This item is only available as the following downloads:
1 ASSESSING PATIENT DOSE IN INTERVENTIONAL FLUOROSCOPY USING PATIENT DEPENDENT HYBRID PHANTOMS By PERRY BARNETT JOHNSON 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 2011
2 2011 Perry Barnett Johnson
3 T o my family Mom, Dad, Alex, Laura and Maw
4 ACKNOWLEDGMENTS I extend sincere thanks to my graduate adviser, Wesley Bolch for his guidance and encouragement during my time at the University of Florida. Dr. Bolch has defined the role of an adviser for me by constantly providing new ideas and direction, facilitating contacts, teaching, reviewing and editing my publications, a nd always having my best interest at heart. Without his support, my graduate experience would have not have been as enjoyable or as successful. I look forward to staying in touch in the coming years and maintaining a lifelong friendship. I would also like to thank the other members of my graduate committee including Kevin Johnson, Manuel Arreola, David Hintenlang and Scott Banks. Their input helped structure my dissertation and maintain a good timeline for graduation. Specifically, Dr. Johnson played a crit ical role in facilitating the research collaboration between my work and Shands Jacksonville Medical Center. Dr. Johnson was always willing to go out of his way for the benefit of my project and I am sincerely thankful for his help. I would also like to sp ecifically thank Dr. Arreola for providing reference letters for various scholarships and residencies for which I applied. His encouragement meant a great deal to me during these times, and I always enjoyed our interaction in class, research, and at profes sional meetings. Dr. Hintenlang also provided reference letters for which I am grateful Additionally, I will always remember warmly our times outside the classroom at weddings and conferences where I was able to hang out with a friend in place of a profes sor. I would also like to thank experts Stephen Balter from Columbia University Medical Center and Daniel Siragusa from Shands Jacksonville Medical Center for their role in providing clinical consultation and collaboration. Having the help of Choonsik Lee during his time as a post doc at UF was also major advantage, and I acknowledge his instrumental role as the primary developer of the UF hybrid phantom family.
5 Several colleagues deserve recognition for both their participation in my research and their f riendship First, is Dan Hyer who served as roommate officemate and private consultant on all things car or bass fishing related. Matt Hoerner also served as great roommate and friend, and I appreciate the help of other graduate colleagues Chris Tien, Ba dal Juneja, Ryan Fisher, Amir Bahadori, Matt Maynard, Mike Wayson, David Borrego, Amy Geyer, and Deanna Pafundi. I wo uld also like to thank Jing Sun who supervised my time at the Community Cancer Center and provided me a solid clinical foundation for my re sidency. Finally, I would like to give special thank s to my family for all their support. I thank my brother for being my closest friend and companion. I thank my sister for her devotion and encouragement. I thank my grandmother Maw for her love. I thank my brother in law Andrew and sister in law Kim for their friendship. And lastly, I thank my parents for always sacrificing to place my interest above theirs. I would not be here without them.
6 TABLE OF CONTENTS page ACKNOWLEDGMENTS ................................ ................................ ................................ ............... 4 LIST OF FIGURES ................................ ................................ ................................ ......................... 9 ABSTRACT ................................ ................................ ................................ ................................ ... 11 CHAPTER 1 INTRODUCTION ................................ ................................ ................................ .................. 13 Interventional Fluoroscopy ................................ ................................ ................................ ..... 13 High D ose Procedures and the Need for Comprehensive Dosimetry ................................ ..... 13 Available Options for Patient Dosimetry ................................ ................................ ............... 15 Diverse Anthropomorphic Models ................................ ................................ .................. 18 Automatic Monitoring of Exposure Parameters ................................ .............................. 21 Objectives of this Research ................................ ................................ ................................ .... 25 2 CONSTRUCTION OF A PATIENT DEPENDENT PHANTOM LIBRARY ...................... 27 Background ................................ ................................ ................................ ............................. 27 Methods and Materials ................................ ................................ ................................ ........... 28 NHANES III Database ................................ ................................ ................................ .... 28 Anthropometric Targets ................................ ................................ ................................ ... 29 Anchor Phantoms ................................ ................................ ................................ ............ 30 Phantom Remodeling ................................ ................................ ................................ ...... 31 Results ................................ ................................ ................................ ................................ ..... 32 Discussion ................................ ................................ ................................ ............................... 33 Summary ................................ ................................ ................................ ................................ 36 3 IMPACT OF PATIENT PHAN TOM MATCHING ON ORGAN DOSE ............................ 50 Background ................................ ................................ ................................ ............................. 50 Methods and Materials ................................ ................................ ................................ ........... 52 Patient Sp ecific Phantom Construction ................................ ................................ ........... 52 Patient Dependent Phantom Modification ................................ ................................ ...... 53 Monte Carlo Simulation ................................ ................................ ................................ .. 54 Results ................................ ................................ ................................ ................................ ..... 56 Discussion ................................ ................................ ................................ ............................... 59 Summary ................................ ................................ ................................ ................................ 63 4 DEVELOPMENT OF SOFTWARE FOR SKIN AND ORGAN DOSE ASSESSMENT .... 74 Background ................................ ................................ ................................ ............................. 74 Methods and Materials ................................ ................................ ................................ ........... 76
7 RDSR Extraction ................................ ................................ ................................ ............. 76 Skin Dose Mapping Software ................................ ................................ .......................... 77 Phantom formatting and orientation ................................ ................................ ......... 77 Determination of affected skin area ................................ ................................ ......... 78 Skin dose assessment ................................ ................................ ............................... 80 Examination Characterization for Organ Dose Assessment ................................ ........... 80 Determining interesting irradiation events and common tube geometries ............... 81 Preparing and writing the MCNPX inpu t file ................................ .......................... 82 Test of Skin Dose Mapping System ................................ ................................ ................ 83 Results ................................ ................................ ................................ ................................ ..... 83 Discussion ................................ ................................ ................................ ............................... 84 Technical Challenges ................................ ................................ ................................ ....... 84 Clinical Challenges ................................ ................................ ................................ .......... 86 Summary ................................ ................................ ................................ ................................ 87 5 SENSITIVITY OF SKIN DOSE MAPPING TO PATIENT LOCALIZATION AND BODY MORPHOMETRY ................................ ................................ ................................ ..... 95 Background ................................ ................................ ................................ ............................. 95 Methods and Materials ................................ ................................ ................................ ........... 97 Isocenter Based Orientation ................................ ................................ ............................ 97 Coordinate System Based Orientation ................................ ................................ ............. 97 Construction of Elliptical Contour Phantoms ................................ ................................ .. 98 Patient Phantom Matching for Skin dose Mapping ................................ ........................ 99 Results ................................ ................................ ................................ ................................ ... 100 Discussion ................................ ................................ ................................ ............................. 102 Summary ................................ ................................ ................................ ............................... 104 6 CONCLUSION ................................ ................................ ................................ ..................... 110 Result of this work ................................ ................................ ................................ ................ 110 Opportunities for Further Development ................................ ................................ ............... 113 Additional Patient Dependent Phantoms ................................ ................................ ...... 113 Patient Sculpted Phantoms ................................ ................................ ............................ 114 Skin Dose Mapping in Real Time ................................ ................................ ................. 115 Physical Validation ................................ ................................ ................................ ........ 1 16 Clinical Application ................................ ................................ ................................ ....... 116 Cloud Dosimetry ................................ ................................ ................................ ........... 117 Final Thoughts ................................ ................................ ................................ ...................... 118 LIST OF REFERENCES ................................ ................................ ................................ ............. 121 BIOGRAPHICAL SKETCH ................................ ................................ ................................ ....... 129
8 LIST OF TABLES Table page 2 1 Anthropometric parameterization of the U.S. adult male population. ............................... 38 2 2 Anthropometric parameterization of the U.S. adult female population ............................ 39 2 3 Organ masses selected from the UFHAD M patien t dependent series ............................... 40 3 1 Mean organ volumes as contoured from 14 male and 13 female CT datas ets .................. 64 3 2 Mean absolute percent difference for individual organs of three patie nt groupings ......... 65 3 3 Percentage point improvement over a referen ce hybrid phantom ................................ ..... 66 3 4 Percentage point improvement over a reference stylized phantom ................................ ... 67 4 1 Four ranges of skin effe cts ................................ ................................ ................................ 89 5 1 Error using isocentric system when isocenter is incorrectly located within the body. .... 106 5 2 Error using coordinate bases system when patient location is incorrectly assigned. ....... 107 5 3 Mean absolute percent difference in PSD between patient specific models and four differen t phantom types ................................ ................................ ................................ ... 108
9 LIST OF FIGURES Figure page 2 1 V iews of patient dependent adult male phantoms at fiftieth percentile standing height and tenth, twenty fifth, fiftieth, seventy fifth, an d ninetieth percentile weight ................. 41 2 2 V iews of patient dependent adult female phantoms at fiftieth percentile standing height and tenth, twenty fifth, fiftieth, seventy fifth, and ninetieth percentile weight ...... 42 2 3 V iew s of patient dependent adult male phantoms at fiftieth percentile body mass and tenth, twenty fifth, fiftieth, seventy fifth, and ninet ieth percentile standing height .......... 43 2 4 V iews of patient dependent adult female phantoms at fiftieth percentile body mass and tenth, twenty fifth, fiftieth, seventy fifth, and ninet ieth percentile standing height ... 44 2 5 Correlation of liver mass with body mass index for the UFH ADM patient dependent series ................................ ................................ ................................ ................................ .. 45 2 6 Correlation of spleen mass with body mass index for the UF HADM patient dependent series ................................ ................................ ................................ ................. 45 2 7 Correlation of thyroid mass with body mass index for the UF HADM patient dependent series ................................ ................................ ................................ ................. 46 2 8 Correlation of pancreas mass with body mass index for the UF HADM patient dependent series ................................ ................................ ................................ ................. 46 2 9 Correlation of kidney mass with body mass index for the UFH ADM patient dependent series ................................ ................................ ................................ ................. 47 2 10 Correlation of liver mass with standing height index for the UFHADM patient dependent series ................................ ................................ ................................ ................. 47 2 11 Correlation of spleen mass with standing height for the U FHADM patient dependent series ................................ ................................ ................................ ................................ .. 48 2 12 Correlation of thyroid mass with standing height for the UF HADM patient dependent series ................................ ................................ ................................ ................. 48 2 13 Correlation of pancreas mass with standing height for the UFH ADM patient dependent series ................................ ................................ ................................ ................. 49 2 14 Correlation of kidney mass with standing height for the UFHADM patient dependent series ................................ ................................ ................................ ................................ .. 49 3 1 Patient standing height versus weight shown for patient dependent and patient specific mal e phantoms ................................ ................................ ................................ ...... 68
10 3 2 Patient standing height versus weight shown for patient dependent and p atient specific female phantoms ................................ ................................ ................................ ... 68 3 3 Phantom modification and patient phantom matching techniques ................................ .... 69 3 4 Patient phantom matching by height and weight where the closest patient dependent phantom is shown for three different adult male patients ................................ .................. 69 3 5 Improved accuracy wi th increasing kVp ................................ ................................ ........... 70 3 6 Improved accuracy for heavy patients, but no improvement for light patients ................. 70 3 7 Improved acc uracy for heavy patients, but no improvement for light patients ................. 71 3 8 Percent difference for each of the five heavy male patients as matched to a reference hybrid phantom, matched by height to a patient dependent phantom, and matched by height and weight to a patient dependent phantom ................................ ........................... 72 3 9 Four different anthropometric matching techniques: by reference, by height, by height and weight, and by the patient specific contour ................................ ..................... 72 3 10 Improved accuracy with increasing field of view, shown as the average of all and prima ry organs for two male patients ................................ ................................ ................ 73 4 1 Methodology for dete rmining in field skin locations ................................ ........................ 90 4 2 Skin dose comparison between a real patient and anthropome trically matched hybrid patient depend ent phantom ................................ ................................ ................................ 91 4 3 Relative skin dose maps as calcu lated for 7 real patient exams ................................ ........ 92 4 4 Reference point air kerma calibration using i on chamber and radiopaque scale ............... 93 4 5 Prototype display of cl inical skin dose mapping system ................................ ................... 94 4 6 Prototype display of dose map o n the Siemens Artis Zee console ................................ .... 94 5 1 Six measurements used to create patient sculpted contour phantoms. ............................ 109 5 2 Peak skin dose calculated for a reference stylized, reference hybrid, patient dependent hybrid, and patient sculpted contour phantom ................................ ............... 109 6 1 Cyberwar e Whole Body Color 3D Scanner ................................ ................................ ..... 120
11 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 ASSESSING PATIENT DOSE IN INTERVENTIONAL FLUO ROSCOPY USING PATIENT DEPENDENT HYBRID PHANTOMS By Perry Barnett Johnson August 2011 Chair: Wesley Bolch Major: Biomedical Engineering Interventional fluoroscopy uses ionizing radiation to guide small instruments through blood vessels or other body pathways to sites of clinical interest The technique represents a tremendous advantage over invasive surgical procedures, as it requires only a small incision, thus reducing the risk of infection and providi ng for shorter recovery times The growing use and increasing complexity of interventional procedures, however, has resulted in public health concerns regarding radiation exposures, particularly with respect to localized skin dose Tracking and documenting patient specific skin and internal organ dose has been specifically identified for interventional fluoroscopy where extended irradiation times, multiple projections, and repeat procedures can lead to some of the largest doses encountered in radiology. Fur thermore, in procedure knowledge of localized skin doses can be of significant clinical importance to managing patient risk and in training radiology residents. In this dissertation a framework is presented for monitoring the radiation dose delivered to patients undergoing interventional procedures. The framework is built around two key points, developing better anthropomorphic models, and designing clinically relevant software syst ems for dose estimation. To begin, a library of 50 hybrid patient dependent computational phantoms was developed based on the UF hybrid male and female reference phantoms. These phantoms
12 represent a different type of anthropomorphic model whereby anthropom etric parameters from an individual patient are used during phantom selection. The patient dependent library was first validated and then used in two patient phantom matching studies focused on cumulative organ and local skin dose. In terms of organ dose, patient phantom matching was shown most beneficial for estimating the dose to large patients where error associated with soft tissue attenuation differences could be minimized. For small patients, inherent difference in organ size and location limited the effectiveness of matching. For skin dose, patient phantom matching was found most beneficial for estimating the dose during lateral and anterior posterior projections. Patient ng skin dose estimation and highlighted as a substantial step towards better patient specificity. In order to utilize the models for actual patient dosimetry, two programs were developed based on the newly released Radiation Dose Structured Report (RDSR). The first program allows for the visualization of skin dose by translating the reference point air kerma to the location of el. The program represents an innovative tool that can be used by the interve ntional physician to modify behavior when clinically appropriate. The second program operates by automatically generating an input file from the RDSR which can then be run within a Monte Carlo based radiation transport code. The program has great potential specific radiation transport is performed off site and returned via the internet. Both programs are non proprietary and transferable, and also incorporate the most advanced compu tational phantoms developed to date. Using the tools developed in this work there exist a tangible opportunity to improve patient care with the end goal being a better understanding of the risk/benefit relationship that accompanies the medical use of ionizing radiation.
13 CHAPTER 1 INTRODUCTION Interv entional Fluoroscopy Interventional fluoroscopic procedures are an alternative to invasive surgery whereby ionizing radiation is used to provide image guidance for catheters and other small instruments as they are moved through blood vessels and other body pathways to sites of surgical interest. This sub speci alty of radiology was pioneered in the 1960 s and 1970 s by Dr. Charles Dotter of the University of Oregon in Portland and expanded throughout the lat t e r part of the 20 th century to include a variety of procedures performed by a number of different specialist s including radiologist s cardiologist s and neurologist s  Interventional technique s represent a tremendous advantage over inv asive surgical procedures, as they require only a small incision, thus reducing the risk of infection and providing for shorter recovery times in comparison to surgical alternatives. Th e growing use and increasing complexity of interventional fluoroscopic procedures, however, has resulted in public health concerns regarding radiation exposures, particularly with respect to localized skin dose High Dose Procedures and the Need for Compre hensive Dosimetry In March of 2009 estimates from the National Council on Radiation Protection and Measurements (NCRP) review on medical radiation exposure in the United States were released. The results tabulated from 1980 to 2006 show a significant incr ease of 600% in the per capita effective dose incurred primarily from increased use of diagnostic medical radiation  This dramatic increase has prompted strong recommendations by the scientific and medical community to encourage patient specific tracking of medical exposures and resulting radiation doses [3 8] The tracking of skin and organ dose has been specifically identified for interventional fluoroscopy where extended irradiation, multiple projections, and repeat
14 procedures can lead to some of the largest doses encountered in radiology [9, 10] The National Academy of Sciences BEIR VII Committee compiled a report in 2006 which highlighted many of the dose ranges encountered in diagnostic imaging Effective dose s for f luoroscopically guided interventions (FGIs) range from 10 300 mSv, which put s them well above doses seen in conventional x ray (0.02 10 mSv), CT (5 20 mSv), and nuclear medicine exams (3 14 mSv)  According to currently accepted risk models, these doses put patients at an increased risk for radiation induced cancers. More importantly, the likelihood of encountering levels of radiation high enough to cause deterministic effects i s increased due to prolonged irradiation of localized areas of the skin Radiation induced skin injury is a primary concern for many inte rventional procedures as skin dose s in FGIs can exceed levels received dur ing cancer radiotherapy [5, 11] Considerable effort has been devoted toward the prevention of radiation induced injuries through intensive training of radiology residents, the development of dose reducing sy stems, and an overall increase in awareness However, as noted in one well interventional procedures) can result in clinically significant radiation dose to the patient, even when performed by trained operators with use of dose reducing technology and modern fluoroscopic equipment  Additionally, The Joint Commission has specifically identified skin burns caused by prolonged fluoroscopy greater that 15 Gy as one of 10 sentinel events requiring root cause analysis and a comprehensive response  Currently, a large burden is placed on radiology staffing to reconstruct skin dose when a sentinel event is thought to have occur red. In effect, medical physicists must play the role of detective by interviewing physicians to determine details from an individual examination and then try to piece together limited information found in the [13, 14] A fast, automated reporting of skin dose would
15 reduce this burden and allow radiology departments a better way to identify and assess sentinel events  This information could then be used to optimize high dose proc edures, train radiology residents on dose reducing techniques, and set better diagnostic reference levels. More importantly, real time reporting of localized skin dose would provide a useful alert to the physician as to when dose thresholds are being appr oached so that potential alternative fields or exam techniques may be applied. Following concerns of deterministic effects are those associated w ith long term stochastic risk of cancer initiation and promotion Proper documentation of internal organ doses to FGI patients are highly relevant to their inclusion in epidemiological studies aim ed at supplementing the Life Span Study (LSS) cohort of survivors of the atomic bombings. A strong emphasis has been placed on interventional fluoroscopy by the BEIR VII Committee for its role in providing epidemiological data for patients who receive high to moderate medical exposures. Noted in the procedures in the heart, lungs, abd omen, and many vascular beds, with extended fluoroscopic exposure time of patients and operators, emphasize the need for recording dose and later follow up studies of potential radiation effects among these populations  work detailed in this dissertation is designed to provide the technological basis for these types of scientific research needs while at the same time maintaining a clinically relevant focus. Available Options for Patient Dosimetry As noted in the previous section, patients undergoing FGI procedures incur an increased risk for developing both stochastic and deterministic effects. In each case the interest is in estimating the radiation dose most closely associated with each effect, namely cumulative organ dose and local skin dose. Several dose metrics are available to clinicians and have been used in the past to indirectly quantify these values. The simplest of these is fluoroscopy time which is
16 displayed within the fluoroscopy suite and monitored by an audible alarm. The alarm sounds at th e end of each 5 minute interval and is used to discourage the excessive use of radiation. Fluoroscopy time may be helpful in certain situations to identify unusual exposures, but it is an unreliable estimator of patient risk due to the fact that it include s no information about the dose rate or intensity of the beam. An improvement over fluoroscopy time is the dose area product (DAP) which is defined as the dose at a point multiplied by the area of the beam at that point. Dose area product is measured by a flat ion chamber located in the head of the fluoroscopy unit which can be installed with the machine or added later as an aftermarket purchase. The measurement of DAP provides a quantification for the total amount of energy delivered to a patient. Alone this value can only be used comparatively, but when paired with a Monte Carlo based dose conversion coefficient (DCC), DAP becomes a very useful metric for the evaluation of stochastic risk. Dose conversion coefficients are the most common method for estim ating this type of risk and relate organ absorbed dose for frequently encountered patient/irradiation geometries to a clinically measureable indicator quantity. An example would be organ absorbed dose per unit DAP for a posterior anterior DSA run. One uniq ue benefit of DCCs is that they can be pre calculated for a variety of exam parameters. This means that if a system can be arranged to automatically select the proper DCC using current information extracted from the fluoroscopy unit, organ dose can be esti mated in real time. While DAP provides a useful metric for estimating organ dose, the reference point air kerma (K a,r ), also known as the cumulative dose, provides a useful metric for estimating skin dose. The reference point air kerma was first proposed in 2000 by the International Electrotechnical Commission (IEC)  and later adopted as a regulation in 2005 by the U.S.
17 Food and Drug Administration (FDA)  The intent was to provide a better way to estimate air kerma at the location of the from the isocenter (x ray tube side) along the central axis of the C arm. The air kerma at this location can be provided in a number of ways depending on the vendor. Some manufacturers provide the reference point air kerma using internal look up tables based on exposure parameters. If the fluoroscope is equipped with a DAP meter, the reference point air kerma is sometimes measured directly by dividing out the field size at the reference location. A third method employs two DAP meters in the head of the machine to determine a central axis dose which is then projected to the reference location. Regardless of the method used, the result is an estimation of the air kerma at a point 15 cm from the isocenter which moves with the gantry and traces the contour of a cylindrical phantom having a diameter of 30 cm. Due to the fact that this contour will differ from that of a real patient, K a,r itself does not provide enough information to determine skin dose. What is co nvenient about this metric is that given proper geometrical information, it provides a free in air estimation of kerma which can be translated to the actual over distance squared correction. When multiplied by a b ackscatter factor and the ratio of the mass energy absorption coefficients of tissue to air, this value becomes the entrance surface dose a lso known as the peak skin dose (PSD) The relation between K a,r and PSD forms the basis for skin dose mapping where by the local skin dose is mapping can be implemented in real time if current exposure and geometric parameters are available. While the methods described previou sly for estimating organ and skin dose appear simple in theory, there are significant scientific and technical challenges posed by 1) the anatomical and
18 anthropometric diversity of a patient population, and 2) the dynamic nature of interventional procedure s and subsequent monitoring of relevant examination parameters These challenges have so far limited the widespread inclusion of dosimetric information in the patient record and must be overcome before patient dose tracking can become a reality. Diverse Anthropomorphic M odels In order to calculate organ and skin dose f or interventional patients, DCC and dose mapping methods rely on computational representations of the human body. Currently, three types of computational phantoms exist for these purposes: ( 1) stylized phantoms, where organs are re presented by geometric shapes; (2) tomographic phantoms, where organs are delineated by groups of voxels segmen ted from CT or MR patient scans; and (3) animation or hybrid based phantoms where organs are originally described using imaging data but subsequently defined by a combination of stylized structures and deformable surfaces. Multiple DCC studies have been performed using the former type with the two most significant studies being those published by the U.S. Fo od and Drug Administration  and the British National Radiological Protection Board  Dose conversion coefficients based on tomogra phic models represent a more recent development with extensive publications appearing in the literature within only the last few years [20 23] Two skin dose mapping systems have been produced; both systems utilize mathematically based stylized models [24, 25] Computa tional phantoms can be further c lassified into three categories: (1) reference, (2) patient specific, and (3) patient dependent models. Reference models are an example of designing for the average, where the phantom is created using 50 th percentile values for relevant parameters such as patient height, weight, and organ mass. Reference models have been developed utilizing all three phantom types and a variety of different reference databases [26 28] In the past, these models have often represented the best available option for patient
19 dosimetry due to the limited number of anthropomorphic phantoms and a desire to standardize a model for the representation of large populations. While providing a certain level of practicality for such appl ications, reference models have significant drawbacks for the dosimetry of individual patients because they lack patient specificity. In reality, the characteristics of most patients will deviate from 50 th percentile values, and by ignoring anatomic and an thropometric variability, the usefulness of reference phantoms for individual patient dose assessment is diminished. While reference models represent the bottom of a continuum of anatomic specificity, patient specific models represent the very top. Unmodi fied tomographic phantoms are the only type of patient specific model currently available and can be considered a computational replica of the person who provided the imaging data. Patient specific models play an important role as a benchmark for radiation dosimetry studies, and have been used by multiple researchers to demonstrate the benefits of anatomically correct tomographic phantoms over more general stylized versions [20, 23, 29] Al though patient consuming process, along with the fac t that high resolution images are not always available, means that patient specific models cannot be created for every patient. This limitation presents a problem for medical dosimetry, because while patient specific models represent a high level of specif icity, they represent it only for patient s with attributes similar to those found in the original images. In this sense, these models may be considered too specific to accurately represent any single individual selected from a diverse population. The fina l category of computational phantoms includes those deemed patient dependent. Patient dependent models are designed based on an adjustable range and developed by
20 mod els represent the best choice for prospective medical dosimetry because they balance the needs of practicality with those of specificity. Patient dependent models are an off the shelf solution and can thus be used to pre calculate organ dose and provide co ntours for skin dose mapping At the same time, patient dependent models build in specificity by relying on anthropometric parameters of individual patients. Because patient dependent models require extensive remodeling, the flexibility of the anchor phant om is very important. Stylized phantoms have always offered the ability to modify posture, reposition organs, and scale to different body sizes, and have thus been used extensively in programs such as Body Builder (White Rock Science, Los Alamos, NM) and P CXMC (STUK Radiation and Nuclear Science Authority, Helsinki, Finland) to create patient dependent models. Stylized phantoms, however, also depend upon a simplified description of patient anatomy which limits the accuracy of any dose estimate. Conversely tomographic phantoms provide a highly accurate depiction of patient anatomy but are bound by a rigid voxel structure. Because of this, patient dependent tomographic phantoms are virtually nonexistent and have been limited to a few studies which alter vox el size in different dimensions in order to scale to various patient sizes [30 32] Hybrid phantoms represent the newest generation of animation based computational anthropomorphic phan toms and were developed out of a need for models that combine the anatomically accuracy of tomographic phantoms with the flexibility of stylized phantoms. Hybrid phantoms, as developed by the Advanced Laboratory for Radiation Dosimetry Studies (ALRADS) at the University of Florida, utilized non uniform rational B spline (NURBS) surface modeling to d escribe organ/tissue boundaries [33, 34] This type of modeling relies on the
21 manipulation of surface control points and thus allows for the preservation of anatomical realism while at the same time achieving a level of anthropometric remodeling not previously available. In this dissertation the concept of a NURBS based hybrid phantom was used to develop a comprehensive library of patient depende nt phantoms. These phantoms wer e utilized to produce better DCCs and more specific patient contour s for skin dose mapping. Automatic Monitoring of Exposure Parameters The application of phantom patient matching through the use of patient dependent hybrid phantoms provides one solution for a two part problem. The second challenge that must be overcome is the dynamic nature of interventional procedures. Due to the fact that DCCs are simulation based quantities, they are only applicable under irradiation conditions comparable to those that were simulated. Included in these conditions are exposure parameters (kVp, mAs, filtration, and DAP/Ka,r) and geometry factors (source to skin distance, field size, field position, rotation, angulation, table location, etc.). Skin dose mapping also requir es many of the same parameters, specifically the source to skin distance and the Ka,r. The difficulty in fluoroscopy is that the irradiation conditions are not typically standardized, as in CT, and change often. For dosimetry performed retrospectively, it is then important to know how these parameters changed throughout the procedure and when. For prospective, or real time, dosimetry, the situation becomes more complicated as DCCs must be pre calculated assuming certain conditions and then matched based upo n what actually occurred. In both cases, there is the principal need for a system that monitors the irradiation conditions and produces an automated report, preferably in real time. There are three basic approaches for automated monitoring of exam paramet ers. The first is to extract information directly from the fluoroscopy unit. Direct extraction is fast, efficient, and reliable. It can, however, be difficult to access the needed information due to a lack of an
22 accessible output or knowledge of how the pa rameters are stored within the machine. A number of studies have attempted to tap into the state of the fluoroscopy system by utilizing certain analogue outputs [35 37] In each case, a complex system involving signal conversion, processing, a nd analysis was used to derive the irradiation conditions as a function of time. This information was then used for a variety of applications including the determination of organ dose through the use of DCCs. The monitoring systems developed in these studi es represent a high level approach, but one that is difficult to implement for non research oriented hospitals. On a commercial level, two direct monitoring systems have been developed which offer customized solutions. The first commercial system, the Pati ent Exposure Management Networks (PEMNET; Clinical Microsystems, Arlington, VA), was designed in the mid few institutions, one of which was the University of Florida. Researchers at UF published two papers describing the syst em and its use for monitoring patient skin dose in interventional fluoroscopy [38, 39] In the papers, PEMNET is described as being passively hardwired to the x ray generator which then passed information to a micro processor syst em running on board software. In part due to the complex nature of the system, including installation, calibration, and maintenance, the PEMNET system never gained widespread use [40, 41] The second commercial system used for automated parameter extraction was developed originally in 2003 by den Boer et al.  and subsequently marketed by Siemens Medical Solutions (Munich, on commercial system was geared mainly toward skin dose and utilized real time monitoring of the irradiation conditions in coordination with mathematical models to provide dose estimates. Unfortunately the system was not popular with consu mers and was subsequently discontinued  The failure of the PEMNET and CareGraph systems
23 highlight the need for a simplified solution, and one that can be installed easily across sever al platforms and institutions. Along these lines, the second basic approach for automatic monitoring of exam parameters is to extract the information indirectly from the control room monitors. This can be achieved either through the use of an external fra me grabber, or as seen in a number of studies, through the use of a CCD video camera [43 45] Such a method has the benefits of being completely external, and hence, transferrable across device makes and models. In order to automate the extraction, some form of optical character recognition (OCR) must be used to identi fy the on screen alphanumeric characters. This type of automation has not yet been attempted within the realm of medical dosimetry, but co uld be implemented so long as the proper information is displayed on the control room monitor. All modern systems disp lay a minimal amount of information on screen including kVp, mAs, rotation, angulation, and table height. Additionally, many systems also display detailed table and tube location, field of view, and some form of dose monitoring. Much of this information is dependent on th e manufacturer, however, and enough information needed for a full dose reconstruction is typically not available. The final approach for extracting pertinent information from an interventional exam is to use information found within the im ages themselves. The Digital Imaging and Communications in Medicine (DICOM) is a standard for handling, storing, printing, and transmitting information in medical imaging. Within the DICOM standard are fields for a large variety of information including de tails about the patient, image, equipment, and exposure conditions. This information, referred to as the DICOM header, can be integrated easily within a dosimetry system if these fields are filled and can be accessed. In the past, there has been large vari ation between manufactures as to which parameters are available. One study which evaluated the DICOM
24 headers by the different manufacturers differs substantiall center recorded enough information to retrospectively calculate dos e  A newer report containe d in private tags. The format and meaning of these fields is not easily available and not well defined in the DICOM conformance statement documents  In response to the pressing need for standardization, Th e DICOM Committee published Supplement 94 to the DICOM standard  This u pdate provided a framework for dose reporting by creating the Radiation Dose Structured Report (RDSR). The RDSR was built as an independent DICOM object. It can be managed like other DICOM objects and is both flexible and robust. The RDSR is comprised prim arily of irradiation events which are created every time the clinician depressed the foot pedal. A coordinated effort has been made between DICOM and the IEC to standardize what parameters are documented during each event, and in 2007, the IEC published th e Publicly Available Specification (PAS) 61910 1  This document outlines an extensive set of required parameters and defines several layers of conformance for past, current, and future machines. Implementation of the RDSR across multiple vendors has been managed according to the Integrating the Healthcare Enterprise (IHE) Integration Profi le for Radiation Exposure Monitoring  Following the initial release in 2009, several institutions have su ccessfully installed RDSR compatible units, including a Siemens Artis Zee system at Shands Jacksonville Medical Center While the use of hybrid patie nt dependent phantoms will be shown to improve the accuracy of current dosimetry methods, the development o f the RDSR will make them practical
25 for the clinic. Both aspects represent state of the art technology and form ed the basis for this dissertation Objectives of this Research The overall goal of this research was to develop advanced methods for in cl inic estimation of skin and organ dose during high risk FGI procedures. In order to a chieve this goal, it was hypothesized that patient dependent dose coefficients calculated using NURBS based hybrid computational phantoms would significantly increase the accuracy and scope of current dose coefficient libraries Additionally, when paired with automated extraction of exam parameters from the fluoroscopy unit, patient dependent phantoms would provide a feasible solution for real time skin dose mapping and pos t procedure organ and effective dose estimation. In order to effectively evaluate this hypothesis, the following specific aims were identified. The first aim was to d evelop methods for anthropometric re modeling of the UF adult male and adult female refer ence hybrid phantoms to construct a library of 25 male and 25 female patient dependent hybrid phantoms. The library was based on anthropometric data of the U.S. adult population as determined from the NHANES III database provided by the National Center for Health Statistics. In order to investigate the usefulness of the patient dependent libraries, the second aim was to develop patient phantom matching techniques for patient dependent hybrid phantoms and validate against patient specific models. Patients were matched to a pre configured patient dependent phantom based on standing height and total body mass. Validation was performed using st andard fluoroscopy fields and 27 (14 male/ 13 female) pati ent specific phantoms created from CT chest abdome n pelvis (CAP) image segmentation. The third research aim was to i nvestigate data acquisition and develop software for performing dose assessment of regional skin dose and cumulative organ dose. Several o ptions for data acquisition were explored including optical character recognition and direct extraction using internal log files. T he DICOM Radia tion Dose Structured Report was also investigated as the primary candidate for parameter extraction. A system which reads an RDSR and couples the patient/tube geom etry with reference point air kerma was developed. The RDSR was also utilized to produce custom MCNPX input files. The final aim was to a nalyze the skin dose mapping system for sensitivity to patient localization and body morphometry. This was done by comp aring patient specific phantoms created from CT image segmentation and phantoms selected from the patient
26 dependent libraries dev eloped in A im 1. Information from real patient examinations as recorded in RDS R and internal log files were used to perform simulations. Each aim corresponds to an individual research project. The projects are subsequently formatted as separate chapters in this dissertation. The overall impact of this work and its significance for medical dose reconstruction is then discu ssed in the final chapter.
27 CHAPTER 2 CONSTRUCTION OF A PA TIENT DEPENDENT PHANTOM LI BRARY Background Since first being used in 1999 as a developmental tool for the NCAT heart phantom  computer animation software has become the standard for creating the next generation of anthropomorphic computational phantoms. Programs such as Rhinoceros (McNeel North America, Seattle, WA), 3D Doctor (Able Software Corp., Lexington, MA), Blender  Aut odesk Maya (Autodesk, Toronto, Canada), and Makehuman  have all been used to create a variety of NURBS and mesh based models of human anatomy for radiation dose assessment [34, 54, 55] These models share the advantages of animation software including the ability to modify po sture, organ size, organ location, and total body shape, while at the same time maintaining anatomical accuracy. This wide ranging adaptability provides a means to more accurately represent individual patients, a major shift from previous convention which relied heavily on standardized reference phantoms and their efficacy for dosimetry across large patient populations. Animation based phantoms allow for increased patient specificity through the developm ent of patient dependent models As discussed in the previous chapter patient dependent models are created by in order to match t arget anthropometric parameters. This enables two unique benefits. First, patient specific information is included directly in the dose estimate. Second, because patient dependent models are pre configured, skin and organ dose can be assessed prospectively. These benefits represent significant advantages over patient specific and reference phantoms where the former are impract ical for the clinic, and the latter may be too general for medical dose reconstruction.
28 In this chapter a methodology is presented which utilizes hybrid phantoms to construct a broad library of patient dependent phantoms The methodology follows a general format whereby a population is first parameterized in terms of target anthropometric measurements, and anchor phantoms are remodeled accordingly The methodology is further implemented for the construction of two representative libraries covering the anth ropometric distributions of a U.S. adult male a nd female population. Methods and Materials NHANES III Database The National Health and Nutrition Examination Surveys (NHANES) is a survey research program conducted by the National Center for Health Statistic s of the Centers for Disease Control and Prevention (CDC). The NHANES III (1988 1994) examination data file is available on the CDC website (http://www.cdc.gov/nchs/nhanes.htm) and contains data for 33,994 individuals (ages 2 months 90 years) who partic ipated in the survey. This database was chosen over a more recent NHANES survey (2005 2006) as it contained more individuals and parameters such as age, gender, and sitting height which are absent in updated survey s In order to create patient dependent ph antoms specific to a U.S. adult population, the NHANES III database was used to provide tar get anthropometric parameters. The information retrieved from the database included primary parameters such as standing height, sitting height, and total body mass, secondary parameters such as waist, buttocks, arm, and thigh circumference, and tertiary parameters such as triceps, subscapular, and s uprailiac skinfold thicknesses. Age and gender were also retrieved and used to split the database into two groups, adul t male (7,002 patients) and adult female (7,775 patients). The adult subjects ranged from age 18 to 90 years These datasets were used independently to describe their respective populations according to the following methodologies.
29 Anthropometric Targets A patient dependent phantom library may be potentially based on any number of anthropometric measurements. However, consideration must be given to both the size of the original database and also which measurements can be most easily manipulated within the starting anchor phantoms The U.S. adult population was parameterized by selecting standing height as a first scaling parameter. Standing height represents a good starting point for phantom remodeling because it is a convenient and familiar anthropometric measurement and can be altered readily Another benefit to using standing height is that it takes into account overall body size, and when fixed, limits variability in both leg length and sitting height. In analyzing the adult databases, standing height wa s shown t o follow a normal distribution. It also showed correlation with both sitting height and total body mass (r 2 = 0.24 and 0.21 respectively for both the adult male and female databases). In order to determine target standing heights, a histogram was created from the standing height distributi on of the each adult database. A Gaussian fit was then used to determine 10 th 25 th 50 th 75 th and 90 th percentile target values for both mal es and female s. A cut was then made based upon these values using a to lerance of 1 cm. Approximately 600 patients were left within each standing height bin. The adult population was further parameterized accordin g to total body mass. Similar to standing height, total body mass characterizes the size of a patient and als o represents a general indicator of subcutaneous fat. In order to determine target values, histograms for each standing height bin were generated The weight distributions showed a slight positive skew for 10 th and 25 th percentile standing heights and even ed out as the height percentile increased. A combination of Gaussian and polynomial fits were used in coordination with numerical integration to determine 10 th 25 th 50 th 75 th and 90 th percentile weights. Each adult database was culled once more using a tolerance of 0.5 kg leaving 50 unique datasets each including roughly 25 45 adult
30 patients. Due to the limited number of patients remaining within each sub grouping, the data was not split further, and secondary anthropometric parameters for each standi ng height/total body mass combination were selected based upon the average individual f ound within each sub grouping. Tertiary parameters, such as skin fold thickness, were not included as these data did not translate w ell to computational phantoms. A list of the final anthropometric target parameters can be seen in Tabl e 2 1 for adult males and Table 2 2 for adult females. Anchor Phantoms The UF family of adult hybrid computational phantoms includes models for the adult male, adult female, and a variety of differe nt pediatric ages and genders. From this family, the UF hybrid adult male (UFHADM) and female (UFHAD F) were chosen as representative anchor phantoms fo r this study  In order to create a patient dependent adult male series, the UFHADM was modified according to the target parameters defined in T able 2 1 For the UFHAD F, target par ameters were chosen from Table 2 2 The torso of the UFHADM was created based on CT imag ing data ( 1.97 x 1.97 x 3 mm 3 ) collected from a 36 year Korean male volunteer The torso of the UFHAD F was created using CT imaging data (0.66 x 0.66 x 5 mm 3 ) collected from a 25 year female volunteer. The a rms, legs and head of the UFHADM and UFHAD F were segmented from high resolution CT sca ns of an 18 year male and 15 year female cadaver, respectively The arm and leg bones in the CT images were segmented and attached to the to rso at the NURBS modeling stage after careful scaling. NURBS surfaces were use d to describe the outer body contour and the boun daries of most internal organs. A limited number of structures, including the skeleton, brain, cartilage, and extrathoracic airways were difficult to model as NURBS surfaces and thus a variety of formats wer e used to describe them including polyg on meshes and stylized objects. Once the initial modeling was completed, the organ sizes were adjusted to match reference masses given in ICRP
31 Publication 89  The outer body contours were also modified to match ICRP 89 reference parameters includ ing standing height (176 an d 163 cm, respectively ) and total body mass (73 and 59 kg, respectively). Skin was not included during the initial modeling process but was left to be added during voxelization. These hybrid reference phantoms provided an important link to a robust set of reference organ masses and represent the starting point for further anthropometric modeling. Phantom Remodeling Both the UFHADM and UFHADF anchor phantoms were modified acco rding to the same methodology. To begin, average sitting height and leg length values were determined for each standing height bin. It was important to fix these parameters in order to maintain uniformity between phantoms of a certain standing height which increased the efficiency of the scaling method. The targeted sitting height wa s matched by uni formly scaling in 3D the head, arms and torso (including the regional skeleton and all internal organs) within Rhinoceros TM with the base of the ischium acting as the origin. With sitting height set, leg length was adjusted next to achieve the appropriate target standing height. The next step in phantom modification was to match secondary anthropometric parameters including waist, buttocks, arm, and thigh circumference. For the 50 th 75 th and 90 th weight percentile phantoms, this wa s achieved by altering control points of the outer body contour, simulating a change in subcutaneous fat thick ness and its body distribution. For the 10 th and 25 th weight percentile phantoms, the targeted waist circumference was found to be smaller than al lowed b y the existing skeletal model. In order to accommodate the reduced waist circumference, the phantom was scaled slightly inward in 2D. This method of scaling for underweight and overweight phantoms was developed empirically but mimics methods used pr eviously in a phantom study based on statistical studies
32 of the Finnish clothing industry  After scaling the phantom in 2D, secondary parameters were matc hed by fine tuning control points of the outer body contour. The final step of phantom construction was to match the target weight percentiles. This process involved iteration between evaluating the total body mass and adjusting the outer body contour. The total organ mass of the phantom was determined within Rhinoceros TM by taking the product of the organ/tissue volumes and their corresponding reference densities as defined in ICRU Report 46  The residual soft tissue mass was determined by subtracting the total organ volume from the total phantom volume and multi plying by the refe rence density for soft tissue. Total body mass was calculated as the sum of the total organ an d residual soft tissue masses. With this parameter evaluated, any difference between the phantom and target mass was accounted for by adjusting control points in areas not constrained by secondary parameters, typically within the upper torso. The time required to modify a single anchor phantom into a patient dependent model was roughly 30 50 minutes and decreased with modeling experience. Result s Example images of the patient dependent adult male and female series are shown in Figures 2 1 2 2, 2 3 and 2 4. Figure s 2 1 and 2 2 represents all phantoms created at the 50th percentile standing height, while figures 2 3 and 2 4 represents all phantoms create d at a 50th percentile weight. The naming of the adult series follows a moniker whereby the anchor phantom is subscripted first by standing height percentile, a nd second by weight percentile. Selected organ masses from the UF HADM series are displayed in Table 2 3 alon g with ICRP 89 reference values. Due to the fact that organ sizes remained the same for overweight phantoms at each respective standing height, these values were not included. As seen in Table 2 3 organ masses fo r the UFHADM 50 50 closely resemble those of the ICRP 89 compliant adult hybrid. Organ
33 masses moved away from these values as both standing height and weight were altered with the relative variation in individual organ mass remaining constant between diffe rent phantoms. Discussion The patient dependent phantoms created in this study represent a first attempt at comprehensive anthropometric modeling for rea listic computational phantoms. As such, the phantoms were evaluated based on both their appearance and description of internal organ mass. From visual inspection of Figures 2 1 through 2 4 the dimensions of the patient dependent phantoms appear appropriate. Arm length extends to mid thigh, the head and body size maintain the generally accepted ratio of 1 :8, and the church pew effect 1 can be witnessed as the variation in leg length is more pronounced than the corresponding variation in sitting height. While the method for adding subcutaneous fat is admittedly somewhat discretionary, by fixing secondary par ameters, definite constraints are built into the process which helps limit unrealistic body contour modeling. Consequently, the phantom subcutaneous fat distribution also appears appropriate and within reasonable expectations. In order to evaluate the ac curacy of the scaled organ masses, a comparison was made with a recently published French based autopsy study  This study represents one of the few available surveys presenting o rgan mass data in combination with anthropometric measurements. In the autopsy study, adult cadavers were assembled into three subgroups defined so as to provide sufficient data points to ensure statistical significance. Within each subgroup, the average and standard deviation for standing height, total body mass, a nd organ mass were determined. Using this data, organ mass was correlated with both standing hei ght and body mass 1 Observation that variations in individual heights of a congregation are noticeably greater during standing versus seated portions of the church service.
34 index (BMI). In order to make a comparison, similar correlations were cal culated for the UFHADM series. Figures 2 5 through 2 9 display liver, spleen, thyroid, pancreas, and kidney mass as correlated with BMI. The statistical parameters presented in the autopsy study are also displayed f or each of the three subgroups. While heart and lung masses were also available in the autopsy study, they were not included in the comparison due to uncertainties in how their volumes were assessed. As seen in the figures, the data are grouped vertically a ccording to weight percentile. The variance in each grouping represents a spreading of organ mass at different standing heights and is noticeably less than what is observed in the autopsy data. One inference that can be drawn from this reduction is that while anthropometric variation c an be largely parameterized, there will always be significant variation in the size of individual organs (i.e., patients with similar body sizes will never have exactly the same organ mass) While NURBS surfaces offer the possibility to modify individual o rgan boundaries, the prospect of creating patient dependent phantoms with various combinations of organ size represents an overly extensive task, and one which would require a comprehensive organ mass/anthropometric database w hich does not currently exist. Furthermore, without patient specific imaging, the only indication of internal organ size is through anthropometric measurement. It would thus be difficult to match patients with individually ta rgeted organ mass percentiles. Patient dependent phantoms rep resent a compromise between specificity and practicality, and thus as long as the scaled organ masses fall within reasonable bounds, they may be considered useful for medical dosimetry purposes, either retrospective or prospective in nature. More evidence for the usefulness of these phantoms is seen in Figures 2 5 through 2 9 as the UFHADM organ masses follow similar trends as re presented in the autopsy data. In all cases,
35 increasing BMI leads to a gradu al increase in the organ mass. There is, however, a s hift in the UFHADM data towards larger body mass indexes along this axi s. This can be explained by noting that while the average height recorded in both French based autopsy study (172 cm) and this U.S. based phantom study (173.2 cm) was similar, the avera ge weight was found to be 12 kg larger in the U.S. population (68 kg compa red to 80 kg). This shift results in organ masses that appear slightly lower than expected according to the autopsy data. In order to evaluate this trend further, the selected organ masses were correlated w ith standing height. Figures 2 10 through 2 14 display these correlations along with the statistical parameters p resented in the autopsy study. As seen in these figures, the shift has been lessened and the 50 th percentile organ ma sses trend better with the autopsy study. This comparison highlights the differences in the anthropometric parameters of various human populations and how these differences may potentially af fect phantom patient matching. One organ that showed discrepancy with the general trend of increasing mass with increasing standing height was t he thyroid. In this case, the average thyroid mass from each sub group showed no increase. However, after reviewing the autopsy study further where a weak correlation was liste d for thyroid mass and standing height (r 2 = 0.26), it appears that the di screpancy seen in the Figure 2 12 is due to a combination of the way the data is presented and the large variation within each sub group. Also noteworthy in Figures 2 10 through 2 14 is the vertical trend between the organ masses of e ach height percentile grouping. Due to the fact that the 75 th and 90 th percentile weight phantoms have the same organ mass as their 50 th percentile counterpart, there are no points above the 50 th percenti le values. However, the variance seen in the autopsy correlations suggests organs with higher masses. As discussed previously, there is wide variability in the sizes of
36 individual organs. Accordingly, it is difficult to determine if the organs of overwei ght patie nts need to be scaled further. For future modeling, more complicated parameters such as biacromial and biiliac breadth can be retrieved from the NHANES III database and adde d as target measurements. These measurements will characterize ventral cav ity volume more completely and better determine the balance between torso volumetric scaling and the simple addition of subcutaneous fat. One notable omission in this study is the lack of in tra abdominal or visceral fat. This type of fat wa s not modeled for two reasons. First, intra abdominal fat is difficult to assess throu gh anthropometric measurement. In one study aimed at classifying obesity levels, sumo wrestlers were shown to have much lower visceral to fat ratios than similarly sized individuals  Also, increased levels of visceral fat can be found in relatively thin patients who live sedentary lifestyles. Second, without patient specific MRI imaging, there is no way of determining exactly the distribution of visceral fat betwe en organs. One solution which could be explored in the future would be to define levels of visceral fat based on a combination of factors including BMI, percent body fat, lifestyle, and certain disease factors such as Type 2 diabetes and heart disease. Layers of adipose tissue could then be added around abdominal organs in accordance with these levels. Such an approach would be most important for internal dosimetry where t he distance between organs is a major factor in determining cross organ photon dose. Summary A methodology has been presented for the construction of patient dependent phantoms built around the anthropometric distribution of a U.S. adult population. The me thodology relies on the flexibility of hybrid phantoms to match target anthropometric parameters as determined from the NHANES III database. Target parameters for the adult population were established based on standing height and weight percentiles. Target parameters for this study included the
37 primary parameters standing height, average sitting height, and total body mass, and the secondary parameters waist, arm, thigh, and buttocks circumference. Representative patient dependent phantoms for two tar get p opulations (adult male and female) were created by modifying the IC RP 89 compliant UFHADM and UFHAD F anchor phantoms Standing height was matched by first scaling sitting height, then leg length. In order to simulate different weight percentiles, the cont rol points of the outer body contour were manipulated within the boundaries se t by the secondary parameters. For underweight patients, 2D scaling was necessary in order match targeted waist circumferences. The resulting phantoms were evaluated based on app earance and internal organ mass. Aesthetically, the phantoms appeared correct and displayed characteristics of a diverse population including variability in s hape and the church pew effect. Organ masses for the UFHADM were presented and displayed several general trends including a gradual increase with bo th standing height and weight. Selected organ masses from the UFHADM series were also compared with published correlations taken from a French based autopsy study. The organ masses were located within the statistical deviation presented in the autopsy study and followed similar trends when correlated with both standing height and BMI. Lastly, recognition was made for the challenges presented by both intra organ variab ility and intra abdominal fat. While t hese realities introduce uncertainty during phantom patient matching, the methodology presented in this paper was designed out of need for phantoms that are both realistic and practical As such, the UFHADM and UFHADF series offer unique advantages for a w ide variety of medical applications where body size may have a large influence on patient dose and can be used in the future to help explore the benefit s of phantom patient matching.
38 Table 2 1. Anthropometric parameterization of the U.S. adult male population based on the NHANES III database.
39 Table 2 2. Anthropometric parameterization of the U.S. adult female population based on the NHANES III database.
40 Table 2 3. Organ masses selected from the UFHADM patient dependent series including the brain, thyroid, pancreas, heart wall, liver kidneys and spleen.
41 Figure 2 1. Frontal and lateral view s of patient dependent adult male phantoms at fiftieth percentile standing height and tenth, twenty fifth, fiftieth, seventy fifth and ninetieth percentile body mass.
42 Figure 2 2. Frontal and lateral views of patient dependent adult female phantoms at fiftieth percentile standing height and tenth, twenty fifth, fiftieth, seventy fifth, and ninetieth percentile body mass.
43 Figure 2 3. Frontal and lateral view s of patient dependent adult male phantoms at fift ieth percentile body mass and tenth, twenty fifth, fiftieth, seventy fifth, and n inetieth percentile standing height
44 Figure 2 4. Frontal and lateral view s of patie nt dependent adult fe male phantoms at fift ieth percentile body mass and tenth, twenty fifth, fiftieth, seventy fifth, and n inetieth percentile standing height
45 Figure 2 5. Correlation of liver mass with body mass index for the UFHADM patient dependent series. Statistical parameters as outlined in a French based autopsy study are also included. These parameters include average liver mass and standard deviation for three subgroups as defined by the adult male cadaver population. Figure 2 6. Correlation of spleen mass with body mass index for the UFHADM patient dependent series. Statistical parameters as outlined in a French based autopsy study are also included. These parameters include average spleen mass and standard deviation for th ree subgroups as defined by the adult male cadaver population.
46 Figure 2 7. Correlation of thyroid mass with body mass index for the UFHADM patient dependent series. Statistical parameters as outlined in a French based autopsy study are also included. Th ese parameters include average thyroid mass and standard deviation for three subgroups as defined by the adult male cadaver population. Figure 2 8. Correlation of pancreas mass with body mass index for the UFHADM patient dependent series. Statistical pa rameters as outlined in a French based autopsy study are also included. These parameters include average pancreas mass and standard deviation for three subgroups as defined by the adult male cadaver population.
47 Figure 2 9. Correlation of kidney mass wit h body mass index for the UFHADM patient dependent series. Statistical parameters as outlined in a French based autopsy study are also included. These parameters include average kidney mass and standard deviation for three subgroups as defined by the adult male cadaver population. Figure 2 10. Correlation of liver mass with standing height index for the UFHADM patient dependent series. Statistical parameters as outlined in a French based autopsy study are also included. These parameters include average liver mass and standard deviation for three subgroups as defined by the adult male cadaver population.
48 Figure 2 11. Correlation of sp leen mass with standing height for the UFHADM patient dependent series. Statistical parameters as outlined in a French based autopsy study are also included. These parameters include average spleen mass and standard deviation for three subgroups as defined by the adult male cadaver population. Figure 2 12. Correlation of thyroid mass with standing height for the UFHADM patient dependent series. Statistical parameters as outlined in a French based autopsy study are also included. These parameters include average thyroid mass and standard deviation for three subgroups as defined by the adult male cadaver population.
49 Figure 2 13. Correlation of pancreas mass with standing height for the UFHADM patient dependent series. Statistical parameters as outlined i n a French based autopsy study are also included. These parameters include average pancreas mass and standard deviation for three subgroups as defined by the adult male cadaver population. Figure 2 14. Correlation of kidney mass with standing height for the UFHADM patient dependent series. Statistical parameters as outlined in a French based autopsy study are also included. These parameters include average kidney mass and standard deviation for three subgroups as defined by the adult m ale cadaver population.
50 CHAPTER 3 IMPACT OF PATIENT PHANTOM MATCHING ON ORGAN DOSE Background In the previous chapter the concept of a patient dependent phantom was first introduced. This phantom cat egory consists of off the shelf models created through anthropometric re modeling of a reference phantom. The goal of modification is to create a library of phantoms representing a variety of different body shapes and contours as might be see n in a real patient population. Patient phant om matching is then defined as the selection of a patient dependent phantom or patient dependent dose metric based on anthropometric measur ement of an individual patient. The primary benefit is the balance between specificity and practicality Previously, tomographic based phantoms have provided high specificity, but as a tradeoff, require large sets of imaging data and time consuming segmentation. Conversely, reference ph antoms provide an off the shelf solution but ignore anatomic and anthropometric variab ility. By using patient phantom matching, patient information can be included in a near real time dose estimate, thus opening the possibility for individual dose tracking. While patient phantom matching represents an obvious extension for animation based p hantoms, the question remains as to whether or not anthropometric matching can actually improve dose estimates to individual patients. In previous studies, an increased body diameter, body mass index, and weight percentile were all shown to increase organ dose for a given image quality [31, 61, 62] These results suggest having a larger phantom to represent a larger patient would help mitigate dosimetric differences due to body morphometry. Beyond these studies, little work has bee n published comparing phantoms and patients of different sizes for projection based radiology (fluoroscopy and radiography).
51 Another important aspect of patient phantom matching independent of patient size is the inherent variability in organ size, shape, and location. Such variability introduces uncertainty into any dose estimate and it is important to consider when assessing the effectiveness of matching techniques. One notable study performed by Zankl et al.  provided an inter comparison between seven different tomographic based models (Donna, Irene, Frank, Helga, Golem, Voxelman, and Visible Human). The study ha d several interesting findings. Firs t, the influence of individual anatomy was found most relevant for incident photon e nergies between 60 and 200 keV. Below this range, even small individual variations, both anthropometric and anatomical, produced dose differences of hundreds of percent. Ab ove this range, the penetration and scatter of the photon beam was relatively high thus lessening the effects of individual organ variations Second, by comparing voxelized organ volumes between the Visible Human and VIP Man which were both segmented from the same dataset, the study concluded segmentation could account for errors up to 15% for large organs, and 25 60% for small and walled organs. Finally, the authors found dose differences between phantoms ranged up to 30% for organs located at shallow dept hs and within the field of view (FOV). For deep seated organs or those outside the FOV, differences in organ doses ranged from 30 100%. While anthropometric differences accounted for part of this error (Irene was thin while Visible Human, Frank, and Helga were larger), the results suggest a residual limitation due to anatomical (organ related) differences. While the aforementioned study included seven different patient specific or semi patient specific models, it was clearly limited by sample size. Also, the purpose of the study was not to test patient phantom matching, but to investigate systematic differences when compare d with older stylized phantoms. In order to provide a comprehensive analysis of patient phantom matching, two robust sets of phantoms a re needed: one consisting of patient specific models, and
52 the other consisting of a patient dependent library. In this present study, both phantom sets have been compiled and include 27 patient specific models created through CT segmentation, and 50 patien t dependent phantoms selected from the UF hybrid adult male (UFHADM) and female (UFHADF) patient dependent series outlined in C hapter 2 Assuming the patient specific models phantom m atching using hybrid patient dependent phantoms would produce more accurate organ dose estimates than those determined using reference phantoms. The study was focused on projection based radiology, specifically dose conversion coefficients used in fluorosc opically guided interventions. Methods and Materials Patient S pecific Phantom Construction To begin the study, 27 CT datasets (14 male/ 13 female) were retrieved from the PACS archives at Shands Jacksonville Medical Center under an approved IRB protocol The datasets covered the chest, abdomen, and pelvic regions (CAP) and were selected preferentially so as to cover broad ranges of height and weight. In order to create a computational model for each patient, the CT datasets were contoured using the segmen tation software 3D Doctor. As it was difficult to delineate certain soft tissue organs such as the colon and small intestine, the following organs/structures were chosen as targets for this study: the pericardium, liver, spleen, stomach (wall and contents) pancreas, kidneys, bladder (wall and contents), skeleton, subcutaneous fat, and outer body contour. After all structures of a given dataset were contoured, the model was imported as a polygon mesh into the computer animation software Rhinoceros. Due to t he fact that the CAP scans often included two separate datasets (abdomen/pelvis and chest), each half of the patient specific phantoms were aligned properly within Rhinoceros. Following this
53 adjustment and a quick anatomical review, the phantoms were voxel ized at a resolution o f 2 x 2 x 2 mm 3 and converted into a MCNPX lattice structure. Figures 3 1 and 3 2 show height and weight information for the patient specific phantoms overlaid on a plot of standing height verses weight for the male and female UF hyb rid adult patient dependent series, respectively. As mentioned previously, this database consists of 25 distinct male and female phantoms created by modifying the UF hybrid adult male and female reference phantoms. The phantoms for each gender were created at five different height percentiles (10th, 25th, 50th, 75th, and 90th), and within each height percentile, at five different weight percentiles (10th, 25th, 50th, 75th, and 90th). As can be seen in the figures, the selected patients cover these ranges fa irly well and also include a number of outliers representing body types outside the 10th and 90th percentile bounds. Patient D ependent Phantom Modification In order to make a consistent comparison with the patient specific models, each patient dependent ph antom was modified in th ree ways. First, the arms, legs, and head were removed in accordance with information available in the CAP datasets. Second, organs and structures not contoured in the patient specific models were removed. These included the costal cartilage, intestines and prostate among others. The final modification was to adjust the angle of the scapulae to mimic the arms raised positioning of a real CT setup. Figure 3 2 illustrates a modified patient dependent phantom shown along side a patient specific model. While every effort was made to normalize the patient dependent phantoms, as seen in the figure, differences due to variable filling of the lung, bladder, and stomach were not addressed. This limitation will be discussed in f urther sections of this study. As with the patient specific models, the modified phantoms were voxelized at a resolution of 2 x 2 x 2 mm 3 and converted into an MCNPX lattice structure.
54 Monte Carlo Simulation With both phantom libraries compiled, four different fluoroscopi c projections were simulated using the radiation transport code MCNPX 2.6.0  The projections included two abdominal stu dies centered on the stomach, LP O/RAO, and two cardiac studies centered on the heart, PA/Left lateral. For the purposes of this study, all projections were viewed from the perspective of the x ray tube. Details regarding field size, source di stance, and beam quality were taken from organ dose handbooks compiled by the Center for Devices and Radiological Health (CDRH) of the FDA [18, 65] These parameters were then modified slightly to account for differences in phantom sizi ng. For abdominal projections, the field of view at the detector was set to 11.5 x 11.5 cm 2 This was done by simulating an ad justable lead collimator located 10 cm from the source term. The source to skin distance was fixed at 50 cm, and the detector was positioned roughl y 6 7 cm away from the patient. For cardiac projections, the field of view was set to 6.5 x 6.5 cm 2 and 10 x 10 cm 2 for the l eft lateral and PA projections. The source to skin distance was fixed at 50 cm, and the detector was positioned 10 cm from the patient. In order to simplify the simulations, b oth the phantom and collimator were located within an air filled medium without the addition of a table or mattress Three diagnostic x ray spectra were simulated for each projection using the SPEC 78 spectrum generator  an d parameters taken from the CDRH dose handbooks. For abdominal projections, peak voltages were set at 80, 100, and 120 kVp. Tungsten was used as a target material with an anode angle of 12 and filtration/half value layers set at 4.0/4.8, 4.7/5.0, and 3.8/ 5.5 mm Al, respectively. For cardiac projections, peak voltages were set at 60, 90, and 120 kVp. Tungsten was again used as the target material with the filtration/half value layers set at 3.5/2.5, 4.0/4.1, and 4.3/5.8 mm Al. A total of 78 phantoms were us ed in this study 27 patient specific, 50 patient dependent, and one reference stylized phantom  For each phantom, the
55 F6 tally (MeV g 1 ) was used to estimate dose to the eight organs listed previously. This tally provided an estimation of kerma w hich was used as an analogue for absorbed dose in this study. The tallies were further normalized by dose area product (DAP) which was simulated using a 1 cm thick rectangular air filled volume located 10 cm from the collimator. An entrance side metric was chosen to mimic how organ dose is calculated in the clinic; DAP is first measured during the procedure, and dose conversion coefficients (dose/DAP or DCC) are then selected from published values. Besides providing an entrance side normalization factor, th e DAP was used as a convenient check on the simulation as the DAP calculated for each phantom should be similar for a given projection/spectrum combination. The Monte Carlo simulations were run on the ALRADS cluster at UF comprised of 9 AMD Dual Opteron 22 16 processors with 4 GB of RAM and 4 AMD Quad Opteron 23 50 processors with 8 GB of RAM. All runs included ten million photon historie s and generally took between 400 to 700 minutes each. The number o f histories was sufficient such that the relative error w as reduced below 1% for all organs except the bladder which ranged between 1 10%. After the simulations were completed, the dose conversion coefficients were analyzed for any correlation between patient specificity and the accuracy of the dose estimate. T his was done by comparing the conversion coefficients calculated from a reference stylized phantom, the reference hybrid phantom (50 th percentile by height and weight), and a matched patient dependent phantom to the conversion coefficients calculated fr om each patient specific model. To assist the matching process, a surface plot was created for each organ based on the height, weight, and magnitude of the dose conversion coefficient as calculated from the 25 male and 25 female patient dependent phantoms. Ma tching was then performed according to height and weight where interpolation along the surface plot was used whenever the anthropometric
56 parameters of the patient specific model did not agree closely with one of the defined patient dependent phantoms. Figu re 3 4 displays a large, medium, and small individual shown with their closest patient dependent counterpart. The figure provides a good illustration of how patient dependent phantoms can more accurately describe a variable patient population. It is import ant to remember however, that matching was performed using interpolation between patient dependent dose metrics which allowed for more than a one to one complement. Accuracy was quantified for each phantom type by calculating an absolute percent difference using the patient specific dose conversion coefficients as the true value. This method of calculating percent difference is defined in Equations 3 1 through 3 3 ( 3 1) ( 3 2) (3 3 ) A percentage point improvement was also utilized as defined in Equations 3 4 and 3 5. ( 3 4) ( 3 5) Results Mean organ volumes as segmented from the patient specific CT datasets are listed in Table 3 1. Reference volumes are also listed for the UF HADM, UFHADF a nd reference stylized phantoms. The expectation was to see organ volumes close to or slightly higher than the
57 reference volumes as both the mean height and weight of the male and female datasets were greater than their corresponding reference values. As shown in Table 3 1, several organs matched closely with this expectation including the male liver, pericardium, stomach, and kidneys, and female liver, pericardium, stomach kidneys, spleen, and bladder. In both the male and female cases, the l ung volumes were greater by approximately 40%. In addition to differences in phantom sizing, this discrepancy was most likely due to the expanded lung volumes of patients undergoing CT scans where a breath hold is required in order to avoid motion blur. Th ree organs, the male and female pancreas, and the male spleen, did not agree closely with expectation. While differences in pancreas volume can be explained by segmentation error (this organ was notoriously difficult to visualize in the CT images), the spl een was clearly visible and contoured appropriately in the female datasets. After reviewing dictation notes for the male patients, in only 9 out of 14 cases was the spleen noted as having a normal appearance. In three cases splenomegaly was specifically id entified. No information was given for the remaining two patients. These findings agree with observations from the contoured datasets, and as a result, the mean spleen volume was increased higher than what would be expected in a normal patient population. With the exception of these two cases, however, the organ volumes for the male and female patient specific models were found within normal bounds. As mentioned previously, 78 phantoms were used in this study with 12 different Monte Carlo runs performed fo r each phantom. Dose conversion coefficients were calculated for each organ and an absolute percent difference was determined for each of three phantom types: reference stylized, reference hybrid, and patient dependent hybrid. Table 3 2 lists these results for RAO projections where the absolute percent difference has been averaged for each male
58 organ. The table is structured in multiple ways. First, the values are separated by tube voltage. Second, the values have been compiled into three column groups as the average of all patients, as the average of heavy patients (>50 th percentile by weight), and as an average of light patients th percentile by weight). Third, at the bottom of each column, the table includes both the average of all organs, and the av erage of organs considered primary for the projection based on the magnitude of the conversion coefficients. For RAO projections these organs were the pericardium, stomach, pancreas, and liver. The primary organs for LPO projections were the stomach, splee n, and kidneys, for PA projections the lungs, pericardium, and spleen, and for left lateral projections the lungs, pericardium, stomach, and spleen. The RAO projection selected for Table 3 2 highlights many of the general trends observed across all projec tions. It can be seen that increasing tube potential improves the accuracy of the dose estimate. This is further illustrated in Figure 3 5 which shows percent differences for 80, 100, and 120 kVp RAO projections, taken as the average of all organs for all male patients. This trend was also seen, however, for i ndividual organs of both sexes. Also shown in Figure 3 5 is the magnitude of the differences between the three phantom types. In Table 3 2 these differences are quantified where, taken as an average o f all patients, the stylized phantom provided the least accurate dose estimates while the patient matched phantom provided the best estimate. While giving some support for the concept of patient phantom matching, this conclusion changes slightly when patie nts are separated by weight. Figures 3 6 (male) and 3 7 (female) show percent difference for 80 kVp projections taken as the average of all organs for each of two groups: heavy and light patients. In these figures, it is clearly seen that while the stylize d phantom provided the least accurate dose estimate overall, patient phantom matching was superior to using a reference hybrid phantom only for heavy patients. For light patients, the
59 two phantom types provided an equivalent level of accuracy. Again, this trend was also seen when individual and primary organs were considered. In order to summarize these results for the complete study, Tables 3 3 and 3 4 list the percentage point improvement gained by using patient phantom matching over hybrid and stylized reference phantoms, respectively. The tables are structured by tube potential, patient grouping (out of all 27 patients), and how absolute percent difference was averaged across the eight organs of interest. As seen in Figures 3 6 and 3 7 for each projecti on, patient phantom matching provided significant improvement for heavy patients but little to no improvement for light patients when compared with a reference hybrid phantom. In comparison with the reference stylized phantom, patient phantom matching prov ided better dose estimates for all patient groupings when abdominal studies were considered, but results varied for cardiac projections. In this case, the hybrid based phantoms provided more accurate estimates for light patients but were slightly less accu rate for heavy patients. Discussion In order to further investigate the differences between heavy and light patients, specific contour matching was performed for each of the five male patients se lected from the heavy grouping. To do this, a new phantom was created for each patient using patient dependent organs but using the patient specific outer body contours. The phantoms were created within Rhinoceros and subsequently used to calculate organ dose conversion coefficients for a 100 kVp LPO abdominal projection. Differences between patient specific phantoms and the phantoms created using the patient specific contours were quanti f ied and are shown in Figures 3 8 as percent difference for the average of all organs. Percent differ ence is also shown for the original patient specific phantom matched to a reference phantom, matched by height to a patient dependent
60 phantom, and matche d by height and weight. The different matching techn i ques are clarified in Figure 3 9 There were sever al interesting findings from this comparison. For the smallest of the three inner contour. For the heaviest two patients, a gradual improvement was observed for each sequential matching technique. As seen in Figure 3 1, these two patients were heavier than the largest phantom selected from the patient dependent library. If a larger patient dependent phantom had been available, a similar baseline may have been reached. By matching using an inner body contour, variation in the amount of soft tissue which shields each internal organ is mitigated. This small test indicates matching using patient height and weight has a similar effect. Further support for this theor y can be deduced from Figures 3 6 and 3 7 which show patient phantom matching effective for heavy patients, where variation in soft tissue attenuation is large, but having little effect for light patients, where variations in soft tissue are small in comparison to the reference version. Interestingly, Figures 3 6 and 3 7 also reveal a baseline error of roughly 35 45% which was similarly obse rved across all projections. In the Zankel et al.  study, comparable differences were found between the seven adult voxel models where individual anatomical variation in organs size and location was d iscussed as a main contributor. To test this theory, a heavy and light pat ient specific phantom were selected from the library along with their patient dependent counterparts and re run for a 100 kVp LPO abdominal projection with four different fields of view including 5.7 x 5.7 cm 2 11.5 x 11.5 cm 2 22.9 x 22.9 cm 2 and 45.9 x 45.9 cm 2 Percent difference between patient specific and patient dependent phantoms was quantified as th e average of all o rgans a nd is plotted in Figure 3 10 for different field sizes. In each case,
61 increasing the FOV, or effectively limiting differences in organ location, led to a decrease in error. With an increased FOV, both the patient specific and patient dependent phantoms received a more uniform fluence across each organ. An example of this would be the stomach which was found completely within the FOV at 45.9 x 45.9 cm 2 but only partial within the FOV at 5.7 x 5.7 cm 2 Because the amount stomach found within the FOV differs between phantoms at small FOVs due to specific organ locations, the overall disagreeme nt in organ dose is increased. This resu lt further supports the notion that a residual limit or uncertainty is always present when patients are matched to phantoms using anthropometric parameters. This uncertainty is due to anatomical difference in organs size and location which cannot be accoun ted for without patient specific imaging data. In regards to stylized models, Table 3 4 indicates patient phantom matching provides major advantages for abdominal projections, and minor advantages for cardiac projections As noted in previous studies, styl ized phantoms utilize a highly elliptical cylinder to represent the torso. The cylinder is unrealistically wide in the lateral dimension leading to organ positions that are too peripheral  Furthermore, the cross section of the cylinder remains constant with height. For abdominal projections where both the axial and sagittal body contours are quite variable, a constant cross section introduces additional error. Patient phantom matching reduces this error by folding patient height and weight into the dose estimate. As weight is well correlated with waist circumference, selecti ng a larger phantom to represent a larger patient helps reduce differences in soft tissue attenuation as mentioned previously. For cardiac projections, the wide breadth of the cylinder actually matched better with the heavy patient grouping. As a result, t he trend for light and heavy patients was reversed for left lateral projections. In this case, the stylized phantom overestimated lateral attenuation for light
62 patients, and as a consequence, patient phantom matching proved most beneficial for this patient class. For posterior anterior projections, the data showed little indication of a common trend. While patient phantom matching slightly improved accuracy when taken as the average of all organs, when only primary organs were considered, the stylized phan tom exhibited better agreement with the patient specific data. Upon further inspection, the male spleen was found as the main organ causing significant disagreement. In addition to issues mentioned previously related to the size of the male spleen, the loc ation of the male spleen within the hybrid phantoms was found medial and superior to what was seen in the both male and female patient specific datasets. This was not the case for the female hybrid phantoms, and as a result, the female patient dependent DC Cs aligned much better with the patient specific data. While the purpose of this study was not to verify the position of any specific organ within the UF hybrid patient dependent series, the male spleen is an item that can be added to a list of future adju stments to better define a supine patient as most commonly seen in fluoroscopy. The list may also include the sagittal angle of the kidney which was observed to be slightly less than what was seen in the patient images. Beyond the anatomical differences of these organs, the expanded lung volume of the patient specific phantoms, and variable filling of the bladder, great effort was made to limit variables and simplify the study as much as possible in order to derive general conclusions and error trends. For this reason, the study relied on an absolute versus relative percent difference and expressed results in terms of mean values. Taken individually, organ dose as calculated using a patient dependent phantom ranged in extreme cases from 300% high to 75% low. Using a relative percent difference would have thus underestimated the mean disagreement. While 27 patients provided enough data to compile over 900 Monte Carlo runs, the study would have
63 benefited from a broader patient specific data set. With a larger l ibrary, a more thorough analysis of the dose variation to individual organs could be performed. Summary The purpose of this study was to investigate the effectiveness of patient phantom matching in comparison with stylized and hybrid reference phantoms. B y analyzing percent difference between actual patient dose and phantom dose, several conclusions were reached. Results indicate two sources of error when phantoms are used to represent individual patients. These include uncertainty associated with variabil ity in organs size and location, and error associated with differences in soft tissue attenuation. The first type is inherent and accounts for dosimetric differences of approximately 35 45%. The second type depends on patient size, and can be addressed usi ng anthropometric based patient phantom matching, specifically for large patients where error can be reduced approximately 20 60% depending on projection. Additionally, in cases where tube potential is increased, error is further reduced as differences in organ location and patient size are lessened by a more penetrating beam. While the results of this study indicate that patient phantom matching is only truly useful to larger members of the patient population, obesity rates are on the rise and thus these p atients will continue to make up a growing fraction of all patients undergoing medical imaging. In response to these findings, additional phantoms representing heavier weight percentiles can be added to the UFHADM and UFHADF patient dependent series. These phantoms can be used to better represent the over weight population representing a considerable improvement over previous methods for dose reconstruction in radiology and fluoroscopy.
64 Table 3 1. Mean organ volumes as contoured from 14 male and 13 fema le CT datasets. Reference organ volumes are also listed for the 50th percentile by weight / 50th perce ntile by mass UFHADM and UFHADF and for the reference stylized model.
65 Table 3 2. Mean absolute percent difference for individual organs of three patient groupings, all (14 patients), heavy (5), and light (9) male patients as calculated for 80, 100, and 120 kVp RAO projections. Primary organs for RAO projections were considered to be the per icardium, stomach, pancreas, and liver.*
66 Table 3 3 Percentage point improvement over a reference hybrid phantom. Primary organs were those which received the highest dose in each projection.
67 Table 3 4 Percentage point improvement over a reference stylized phantom. Primary organs were those which received the highest dose in each projection.
68 Figure 3 1. Patient standing height versus weight shown for patient dependent and patient specific male phantoms. Figure 3 2 Patient standing height versus weight shown for patient dependent and patient specific fe male phantoms.
69 Figure 3 3. Patient dependent (P d) phantoms were modified to match the contoured patient specific (P s) datasets. Mod ifications included the removal of cartilage, intestines, and prostate among others, and the rotation of the scapulae to mimic an arms raised positioning. The increased lung volume of the patient specific phantoms due to breath holding techniques is also h ighlighted. Figure 3 4. Patient phantom matching by height and weight where the closest patient dependent phantom is shown for three different adult male patients. [( a ) and ( b ) large ] P atient dependent 90th percentile by height/90th percentile by weight, 182.9 cm/110.0 kg P atient specific 182.9 cm/112.7 kg [( c ) and (d) medium ] P atient dependent 75th/50th 178.3 cm/82.3 kg P atient specific 175.2 cm/80.9 kg [ (e ) and( f ) small ] P atient dependent 10th/10th 163.7 cm/57.6 kg P atient specific 15 7.5 cm/43.6 kg.
70 Figure 3 5. Improved accuracy with increasing kVp. Shown for RAO projections as the average of all organs for all male patients. Figure 3 6 Improved accuracy for heavy patients, but no improvement for light patients. Shown for 80 kVp RAO, LPO, Left lateral, and PA projections as the average of all organs for all male patients.
71 Figure 3 7 Improved accuracy for heavy patients, but no improvement for light patients. Shown for 80 kVp RAO, LPO, Left lateral, and PA projections as th e average of all organs for all fe male patients.
72 Figure 3 8 Percent difference for each of the five heavy male patients as matched to a reference hybrid phantom, matched by height to a patient dependent phantom, and matched by height and weight to a patient dependent phantom. Each phantom was also matched using a patient specific contour but using patient dependent organs. Figure 3 9 Four different anthropometric matching techniques: by reference, by height, by height and weight, and by the patien t specific contour.
73 Figure 3 10 Improved accuracy with increasing field of view, shown as the average of all and primary organs for two male patients.
74 CHAPTER 4 DEVELOPMENT OF SOFTW ARE FOR SKIN AND ORG AN DOSE ASSESSMENT Background As mentioned previously t he application of phantom patient matching addresses only one s olution for a two part problem. A significant hindrance for the implementation of computational dosimetry within the clinic is the burden placed on staff to record pertinent inform ation and provide customized dose reconstructions. Accordingly, very few institutions have dedicated programs for the monitoring of individual patient dose Two examples of such programs which span ned across multiple institutions were the RAD IR and DIMOND III study groups [8, 68] Both groups used a variety of dose metrics, including DAP and t he reference point dose (K a,r ), to categorize patient dose for different interventional procedures. The studies published in the years 2003 2004 relied on observation, information found within the DICOM header, and the add on dosimetry system to collect information While organ dose and stochastic risk were addressed in the form of overall patient dose, a primary focus was placed on the recording of peak skin dose (PSD) which was evaluated using Caregraph and customized dose reconstructions p rovided by physic staff Both studies reached similar conclusion s that 1) the determination of PSD is a critical component of patient safety, 2) the vast majority of fluoroscopic units have no form of automated PSD monitor ing, and 3) the FDA and European U nion should require a real time method for estimating PSD in the clinic. In order to reach this goal, two components are needed. The fist is a way to automatically extract relevant examination parameters. As mentioned in C hapter 1, previous methods have relied on optical character recognition, video recording, integrated systems, and the DICOM header. The disadvantages of these methods were numerous as they provided only a partial summary of the procedure and required either significant interaction by cli nical staff or
75 complicated machine installation. The solution for these issues came in the release of the Radiation Dose Structure Report (RDSR). The RDSR provides a significant amount of technical information which can be readily accessed using software a pplications. The second component for patient dose monitoring is then a system which translates this information into patient dose. To date, only one system has been developed which utilizes the RDSR to estimate patient skin dose. The system, designed by researchers at the Mayo Clinic in Rochester, extracts geometric information from the RDSR and pairs this with a stylized reference phantom  The system works by first determining the patient entrance refe rence point (PERP) using known distances A four sided project ion pyramid is next conceptualized having its base at the PERP location and apex at the source location. The irradiated skin area is then determined according to mathematical equations which relate the four planes of the pyramid to points on the stylized p The skin dose mapping system has been installed within the Radiology department at the Mayo clinic and is undergoing validation and testing. The successful design and implementation of this program gives credibility to the type of skin d ose mapping mad e available by the RDSR. In this work innovative software for calculating PSD from the RDSR is presented. The primary advantages are the incorporation of table attenuation and MEAC ratios, the use of a flexible vector based algorithm, and t he implementation of more realistic outer body contours as provided by male and female hybrid phantoms. Additionally, a compelling case is made for the use of patient sculpted phantoms based on the results of a patient phantom matching study whereby 26 pat ient specific anatomical models were matched to phantoms using anthropometric measurement. Also presented in this study is a method to characterize a complete examination based upon the RDSR. Such a
76 characterization is needed for the development of a compr ehensive dose conversion coefficient handbook and the estimation of stochastic risk. Methods and Materials RDSR Extraction Formally, the Radiation Dose Structure Report was created in 2005 with the release of Supplement 94 to the DICOM standard. The RD SR i s built as an Information Object D efinition (IOD). The IOD is comprised of several DICOM attributes such as names, tags, and types which are arranged a ccording to specified Template IDentifiers (TID). Figure 99 displays how these TIDs comprise a hierarchical tree structure where TID 10001 (Projection X Ray Radiation Dose) contains TIDs 1002 (Observer Context), 10002 (Accumulated X Ray Dose Data), and 10003 (Irradiation Event X Ray Data). During an exam t here will be one instance of TID 1002 per procedure and up to two instances of TID 10002 depending on the fluoroscopy unit, either single or bi plane. The number of exposures will determine the number of irradiation event templates Within each template are the attributes which help describe the physical context of the irradiation. In order to access this information, a DICOM compatible reader is required. DICOM readers come in a variety of fashions including independent programs, modules, and programming toolkits. In this research the programming language Python was chosen along with the DICOM compatibility module Pydicom  foundatio n as a general purpose, scientific friendly programming language. A dditionally, the Pydicom module provides specific functionality for reading, interpreting, and modifying DICOM objects. The program begins by searchi ng for an RDSR within a specifi ed direct ory. It then uses the Pydicom module to read the RDSR and determine the number of irradiation events exclusive of those contributing dose due to cone beam CT. The program next build s an n x 10 dimensional
77 array, where n represents the number of irradiation events. The program fills each column of each row with the corresponding information as identified by name in the RDSR file: 1. Irradiation event number 2. Table lateral position (mm) 3. Table longitudinal position (mm) 4. Table height (mm) 5. X ray tube primary angle o r rotation (degrees) 6. X ray tube secondary angle or angulation (degrees) 7. Source to ioscenter distance (cm) 8. Dose area product (Gy cm 2 ) 9. Source to detector distance (cm) 10. Reference point air kerma (mGy) While the program f ills the irradiation event array, it a lso simultaneously discriminates between planes A and B for bi plane s ystems. Each of these planes is organized such that the data needed for dose reconstruction is made available. Skin Dose Mapping Software In order to translate the information extracted from the RDSR into PSD, a dose mapping algorithm was constructed using programming tools available within MATLAB In this case, the matrix based language provided the best option for development The final al gorithm, however, was ported into Python and compiled as an independent executable. The algorithm has several independent steps which are outlined in the following sections. Phantom formatting and orientation In contrast to previous methods, the skin dose mapping software developed in this research incorporates a patient dependent phantom type To begin, a phantom is first selected from the patient dependent library using ma tching techniques described in C hapter 3. The phantom is next read into the program as a three dimensional matrix where the x, y, and z dimensions correspond to the anterior/posterior, left/right, and superior/inferior orientations. The matrix is comprised of only three tags, sk in (5), body (1), and air (0).
78 An initi al method for orienting the patient and tube was devised wher eby a timestamp would mark the point in the exam when the tube isocenter was located within the organ of interest. S hifts in table height, latitudinal, and longitudinal positio ns as identified in the RDSR would then be applied to the isocenter based on the know position of the organ within the phantom While this method of patient localization provided a workable system for any configuration, it has notable drawbacks whic h will be discussed furthe r in C hapter 4. As an alternative, a second method was devised which utilizes the coordinate system provided by t he Siemens Arti s Zee system for which the skin dose mapping program was designed The Artis Zee system locates the C arm isocenter at the table home position (0 cm lateral, 0 cm longitudinal, and 0 cm table height). Assuming a supine orientation with the tube located beneath the table, the posterior skin of the phantom correspondingly rests at the tube isocenter. The position of the patient in re lation to the head of the table is pre determined and used to locate the phantom longitudinally. Additionally, the phantom is assumed to lay middle of the table and not move. S hifts in table height, latitudinal, and longitudinal positions as identified in the RDSR are applied to the phantom directly The primary (LAO/RAO) and secondary (Cranial/Caudal) angles are then used in correspondence with the source to isocenter distance to determine the xyz location of the sourc e in relation to the phantom. Determin ation of affected skin area After the phantom h as been correctly oriented, the three dimensional phantom matrix is searched for voxels tagged as skin. Using the known positions of these voxels in relation to the xyz location of the source, unit vectors are calculated from the origin and in t he direction of each skin voxel ( Figure 4 1A ). The unit vectors are stored in a [n x 3] matrix. In order to determine which skin voxels are found within the field of view, this matrix is rotated twice so as to orient the source to isocenter vector along a known axis ( Figure 4 1 B ) Using the source to detector
79 distance and FOV at the detector, two angles alpha and beta, needed to define a 4 sided projection pyramid are calculated ( Figure 4 1 C ) Two angles gamma and theta are also calculated for each unit vector based on their relation to the chosen orientation axis ( Figure 4 1 D ) By comparing these two angles with those calculated for the projection pyramid a determination can be made as to which skin voxels are found w ith in the irradiated area. The conditional statement is listed belo w. (4 1) The conditional statement culls the unit vectors based on their position either inside or outside the irradiation projection. To differentiate between s kin voxels on the entrance and exit side s of the phantom, the source to skin distance for each voxel determined to be within the beam is compared with minimum source to skin distance. A tolerance is set using this ratio and the FOV, and a final vector whic h includes the source to skin distance for each in beam, entrance side skin voxel is created. To account for table attenuation, the program calculates the distance through the table for each point found in the final list of affected skin locations. The di stance is determined using each source to skin unit vector and the x, y, and z planes which describe the table location. By moving in small increments along the unit vector, the entrance and exit points can be established. The separation is then a calculat ed directly as the distance between two points. Attenuation factors can be measured or selected from literature.
80 Skin dose assessment The calculation of dose is performed for each affected skin location according to E quation 4 2 where BF is a backscatter factor selected from ICRU 74 is the ratio of mass energy absorption coefficients for tissue to air as determined from the NIST Physical Reference Data Library and represents table attenuation [70, 71] T he BF MEAC ratio and attenuation coefficient are energy dependent and chosen based on the effective energy of the x ray beam. (4 2) Equation 4 2 is used to determine skin dose for each in beam, entrance side skin voxel. The peak skin dose is then calculated as the maximum of these dose s. In addition to PSD, the skin dose mapping program keeps track of the amount of skin area receiving doses within pre skin and hair performed by Stephen Balter at Columbia University Medic al Center  Table 4 1 list s the four monitored dose le vels and has been reprinted here with permission from Dr. Balter. Examination Characterization for Organ Dose Assessment The RDSR provides a wealth of information which can be used to determine common parameters for individual procedure types. These parame ters may then be used along with the UF hybrid adult patient dependent library to calculate organ dose conversion coefficients for individual stochastic risk assessment. In this work, a MATLAB code was written to translate the RDSR into an MCNPX input file The code serves two purposes. First, because the code was written for complete automation, it can be used to provide personalized organ dose reports in
81 clinic. While it is difficult to foresee a hospital installing dedicated clusters for radiation transp ort, the shift in computing has been towards internet programs are run on off site servers which can be accessed by users locally. In this environment, an RDSR could be uploaded automatically to the web and returned within a m atter of hours as a detailed organ dose report. The second purpose of thi s code was to provide a tool which will allow for the building a comprehensive organ dose conversion coefficient library. In cases where patient specific Monte Carlo is not feasible, this library could be used to provide a post procedure reporting of organ dose according to a look up table format. In order to serve both these stated purposes, t he MATLAB program has several functions which are described in the following sections. Determ ining interesting irradiation events and common tube geometries A radiation dose structured report may contain upwards of three hundred irradiation events depending on how many times the patient was exposed to ionizing radiation. Many of these exposures occur during catheter insertion where a low dose panning mode is p rimarily used. In order to reduce the number or irradiation events to those which deliver a significant amount of radiation, the RDSR is culled based on a dose threshold. The threshold is set so as to select only irradiation events which, when summed, deli ver 90% of the total dose. The threshold is pre set but is easily configured to provide different percentiles. Once the RDSR has been condensed to a set of significant irradiation events, the code implements a two dimensional histogram based on the tube r otation and angulation, and a two dimensional grid is displayed listing rotation along the x axis and angulation along the y axis. The grid is filled based upon the number of irradiation events having similar tube geometries. From the display, the user may select the most common tube geometries or the code can determine these geometries independently In tightly focused cases, the number of geometries
82 may be one or two. For procedures where multiple views are common, the number may be five or more. With th e primary geometries selected, the RDSR is culled based upon rotation and angulation. The RDSR is then summarized into a limited number or irradiation events where the geometric parameters such as table height and source to imager distance have been averag ed and the dose to the reference point has been summed for a given tube rotation and angulation. Preparing and writing the MCNPX input file In order to write the MCNPX input file, a template file was first created. The template orients a voxelized patient dependent phantom with an x ray source located beneath the patient. For each irradiation event of the summarized RDSR, the template file is modified to provide a customized MCNPX simulation. In order to provide a square beam, a lead collimator was placed 1 0 cm from the source and a DAP meter place a further 10 cm beyond the collimator. The coordinate transformation card is then used to rotate the collimator and DAP a ccordingly about the iso center The coordinate transformation card takes as inputs the angles between the original and transformed xyz axes. In order to determine these angles, two rotation matrices were applied to the original xyz axes. First the system was rotated about the superior/ inferior axis representing lao/rao rotation. Second, the system was rotated about the transformed left/right axis representing cranial/caudal angulation. The angles between the original and transformed axes were then determined using the formulation of the dot product. The template file has eight locations which need to be modified for each irradiation event. Each location is marked using a section of comments which are identified by the MATLAB code. The sections include: 1. S urface card for the box which hous es the phantom 2. S urface ca rd for the collimator shielding 3. S urface ca rd for the collimator beam port 4. S urface card for the DAP meter 5. C ell card fo r the phantom lattice structure
83 6. Co ordinate transformation card 7. S ource definition 8. S ource bias The MATLAB code thu s reads in an RDSR, selects common geometries, summarizes the RDSR, organizes a set of eight lines of code based upon a template file, and writes these lines over the template to create a unique MCNPX input file for each irradiation event. Test of S kin Dos e M apping S ystem In order to test the skin dose mapping program, an internal service log file from a representative interventional cardiac procedure was provided by Dr. Stephen Balter from the Columbia University Medical Center Dr. Balter was instrumental during the development of the RDSR as the point person representing the IEC, the internal service log files obtained from the fluoroscopy units at Columbia helped serve as pre cursers for the RDSR. From the log file, 10 projections were identified as prim ary contributors. Parameters for these projections were input to the skin dose software along with a patient dependent skin phantom (female 25 th height percentile and 90 th weight percentile). From the log file, the cumulative air kerma for all projection s was listed at 8,403 mGy. When multiplied by a backscatter factor of 1.35 and surface air kerma was found to be 13,351 mGy. This represents the maximum entran ce air kerma if all beams were incident on the same location. Because each of the ten projections was slightly different, the peak skin dose should be close to but less than this value. Results As determined from the skin dose mapping code, the highest dos e received by an individual voxel for the test patient was 12,003 mGy, a n appropriate estimate. Figure 4 2 shows a posterior comparison with a photog raph of the actual patient ( review article  ). Both maps, produced using the program TECPLOT TM provide clinically relevant dosimetric i nformation
84 which could be used by the physician to manage radiological risk. In terms of real time dosimetry, program execution was very fast and could realistically produce results in real time if fed with real time inputs from the RDSR. The skin dose map ping program was further evaluated with seven simulated RDSRs provided by Columbia University Medica l Center. Figure 4 3 shows the dose maps for these exams as mapped onto a variety of patient dependent phantoms. In all cases, the skin dose mapping program was able to identify the appropriate geometry and map to the patient Discussion The skin dose mapping and organ dose assessment software represent first generation tools which form the basis for further development. There are both technical and clinical driven challenges associated with the implementation of these tools. The following sections will discuss these challenges and possible solutions. Technical Challenges On the technical side there are factors which can be readily considered, and those which will require future updates to the RDSR. Table and p ad attenuation is one factor that will require further experimentation. While the curre nt software model which addresses the distance through the table, attenuation factors are needed Fluoroscopy tables are almost exclusively made out of low attenuation carbon fiber with measured attenuation factors between 0.7 and 0.8  The pad s placed between the p atient and table are made out of high density memory foam or gel and can vary as an attenuator depending on thickness and material type. Measured attenuation factors have published at 0.9 but can range in extreme cases to 0.5 when thick gel pads are used  A better description of this variable could be obtained through site specific measurement or Monte Carlo simulation.
85 A second technical factor which could be addressed presently is the influence of beam quality on both skin and organ dose. For skin dose mapping, beam quality is important in ch oosing the correct mass energy absorption coefficient (MEAC) ratios between tissue and air, although these ratios remain close to unity and generally introduce less than 5% error. More important is the eff ect of beam quality on the Monte C arlo simulations used to determine organ dose. Spectrum generators have traditionally been used to provide energy distributions but in room measurements would improve the realism of the simulation. Measured spectrums with different filtrations and tube potentials could for m a database for use as a look up table. The drawback s to such measurements are that they are time consuming and machine specific. The differences between machines, especially those manufactured by different vendors, is a problem that extends beyond beam quality. The RDSR provides a universal system to record exam parameters. Unfortunately, the meaning and orientation of these paramet ers is not always standardized. As examples, rotations may be positive or negative for different systems, the description of the table in relation to the tube isocenter may not be the same, and fluoroscopy units may differ in the degrees of freedom allowed to the C arm. As such, a physics evaluation is necessary before the skin dose mapping and organ dose estimation software can be implemented. For this work, both programs were designed for the Siemens Artis Zee fluoroscopy unit using Siemens defined orient ations. In the future, an additional interface may be added whereby a physic s evaluation can be entered for different machine makes and models Also to be included in a physics evaluation is a calibration of the machine provided reference point air kerma The recommended tolerances for this parameter are fairly wide according to the IEC (50% for values over 100 mGy) and the FDA (35%), although with proper calibration a precision of 15% may be maintained  A calibration factor can be
86 obtained through two measurements using on an ion chamber first, and a radiopaque scale second. Both the DAP and reference point air kerma can be derived fr om these measurements and compared to the values provided by the machine. An illustration of the setup is shown in Figure 4 4 where the table has been rotated to 90 degrees to limit the effects of any intermittent attenuators such as the pad and table. As mentioned, there are a few technical challenges which will require future action by the DICOM committee. The easiest of these challenges to address is a better description of the field of view. Currently, the FOV is defined at the detector based on the de Because collimation can extend within the active area, the FOV may be overestimated in some cases. Another way to determine field size is to divide the DAP by the reference point dose. Both methods provide conservative estimates but a ssume a square field. It is likely that fu ture releases to the RDSR will include this information and can thus supplement the current dosimetry programs. At present the RDSR also does not include real time streaming availability. Streaming is already buil t into the IEC/DICOM specifications, and all indication s point towards this capabili ty becoming available within the next few years In order to preliminarily tes t the system, streaming can be simulated using time stamps provided by the RDSR. In this way, the software can be optimized. The current system has a refresh rate of one second on a standard Dell Precision workstation, which is well within the rate at which a streaming RDSR system will record irradiation events to file. Clinical Challenges As with the physics evaluation, the dosimetry systems developed through this research will require a basic level of input from clinical staff. In order to take advantage of patient phantom matching, patient height and weight must be measured prior to the examinat ion. This
87 information is then used to select the appropriate computational model from the UF hybrid patient dependent library. A second needed mea surement is the distance between the patient and the head of the table. This distance is used to orient the pa tient longitudinally in relation to the table and tube isocenter. A procedure must be devised that allows for these types of measurements to be taken with minimal interference to the normal routine. Another clinical challenge is to develop a display that d oes not interrupt the concentration of the operator but instead provides relevant information which can be used to modify behavior when clinically necessary. Relevant information may include the visual mapping of skin dose onto a patient dependent phantom, a dose area histogram, the amount of skin area receiving a certain percentage of the peak skin dose, or the amount of skin area exceeding pre defined threshol ds. A prototype of this type of display is shown in Figure 4 5 a long with its implementation on the in clinic monitor of the Artis Zee system in the interventional surgery suite at UF Jacksonville (Figure 4 6 ). Additional features could be added to include warnings to the physician when clinically important skin dose t hresholds are approached Summary In this study two software programs were developed. The fi rst utilizes the radiation dose structured report to determine patient skin dose. The program operates by processing each irradiation event and orienting a voxeliz ed patient dependent phantom with the source location. Next, the distance between the source and each skin voxel is determined. After selecting all skin voxels within the field of view and on the entrance side of the patient, the skin dose at each voxel is determined using the reference point air kerma and a one over distance squared correction. The skin dose mapping program is the second program in the world to utilize the RDSR for these purposes, and was written independent to any knowledge of the previou s system. The program introduces a n innovative algorithm for calculating affected skin area using patient dependent
88 phantoms and has been compiled using the programming language Python as a stand alone executable. The second program operates by analyzing a n RDSR and summarizing it into a limited number of irradiation events based on tube rotation, angulation, and the reference point dose. For each standardized irradiation event an MCNPX input file is generated by modifying a template file. The program has g reat potential when paired with cloud computing for post procedure recording of individual organ dose. Several limitations were identified and assessed including the lack of table and pad attenuation, experimentally derived x ray spectra, dose calib ration, problems related to differences in orientation between different vendors, lack of collimator settings, real time streaming, and issues related to clinical implementation. These limitations will form the basis for future development and improvement. The underlying capability for providing individualized skin and organ dose estimates for interventional procedures, however, has been realized and appears promising.
89 Table 4 1. The skin dose mapping program determines the amount of skin area receiving do ses within the four ranges where effects can be expected.
90 Figure 4 1. Methodology for determining in field skin locations: In Fig 4 1A a unit vector from the source to each skin location is determined. In Fig 1B, these vectors are rotated cranial/caudal and LAO/RAO rotations define a four sided projection pyramid. In Fig
91 Figure 4 2. Skin dose comparison between a real patient and anthropome trically matched hybrid patient dependent phantom (view is posterior).
92 Figure 4 3. Relative skin dose maps as calculated for 7 real patient exams from Columbia University Medical Center. Skin doses are relative to the PSD for each individual patient.
93 Figure 4 4. Reference point air kerma calibration using ion chamber and radiopaque scale. The tube is placed at 90 to limi t all intermittent attenuators.
94 Figure 4 5 Prototype display of clinical skin dose mapping system. Figure 4 6 Prototype display of dose map o n the Siemens Artis Zee console. Dr. Dan Siragusa is shown on the left
95 CHAPTER 5 SENSITIVITY OF SKIN DOSE MAPPING TO PATIENT L OCALIZATION AND BODY MORPHOMETRY Background The skin dose mapping pr ogram developed in C hapter 4 provides a method previously not available for determining the effects of body morphometry on patient skin dose. The same question asked in C hapter 3 for organ dose may now be asked in terms of skin dose. Can patient phantom matching actually improve dose estimation for individual patients? In contrast to organ dose which required detailed Monte Carlo simulation, th e determination of skin dose is a relatively straightforward calculation As shown previously, skin dose is calculated by translating squared correction. A factor is then applied to adapt air kerma to tissue dose. Thus regardless of phantom type, the difference in dose between two points can be readily derived. The primary issue then arises in how the two points are determined based on the size of the phantom and i ts locatio n in relation to the x ray tube. Two methods have been derived in this research for orienting a phantom and x ray tube according to geometric parameters extracted from the radiation dose structured report. In the first method, the user must selec t the point during the exam when the isocenter is located within the organ of interest (OOI) All table shifts are then applied in relation to the know n position of the specified organ within the phantom. This method has two benefits. First, the position o f the patient in relation to the table is rendered irrelevant. Second, vendor or machine specific coordinate systems for table location are normalized to a common point of interest. As an example, two machine s may define the table height zero position diff erently at a point either above below, or at the tube isocenter. With the isocenter selection method, the table height zero position for both systems is normalized to the table height at the location of the OOI. The
96 primary disadvantage for this arrangement is the obvious difficulty in selecting the exact point in time at which the isocenter rests within the organ of interest Secondarily, the position of the phantom OOI in relation to a patient OOI will always be uncertain to the order of a few c entimeters. The second method for orienting the patient utilizes the coordinate system provided by the fluoroscopy unit. In this method, a physics evaluation is performed prior to implementation rded. There are only two offsets needed during this evaluation, the vertical distance between the table height zero position and the isocenter, and the longitudinal distance from the isocenter to the head of the table. Prior to an exam, two more offsets ma y be recorded which include the longitudinal distance between the nt from the table midline. While the coordinate based orientation system requires more information abou t each specific machine, it also minimizes uncertainties related to organ variation and isocenter selection. In this study, both orientation systems were tested based on their sensitivity to errors in patient/tube alignment. For the isocenter selection me thod, this involved systematically selecting an isocenter at different locations within a phantom. For the coordinate based method, different offsets were selected simulating error in these in clinic measurements. Skin dose was then calculated using both m ethods and compared with the dose found using reference values for the isocenter and measured offsets. With the uncertainty in patient/tube alignment quantified, an an alysis similar to that used in C hapter 3 was performed using patient specific, patient de pendent, and two different reference phantoms. A fifth type of phantom based on
97 circumferential measurements was also developed and used along with the original three phantom types to analyze the impact of patient phantom matching on skin dose mapping. Met hods and Materials Isocenter Based Orientation In order to test the sensitivity of skin dose mapping to isocenter selection, the male reference hybrid phantom (50 th percentile by weight, 50 th percentile by height) was chosen along with two patient specific male phantoms ( 183 cm/113 kg, 157 cm/44 kg ) selected from the phantom libraries of C hapter 3. For each or the three phantom s, the center of the heart was determined as an xyz coordinate and a representative posterior anterior cardiac procedure was simulated using the xyz coordinate as the tube isocenter. The source to skin distance was set at 72 cm, the field of view set at 10 x 10 cm 2 and the source to detector distance set at 100 cm. The reference peak skin dose was calculat ed using the developed skin dose mapping system. With a baseline peak skin dose determined for each phantom, the z coordinate (anterior/posterior patient axis) of the isocenter was shifted by a half centimeter towards the tube and peak skin dose recalculat ed. This process was repeated at half centimeter increments until the isocenter was located five centimeters posterior to its original location. The process was also repeated in the opposite direction until the isocenter was located five centimeters anteri or to its original location. Error was quantified at each step by determining the percent difference between peak skin dose and the reference peak skin dose. Coordinate System Based Orientation A similar sensitivity analysis was perfo rmed using the coordinate system based method. First, each of the three phantoms was positioned using a table vertical offset of zero (vertical distance from table height zero position to tube isocenter), a table longitudinal offset of 20 cm (longitudinal distance from superior end of table to tube isocenter), and patient longitudinal and
98 distance of patient from midline). Peak skin dose was then determined fo r each phantom using the reference offsets. Three different projects were simulated including tube rotations of 0 and 90 degrees, and one projection having a rotation of 45 and an angulation of 30 degrees. Next, the patient longitudinal and latitudinal off sets were changed in half centimeter increments, thus simulating error in these measurements. After each change, a new peak skin dose was determined and compared to the reference peak skin dose as a percent difference Construction of Elliptical Contour Phantom s With the uncertainty in patient/tube alignment quantified, patient phanto m matching was tested using five different phantom types including a reference stylized, reference hybrid, patient dependent hybrid, patient specific, and a measurement based contour phantom The concept of a contour phantom was based on the idea of creating a unique model for each patient. In order to create these phantoms at the time of examination, a stylized approach was necessary In the future automatic sculpting of the NURBS based patient dependent hybrid phantom can be pursued, thus allowing for rapid development of a unique surface phantom of the patient at the time of intervention. For this work, contou r phantoms were created for 26 patients. The surface of each con tour phantom was defined according to three ellipse halves one at each end and one in the middle. The ellipse halves themse lves were defined by a majo r and semi minor axis which was taken as measurements from each of the chosen five patient specific phant oms. The major axis s lateral width, and t he semi posterior/anterior width as measured for a supine patient. In total, six measurements were needed to create the phantoms and are illustrated in F igure 5 1 It is feasible that the same six measurements could be taken during a fluoroscopy procedure by a technician or nurse. The first
99 middle torso, and t To actually construct each phantom, a MATLAB program was written which took as inputs each of the previously defined six measurements. The program begins by defining the three ellipse halves and then inte rpolates between the three halves to complete the surface. As with the phantoms used in the skin dose mapping program in C hapter 4 the contour phantoms were created as a three dimensional matrix where the x, y, and z dimensions corresponded to the anterio r/posterior, left/right, and superior/inferior orientations. Each matrix was al s o comprised of only three tags, skin (5), body (1), and air (0). Patient Phantom Matching for Skin dose M apping Patient phantom matching was evaluated using six beam projections. The fir st set of three projections was centered on the heart and included tube rotations of 0, 90, and 180 degrees. The second set of projection s was centered on the abdomen and also included tube rotations of 0, 90, and 180 degrees. The field of view for all projections was set at 15 x 15 cm 2 the source to isocenter distance set at 72 cm, and the source to detector distance set at 100 cm. Implementing the coordinate based orientation system, peak skin dose was calculated for e ach projection u sing each of the 26 diff erent patient specific phantoms. Peak skin dose was also calculated for each projection using the reference hybrid phantom reference stylized phantom, and each of the created contour phantoms. Finally, the patient phantom ma tching techniques described in C hapter 3 were used to select patient dependent phantoms for each patient specific model and peak skin dose was subsequently calculated for each projection. Similar to the analysis perfor med in C hapter 3, accuracy was quantified f or each phantom type by calculating a percent difference using the patient sp ecific dose as the true value. Figure 5 2 illustrates the different phantom types and matching technique.
100 Results Percent difference bet ween the reference peak skin dose and the dose determined using different isocenters is shown in Table 5 1. The results were similar across all phantoms with the greatest disagreement with the reference found at 5 cm in the direction of the x ray tube. When divided by distance, the p ercent difference per centimeter was also very similar across each step. These results can be verified in a straightforward fashion by applying the inverse square law. Using the reference hybrid phantom as an example, the source to skin distance was found to be 50.5, 55.5, and 60.5 cm when the isocenter was placed at locations +5 (toward the tube), 0, and 5 cm. The inverse square law then predicts differences of 20.8 and 15.8 percent which match the calculations of skin dose mapping program. Results for t he second test focusing on the coordinate system method are shown in Table 5 2. The table organized percent difference into sections for each tube a ngle, and within each section the results are organized by the direction of the phantom shift, either superi or/inferior (longitudinal) or right/left (latitudinal). Again the results for each phantom were very similar. Also immediately noticed is the patent insensitivity of peak skin dose to longitudinal and lateral shifts for under the table projections. This follows from the fact that for these projections, patient location in the direction of the x ray tube is governed primarily by table height. Besides uncertainty related to tabl e pad thickness, table height provides a robust determination of patient location along the vertical axis. For lateral projections the situation changes, and patient right to left alignment becomes the determining factor for patient location in the directi on of the x ray tube. In these cases, Table 5 2 indicates the calculation of peak skin dose is very sensitive to shifts along the lateral axis. The results for the patient phantom matching study are highlighted in Table 5 3. The table is organized by tube angle and gender, and lists percent difference between peak skin dose
101 calculated using patient specific phantoms and peak skin dose calculated using reference, patient dependent, and patient sculpted phantom types. As in the previous patient phantom matchi ng study, the results have been aggregated according to patient size. The values found in the table represent the mean absolute percent difference for each group. Several interesting trends were found. For posterior anterior projections, skin dose was se en relatively insensitive to anthropometric differences between the reference and patient dependent phantom types. This follows the fact that for these projections, the source to skin distance is governed primarily by table height, not the patient contour. Another consideration is that for a supine patient, the posterior contour will flatten as a consequence of lying on a flat table. The patient sculpted contour phantoms provided a completely flat posterior contour. This matched more closely with the poster ior contour of the patient specific phantoms which were created directly from CT image s In a number of cases involving female patients, the patient specific posterior contours were not completely flat due to an alternate patient positioning where the tors o was raised slightly above the table For this reason the mean difference for PA female projections was slightly higher than for males. In both cases however, using a patient sculpted contour phantom provided the most accurate dose estimates. For left la teral projections, using a patient dependent hybrid phantom had a small, but noticeable impact for both heavy and light patients. On average the improvement was 2 3 percentage points better than using a hybrid reference phantom and 5 10 percentage points b etter than using a stylized reference phantom For anterior posterior projections, significant improvement was seen when patient phantom matching was employed to estimate the dose to large male patients. For females, using a patient dependent phantom type also had a significant impact, in this case most noticeably for abdominal projections for all patients and cardiac
102 projections for light patients. The AP female projections were complicated by the large variability in patient and phantom breast sizing. Err or in dose assessment was thus greatest for the AP female cardiac projections. Overall, the patient sculpted contour phantoms again provided the most accurate dose estimates for all patient s across both left lateral and AP projections, while the reference stylized phantoms provided the least accurate estimates by a wide margin. Discussion The purpose of these three experiments was first to resolve which orientation system proved least sensitive to operator error and second to determine whether or not p ati ent phantom matching provides a dosimetric benefit. In the first instance, a solid conclusion can be made that patient skin dose is most sensitive to phantom positioning in the direction of the x ray tube. Using the isocenter based orientation system, manu al sel ection introduces uncertainty along all three directions, superior/inferior, right/left, and anterior/posterior. Thus no matter what tube angle is used during acquisition, a residual uncertainty remains of up to 20%. For the coordinate based system, patient location in the anterior/posterior direction is not dependent upon operator input. This means for under the table configurations, uncertainty in peak skin dose related to phantom positioning can be minimized to approximately five percent or less. A s the tube rotates to a more lateral position, patient latitudinal positioning becomes more important. Similarly, as the tube angulates, patient longitudinal positioning becomes more impo rtant. Due to the fact that the majority of fluoroscopic images are acquired using an under the table tube configuration the coordinate based orientation system remains the clear choice for patient/phantom positioning. Another consideration that benefits the coord inate based system is the expected magnitude of any unintended shift in phantom alignment. For the isocenter based system error up to five centimeters would not be unexpected as the true location of any internal organ is difficult to
103 ascertain using a com putation phantom. For the coordinate based system, one would expect much less error as the system is based on external measurement made with a tape measure. In this case, a reasonable assumption would be a divergence of two centimeters or less At worst, t his w ould lead to error of 10% for less frequent lateral projections. In terms of patient phantom matching, the data found in Table 5 3 points towards two conclusions. First, error introduced by anthropometric differences is minimized for under the table projections. As mentioned previously, this follows from the body flattening effects of the table and the fact that table height is the primary determinant of source to skin distance. Because the majority of fluoroscopic images are acquired using an under t he table tube configuration, anthropometric differences are expected to introduce a very acceptable level of uncertainty in most situations. Second, a s the tube rot ates to a more lateral position details about the patient contour become more important. I n these cases, Table 5 3 indicates patient sculpted phantoms provide the best means for estimating peak skin dose. While patient dependent hybrid phantoms proved more effective than using a reference phantom for almost all left lateral and AP projections, the gains were roughly half of what was seen when using the patient sculpted contour models. The ability to adapt to different patient thicknesses also provided a stark contrast between the stylized reference and patient sculpted contour models, both of w hich were based on elliptical stylized surfaces. The fixed 20 cm thickness of the reference version led to large errors which were significantly lessened when a sculpted phantom was used. On a case by case ba sis, the use of contour phantoms was most effect ive in situations where the anthropometric parameters of the patient specific phantom lied outside the bounds of the current patient dependent library. Also in
104 cases where the patient had a unique body type, contour phantoms provided significant improvemen ts in comparison with hybrid phantoms. The patient sculpted models developed in this work represent a simple, but effective approach to patient contour modeling. By adding additional measurements, the specificity of these models could be improved. The pri mary factors to consider for building a better model are how any additional measurement would interrupt the workflow of the interventional suite, how different patient positioning of the arms and torso could be included, and how to better handle female spe cific issues related to breast sizing. The most important modeling aspect to keep in mind, however, is that the contour in contact with the table should be relatively flat. Summary In this study, two patient orientation methods were tested. The first reli ed on a user defined isocenter to orient the phantom and x ray tube, the major benefit being a relatively universal method for alignment. The second method relied on a vendor defined coordinate system independent to organ variation and isocenter selection. Both orientation systems were tested by first establishing a baseline peak skin dose using a variety of different phantom types and th e skin dose mapping program of C hapter 4. Offsets were then applied to test how sensitive each system was to either isoce nter selection or patient setup. Results showed peak skin dose most sensitive to changes which affect the source to skin distance in the direction of the x ray tube For the isocenter based system these changes occur in all direction, thus introducing a un certainty no matter what tube angle is chosen. For the coordinate based system, these changes occur only during lateral and angulated tube angles. The magnitude and associated uncertainty of the changes is also expected to be less using this system. Patie nt ph antom was also tested using s everal different anatomical models including reference hybrid, reference stylized, patient dependent hybrid, and patient sculpted contour
105 phantoms. While patient dependent hybrid phantoms provided better dose estimates than the hybrid reference phantom for lateral and anterior posterior projections, the patient sculpted contour phantoms were clearly superior at producing more accurate skin d ose estimates. These relatively simple models can be refined in future studies but are already accurate to within 1 4% for PA projections, 2 5% for Left lateral projections, and 3 8% for AP projections.
106 Table 5 1 Error using isocentric system when isocenter is incorrectly located within the body.
107 Table 5 2 Error using coordinate bases system when patient location is incorrectly assigned.
108 Table 5 3. Mean absolute percent difference in PSD between patient specific mod els and four different phantom types. Results are grouped according to patient size, tube projection, and orientation.
109 Figure 5 1 Six measurements used to create patient sculpted contour phantoms. Figure 5 2 For each patient specific model, peak skin dose was also calculated for a reference stylized, reference hybrid, patient dependent hybrid, and patient sculpted contour phantom. Accuracy was quantified using the PSD calculated using the patient specific model as the standard.
110 CHAPTER 6 CONCLUSION Result of this work In this research, a framework has been presented for monitoring the radiation dose delivered to patients undergoing interventional fluoroscopic procedures. The topic is significant in that radiation induced burns, categ orized as sentinel event s represent a chief concern in the management of patient risk. Additionally, th e recent release of NCRP Report No. 168 has raised awareness about the marked increase in medical radiation exposures, thus making an attempt to quantify these doses both relevant and timely  The framework began with the introduction of patient dependent phantom s a type of anthropomorphic model based on anthropometric measurements of an individual patient. The concept of a patient de pendent phantom was advanced in order to overcome the limitations of both reference phantoms which lack specific ity, and tomographic based phantoms which lack practical ity The primary goal was to move beyond a one size fits all approach by developing a ri ch library of phantoms from which selections can be made based on patient size. In order to create the library, a methodology was developed based on modifications made to the UF hybrid adult male and female reference phantoms. The modifications were govern ed by anthropometric target values as derived from the NHANES III which was parameterized according to standing height and total body mass. The resulting library includes 25 male and 25 female patient dependent phantoms representing 10 th 25 th 50 th 75 th and 90 th height and weight percentiles. Due in part to the publication of this library several researchers have recognized the limitations of current approach es and have begun focusing on size adjustable phantoms. In addition to the work do ne in this pro ject two other groups have recently published papers dealing with patient dependent phantoms [54, 55, 76]
111 The second step in the overall framework was to investigate the concept of patient phantom matching for estimating a more accurate organ dose. In this step, 27 patient specific phantoms were created from segmented CT datasets and matched based on he ight and weight to patient dependent phantoms. The organ dose conversion coefficients which were calculated using these phantoms were compared using the patient specific coefficients as a gold standard. The results indicated two sources of inaccuracy when phantoms are used to represent individual patients. These include uncertainty associated with variability in organs size and location, and error associated with differences in soft tissue attenuation. Both conclusions help frame the argument for building b etter phantoms. On one hand, phantoms are limited by a residual uncertainty which reduces the need for non uniform, organ specific adjustments. On the other hand, patient phantom matching was shown uniquely suited fo r improving the dose estimates of large patient, thus necessitating the expansion of the patient dependent library to higher weight percentiles The latter point will be discussed in the further developments section The third step in the framework for building a better dose monitoring system wa s the development of two programs, the first to map skin dose and the second to automatically create Monte Carlo input files for organ dose assessment Both programs utilize the radiation dose structured report which provides information needed to describ e the physical context of each irradiation event. The skin dose mappi ng program functions by calculating the distance from the source to each in beam, skin voxel of a given phantom. The reference point dose is then translated to each location using a one o ver distance squared correction and factors for backscatter and absorption differences. The output of the program is a surface plot of dose overlaid on an anth ropomorphic model. As seen in Figure 4 5 the purpose of the visual display is to allow the oper ator to monitor patient skin dose and adjust the pro cedure when clinically
112 necessary. The initial program represents the first step towards the full realization of this goal. The horizon fo r clinical implementation is dependent upon the technology transfer from research tool to clinical software package. Progress is already being made in that the entire code has been ported from MATLAB to the more general purpose programming language Python. Additionally, C hapter 4 outlined a number of challenges going forw ard which can be readily addressed either through further refinement to the program or through updates by the DICOM Committee. The second program developed in this research focuses on organ dose by translating the RDSR into an MCNPX input file. The code w as designed to do this automatically by first summarizing an RDSR into a limited n umber of irradiation events, and then configuring the parameters of each event as input cards within an MCNPX template file. The program has great potential for initiating and promoting the co specific Monte Carlo radiation transport is performed off site and returned via the internet. Much work needs to be done in this area, but the developed program has pro ved the utility of the RDSR for designing such a system. In considering these developments, the overall result of this work is an expanded understanding of how computational phantoms can be used to provide better dose estimation for interventional fluoros copic procedures. The framework places heavy emphasis on increasing patient specificity in areas where improvements can be expected ( skin dose mapping for all patients and organ dose estimation for large patients) and on designing software tools that are n on proprietary, transferable, and utilize leading edge technology. In order to advance these concepts further, the following section outlines several areas for additional development
113 Opportunities for Further Development Additional Patient Dependent Phant oms In this work, patient dependent phantoms were shown to have the greatest impact when the anthropometric parameters of an individual patient were largely different than those of the reference phantom This was most obvious when calculating organ dose for very large patients. In a number of instances, the height and/or weight of the patient exceeded the limits of the 50 member patient dependent library. Additionally, the parameters found in the 1988 19 94 NHANES III database may not best reflect the height and weight percentiles of the current 2010 2011 population. In order to address these issues, two steps can be taken. First, recent updates to the NHANES database have become available which include an thropometric parameters collected between the years 1999 2010. This data can be used to supplement the current database and will help reduce problems related to the averaging of secondary parameters for very large and very small patients. Following a norma l distribution, the number of patients found at these extremes was previously very low. By increasing the overall number of patients in the database, more individuals will be found at these height and weights. This will help reduce the variance when second ary parameters (sitting height, arm, thigh, waist, buttock circumference) are determined according to a simple average of all patients found at a given size. Second, because patients are matched by height and weight and not by percentile, the library can be restructured to include phantoms at several increments instead of percentiles. As an example, a 183 cm / 100 kg man seen in 1990 may represent a 90 th percentile by height and weight male patient. Due to increasing obesity rates however, in 2010 a 183 cm /100 kg man may represent 90 th percentile by height but 80% by weight male patient. While the percentiles have changed, a patient with identical height and weight will likely also have similar secondary anthropometric parameters. Thus by restructuring the library according to stepped increments,
114 the total number of patients included in the anthropometric database can be increased regardless of changes in patient size which have occurred in the population between 1988 and 2010. Using an incremental structure, the patient dependent library can be expanded to include several more phantoms. The increment need not be uniform and can include finer gradations for the overweight adults The library will help better define the current population and can be c ontinually updated as new data is made available. Patient Sculpted Phantoms As discussed in Chapter 5, additional refinements to patient sculpting may improve certain aspects of skin dose mapping, namely error reduction for lateral and anterior posterior p rojections. By adding additional measurements, a better stylistic description could be achieved. While the elliptical shaped, patient sculpted contour phantoms add a level of innovation to this work, a number of steps can be taken to improve this aspect. F irst, scripting tools within the modeling program Rhinoceros may allow for the automated sculpting of hybrid phantoms. Unlike stylized contour models, patient sculpted hybrid phantoms would have a set of organs linked directly to reference values. These ph antoms could thus be used to improve organ dosimetry as well as skin dose mapping. The challenge is first to adapt the Rhinoceros scripting language for these purposes, and second, to develop a path from Rhinoceros to voxelization which can be automated in a timely fashion. A second step is to investigate the use of the Civilian American and European Surface Anthropometry Resource (CAESAR) for additional patient contours  This commercial database contains 1D anthropometric measurements and 3D model scans of 2,400 male and female su bjects between the ages 18 65. The benefit of the CAESAR library is having a multitude of patient contours from which to choose. If the library can be automatically searched based on in clinic patient specific measurements, it may limit the need for patien t sculpting.
115 Contours selected from the CAESAR database could be used for skin dose mapping but not organ dose estimation as they only provide a surface with no definable internal structure. The last and most ambitious plan is to determine patient specific contours using 3D scanning hardware. Several options exist including structured light scanners, hand held lasers, triangulation methods, and time of flight scanners. The cost is, however, somewhat prohibitive as is any change to the clinical workflow that would be necessary to implement such a system. While costly and complex, the idea is conceivable for a large research oriented hospital. Figure 6 1 show s the Cyberware WB4 scanner (est. cost $410,000) used by the CAESAR project. Such a scanner could be in stalled within a Radiology department and used to scan interventional patients prior to examination. The current cost estimate for the newer Cyberware WBX model is lower at $225,000. Another option would be to expand the utilization of the scanner to other university or institutional departments who would be able to share time and help defray cost. Any step in this direction would represent a large undertaking, but the added novelty of using such a scanner may help garner high marks for innovation during a NIH scientific review. Skin Dose Mapping in Real Time Currently, RDSRs are accessibly only after the close an exam. As a consequence, peak skin dose cannot be calculated during the procedure or used to monitor patient risk. Streaming is already built into the IEC/DICOM specification but has yet to be formally adapted for the RDSR. IHE REM (Radiation Exposure Monitoring) does not yet define an online dose reporting case, and also sending the full Dose SR for that purpose consecutive to each run may be seen as an may help to refine this use case and derive requirements for m aintaining changes to the DICOM Standard and potentially to the IHE REM profile  From this statement it is evident that the
116 successful development and implementation of dose monitoring systems from both this study and others like it will help encourage the expansion of real time reporting for the RDSR. In order to preliminarily test a real time system, streaming can be simulated using time stamps provided by the RDSR. In this way, the software can be optimi zed. The current skin dose m apping system was designed with these thoughts in mind and is fully capable of rendering dose maps at intervals of less than one second. Physical Validation In order provide physical validation for the programs developed in this work, both skin and organ d ose can be calculated using the NURBS based physical phantoms which have been developed at UF. These phantoms which represent physical replicas of both the UF hybrid adult male and female reference phantoms were constructed slice by slice using soft tissue lung, and bone equivalent material at a resolution of 5 mm  To measure radiation dose both internally and externally, a fiber optic coupled (FOC) dosimetry system has also been developed at UF  The system has been used to calculate organ dose during cone beam CT used in radiation therapy, and has demonstrated the ability to provide radiation dose estimates in real time  Using the FOC system, both skin dose and organ dose can be measured phy sically and compared to values derived using the UFHADM, UFHADF and the programs outlined in Chapter 4. Additional validation of skin dose can be performed u sing Gafchromic film as performed in previous studies [82, 83] Clinical Application Along with sentinel event dose reconstruction, monitoring of diagnostic reference levels, and training of medical residents, a primary use of the skin dose mapping syst em will be the developme nt of better techniques and practices to reduce the radiation burden delivered to the patient. A major focus of the Department of Radiology at the University of Florida in Gainesville
117 has been the standardization of imaging protocol s which define best practices for specific imaging procedures  The skin dose mapping system developed in this work can aid in creation of these protocols f or fluoroscopically guided interventions By providing the physician a high fidelity estimation of peak skin dose and expected effects, the angulation and rotation of the x The significance o f dose reduction to the patient can be analyzed through clinical studies whereby dose saving protocols are implemented and compared to standard protocols using the skin dose mapping program. As a long term vision, a comprehensive clinical program can be de veloped built around strategies for dose reduction to include all of the items listed previously. Techniques and practices learned through this program can then be shared with other radiology departments and medical societies to improve patient care on a l arge scale. Cloud Dosimetry During the previous 5 years, computational architecture has trended towards data access, storage, and services which utilize resources not maintained by the end user. These resources are access ed with the tools developed in this research, RDSRs can be uploaded from the clinic to the web and returned with a matter of hours as detailed radiation dose reports. The c oncept of patient dose tracking has been popularized in recent years with the introduction of the Smart Card project by the International Atomic Energy Agency (IAEA)  The goal is to design a small card that of meetin g of the IAEA held in January 2010, several project recommendations were put forth development and
118 from medical imaging  Clearly, a cloud based dosimetry model fits well within the constructs of the Smart Card project and provides the mechanism needed for dose evaluation. While the RDSR was designed specifically for fluoroscopy, similar DICOM objects are being developed for CT and other forms of diagnostic imaging which utilize ionizing radiation. Future research should focus on developing translational tools for these modalities which can provide dose estimates based on patient d ependent or sculpted phantoms and dose parameters obtained through the DICOM format. A pilot program for interventional dose estimation using the software developed in this research would also provide a first use case which could be followed by other insti tutions. Final Thoughts A consistent effort has been made throughout this study to focus on clinically relevant solutions. Often this required the willingness to adapt when limitations were realized and to explore new options which were not always pr esently available. As an example, much of the skin dose mapping software was written before the RDSR was released. By proactively learning about and planning for the RDSR, the entire project was able to move away from video analysis and OCR techniques whic h had severely diminished the promise for in clinic dosimetry. Another important component was the collaboration with outstanding radiology d epartments at both Shands Jacksonville and Columbia University Medical Center. These collaborations provided an imp ortant link to the interventional clinic and also helped establish contacts with vendors, physicians, and scientific experts with in the field. A continued partnership with both institutions will be necessary as progress is made towards clinical implementat ion. A final point to reiterate is the important context of this research. Due to the current lack of automated dose monitor ing,
119 clinically relevant dosimetric information is being denied to the physician who must then re ly on indirect dose indicators alon g with their clinical experience to manage patient risk. Using the tools developed in this work there exist a tangible opportunity to improve patient care. The end goal is a better understanding of the risk/benefit relationship that accompanies the medica l use of ionizing radiation
120 Figure 6 1 Cyberware Whole Body Color 3D Scanner. Such a scanner could provide patient specific body contours for us with skin dose mapping software.
121 LIST OF REFERENCES  M. M. Payne, "Charles Theodore Dotter. The father of intervention," Tex Heart Inst J, vol. 28, pp. 28 38, 2001.  NCRP, "Ionizing radiation exposure of the population of the United States, National Council on Radiation Protection and Measurement," Nation al Council on Radiation Protection and Measurement, Bethesda, MD Report No. 160, 2009.  BEIR, "Health risks from exposure to low levels of ionizing radiation: BEIR VII Phase 2," National Research Council, Washington, DC Report No. 7, 2006.  E. S. A mis, Jr., P. F. Butler, K. E. Applegate, S. B. Birnbaum, L. F. Brateman, J. M. Hevezi, F. A. Mettler, R. L. Morin, M. J. Pentecost, G. G. Smith, K. J. Strauss, and R. K. Zeman, "American College of Radiology white paper on radiation dose in medicine," J Am Coll Radiol, vol. 4, pp. 272 2 84, 2007.  ICRP, "Avoidance of radiation injuries from medical interventional procedures," International Commission on Radiological Protection, Elmsford, New York Publication 85, 2000.  A. D. Meade, A. Dowling, C. Walsh and J. F. Malone, "Draft proposal for three international standards for Dose Area Product (DAP) measurement, patient dose records and connectivity between equipment," DIMOND III, Dublin, Ireland 2004.  UNSCEAR, "Medical radiation exposures," United Na tions Scientific Committee on the Effects of Atomic Radiation, New York, New York 2008.  D. L. Miller, S. Balter, P. E. Cole, H. T. Lu, B. A. Schueler, M. Geisninger, A. Berenstein, R. Albert, J. D. Georgia, P. T. Noonan, J. F. Cardella, J. St. George, E. J. Russell, T. W. Malisch, R. L. Vogelzang, G. L. Miller, and J. Anderson, "Radiation doses in interventional radiology procedures: the RAD IR Study, Part I: Overall measures of dose," J Vasc Interv Radiol, vol. 14, pp. 711 727, 2003.  M. S. Stecker, S. Balter, R. B. Towbin, D. L. Miller, E. Vano, G. Bartal, J. F. Angle, C. P. Chao, A. M. Cohen, R. G. Dixon, K. Gross, G. G. Hartnell, B. Schueler, J. D. Statler, T. de Ba¨re, and J. F. Cardella, "Guidelines for Patient Radiation Dose Management," Journ al of vascular and interventional radiology : JVIR, vol. 20, pp. S263 S273, 2009.  D. L. Miller, S. Balter, L. K. Wagner, J. Cardella, T. W. I. Clark, C. D. Neithamer, M. S. Schwartzberg, T. L. Swan, R. B. Towbin, K. S. Rholl, and D. Sacks, "Quality Im provement Guidelines for Recording Patient Radiation Dose in the Medical Record," Journal of vascular and interventional radiology : JVIR, vol. 15, pp. 423 429, 2004.  S. Balter, J. W. Hopewell, D. L. Miller, L. K. Wagner, and M. J. Zelefsky, "Fluorosc opically guided interventional procedures: a review of radiation effects on patients' skin and hair," Radiology, vol. 254, pp. 326 3 41, 2010.
122  The Joint Commission, "Sentinenl Event Policies and Procedures," [Online] http://www.jointcommission.org/assets/1/6/2011_CAMH_SE.pdf Accessed April 4, 2011  J. Anderson, G. Arbique, and J. Guild, "TU A 202 01: Peak Skin Dose Reconstruction and TJC Sentinel Event," in AAPM National Mee ting Philadelphia, PA: AAPM, 2010.  A. Jones, "TH A 202 01: Risks in IR and Establishing a Patient Safety Program," in AAPM National Meeting Philadelphia, PA: AAPM, 2010.  Y. Khodadadegan, M. Zhang, W. Pavlicek, R. G. Paden, B. Chong, B. A. Schuele r, K. A. Fetterly, S. G. Langer, and T. Wu, "Automatic Monitoring of Localized Skin Dose with Fluoroscopic and Interventional Procedures," J Digit Imaging, 2010.  IEC, "Medical electrical equipment Part 2 43: Particular requirements for the safety of x ray equipment for interventional procedures," International Electrotechnical Commission, Geneva, Switzerland Vol No. 60601, 2000.  FDA, "Federal performance standard for diagnostic x ray systems and their major components final rule," U.S. Food an d Drug Administration, Silver Spring, MD Fed Regist 70, 2005.  S. H. Stern, M. Rosenstein, L. Renaud, and M. Zankl, "Handbook of selected tissue doses for fluoroscopic and cineangiographic examination of the coronary arteries," Food and Drug Administra tion, Rockville, MD Report 95 8288, 1995.  D. Hart, D. G. Jones, and B. F. Wall, "Estimation of effective dose in diagnostic radiology from entrance surface dose and dose area product measurement," National Radiological Protection Board, Chilton, UK NR PB R262, 1994.  C. Lee, C. Lee, and W. Bolch, "Age dependent organ and effective dose coefficients for external photons: A comparison of stylized and voxel based pediatric phantoms," Phys Med Biol, vol. 51, pp. 4663 4688, 2006.  A. Bozkurt and D. B or, "Simultaneous determination of equivalent dose to organs and tissues of the patient and of the physician in interventional radiology using the Monte Carlo method," Phys Med Biol, vol. 52, pp. 317 3 30, 2007.  H. Schlattl, M. Zankl, and N. Petoussi H enss, "Organ dose conversion coefficients for voxel models of the reference male and female from idealized photon exposures," Phys Med Biol, vol. 52, pp. 2123 21 45, 2007.  S. H. Park, J. K. Lee, and C. Lee, "Dose conversion coefficients calculated using tomographic phantom, KTMAN 2, for X ray examination of cardiac catheterisation," Radiat Prot Dosimetry, vol. 128, pp. 351 35 8, 2008.
123  R. E. Morrell and A. T. Rogers, "A m athematical model for patient skin dose assessment in cardiac catheterization procedures," The British Journal of Radiology, vol. 79, pp. 756 761, 2006.  A. den Boer, P. J. de Feijter, P. W. Serruys, and J. R. T. C. Roelandt, "Real time quantification and display of skin radiation during coronary angiography and intervention," Circulation, vol. 104, pp. 1779 1784, 2001.  C. Lee, C. Lee, J. L. Williams, and W. E. Bolch, "Whole body voxel phantoms of paediatric patients UF Series B," Phys Med Biol, vol. 51, pp. 4649 4661, 2006.  M. Cristy, "Mathematical phantoms representing children of various ages for use in estimates of internal dose," Oak Ridge National Laboratory, Oak Ridge, Tennessee ORNL/NUREG/TM 367, 1980.  C. Lee, D. Lodwick, J. L. W illiams, and W. E. Bolch, "Hybrid computational phantoms of the 15 year male and female adolescent: applications to CT organ dosimetry for patients of variable morphometry," Med Phys, vol. 35, pp. 2366 2382 2008.  R. Kramer, H. J. Khoury, and J. W. Vie ira, "Comparison between effective doses for voxel based and stylized exposure models from photon and electron irradiation," Phys Med Biol, vol. 50, pp. 5105 5126, 2005.  R. Veit and M. Zankl, "Influence of patient size on organ doses in diagnostic radiology," Radiat. Prot. Dosim., vol. 43, pp. 241 243, 1992.  R. Veit and M. Zankl, "Variation of organ doses in pediatric radiology due to patient diameter calculated with phantoms of varying voxel size," Radiat. Prot. Dosim., vol. 49, pp. 353 356, 1993.  M. Zankl, W. Panzer, and C. Herrmann, "Calculation of patient doses using a human voxel phantom of variable diameter," Radiation Protection Dosimetry, vol. 90, pp. 155 158, 2000.  C. Lee, D. Lodwick, D. Hasenauer, J. L. Williams, C. Lee, and W. E. Bolch, "Hybrid computational phantoms of the male and female newborn patient: NURBS based whole body models," Phys Med Biol, vol. 52, pp. 3309 33 33, 2007.  C. Lee, D. L odwick, J. Hurtado, D. Pafundi, J. L. Williams, and W. E. Bolch, "The UF family of reference hybrid phantoms for computational radiation dosimetry," Phys Med Biol, vol. 55, pp. 339 3 63, 2010.  K. Chugh, P. Dinu, D. R. Bednarek, D. Wobschall, S. Rudin, and K. Hoffmann, "A computer graphic display for real time operator feedback during interventional x ray procedures," Proceedings of SPIE, vol. 5367, pp. 464 473, 2004.
124  P. J. Kicken, G. J. Kemerink, P. J. Vaessen, and J. J. Ackermans, "An Automated Me asurement System for Characterisation of Patient Exposure During Angiography," Radiat Prot Dosimetry, vol. 43, pp. 165 169, 1992.  K. Bacher, E. Bogaert, R. Lapere, D. De Wolf, and H. Thierens, "Patient specific dose and radiation risk estimation in pe diatric cardiac catheterization," Circulation, vol. 111, pp. 83 8 9, 2005.  N. A. Gkanatsios, W. Huda, K. R. Peters, and J. A. Freeman, "Evaluation of an on line patient exposure meter in neuroradiology," Radiology, vol. 203, pp. 837 8 42., 1997.  N. A. Gkanatsios, W. Huda, and K. R. Peters, "Adult patient doses in interventional neuroradiology," Med Phys, vol. 29, pp. 717 7 23, 2002.  M. Mahesh, "Fluoroscopy: patient radiation exposure issues," Radiographics, vol. 21, pp. 1033 10 45, 2001.  M. Toivonen and T. Komppa, "Report on methods of evaluating local skin dose in interventional radiology," Dimond 3 WP3.1, STUKA Radiation and Nuclear Safety Authority, Helsinki, Finland, 2004.  R. Morrell, "Dosimetry and optimisation in high dose fluoro scopic and fluorographic procedures Nottingham, UK: University of Nottingham, 2006.  O. H. Suleiman, J. Anderson, B. Jones, G. U. Rao, and M. Rosenstein, "Tissue doses in the upper gastrointestinal fluoroscopy examination," Radiology, vol. 178, pp. 653 658, 1991.  R. J. Staton, J. L. Williams, M. M. Arreola, D. E. Hintenlang, and W. E. Bolch, "Organ and effective doses in infants undergoing upper gastrointestinal (UGI) fluoroscopic examination," Med Phys, vol. 34, pp. 703 710, 2007.  F. D. Pa zik, R. J. Staton, D. E. Hintenlang, M. M. Arreola, J. L. Williams, and W. E. Bolch, "Organ and effective doses in newborns and infants undergoing voiding cystourethrograms (VCUG): A comparison of stylized and tomographic phantoms," Med Phys, vol. 34, pp. 294 306, 2007.  E. Vano, R. Padovani, G. Bernardi, J. I. Ten, A. Peterzol, A. Dowling, H. Bosmans, S. Kottou, Z. Olivari, K. Faulkner, and S. Balter, "On the use of DICOM cine header information for optimisation: results from the 2002 European DIMOND c ardiology survey," Radiat Prot Dosimetry, vol. 117, pp. 162 16 5, 2005.  E. Vano, R. Padovani, V. Neofotistou, V. Tsapaki, S. Kottou, J. I. Ten, J. M. Fernandez, and K. Faulkner, "Improving patient dose management using DICOM header information. The Eur opean SENTINEL experience," in proceedings IEEE ITAB, 2006.
125  DICOM Standards Committee Working Group 6, "Supplement 94: Diagnostic x ray radiation dose reporting (Dose SR)," Digital Imaging and Communications in Medicine, Rosslyn, Virginia 2005.  I EC, "Medical electrical equipment Radiation dose documentation Part 1: Equipment for radiography and radioscopy," International Electrotechnical Commission, Geneva, Switzerland 2007.  IHE Radiological Technical Framework, "Radiation Exposure Monito ring (REM) Integration Profile," Integrating the Healthcare Enterprise, Illinois, USA 2008.  W. P. Segars, D. S. Lalush, and B. M. W. Tsui, "A realistic spline based dynamic heart phantom," IEEE Trans Nucl Sci, vol. 46, pp. 503 506, 1999.  Blender Foundation, Blender, [Online] http://www.blender.org Accessed November 4, 2010  MakeHuman Team, "MakeH uman, [Online] http://makehuman.org Accessed October 12, 2010  V. F. Cassola, V. J. Lima, R. Kramer, and H. J. Khoury, "FASH and MASH: female and male adult human phantoms based on polygon mesh surfaces: I. Development of the anatomy," Phys Med Biol, vol. 55, pp. 133 1 62, 2010.  J. Zhang, Y. H. Na, P. Caracappa, and G. Xu, "RPI AM and RPI AF, a pair of mesh based, size adjustable adult male and female computational phantoms using ICRP 89 parameters and their calculations for organ doses form monoengergetic photon beams," Phys Med Biol, vol. 54, pp. 5885 5908, 2009. [ 56] ICRP, "Basic anatomical and physiological data for use in radiological protection: reference values," International Commission on Radiological Protection, Elmsford, New York Publication 89, 2002.  A. Servomma, S. RAnnikko, V. Nikitin, V. Golikov, I Ermakov, L. Marsarskyi, and L. Saltukova, "A topographically and anatomically unified phantom model for organ dose determination in radiation hygiene," Finnish Center for Radiation and Nuclear Safety, Helsinki, Finland STUK A87, 1989.  ICRU, "Photon, electron, proton and neutron interaction data for body tissues," International Commission on Radiation Units and Measurements, Bethesda, MD Report 46, 1992.  G. L. de la Grandmaison, I. Clairand, and M. Durigon, "Organ weight in 684 adult autopsies: n ew tables for a Caucasoid population," Forensic Sci Int, vol. 119, pp. 149 1 54, 2001.
126  Yuji Matsuzawa, Iichiro Shimomura, Tadashi Nakamura, Yoshiaki Keno, and Katsuto Tokunaga, "Pathophysiology and Pathogenesis of Visceral Fat Obesity," Annals of the N ew York Academy of Sciences, vol. 748, pp. 399 406, 1994.  C. J. Tung, C. J. Lee, H. Y. Tsai, S. F. Tsai, and I. J. Chen, "Body size dependent patient effective dose for diagnostic radiography," Radiat Meas, vol. 43, pp. 1008 1011, 2008.  P. Johnson, C. Lee, K. Johnson, D. Siragusa, and W. E. Bolch, "The influence of patient size on dose conversion coefficients: a hybrid phantom study for adult cardiac catheterization," Phys Med Biol, vol. 54, pp. 3613 36 29, 2009.  M. Zankl, U. Fill, N. Petoussi Henss, and D. Regulla, "Organ dose conversion coefficients for external photon irradiation of male and female voxel models," Phys Med Biol, vol. 47, pp. 2367 2385, 2002.  D. B. Pelowitz, "MCNPX User's Manual, Version 2.6.0," Los Alamos Nation al Laboratory, Los Alamos, New Mexico 2008.  M. Rosenstein, O. H. Suleiman, R. L. Burkhart, S. H. Stern, and G. Willims, "Handbook of selected tissue doses for the upper gastrointestinal fluoroscopic examination," Food and Drug Administration, Rockvill e, MD 92 8282, 1992.  K. Cranley, B. J. Gilmore, G. W. A. Fogarty, and L. Desponds, "Catalogue of diagnostic x ray spectra and other data," The Institute of Physics, 1997.  E. Han, W. Bolch, and K. Eckerman, "Revisions to the ORNL series of adult a nd pediatric computational phantoms for use with the MIRD schema," Health Phys, vol. 90, pp. 337 356, 2006.  DIMOND III Group, "DIMOND III Project," [Online] http://www.dimond3.org/WEB_DIMOND3/ho me.htm Accessed March 15, 2011  Python Software Foundation, Python, [Online] http://www.python.org Accessed December 2, 2010  ICRU, "Patient Dosimetry for X Rays used in Medical Imaging," International Commission on Radiation Units a nd Measurements, Bethesda, Maryland Report 74, 2005.  J. Hubbell and S. Seltzer, "Tables of x ray mass attenuation coefficients and mass energy absorption coeffi cients (Version 1.4)," [Online] ht tp://www.nist.gov/pml/data/xcom/index.cfm Accessed September 13, 2005  B. Schueler, "Patient dose and the modern angiographic system," in AAPM National Meeting Philadelphia, PA, 2010.  W. R. Geiser, W. Huda, and N. A. Gkanatsios, "Effect of pa tient support pads on image quality and dose in fluoroscopy," Med Phys, vol. 24, pp. 377 3 82, 1997.
127  S. Balter, "Capturing patient doses from fluoroscopically based diagnostic and interventional systems," Health Phys, vol. 95, pp. 535 5 40, 2008.  N CRP, "Radiation Dose Management of Fluoroscopically Guided Interventional Medical Procedures," National Council on Radiation Protection and Management, Bethesda, Maryland Report 168, 2011.  Y. H. Na, B. Zhang, J. Zhang, P. F. Caracappa, and X. G. Xu, Deformable adult human phantoms for radiation protection dosimetry: anthropometric data representing size distributions of adult worker populations and software algorithms," Phys Med Biol, vol. 55, pp. 3789 3 811, 2010.  Civilian American and European S urface Anthropometry Resource Project, "CAESAR 3 D Anthropometric Database," [Online] http://store.sae.org/caesar Accessed April 2, 2011  H. Blendinger, Siemens AG, "Personal correspondence," September 2009.  J. F. Winslow, D. E. Hyer, R. F. Fisher, C. J. Tien, and D. E. Hintenlang, "Construction of anthropomorphic phantoms for use in dosimetry studies," J Appl Clin Med Phys, vol. 10, p. 2986, 2009.  D. E. Hyer, R. F. Fisher, and D. E. Hintenlang, "Characterization of a water equivalent fiber optic coupled dosimeter for use in diagnostic radiology," Med Phys, vol. 36, pp. 1711 171 6, 2009.  D. E. Hyer and D. E. Hintenlang, "Organ Doses From Cone Bea m CT in Radiation Therapy," Med Phys, vol. 36 6, p. 2437, 2009.  V. Rana, D. Bednarek, M. Josan, and S. Rudin, "SU F BRA 9: Comparison of skin dose distributions calculated by a real time dose tracking system with that measured by gafchromic film for a fluoroscopic c arm unit," in AAPM National Meeting Vancouver, Canada: AAPM, 2011.  J. F. Dempsey, D. A. Low, S. Mutic, J. Markman, A. S. Kirov, G. H. Nussbaum, and J. F. Williamson, "Validation of a precision radiochromic film dosimetry system for qua ntitative two dimensional imaging of acute exposure dose distributions," Med Phys, vol. 27, pp. 2462 24 75, 2000.  University of Florida Department of Radiology, Standard Names for Imaging Procedures, [Online] https://projects.ctrip.ufl.edu/protocols/snips/index.php Accessed June 1, 2011  International Atomic Energy Agency, "Smart Card/SmartRad Track Project," [Online] http://rpop.iaea.org/RPOP/RPoP/Content/News/smart card project.htm Accessed April 2, 2011
128  International Atomic Energy Agency, "Recommendations Emerging from the 2nd Meetin g of the IAEA Smart Card/SmartRadTrack Project," [Online] http://rpop.iaea.org/RPOP/RPoP/Content/Documents/Whitepapers/recommendations smartradtrac k.pdf Accessed April 2, 2011
129 BIOGRAPHICAL SKETCH Perry Barnett Johnson was born in Augusta, GA to parents Barney and Melissia Johnson. Along with his younger siblings Alex and Laura, Perry grew up in the southeast, eventually attending high school in Owensboro, Kentucky where he played football and subsequently graduated as the 2002 Daviess County High S chool Honor Graduate. Perry pursued an engineering education from the Georgia Institute of Technolo gy, receiving his B.S. degree in nuclear and radiological engineering, Summa cum L aude While at Georgia Tech, Perry completed research internships at Lawrence Livermore National Laboratory and St. Jude aged him to continue on to graduate research and after receiving his M.S. in medical physics from Georgia Tech, Perry enrolled at the University of Florida to complete a research doctorate. While at UF, Perry was a part of nine publications (five as first author), a NIH grant submission, and recipient of several awards for undergraduate mentorship, scholastic achievement, and publication record. Perry earned his Ph.D. degree in 2011 and accepted a therapeutic medical physics residency position at M.D. Ander son Cancer Center Orlando.