard.incidence.lung.ERR.* ... survival./survival(age_survival == age_exp).* ... exp( mort_hazard_sum.total)); risk.incidence.breast.EAR = ... trapz(EPA_age_att,hazard.incidence.breast.EAR.* ... survival./survival(age_survival == age_exp).* ... exp( mort_hazard_sum.total)); risk.incidence.breast.ERR = ... trapz(EP A_age_att,hazard.incidence.breast.ERR.* ...

PAGE 594

594 survival./survival(age_survival == age_exp).* ... exp( mort_hazard_sum.total)); risk.incidence.prostate.EAR = ... trapz(EPA_age_att,hazard.incidence.prostate.EAR.* ... survival./survival(age_survival == age_exp).* ... exp( mort_hazard_sum.total)); risk.incidence.prostate.ERR = ... trapz(EPA_age_att,hazard.incidence.prostate.ERR.* ... survival./survival(age_survival == age_exp).* ... exp( mort_hazard_sum.total)); risk.incidence.uterus.EAR = ... trapz(EPA_age_att,hazard.incidence.uterus.EAR.* ... survival./survival(age_survival == age_exp).* ... exp( mort_hazard_sum.total)); risk.incidence.uterus.ERR = ... trapz(EPA_age_att,hazard.incidence.uterus.ERR. ... survival./survival(age_survival == age_exp).* ... exp( mort_hazard_sum.total)); risk.incidence.ovary.EAR = ... trapz(EPA_age_att,hazard.incidence.ovary.EAR.* ... survival./survival(age_survival == age_exp).* ... exp( mort_hazard_sum.total)); risk.incidence.ovary.ERR = ... trapz(EPA_age_att,hazard.incidence.ovary.ERR.* ... survival./survival(age_survival == age_exp).* ... exp( mort_hazard_sum.total)); risk.incidence.bladder.EAR = ... trapz(EPA_age _att,hazard.incidence.bladder.EAR.* ... survival./survival(age_survival == age_exp).* ... exp( mort_hazard_sum.total)); risk.incidence.bladder.ERR = ... trapz(EPA_age_att,hazard.incidence.bladder.ERR.* ... survival./survival(age_survival == ag e_exp).* ... exp( mort_hazard_sum.total)); risk.incidence.thyroid.EAR = ... trapz(EPA_age_att,hazard.incidence.thyroid.EAR.* ... survival./survival(age_survival == age_exp).* ... exp( mort_hazard_sum.total)); risk.incidence.thyroid.ERR = ... trapz(EPA_age_att,hazard.incidence.thyroid.ERR.* ... survival./survival(age_survival == age_exp).* ... exp( mort_hazard_sum.total)); risk.incidence.remainder.EAR = ... trapz(EPA_age_att,hazard.incidence.remainder.EAR.* ... survival./surviv al(age_survival == age_exp).* ... exp( mort_hazard_sum.total)); risk.incidence.remainder.ERR = ... trapz(EPA_age_att,hazard.incidence.remainder.ERR.* ... survival./survival(age_survival == age_exp).* ... exp( mort_hazard_sum.total)); risk.incidence.kidney.EAR = ... trapz(EPA_age_att,hazard.incidence.kidney.EAR.* ... survival./survival(age_survival == age_exp).* ... exp( mort_hazard_sum.total)); risk.incidence.kidney.ERR = ...

PAGE 595

595 trapz(EPA_age_att,hazard.incidence.kidney.ERR. ... survival./survival(age_survival == age_exp).* ... exp( mort_hazard_sum.total)); risk.incidence.bone.EAR = ... trapz(EPA_age_att,hazard.incidence.bone.EAR.* ... survival./survival(age_survival == age_exp).* ... exp( mort_hazard_sum.tot al)); risk.incidence.bone.ERR = ... trapz(EPA_age_att,hazard.incidence.bone.ERR.* ... survival./survival(age_survival == age_exp).* ... exp( mort_hazard_sum.total)); risk.incidence.skin.EAR = ... trapz(EPA_age_att,hazard.incidence.skin.EAR.* ... survival./survival(age_survival == age_exp).* ... exp( mort_hazard_sum.total)); risk.incidence.skin.ERR = ... trapz(EPA_age_att,hazard.incidence.skin.ERR.* ... survival./survival(age_survival == age_exp).* ... exp( mort_hazard_sum.tota l)); risk.incidence.leukemia.EAR = ... trapz(EPA_age_att,hazard.incidence.leukemia.EAR.* ... survival./survival(age_survival == age_exp).* ... exp( mort_hazard_sum.total)); risk.incidence.leukemia.ERR = ... trapz(EPA_age_att,hazard.incidence.leukemia.ERR.* ... survival./survival(age_survival == age_exp).* ... exp( mort_hazard_sum.total)); % Combine organ specific REIC risk.incidence.stomach.combined = ... risk.incidence.stomach.ERR vT_stomac h + ... risk.incidence.stomach.EAR ( 1 vT_stomach ); risk.incidence.colon.combined = ... risk.incidence.colon.ERR vT_colon + ... risk.incidence.colon.EAR ( 1 vT_colon ); risk.incidence.liver.combined = ... risk.incidence.liver.ERR vT_liver + ... risk.incidence.liver.EAR ( 1 vT_liver ); risk.incidence.lung.combined = ... risk.incidence.lung.ERR vT_lung + ... risk.incidence.lung.EAR ( 1 vT_lung ); risk.incidence.breast.combined = .. risk.incidence.breast.ERR vT_breast + ... risk.incidence.breast.EAR ( 1 vT_breast ); risk.incidence.prostate.combined = ... risk.incidence.prostate.ERR vT_prostate + ... risk.incidence.prostate.EAR ( 1 vT_prostate ); risk.inci dence.uterus.combined = ... risk.incidence.uterus.ERR vT_uterus + ... risk.incidence.uterus.EAR ( 1 vT_uterus ); risk.incidence.ovary.combined = ... risk.incidence.ovary.ERR vT_ovary + ... risk.incidence.ovary.EAR ( 1 vT_ovary ); risk.incidence.bladder.combined = ... risk.incidence.bladder.ERR vT_bladder + ...

PAGE 596

596 risk.incidence.bladder.EAR ( 1 vT_bladder ); risk.incidence.thyroid.combined = ... risk.incidence.thyroid.E RR vT_thyroid + ... risk.incidence.thyroid.EAR ( 1 vT_thyroid ); risk.incidence.remainder.combined = ... risk.incidence.remainder.ERR vT_remainder + ... risk.incidence.remainder.EAR ( 1 vT_remainder ); risk.incidence.kidney.combined = ... risk.incidence.kidney.ERR vT_kidney + ... risk.incidence.kidney.EAR ( 1 vT_kidney ); risk.incidence.bone.combined = ... risk.incidence.bone.ERR vT_bone + ... risk.incidence.bone.EAR ( 1 vT_bone ); risk.incidence.skin.combined = ... risk.incidence.skin.ERR vT_skin + ... risk.incidence.skin.EAR ( 1 vT_skin ); risk.incidence.leukemia.combined = ... risk.incidence.leukemia.ERR vT_leukemia + ... risk.incidence.leukemia.EAR ( 1 vT_leukemia ); % Calculate organ specific REID based on EAR and ERR risk.mortality.stomach.EAR = ... trapz(EPA_age_att,hazard.mortality.stomach.EAR.* ... survival./survival(age_survival == age_exp).* ... exp( mort_hazard_sum.total)); risk.mortality.stomach.ERR = ... trapz(EPA_age_att,hazard.mortality.stomach.ERR.* ... survival./survival(age_survival == age_exp).* ... exp( mort_hazard_sum.total)); risk.mortality.colon.EAR = ... trapz(EPA_age_att,hazard.mortality.colon.EAR. ... survival./survival(age_survival == age_exp).* ... exp( mort_hazard_sum.total)); risk.mortality.colon.ERR = ... trapz(EPA_age_att,hazard.mortality.colon.ERR.* ... survival./survival(age_survival == age_exp).* ... exp( mort_hazard_sum.total)); risk.mortality.liver.EAR = ... trapz(EPA_age_att,hazard.mortality.liver.EAR.* ... survival./survival(age_survival == age_exp).* ... exp( mort_hazard_sum.total)); risk.mortality.liver.ERR = ... trapz(EPA_age_a tt,hazard.mortality.liver.ERR.* ... survival./survival(age_survival == age_exp).* ... exp( mort_hazard_sum.total)); risk.mortality.lung.EAR = ... trapz(EPA_age_att,hazard.mortality.lung.EAR.* ... survival./survival(age_survival == age_exp).* .. exp( mort_hazard_sum.total)); risk.mortality.lung.ERR = ... trapz(EPA_age_att,hazard.mortality.lung.ERR.* ... survival./survival(age_survival == age_exp).* ... exp( mort_hazard_sum.total)); risk.mortality.breast.EAR = ... trapz(EPA_age_att,hazard.mortality.breast.EAR.* ...

PAGE 597

597 survival./survival(age_survival == age_exp).* ... exp( mort_hazard_sum.total)); risk.mortality.breast.ERR = ... trapz(EPA_age_att,hazard.mortality.breast.ERR.* ... survival./survival(age_ survival == age_exp).* ... exp( mort_hazard_sum.total)); risk.mortality.prostate.EAR = ... trapz(EPA_age_att,hazard.mortality.prostate.EAR.* ... survival./survival(age_survival == age_exp).* ... exp( mort_hazard_sum.total)); risk.mortality.prostate.ERR = ... trapz(EPA_age_att,hazard.mortality.prostate.ERR.* ... survival./survival(age_survival == age_exp).* ... exp( mort_hazard_sum.total)); risk.mortality.uterus.EAR = ... trapz(EPA_age_att,hazard.mortality.uterus. EAR.* ... survival./survival(age_survival == age_exp).* ... exp( mort_hazard_sum.total)); risk.mortality.uterus.ERR = ... trapz(EPA_age_att,hazard.mortality.uterus.ERR.* ... survival./survival(age_survival == age_exp).* ... exp( mort_hazard _sum.total)); risk.mortality.ovary.EAR = ... trapz(EPA_age_att,hazard.mortality.ovary.EAR.* ... survival./survival(age_survival == age_exp).* ... exp( mort_hazard_sum.total)); risk.mortality.ovary.ERR = ... trapz(EPA_age_att,hazard.mortality.ovary.ERR.* ... survival./survival(age_survival == age_exp).* ... exp( mort_hazard_sum.total)); risk.mortality.bladder.EAR = ... trapz(EPA_age_att,hazard.mortality.bladder.EAR.* ... survival./survival(age _survival == age_exp).* ... exp( mort_hazard_sum.total)); risk.mortality.bladder.ERR = ... trapz(EPA_age_att,hazard.mortality.bladder.ERR.* ... survival./survival(age_survival == age_exp).* ... exp( mort_hazard_sum.total)); risk.mortality.thyroid.EAR = ... trapz(EPA_age_att,hazard.mortality.thyroid.EAR.* ... survival./survival(age_survival == age_exp).* ... exp( mort_hazard_sum.total)); risk.mortality.thyroid.ERR = ... trapz(EPA_age_att,hazard.mortality.thyroid. ERR.* ... survival./survival(age_survival == age_exp).* ... exp( mort_hazard_sum.total)); risk.mortality.remainder.EAR = ... trapz(EPA_age_att,hazard.mortality.remainder.EAR.* ... survival./survival(age_survival == age_exp).* ... exp( mort_ hazard_sum.total)); risk.mortality.remainder.ERR = ... trapz(EPA_age_att,hazard.mortality.remainder.ERR.* ... survival./survival(age_survival == age_exp).* ... exp( mort_hazard_sum.total)); risk.mortality.kidney.EAR = ...

PAGE 598

598 trapz(EPA_age_att,hazard.mortality.kidney.EAR.* ... survival./survival(age_survival == age_exp).* ... exp( mort_hazard_sum.total)); risk.mortality.kidney.ERR = ... trapz(EPA_age_att,hazard.mortality.kidney.ERR.* ... survival./survival(age_ survival == age_exp).* ... exp( mort_hazard_sum.total)); risk.mortality.bone.EAR = ... trapz(EPA_age_att,hazard.mortality.bone.EAR.* ... survival./survival(age_survival == age_exp).* ... exp( mort_hazard_sum.total)); risk.mortality.bone.ERR = ... trapz(EPA_age_att,hazard.mortality.bone.ERR.* ... survival./survival(age_survival == age_exp).* ... exp( mort_hazard_sum.total)); risk.mortality.skin.EAR = ... trapz(EPA_age_att,hazard.mortality.skin.EAR.* ... survival./survival(age_su rvival == age_exp).* ... exp( mort_hazard_sum.total)); risk.mortality.skin.ERR = ... trapz(EPA_age_att,hazard.mortality.skin.ERR.* ... survival./survival(age_survival == age_exp).* ... exp( mort_hazard_sum.total)); risk.mortality.leukemia.EAR = ... trapz(EPA_age_att,hazard.mortality.leukemia.EAR.* ... survival./survival(age_survival == age_exp).* ... exp( mort_hazard_sum.total)); risk.mortality.leukemia.ERR = ... trapz(EPA_age_att,hazard.mortality.leukemia.ERR.* ... survival./survival(age_survival == age_exp).* ... exp( mort_hazard_sum.total)); % Combine organ specific REID risk.mortality.stomach.combined = ... risk.mortality.stomach.ERR vT_stomach + ... risk.mortality.stomach.EAR ( 1 vT_stomach ); risk.mortality.colon.combined = ... risk.mortality.colon.ERR vT_colon + ... risk.mortality.colon.EAR ( 1 vT_colon ); risk.mortality.liver.combined = ... risk.mortality.liver.ERR vT_li ver + ... risk.mortality.liver.EAR ( 1 vT_liver ); risk.mortality.lung.combined = ... risk.mortality.lung.ERR vT_lung + ... risk.mortality.lung.EAR ( 1 vT_lung ); risk.mortality.breast.combined = ... risk.mortality.breast.ERR vT _breast + ... risk.mortality.breast.EAR ( 1 vT_breast ); risk.mortality.prostate.combined = ... risk.mortality.prostate.ERR vT_prostate + ... risk.mortality.prostate.EAR ( 1 vT_prostate ); risk.mortality.uterus.combined = ... risk.mortality.uterus.ERR vT_uterus + ... risk.mortality.uterus.EAR ( 1 vT_uterus ); risk.mortality.ovary.combined = ...

PAGE 599

599 risk.mortality.ovary.ERR vT_ovary + ... risk.mortality.ovary.EAR ( 1 vT_ovary ); risk.mortality.bladder.com bined = ... risk.mortality.bladder.ERR vT_bladder + ... risk.mortality.bladder.EAR ( 1 vT_bladder ); risk.mortality.thyroid.combined = ... risk.mortality.thyroid.ERR vT_thyroid + ... risk.mortality.thyroid.EAR ( 1 vT_thyroid ); risk.mortality.remainder.combined = ... risk.mortality.remainder.ERR vT_remainder + ... risk.mortality.remainder.EAR ( 1 vT_remainder ); risk.mortality.kidney.combined = ... risk.mortality.kidney.ERR vT_kidney + ... risk.mortality.kidney.EAR ( 1 vT_kidney ); risk.mortality.bone.combined = ... risk.mortality.bone.ERR vT_bone + ... risk.mortality.bone.EAR ( 1 vT_bone ); risk.mortality.skin.combined = ... risk.mortality.skin.ERR vT_skin + ... risk.mortality.skin.EAR ( 1 vT_skin ); risk.mortality.leukemia.combined = ... risk.mortality.leukemia.ERR vT_leukemia + ... risk.mortality.leukemia.EAR ( 1 vT_leukemia ); %% Assign values to structure ExcessRisk_io.REIC.stomach = risk.incidence.stomach.combined; ExcessRisk_io.REIC.colon = risk.incidence.colon.combined; ExcessRisk_io.REIC.liver = risk.incidence.liver.combined; ExcessRisk_io.REIC.lung = risk.incidence.lung.combined; ExcessRisk_io.REIC.breast = risk.incidence.breast.c ombined; ExcessRisk_io.REIC.uterus = risk.incidence.uterus.combined; ExcessRisk_io.REIC.ovary = risk.incidence.ovary.combined; ExcessRisk_io.REIC.prostate = risk.incidence.prostate.combined; ExcessRisk_io.REIC.bladder = risk.incidence.bladder.combined; Exc essRisk_io.REIC.thyroid = risk.incidence.thyroid.combined; ExcessRisk_io.REIC.remainder = risk.incidence.remainder.combined; ExcessRisk_io.REIC.kidney = risk.incidence.kidney.combined; ExcessRisk_io.REIC.bone = risk.incidence.bone.combined; ExcessRisk_io.REIC.skin = risk.incidence.skin.combined; ExcessRisk_io.REIC.leukemia = risk.incidence.leukemia.combined; ExcessRisk_io.REIC.total = ExcessRisk_io.REIC.stomach + ... ExcessRisk_io.REIC.colon + ... ExcessRisk_io.REIC.liver + ... Ex cessRisk_io.REIC.lung + ... ExcessRisk_io.REIC.breast + ... ExcessRisk_io.REIC.uterus + ... ExcessRisk_io.REIC.ovary + ... ExcessRisk_io.REIC.prostate + ... ExcessRisk_io.REIC.bladder + ... ExcessRisk_io.REIC.thyroid + ... Exces sRisk_io.REIC.remainder + ... ExcessRisk_io.REIC.kidney + ... ExcessRisk_io.REIC.bone + ... ExcessRisk_io.REIC.skin + ...

PAGE 600

600 ExcessRisk_io.REIC.leukemia; ExcessRisk_io.REID.stomach = risk.mortality.stomach.combined; ExcessRisk_io.REID.colon = risk.mortality.colon.combined; ExcessRisk_io.REID.liver = risk.mortality.liver.combined; ExcessRisk_io.REID.lung = risk.mortality.lung.combined; ExcessRisk_io.REID.breast = risk.mortality.breast.combined; ExcessRisk_io.REID.uterus = risk.mortality.uterus .combined; ExcessRisk_io.REID.ovary = risk.mortality.ovary.combined; ExcessRisk_io.REID.prostate = risk.mortality.prostate.combined; ExcessRisk_io.REID.bladder = risk.mortality.bladder.combined; ExcessRisk_io.REID.thyroid = risk.mortality.thyroid.combined; ExcessRisk_io.REID.remainder = risk.mortality.remainder.combined; ExcessRisk_io.REID.kidney = risk.mortality.kidney.combined; ExcessRisk_io.REID.bone = risk.mortality.bone.combined; ExcessRisk_io.REID.skin = risk.mortality.skin.combined; ExcessRisk_io.REID.leukemia = risk.mortality.leukemia.combined; ExcessRisk_io.REID.total = ExcessRisk_io.REID.stomach + ... ExcessRisk_io.REID.colon + ... ExcessRisk_io.REID.liver + ... ExcessRisk_io.REID.lung + ... ExcessRisk_io.REID.breas t + ... ExcessRisk_io.REID.uterus + ... ExcessRisk_io.REID.ovary + ... ExcessRisk_io.REID.prostate + ... ExcessRisk_io.REID.bladder + ... ExcessRisk_io.REID.thyroid + ... ExcessRisk_io.REID.remainder + ... ExcessRisk_io.REID.kidney + ... ExcessRisk_io.REID.bone + ... ExcessRisk_io.REID.skin + ... ExcessRisk_io.REID.leukemia; end transfer_weight.m function vT = transfer_weight(organ,mode) % Point Estimate if strcmp(mode, 'NASA point' ) switch organ case 'Stomach' vT = 0.7; case 'Colon' vT = 0.7; case 'Liver' vT = 0.5; case 'Lung' vT = 0.5; case 'Breast' vT = 0.0; case 'Prostate' vT = 0.5; case 'Uterus' vT = 0.5; case 'Ovary'

PAGE 601

601 vT = 0.5; case 'Bladder' vT = 0.5; case 'Esophagus' vT = 0.7; case 'Brain CNS' vT = 0.5; case 'Thyroid' vT = 1.0; case 'Oral Cavity' vT = 0.5; case 'Remainder' vT = 0.5; case 'Leukemia' vT = 0.5; end elseif strcmp(mode, 'EPA point' ) || strcmp(mode, 'No DDREF' ) switch organ case 'Stomach' vT = 0.7; case 'Colon' vT = 0.7; case 'Liver' vT = 0.7; case 'Lung' vT = 0.3; case 'Breast' vT = 0.0; case 'Prostate' vT = 0.7; case 'Uterus' vT = 0.7; case 'Ovary' vT = 0.7; case 'Bladder' vT = 0.7; case 'Thyroid' vT = 1.0; case 'Remainder' vT = 0.7; ca se 'Leukemia' vT = 0.7; case 'Kidney' vT = 0.7; case 'Skin' vT = 0.7; case 'Bone' vT = 0.0; end elseif strcmp(mode, 'EPA sample' ) switch organ case 'Stomach' unif_sample = unifrnd(0,1,1,1); cumul_sample = unifrnd(0,1,1,1); if cumul_sample <= 0.05

PAGE 602

602 vT = 0.0; elseif cumul_sample <= 0.55 vT = unif_sample; else vT = 1.0; end case 'Colon' unif_sample = unifrnd(0,1,1,1); cumul_sample = unifrnd(0,1,1,1); if cumul_sample <= 0.05 vT = 0.0; elseif cumul_sample <= 0.55 vT = unif_sample; else vT = 1.0; end case 'Liver' unif_sample = unifrnd(0,1,1,1); cumul_sample = unifrnd(0,1,1,1); if cumul_sample <= 0.05 vT = 0.0; elseif cumul_sample <= 0.55 vT = unif_sample; else vT = 1.0; end case 'Lung' unif_sample = unifrnd(0,1,1,1); cumul_sample = unifrnd(0,1,1,1); if cumul_sample <= 0.05 vT = 1.0; elseif cumul_sample <= 0.55 vT = unif_sample; else vT = 0.0; end case 'Breast' vT = 0.0; case 'Prostate' unif_sample = unifrnd(0,1,1,1); cumul_sample = unifrnd(0,1,1,1); if cumul_sample <= 0.05 vT = 0.0; elseif cumul_sample <= 0. 55 vT = unif_sample; else vT = 1.0; end case 'Uterus' unif_sample = unifrnd(0,1,1,1); cumul_sample = unifrnd(0,1,1,1); if cumul_sample <= 0 .05 vT = 0.0; elseif cumul_sample <= 0.55 vT = unif_sample;

PAGE 603

603 else vT = 1.0; end case 'Ovary' unif_sample = unifrnd(0,1,1,1); cumul_sample = unifrnd(0,1,1,1); if cumul_sample <= 0.05 vT = 0.0; elseif cumul_sample <= 0.55 vT = unif_sample; else vT = 1.0; end case 'Bladder' unif_sample = unifrnd(0,1,1,1); cumul_sample = unifrnd(0,1,1,1); if cumul_sample <= 0.05 vT = 0.0; elseif cumul_sample <= 0.55 vT = unif_sample; else vT = 1.0; end case 'Thyroid' vT = 1.0; case 'Remainder' unif_sample = unifrnd(0,1,1,1); cumul_sample = unifrnd(0,1,1,1); if cumul_sample <= 0.05 vT = 0.0; elseif cumul_sample <= 0.55 vT = unif_sample; else vT = 1.0; end case 'Leukemia' unif_sample = unifrnd(0,1,1,1); cumul_sample = unifrnd(0,1,1,1); if cumul_sample <= 0.05 vT = 0.0; elseif cumul_sample <= 0.55 vT = unif_sample; else vT = 1.0; end case 'Kidney' unif_sample = unifrnd(0,1,1,1); cumul_sample = unifrnd(0,1,1,1); if cumul_sample <= 0.05 vT = 0.0; elseif cumul_sample <= 0.55 vT = unif_sample; else vT = 1.0; end

PAGE 604

604 case 'Skin' unif_sample = unifrnd(0,1,1,1); cumul_sample = unifrnd(0,1,1,1); if cumul_sample <= 0.05 vT = 0.0; elseif cumul_sample <= 0.55 vT = unif_sample; else vT = 1.0; end case 'Bone' vT = 0.0; end end end BEIR_EAR.m % This function calculates the ERR for a given cancer site, dependent upon % gender, age at exposure in y(e), attained age in y (a), and dose in % Sv (d). function EAR_value = BEIR_EAR(site,gender,d,e,a) % Load coefficients from as given in BEIR VII load BEIR_EAR_model.mat % Define e_ ref and a_ref e_ref = 30; a_ref = 60; % Define e* e_star = ( e < e_ref ) ( e e_ref ) / 10 + ( e >= e_ref ) 0; % Retrieve appropriate EAR coefficients if strcmp(gender, 'M' ) beta_col = 2; elseif strcmp(gender, 'F' ) beta_col = 3; end switch site case 'Stomach' row = 2; case 'Colon' row = 3; case 'Liver' row = 4; case 'Lung' row = 5; case 'Breast' row = 6; e_ref = 25; a_ref = 50; e_star = ( e e_ref ) / 10; index = ( a < a_ref ) 1 + ( a >= a_ref ) 2;

PAGE 605

605 case 'Prostate' row = 7; case 'Uterus' row = 8; case 'Ovary' row = 9; case 'Bladder' row = 10; case 'Remainder' row = 11; case 'Thyroid' row = 12; e_star = ( e e_ref ) / 10; case 'Leukemia' % This is a special case (linear quadratic fit) if strcmp(gender, 'M' ) beta = 1.62; elseif strcmp(gender, 'F' ) beta = 0.93; end gamma = 0.29; delta = 0; phi = 0.56; theta = 0.88; t = a e; EAR_value = beta d ( 1 + theta d ) exp( gamma e_star + ... delta log( t / 25 ) + phi e_star log( t / 25 ) ); re turn end beta = BEIR_EAR_model{row,beta_col}; gamma = BEIR_EAR_model{row,4}; eta = BEIR_EAR_model{row,5}; if strcmp(site, 'Breast' ) && strcmp(gender, 'F' ) eta = eta(index); end % Calculate EAR if isempty(beta) || isempty(gamma) || isempty(eta) EAR_value = 0; else EAR_value = beta d exp( gamma e_star ) ( a / a_ref ) ^ eta; end BEIR_ERR.m % This function calculates the ERR for a given cancer site, dependent upon % gender, age at exposure in y(e), attained age in y (a), and dose in % Sv (d). function ERR_value = BEIR_ERR(site,gender,d,e,a) % Load coefficients from as given in BEIR VII load BEIR_ERR_model.mat % Define e_ref and a_ref e_ref = 30;

PAGE 606

606 a_ref = 60; % Define e* e_star = ( e < e_ref ) ( e e_ref ) / 10 + ( e >= e_ ref ) 0; % Retrieve appropriate ERR coefficients if strcmp(gender, 'M' ) beta_col = 2; elseif strcmp(gender, 'F' ) beta_col = 3; end switch site case 'Stomach' row = 2; case 'Colon' row = 3; case 'Liver' row = 4; case 'Lung' row = 5; case 'Breast' row = 6; e_star = ( e e_ref ) / 10; case 'Prostate' row = 7; case 'Uterus' row = 8; case 'Ovary' row = 9; case 'Bladder' row = 10; case 'Remainder' row = 11; case 'Thyroid' row = 12; e_star = ( e e_ref ) / 10; case 'Leukemia' % This is a special case (linear quadratic fit) if strcmp(gender, 'M' ) beta = 1.1; elseif strcmp(gender, 'F' ) beta = 1.2; end gamma = 0.4; delta = 0.48; phi = 0.42; theta = 0.87; t = a e; ERR_value = beta d ( 1 + theta d ) exp( gamma e_star + ... delta log( t / 25 ) + phi e_star log( t / 25 ) ); return end beta = BEIR_ERR_model{row,beta_col}; gamma = BEIR_ERR_model{row,4};

PAGE 607

607 eta = BEIR_ERR_model{row,5}; % Calculate ERR if isempty(beta) || isempty(gamma) || isempty(eta) ERR_value = 0; else ERR_value = beta d exp( gamma e_star ) ( a / a_ref ) ^ eta; end

PAGE 608

608 APPENDIX R PHITS AND HZETRN ORGAN ABSORBED DOSES (PHITS VS. HZETRN) Figure R 1 August 1972 SPE with suit shielding male D T (PHITS vs. HZETRN) Figure R 2 August 1972 SPE with suit shielding female D T (PHITS vs. HZETRN)

PAGE 609

609 Figure R 3 August 1972 SPE with suit shielding female D T (PHITS vs. HZETRN) Figure R 4 August 1972 SPE with shelter shielding female D T (PHITS vs. HZETRN)

PAGE 610

610 Figure R 5 February 1956 SPE with suit shielding ma le D T (PHITS vs. HZETRN) Figure R 6 February 1956 SPE with suit shielding female D T (PHITS vs. HZETRN)

PAGE 611

611 Figure R 7 February 1956 SPE with shelter shielding male D T (PHITS vs. HZETRN) Figure R 8 February 1956 SPE with shelter shielding female D T (PHITS vs. HZETRN)

PAGE 612

612 Figure R 9 Trapped environment with PV shielding male D T (PHITS vs. HZETRN) Figure R 10 Trapped env ironment with PV shielding female D T (PHITS vs. HZETRN)

PAGE 613

613 Figure R 11 GCR hydrogen irradiation with PV shielding male D T (PHITS vs. HZETRN) Figure R 12 GCR hydrogen irradiation with PV shielding femal e D T (PHITS vs. HZETRN)

PAGE 614

614 Figure R 13 GCR helium irradiation with PV shielding male D T (PHITS vs. HZETRN) Figure R 14 GCR helium irradiation with PV shielding female D T (PHITS vs. HZETRN)

PAGE 615

615 Figure R 15 GCR carbon irradiation with PV shielding male D T (PHITS vs. HZETRN) Figure R 16 GCR carbon irradiation with PV shielding female D T (PHITS vs. HZETRN)

PAGE 616

616 Figure R 17 GCR ox ygen irradiation with PV shielding male D T (PHITS vs. HZETRN) Figure R 18 GCR oxygen irradiation with PV shielding female D T (PHITS vs. HZETRN)

PAGE 617

617 Figure R 19 GCR magnesium irradiation with PV shielding male D T (PHITS vs. HZETRN) Figure R 20 GCR magnesium irradiation with PV shielding female D T (PHITS vs. HZETRN)

PAGE 618

618 Figure R 21 GCR silicon irradiation with PV shielding male D T (PHITS vs. HZE TRN) Figure R 22 GCR silicon irradiation with PV shielding female D T (PHITS vs. HZETRN)

PAGE 619

619 Figure R 23 GCR iron irradiation with PV shielding male D T (PHITS vs. HZETRN) Figure R 24 GCR iron irradiation with PV shielding female D T (PHITS vs. HZETRN)

PAGE 620

620 Figure R 25 GCR ion group 1 irradiation with PV shielding male D T (PHITS vs. HZETRN) Figure R 26 GCR ion group 1 irradiation with PV shielding female D T (PHITS vs. HZETRN)

PAGE 621

621 Figure R 27 GCR ion group 2 irradiation with PV shielding male D T (PHITS vs. HZETRN) Figure R 28 GCR ion group 2 irradiation w ith PV shielding female D T (PHITS vs. HZETRN)

PAGE 622

622 Figure R 29 GCR ion group 3 irradiation with PV shielding male D T (PHITS vs. HZETRN) Figure R 30 GCR ion group 3 irradiation with PV shielding female D T (PHITS vs. HZETRN)

PAGE 623

623 APPENDIX S PHITS AND HZETRN ORG AN DOSE EQUIVALENT VALUES Figure S 1 August 1972 SPE with suit shielding male H T ( PHITS vs. HZETRN) Figure S 2 August 1972 SPE with suit shielding female H T ( PHITS vs. HZETRN)

PAGE 624

624 Figure S 3 August 1972 SPE with shelter shielding male H T ( PHITS vs. HZETRN) Figure S 4 August 1972 SPE with shelter shielding female H T ( PHITS vs. HZETRN)

PAGE 625

625 Figure S 5 February 1956 SPE with suit shielding male H T ( PHITS vs. HZETRN) Figure S 6 February 1956 SPE with suit shielding female H T ( PHITS vs. HZETRN)

PAGE 626

626 Figure S 7 February 1956 SPE with shelter shielding male H T ( PHITS vs. HZETRN) Figure S 8 February 1956 SPE with shelter shieldi ng female H T ( PHITS vs. HZETRN)

PAGE 627

627 Figure S 9 Trapped environment with PV shielding male H T ( PHITS vs. HZETRN) Figure S 10 Trapped environment with PV shielding female H T ( PHITS vs. HZETRN)

PAGE 628

628 Figure S 11 GCR hydrogen irradiation with PV shielding male H T ( PHITS vs. HZETRN) Figure S 12 GCR hydrogen irradiation with PV shielding female H T ( PHITS vs. HZETRN)

PAGE 629

629 Figure S 13 GCR helium irradiation with PV shielding male H T ( PHITS vs. HZETRN) Figure S 14 GCR helium irradiation with PV shielding female H T ( PHITS vs. HZETRN)

PAGE 630

630 Figure S 15 GCR carbon irradiation with PV sh ielding male H T ( PHITS vs. HZETRN) Figure S 16 GCR carbon irradiation with PV shielding female H T ( PHITS vs. HZETRN)

PAGE 631

631 Figure S 17 GCR oxygen irradiation with PV shielding male H T ( PHITS vs. HZETRN) Figure S 18 GCR oxygen irradiation with PV shielding female H T ( PHITS vs. HZETRN)

PAGE 632

632 Figure S 19 GCR magnesium irradiation with PV shielding male H T ( PHITS vs. HZETRN) Figure S 20 GCR magnesium irradiation with PV shielding female H T ( PHITS vs. HZETRN)

PAGE 633

633 Figure S 21 GCR silicon irradiation with PV shielding male H T ( PHITS vs. HZETRN) Figure S 22 GCR silicon irradiation with PV shielding female H T ( PHITS vs. HZETRN)

PAGE 634

634 Figure S 23 GCR iron irradiation with PV shielding male H T ( PHITS vs. HZETRN) Figure S 24 GCR iron irradiation with PV shiel ding female H T ( PHITS vs. HZETRN)

PAGE 635

635 Figure S 25 GCR ion group 1 irradiation with PV shielding male H T ( PHITS vs. HZETRN) Figure S 26 GCR ion group 1 irradiation with PV shielding female H T ( PHITS vs. HZETRN)

PAGE 636

636 Figure S 27 GCR ion group 2 irradiation with PV shielding male H T ( PHITS vs. HZETRN) Figure S 28 GCR ion group 2 irradiation with PV shielding female H T ( PHITS vs. HZETRN)

PAGE 637

637 Figure S 29 GCR ion group 3 irradiation with PV shielding male H T ( PHITS vs. HZETRN) Figure S 30 GCR ion group 3 irradiation with PV shielding female H T ( PHITS vs. HZETRN)

PAGE 638

638 APPENDIX T PHITS AND HZETRN ORG AN ABSORBED DOSE PERCENT DIFFERENCES Figure T 1 August 1972 SPE with suit shielding D T PD (PHITS vs. HZETRN) Figure T 2 August 1972 SPE with suit shielding female D T PD (PHITS vs. HZETRN)

PAGE 639

639 Figure T 3 August 1972 SPE with shelter shielding male D T PD (PHITS vs. HZETRN) Figure T 4 August 1972 SPE with shelter shielding female D T PD (PHITS vs. HZETRN)

PAGE 640

640 Figure T 5 Febru ary 1956 SPE with suit shielding male D T PD (PHITS vs. HZETRN) Figure T 6 February 1956 SPE with suit shielding female D T PD (PHITS vs. HZETRN)

PAGE 641

641 Figure T 7 February 1956 SPE with shelter shielding male D T PD (PHITS vs. HZETRN) Figure T 8 February 1956 SPE with shelter shielding female D T PD (PHITS vs. HZETRN)

PAGE 642

642 Figure T 9 Trapped environment with PV s hielding male D T PD (PHITS vs. HZETRN) Figure T 10 Trapped environment with PV shielding female D T PD (PHITS vs. HZETRN)

PAGE 643

643 Figure T 11 GCR hydrogen irradiation with PV shielding male D T PD (PHITS vs. HZETRN) Figure T 12 GCR hydrogen irradiation with PV shielding female D T PD (PHITS vs. HZETRN)

PAGE 644

644 Figure T 13 GCR helium irradiation with PV shielding male D T PD (PHITS vs. HZETRN) Figure T 14 GCR helium irradiation with PV shielding female D T PD (PHITS vs. HZETRN)

PAGE 645

645 Figure T 15 GCR carbon irradiation with PV shielding male D T PD (PHITS vs. HZETRN) Figure T 16 GCR carbon irradiation with PV shielding female D T PD (PHITS vs. HZETRN)

PAGE 646

646 Figure T 17 GCR oxygen irradiation with PV shielding male D T PD (PHITS vs. HZETRN) Figure T 18 GCR oxygen irradiation with PV shielding female D T PD (PHITS vs. HZETRN)

PAGE 647

647 Figure T 19 GCR magnesium irradiation with PV shielding male D T PD (PHITS vs. HZETRN) Figure T 20 GCR magnesium irradiation with PV shielding female D T PD (PHITS vs. HZETRN)

PAGE 648

648 Figure T 21 GCR silicon irradiation with PV shielding male D T PD (PHITS vs. HZETRN) Figure T 22 GCR silicon irradiation with PV shielding female D T PD (PHITS vs. HZETRN)

PAGE 649

649 Figure T 23 GCR iron irradiation with PV shielding male D T PD (PHITS vs. HZETRN) Figure T 24 GCR iron irradiation with PV shielding female D T PD (PHITS vs. HZETRN)

PAGE 650

650 Figure T 25 GC R ion group 1 irradiation with PV shielding male D T PD (PHITS vs. HZETRN) Figure T 26 GCR ion group 1 irradiation with PV shielding female D T PD (PHITS vs. HZETRN)

PAGE 651

651 Figure T 27 GCR ion group 2 irradiation with PV shielding male D T PD (PHITS vs. HZETRN) Figure T 28 GCR ion group 2 irradiation with PV shielding female D T PD (PHITS vs. HZETRN)

PAGE 652

652 Figure T 29 GCR ion group 3 irradiation with PV shielding male D T PD (PHITS vs. HZETRN) Figure T 30 GCR ion group 3 irradiation with PV shielding female D T PD (PHITS vs. HZETRN)

PAGE 653

653 APPENDIX U PHITS AND HZETRN ORG AN DOSE EQUIVALENT P ERCENT DIFFERENCES Figure U 1 August 1972 SPE with suit shielding male H T PD (PHITS vs. HZETRN) Figure U 2 August 1972 SPE with suit shielding female H T PD (PHITS vs. HZETRN)

PAGE 654

654 Figure U 3 August 1972 SPE wi th shelter shielding male H T PD (PHITS vs. HZETRN) Figure U 4 August 1972 SPE with shelter shielding female H T PD (PHITS vs. HZETRN)

PAGE 655

655 Figure U 5 February 1956 SPE with suit shielding male H T PD (PHITS vs. HZETRN) Figure U 6 February 1956 SPE with suit shielding female H T PD (PHITS vs. HZETRN)

PAGE 656

656 Figure U 7 February 1956 SPE with shelter shielding male H T PD (PHITS vs. HZETRN) Figure U 8 February 1956 SPE with shelter shielding female H T PD (PHITS vs. HZETRN)

PAGE 657

657 Figure U 9 Trapped environment with PV shielding male H T PD (PHITS vs. HZETRN) Figure U 10 Trapped environment with PV shielding female H T PD (PHITS vs. HZETRN)

PAGE 658

658 Figure U 11 GCR hydrogen irradiation with PV shielding male H T PD (PHITS vs. HZETRN) Figure U 12 GCR hydrogen irradiation wit h PV shielding female H T PD (PHITS vs. HZETRN)

PAGE 659

659 Figure U 13 GCR helium irradiation with PV shielding male H T PD (PHITS vs. HZETRN) Figure U 14 GCR helium irradiation with PV shielding female H T PD (P HITS vs. HZETRN)

PAGE 660

660 Figure U 15 GCR carbon irradiation with PV shielding male H T PD (PHITS vs. HZETRN) Figure U 16 GCR carbon irradiation with PV shielding female H T PD (PHITS vs. HZETRN)

PAGE 661

661 Figure U 17 GCR oxygen irradiation with PV shielding male H T PD (PHITS vs. HZETRN) Figure U 18 GCR oxygen irradiation with PV shielding female H T PD (PHITS vs. HZETRN)

PAGE 662

662 Figure U 19 GCR magnesium irradiation with PV shielding male H T PD (PHITS vs. HZETRN) Figure U 20 GCR magnesium irradiation with PV shielding female H T PD (PHITS vs. HZETRN)

PAGE 663

663 Figure U 21 GCR silicon irradiation with PV shielding male H T PD (PHITS vs. HZETRN) Figure U 22 GCR silicon irradiation with PV shielding female H T PD (PHITS vs. HZETRN)

PAGE 664

664 Figure U 23 GCR iron irradiation with PV shielding male H T PD (PHITS vs. HZETRN) Figure U 24 GCR iron irradiation with PV shielding female H T PD (PHITS vs. HZETRN)

PAGE 665

665 Figure U 25 GCR ion group 1 irradiation with PV shielding male H T PD (P HITS vs. HZETRN) Figure U 26 GCR ion group 1 irradiation with PV shielding female H T PD (PHITS vs. HZETRN)

PAGE 666

666 Figure U 27 GCR ion group 2 irradiation with PV shielding male H T PD (PHITS vs. HZETRN) Figure U 28 GCR ion group 2 irradiation with PV shielding female H T PD (PHITS vs. HZETRN)

PAGE 667

667 Figure U 29 GCR ion group 3 irradiation with PV shielding male H T PD (PHITS vs. HZETRN) Figure U 30 GCR ion group 3 irradiation with PV shielding female H T PD (PHITS vs. HZETRN)

PAGE 668

668 APPENDIX V PHITS AND HZETRN REI D COMPARISON Figure V 1 REID values for August 1972 SPE with suit shielding Figure V 2 Percent differences in REID values for August 1972 SPE with suit shielding

PAGE 669

669 Figure V 3 REID values for August 1972 SPE with shelter shielding Figure V 4 Percent differenc es in REID values for August 1972 SPE with shelter shielding

PAGE 670

670 Figure V 5 REID values for February 1956 SPE with suit shielding Figure V 6 Percent differences in REID values for February 1956 SPE with suit shielding

PAGE 671

671 Figure V 7 REID values for February 1956 SPE with shelter shielding Figure V 8 Percent differences in REID values for February 1956 SPE with shelter shielding

PAGE 672

672 Figure V 9 REID values for trapped environment with PV shielding Figure V 10 Percent differences in REID values for trapped environment with PV shielding

PAGE 673

673 Figure V 11 REID values fo r GCR with PV shielding Figure V 12 Percent differences in REID values for GCR with PV shielding

PAGE 674

674 LIST OF REFERENCES Alsmiller R G, Irving D C, Kinney W E and Moran H S 1965 The Validity of the Straighta head Approximation in Space Vehicle Shielding Studies. (Washington, DC: NASA) Amin S 2010 Mechanical factors and bone health: Effects of weightlessness and neurologic injury Current Rheumatology Reports 12 170 6 ANS 2005 Computational Medical Physics Working Group. http://cmpwg.ans.org/phantoms.html Accessed 16 November 2012 Badavi F F, Adams D O and Wilson J W 2010 On the validity of the aluminum equivalent approximation in space radiation shielding ap plications Advances in Space Research 46 719 27 Badavi F F, West K J, Nealy J E, Wilson J W, Abrahms B L and Luetke N J 2006 A Dynamic/Anisotropic Low Earth Orbit (LEO) Ionizing Radiation Model. (Hampton, VA: NASA Langley Research Center) Badhwar G D, A twell W, Badavi F F, Yang T C and Cleghorn T F 2002 Space radiation absorbed dose distribution in a human phantom Radiation Research 157 76 91 Bahadori A A, Van Baalen M, Shavers M R, Dodge C, Semones E J and Bolch W E 2011 The effect of anatomical modeli ng on space radiation dose estimates: a comparison of dsoes for NASA phantoms and the 5th, 50th, and 95th percentile male and female astronauts Physics in Medicine and Biology 56 1671 93 Bahadori A A, Van Baalen M, Shavers M R, Semones E J and Bolch W E 2 012 Dosimetric impacts of microgravity: an analysis of 5th, 50th and 95th percentile male and female astronauts Physics in Medicine and Biology 57 1047 70 Ballarini F, Battistoni G, Cerutti F, Fass A, Ferrari A, Gadioli E, Garzelli M V, Mairani A, Ottole nghi A, Paretzke H G, Parini V, Pelliccioni M, Pinsky L, Sala P R, Scannicchio D, Trovati S and Zankl M 2006 GCR and SPE organ doses in deep space with different shielding: Monte Carlo simulations based on the FLUKA code coupled to anthropomorphic phantoms Advances in Space Research 37 1791 7 Barratt M R and Pool S L eds 2008 Principles of Clinical Medicine for Space Flight (New York: Springer) Billings M P and Langley R W 1971 A Technique for Evaluation of Space Radiation Dose to Distributed Body Organs. In: American Nuclear Society Annual Meeting, (Boston, MA: McDonnell Douglas Company)

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675 Billings M P and Yucker W R 1973 The Computerized Anatomical Man (CAM) Model. (Houston, TX: NASA Johnson Space Center) Billings M P, Yucker W R and Heckman B R 1973 Body self shielding data and analyses. (Huntington Beach, CA: McDonnell Douglas Astronautics Company West) Cucinotta F A 2007 Space Radiation Organ Doses for Astronauts on Past and Future Missions. (Houston, TX: NASA Johnson Space Center) Cucinotta F, Badhwar G, Saganti P, Schimmerling W, Wilson J, Peterson L and Dicello J 2002 Space Radiation Cancer Risk Projections for Exploration Missions: Uncertainty Reduction and Mitigation. (Houston, TX: NASA Johnson Space Center) Cucinotta F A, Kim M H Y and Ch appell L J 2011 Space Radiation Cancer Risk Projections and Uncertainties 2010. (Houston, TX: NASA Johnson Space Center) Cucinotta F A, Kim M H Y and Ren L 2005 Managing Lunar and Mars Mission Radiation Risks Part I: Cancer Risks, Uncertainties, and Sh ielding Effectiveness. (Houston, TX: NASA Johnson Space Center) Cucinotta F A, Kim M Y, Willingham V and George K A 2008 Physical and biological organ dosimetry analysis for International Space Station astronauts Radiation Research 170 127 38 Cucinotta F A, Nikjoo H and Goodhead D T 2000 Model of the radial distribution of energy imparted in nanometer volumes from HZE particles Radiation Research 153 459 68 Cucinotta F A, Wilson J W, Shavers M R and Katz R 1997 The Calculation of Heavy Ion Inactivation and Mutation Rates in the Track Structure Model. (Hampton, VA: NASA Langley Research Center) Durante M and Cucinotta F 2011 Physical basis of radiation protection in space travel Reviews of Modern Physics 83 1245 81 EPA 2011 EPA Radiogenic Cancer Risk M odels and Projections for the U.S. Population. (Washington, DC: U.S Environmental Protection Agency) Fortney R E and Duckworth G E 1964 Model Astronaut Radiation Dose Distribution Analysis. (Wright Patterson Air Force Base, OH: Northrop Space Laboratori es)

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676 Gustafsson K, Sihver L, Mancusi D, Sato T, Reitz G and Berger T 2010 PHITS simulations of the Matroshka experiment Advances in Space Research 40 1266 72 Heer M, De Santo N G, Cirillo M and Drummer C 2001 Body mass changes, energy, and protein metabol ism in space American Journal of Kidney Diseases 38 691 5 Heinbockel J H, Slaba T C, Blattnig S R, Tripathi R K, Townsend L W, Handler T, Gabriel T A, Pinsky L S, Reddell B, Clowdsley M S, Singleterry R C, Norbury J W, Badavi F F and Aghara S K 2009a Comparison of Radiation Transport Codes, HZETRN, HETC and FLUKA, Using the 1956 Webber SPE Spectrum. (Hampton, VA: NASA Langley Research Center) Heinbockel J H, Slaba T C, Tripathi R K, Blattnig S R, Norbury J W, Badavi F F, Townsend L W, Handler T, Gabr iel T A, Pinsky L S, Reddell B and Aumann A R 2009b Comparison of Transport Codes, HZETRN, HETC and FLUKA, Using 1977 GCR Solar Minimum Spectra. (Hampton, VA: NASA Langley Research Center) Hoff J L, Townsend L W and Zapp E N 2004 Interplanetary crew doses and dose equivalents: variations among different bone marrow and skin sites Advances in Space Research 34 1347 52 Hough M, Johnson P, Rajon D, Jokisch D, Lee C and Bolch W 2011 An image ba sed skeletal dosimetry model for the ICRP reference adult male -internal electron sources Phys Med Biol 56 2309 46 ICRP 1991 ICRP Publication 60: Recommendations of the ICRP Annals of the ICRP 21 ICRP 2002 ICRP Publication 89: basic anatomical and physio logical data for use in radiological protection: reference values Annals of the ICRP 32 1 277 ICRP 2007 ICRP Publication 103: Recommendations of the ICRP Annals of the ICRP 37 ICRU 1992 Photon, Electron, Proton and Neutron Interaction Data for Body Tissu es. (Bethesda, MD: International Commission on Radiation Units and Measurements) Johnson P B, Whalen S R, Wayson M, Juneja B, Lee C and Bolch W E 2009 Hybrid patient dependent phantoms covering statistical distributions of body morphometry in the U.S. ad ult and pediatric population Proceedings of the IEEE 97 2060 75 Kase P G 1970 Computerized Anatomical Model Man. (Kirtland Air Force Base, NM: Martin Marietta Corporation)

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683 BIOGRAPHICAL SKETCH Amir Alexander Bahadori wa s born in Kansas City, Kansas. He attended high school at Sumner Academy of Arts and Sciences, successfully completing the International Baccalaureate program and graduating in 2003. Amir then attended Kansas State University, majoring in Mechanical Engi neering with Nuclear Engineering Option and Mathematics. It was there that his interest in radiation was kindled by his work as a Reactor Operator at the Kansas State University TRIGA Mark II Nuclear Reactor Facility. Upon graduating summa cum laude from Kansas State University in 2008, he enrolled at the University of Florida, obtaining a Master of Science in Medical Physics in 2010 and continuing work towards a Doctor of Philosophy in Medical Physics. He currently resides in League City, Texas, with hi s wife, Alexandra, and two basset hounds, Walter and Phoebe.