Group Title: radiation dosimetry model for radiolabeled monoclonal antibodies : b Indium-111 labeled B72.3-GYK-DTPA for colorectal cancer /
Title: A Radiation dosimetry model for radiolabeled monoclonal antibodies : b Indium-111 labeled B72.3-GYK-DTPA for colorectal cancer
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 Material Information
Title: A Radiation dosimetry model for radiolabeled monoclonal antibodies : b Indium-111 labeled B72.3-GYK-DTPA for colorectal cancer
Alternate Title: Computerized radiation dosimetry model for radiolabeled monoclonal antibodies : b Indium-111 labeled B72.3-GYK-DTPA for colorectal cancer
Physical Description: xiii, 181 leaves : ill. ; 29 cm.
Language: English
Creator: Wilson, Latresia Ann, 1963-
Publication Date: 1990
Copyright Date: 1990
 Subjects
Subject: Radiation dosimetry   ( lcsh )
Monoclonal antibodies   ( lcsh )
Environmental Engineering Sciences thesis Ph. D
Dissertations, Academic -- Environmental Engineering Sciences -- UF
Genre: bibliography   ( marcgt )
non-fiction   ( marcgt )
 Notes
Thesis: Thesis (Ph. D.)--University of Florida, 1990.
Bibliography: Includes bibliographical references (leaves 140-153).
Additional Physical Form: Also available on World Wide Web
General Note: Typescript.
General Note: Vita.
Statement of Responsibility: by Latresia Ann Wilson.
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Bibliographic ID: UF00097390
Volume ID: VID00001
Source Institution: University of Florida
Holding Location: University of Florida
Rights Management: All rights reserved by the source institution and holding location.
Resource Identifier: alephbibnum - 001677521
oclc - 24887687
notis - AHY9426

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A RADIATION DOSIMETRY MODEL FOR
RADIOLABELED MONOCLONAL ANTIBODIES:
INDIUM-111 LABELED B72.3-GYK-DTPA
FOR COLORECTAL CANCER

















By

LATRESIA ANN WILSON


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


1990






























Copyright 1990

by

Latresia A. Wilson








ACKNOWLEDGEMENTS


First and foremost, I would like to thank my family for

their love and support throughout the years. I would

especially like to thank my uncle, Manuel Lewis Jr., for his

wisdom and support; my grandmother, Lula Lewis, for her

patience and understanding; my mother, Geraldine Solomon, for

her encouragement and support; my aunts, Evelyn Scott and

Marilyn Johnson, for believing in me; and my cousins for their

encouragement.

I would especially like to thank Dr. Genevieve Roessler

for believing and supporting me during the rough years. I am

very thankful to my advisor, Dr. William Properzio, for his

superb guidance and support throughout this study. I am also

grateful to my advisory committee, Dr. Emmett Bolch, Dr.

Walter Drane, Dr. David Hintenlang, and Evelyn Watson, for

their guidance and help in this project.

I would like to thank Evelyn Watson and the staff (Mike

Stabin, Audrey Schlafke-Stelson, Fanny Smith, and Stan Walls)

of the Radiopharmaceutical Internal Dosimetry Center of Oak

Ridge Associated Universities. I would like to thank Oak Ridge

SAssociated Universities for giving me the opportunity and

resources to learn from the best in my field. I would like to

especially thank Martha Kahl and Rana Yalcintes in the medical

iii





library of Oak Ridge Associated Universities for their

excellent support. I would like to thank the staff of the

Nuclear Medicine Department at the University of Tennessee

Hospital for their guidance, patience, and use of their

equipment. I would like to thank Phyllis Cotten, Carmine

Plott, James Stubbs, Pat Harp Family, and the Rose Foster

Family for making my stay in Tennessee an enjoyable one.

I would like to thank Dr. Steven Harwood, Michelle

Morrissey, Linda Zangara, Dr. Will Webster, Dr. Carroll and

Dave Laven and staff of the Nuclear Medicine Department at Bay

Pines Veterans Administrative Medical Center in Bay Pines,

Florida for providing the patient data, use of their

facilities, and financial and expert support in this project.

I would like to thank the people of the Department of

Environmental Engineering Sciences, Dr. Charles Roessler and

fellow graduate students for their encouragement and support.

I would like to also thank Dr. Libby Brateman for being there

to answer all my seemingly endless number of questions and for

providing support.

I would like to thank Dean Rodrick McDavis for his

continued support. And last, I would like to thank the

McKnight Foundation and the Florida Endowment Fund for Higher

Education, Dr. Israel Tribble and staff, for their financial

support for without which, this degree would never have been

undertaken.





TABLE OF CONTENTS

page

ACKNOWLEDGMENTS ............... ......................... iii

LIST OF TABLES ........................ ................ vii

LIST OF FIGURES .......................................... ix

ABSTRACT .......... ................ ..................... xi

CHAPTERS

1 INTRODUCTION ........................................ 1

2 MONOCLONAL ANTIBODIES .............................. 6

Immunoglobulin Structure ..................... 9
Variables Associated with Radioimmunoimaging
and Radioimmunotherapy ................. 14
Tumor Localization ..................... 17
Choice of Radiolabel ............... 18
Tumor Size Effect ................. 24
Fragment vs Whole Antibody ........ 25
Dose Administered Effect ........... 27
Labeling Method Effect ............. 28
Dose Administration Route .......... 29
Tumor Biology .... .................. 30
Other Factors .... .................. 31

3 RADIATION DOSIMETRY .... ........................... 34

MIRD Approach .................................. 36
"Traditional" Point Kernal Method ............ 38
Microdosimetry ................................. 41

4 MATERIALS AND METHODS ........ .................... 47

SPECT Model .................................... 49
Monte Carlo Model ........................... 49
Dosimetry Model ................................ 51
Single-Photon Emission Computed Tomography ... 51
SPECT Quantitation ............................. 53
Photon Attenuation ........................... 54
Photon Scatter .................................. 56
SPECT Camera System .......................... 57
Image Segmentation ......... ................... 58
Program SPECTDOSE .............................. 60
Subroutine THOLD .......... ................ 63
Subroutine CONTOUR ..................... 63
Subroutine OBJSELECT ................... 63






Subroutine CORGAN ............
Subroutine VOXFIL ............
Program ALGAMP ....................
Pixel and Slice Size Determination
Phantom Studies ...................
Phantom Study One ............
Phantom Study Two ............
Phantom Study Three ..........
Thermoluminescent Devices ....
Clinical Studies ..................
Patients .....................
Monoclonal Antibody ..........
Monoclonal Antibody Procedure
Blood Analyses ...............


HPLC Procedure ..........................
Image Analysis ..........................


5 RESULTS AND DISCUSSION ............................

Pixel and Slice Size Determination ...........
Phantom Study One ............................
Phantom Study Two ............................
Phantom Study Three ..........................
Clinical Study ...............................

6 SUMMARY AND CONCLUSIONS ...........................

REFERENCES .............................................

APPENDICES

A SAMPLE CALCULATIONS................................

B TLD CALIBRATION................................... ..

C SPECTDOSE PROGRAM .................................

BIOGRAPHICAL SKETCH ....................................


...........


...........

...........
...........
...........
...........
...........
...........
...........
...........
...........


154

157

158

181


67
69
69
72
73
74
76
80
84
85
85
86
86
88
88
89

90

91
91
97
112
129

133

140








LIST OF TABLES


Table

Table

Table


2-1

2-2

2-3


Table 2-4


Table

Table

Table

Table

Table

Table

Table

Table

Table

Table

Table


Table

Table

Table


Table

Table


3-1

4-1

4-2

4-3

5-1

5-2

5-3

5-4

5-5

5-6

5-7


5-8

5-9

5-10


5-11

5-12


Properties of Human Immunoglobulins ... 11

Properties of Human IgG Subclasses . . . 12

Selected Radionuclides for Radioimmunodetection
and Radioimmunotherapy . . . .... .. 19

Radionuclides for Radioimmunodetection
and Radioimmunotherapy . . . . . 21

Sublethal Radiation Doses. . . . . . 44

Phantom Study One Acquisition Parameters .. .75

Phantom Study Two Acquisition Parameters .. .77

Phantom Study Two Experiments . . . . 79

Phantom Study One Threshold Determination .. 92

Phantom Study One Results . . . ... 94

Phantom Study Two Threshold Determination .98

Phantom Study Two Experiment One Results 100

Phantom Study Two Experiment Two Results .102

Phantom Study Two Experiment Three Results 104

Gaussian Prefilter Comparison: Actual versus
SPECT Measured Volume . . .. . . 107

Phantom Study Two Absorbed Dose Results . 110

Phantom Study Three TLD Measurements. . . 114

Phantom Study Three Geometric Factor Method
and MIRD Pamphlet No. 3 Results . . . 117

Phantom Study Three Dosimetry Model Results 118

Phantom Study Three Results . . . ... 120

vii





Table 5-13 Phantom Study Three Error Anaylsis. ... .121

Table 5-14 TLD Calibration Study Results ..... . 123

Table 5-15 Phantom Study Four TLD Measurements .... .127

Table 5-16 Phantom Study Four Results. .. . .. . 128

Table 5-17 Phantom Study Four Error Analysis . . .. .130

Table 5-18 Clinical Study Results . . ....... 131


viii








LIST OF FIGURES


Figure 1-1


Figure 2-1

Figure 2-2

Figure 2-3

Figure 2-4


Figure 4-1

Figure 4-2

Figure 4-3

Figure 4-4

Figure 4-5


Figure 4-6

Figure 4-7

Figure 4-8


Figure 4-9

Figure 4-10


Figure 4-11


Figure 4-12


Figure 4-13


Antibody Carriers for Diagnosis
and Therapy . . . . . . . . .

Monoclonal Antibody Production . . . .

HAT Mediated Hybridoma Production . . .

IgG Molecule . . . . . . . .

Enzymatic Digestion of IgG Molecule
into Fragments . . . . . . . .

Research Methodology. . . . . . .

Single-Photon Emission Computed Tomography

SPECT Model Flow Chart. . . . . .

SPECTDOSE Program Subroutine Flow Chart .

Illustration of Subroutine THOLD Object
Segementation .. . . . . . . .

Subroutine CONTOUR Object Segmentation

Subroutine CONTOUR Object Assignment . .

Illustration of Subroutine OBJSELECT
Selected Object Comparison . . . . .

ALGAMP Flow Chart . . . . . . .

Phantom Study Two Torso Phantom and Organ
Inserts . . . . . . . . .

Phantom Study Three Experiment One TLD
Location . . . . . . . . .

Phantom Study Three Experiment Two TLD
Location .. . . . . . . . .

B72.3 Linker Complex . . . . .





Figure 5-1 Phantom Study One:Actual versus SPECT
Measured Volume . . . . . . . 95


Figure 5-2 Phantom Study One:SPECT Measured versus
Actual Activity Concentration . . . . 96

Figure 5-3 Phantom Study Three TLD Experimental
Locations. . . . . . . . . 113

Figure 5-4 Phantom Study Four TLD Chip Packaging . 124

Figure 5-5 Phantom Study Four TLD Locations. . .. 126








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

A COMPUTERIZED RADIATION DOSIMETRY MODEL FOR
RADIOLABELED MONOCLONAL ANTIBODIES:
INDIUM-111 LABELED B72.3-GYK-DTPA
FOR COLORECTAL CANCER

By

LATRESIA ANN WILSON

DECEMBER 1990


Chairperson: William S. Properzio
Major Department: Environmental Engineering Sciences

A foundation was developed for a dosimetry

methodology that could be used to calculate absorbed doses

in target and nontarget tissues using uniformly and

nonuniformly distributed activity. In this methodology, a

dosimetry model was developed which consisted of three

independent models: 1) the SPECT Model, 2) the Monte Carlo

Model, and 3) the Dosimetry Model. The SPECT Model uses

Single-Photon Emission Computed Tomography (SPECT) images to

determine the volume and radioactive uptake. A computer

program was written to automatically read and analyze SPECT

images. This program uses an edge detection method to

determine the volume. Voxel elements within the identified

volume are used to calculate the activity concentrations.

The Monte Carlo Model uses a monte carlo simulation method

xi





and results of the SPECT Model to calculate the fraction of

photon energy deposited in target and nontarget tissues. The

Dosimetry Model combines the results of the SPECT and Monte

Carlo Models to determine the absorbed dose in target and

nontarget tissues.

Several phantom studies were conducted to verify the

ability of the Dosimetry Model to evaluate organ and tumor

uptake, sizes, and to calculate absorbed doses. Comparisons

were made between the Dosimetry Model, other calculational

methods (MIRDOSE2, Geometric Factor Method, MIRD Pamphlet

No. 3), and TLD measurements.

For diagnostic activity doses, the SPECT Model was

found to calculate organ volumes of the order of 1000 ml to

within fifteen percent of the actual volumes but it failed

to accurately calculate organ volumes of 200 ml or less.

No meaningful relationship was found between the actual

and SPECT measured activity concentrations.

The Dosimetry Model agreed within 12% when compared

with the Geometric Factor Method and the MIRD Pamphlet No.3

results using homogeneously and heterogeneously distributed

"'In. The TLD measurements were within 30% at most of the

other methods.

Results of the several phantom studies indicated the

Dosimetry Model was an appropriate methodology for

calculating absorbed doses for homogeneously distributed

activity. Further investigation is needed to determine the


xii





accuracy of the Dosimetry Model in the heterogeneously

distributed activity case.

The addition of photon attenuation and scatter

correction and nonpenetrating radiation transport is

pertinent to the accuracy of the dosimetry methodology.


xiii









CHAPTER 1

INTRODUCTION


In the United States, cancer is the second leading

cause of death with the number of annual deaths fast

approaching 400,000 (1). This value represents a little over

20% of all deaths. Women are more susceptible to cancer than

men and except for accidents, cancer kills more children

than any other illness (1). In England, cancer is the

leading cause of death in children 1-14 years of age (1).

Utilization of antibodies to fight cancer started as

early as 1946 when Pressman theorized that polyclonal

antibodies directed against antigens expressed on tumor

cells could be used to localize radionuclides in the tumor.

He believed that once the antibodies were bound to the

antigen-rich tumor site, the radioactivity could be detected

with a gamma scanning device or if the radionuclide

concentration in the tumor was sufficient, serve as local

radiation therapy. So, after a series of ingenious

experiments, he successfully demonstrated that immune

proteins could be used to target radioactivity to tumors in






2

living animals (2). Unfortunately at that time, it was

difficult to produce antibodies that would survive in

cultured media, thus limiting the ability to produce

sufficient amounts with the specificity needed for clinical

studies. This ultimately limited the further use of this

technology for many years to come.

In 1975, Kohler and Milstein introduced a new technique

called hybridization, which would allow for the production

of large quantities of identical (monoclonal) antibodies

(3). This technique made it possible for the methodologies

proposed by Pressman to be applied clinically. Kohler and

Milstein later went on to receive the Nobel Prize for their

contribution.

With the advent of the hybridization technique, there

was renewed interest in the use of radiolabeled antibodies

for tumor therapy. It is generally believed that monoclonal

antibodies attached to radiolabels for therapy

(radioimmunotherapy) may be effective in treating metastases

and small tumors, where surgery may not be feasible. This

new technique offers some ray of hope in the fight against

cancer.

Recent advances in biotechnology have given new hope to

achieving the ultimate goal of using monoclonal antibodies

for targeting radioactivity for the dual purpose of cancer

diagnosis and therapy (Figure 1-1). This potential has















Antibody
to p97


Label With
Small Amount of
Radioactivity


Patient With
Undisclosed Tumor


Melanoma
Tumor Therapy


Attach Anti-Tumor
Drugs or High Dose
Radioactivity


Patient With Tumor








Tumor
Destruction


Figure 1-1. Antibody Carriers for Diagnosis and Therapy"


Adapted from Reference 4





4

generated a significant amount of interest and growth in the

field of nuclear medicine over the past few years. This

growth, in turn, has generated many new problems and

questions. One of these problems, the radiation dosimetry of

using radiolabeled monoclonal antibodies, is the focus of

this research.

Current radiation dosimetry methods, which allow for

the calculation of absorbed doses for both target and

nontarget tissues, assume that the radiolabel's energy is

distributed uniformly throughout the target and nontarget

organ. This assumption is not valid in the case of

radioimmunotherapy, since it has been shown that

radiolabeled monoclonal antibodies distribute

heterogeneously throughout a given organ and on the tumor

cell (5). It is, therefore the objective of this research to

develop a foundation for a radiation dosimetry methodology

that could be utilized for radiolabeled monoclonal

antibodies; i.e., a methodology which would allow for the

calculation of absorbed doses in tissues with a

heterogeneous or homogeneous radioactivity distribution. A

computerized dosimetry model, which allows for the

calculation of absorbed doses to both target and nontarget

tissues after intravenous (IV) injection of Indium-111

labeled B72.3-GYK-DTPA monoclonal antibody directed against

colorectal cancer, will be proposed in this research.

Clinical applications and ease-of-use of this dosimetry


















5

model will be emphasized. A comparison of the results from

this model with that of current dosimetry methods will be

made.

This dissertation is divided into five basic sections.

First, an overview of monoclonal antibodies and the factors

that affect their localization are presented. Second, there

is a discussion of the current radiation dosimetry methods

and their inadequacies for use with radiolabeled monoclonal

antibodies. Third, a discussion of the experimental methods,

computer models, and imaging techniques used in this study

are presented. Next, the computational results are presented

and analyzed. Finally, the results are summarized and

suggestions for future applications of this method are made.










CHAPTER 2

MONOCLONAL ANTIBODIES



Antibodies, or immunoglobulins, are proteins made by

many animal species as part of their specific response to

foreign substances (antigens). When antibody-antigen binding

occurs, this immunologic response usually results in the

destruction or elimination of the antigen.

Immunoglobulins are produced by the activity of the B

lymphocytes and possess specific binding regions that

recognize the shape of particular sites or determinants on

the surface of the antigen. An antigen may have several

determinants, or epitopes, each of which is capable of

stimulating one or more B lymphocytes. For this reason, an

antigenic challenge results in the production of a variety

of antibodies (6).

Early antibody production techniques employed the use

of animals, usually a mouse or rabbit, immunized with an

antigenic substance, to obtain antibodies, which were found

in the serum of the immunized animal. These antibodies were





7

polyspecific because they reacted with a wide variety of

antigenic binding sites.

Highly specific antibodies can be developed by

extracting individual lymphocytes and cloning them in tissue

culture; each clone would have the potential to manufacture

a single antibody species, a monoclonal antibody (Figure 2-

1). Unfortunately, normal antibody-producing cells do not

survive in culture media. It took Nobel laureates Kohler and

Milstein (3) to recognize that myeloma cells, which are

cancer cells that produce large amounts of identical but

nonspecific immunoglobulins, and which can survive in

cultures indefinitely, might be altered by the new

techniques of recombinant genetics to construct immortal

clones that secrete immunoglobulins.

Kohler and Milstein developed a method of producing

such monoclonal antibody strains by fusing the lymphocytes

from the spleen of an immunized mouse with mouse myeloma

cells, thus forming clones of hybrid cell lines, called

hybridomas (4). These cells are usually fused in

polyethylene glycol and result in clones that have the

specific-antibody characteristics of the lymphocytes and the

longevity of the myeloma cells. Additionally, pure hybridoma

cells are selectively grown in hypoxanthene-aminopterin-

thymidine (HAT) media since it supports neither the unfused

lymphocytes nor the myeloma cells. Once these hybridomas are

produced, they can be assayed for antibody activity and for






















Antigen
Antigenic
?Determinant
Lymphocytes Myeloma Cells
o Fuse 0

Spleen / \

\Hybrid
00 0 Myeloma
SLymphocytes Cells




1 2 3 4 Clot
Antibody Antigen


Antiserumlonl
Polyclonal Antibodies Monclonal Antibodies


Figure 2-1. Monoclonal Antibody Production'


Adapted from Reference 4


ne






9

further selective cultivation (Figure 2-2). The reader is

referred to Reference 6 for an excellent review of the

techniques involved in the production, purification,

analysis, quality control, radiolabeling, and storage of

monoclonal antibodies.


Immunoqlobulin Structure


Immunoglobulins (Ig) are divided into five classes:

IgG, IgA, IgM, IgD, and IgE and can further be subdivided

(isotypes) on the basis of internal attributes (see Table 2-

1 and 2-2). IgM antibodies are often the first to appear

during immunization and IgE antibodies mediate

hypersensitivity reactions (8).

Immunoglobulins of all classes are composed of two

heavy (H) chains and two light (L) chains in their simplest

form. All classes share the same light chains and differ

solely in the structure of the heavy chains. The heavy

chains are attached to one another by means of one or more

disulfide bonds, and a light chain is attached to each heavy

chain by a disulfide bond (Figure 2-3). Isotypes differ

structurally in the number of disulfide bonds linking the

two heavy chains together, and they differ functionally in

their ability to fix complement and to interact with

effector cells such as macrophages and mast cells (Table 2-

2).













Cell culture
Myeloma Line
Fuse In -n
Polyethylene
Glycol
-----*----.
Spleen Cells Myeloma Cells



Hat Medium feJ0' *0 Select Hybrid Cells
Assay For Antibody
T -- Freeze


Clone @0




Assay For Antibody
Freeze


Redone Q ( c



P Analyze to Select Variants
Propagate -- -- Freeze
Desired Clones V Thaw
Gr Induce
Grow in
Mass Culture/




Antibody Antibody


Figure 2-2. HAT Mediated Hybridoma Production"


SAdapted from Reference 7








11








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H2N NH2
H2N NH2
L L
sH CS
HOOC COOH


s s
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HOOC COOH









Figure 2-3. IgG Molecule*


Adapted from Reference 8





14

The antibody-specific sites of the immunoglobulins are

situated near the amino-terminal (NH2) end of each of the

four chains (Figure 2-3), and it is in this region (variable

region) that the greatest variability in amino acid sequence

occurs from immunoglobulin to immunoglobulin (9). Constant

amino acid sequences are found in the carboxyterminal (COOH)

regions (constant region) of the immunoglobulin chains

(Figure 2-3). The two variable regions bind to specific

antigenic sites and the constant region (Fc) interacts with

the host immune system.

Since the Fc region of the antibody is most likely to

trigger allergic responses, fragmentation has been used to

remove this portion from the antibody molecule. Pepsin, a

proteolytic enzyme, cleaves off most of the Fc region, which

leaves two Fab fragments bound together in a divalent

structure known as the F(ab')2 fragment (Figure 2-4). The

enzyme papain breaks the immunoglobulin into two monovalent

Fab fragments and an intact Fc fragment.


Variables Associated with Radioimmunoimaging
and Radioimmunotherapy


A number of variables that must be considered before

diagnostic and therapeutic applications of monoclonal

antibodies can be utilized. Generally monoclonal antibodies

alone are not effective in tumor destruction (10). This has

been attributed in part to the heterogeneous distribution of

tumor-associated antigens on cell surfaces, which leads to






















VARIABLE
\ REGION


LIGHT CHAIN


HEAVY CHAIN


PEPSIN/ IgG





F(ab')2
+ FRAGMENTS OF Fc


PAPAIN


Fab I.I Fab


Figure 2-4. Enzymatic Digestion of IgG Molecule into
Fragments*

Adapted from Reference 9





16

variable attachments of the antibodies to the different

tumor cells; more antibodies are attached to those cells

which have significant amounts of the antigen on their

surfaces but none to other tumor cells that are devoid of

the specific antigen and are therefore allowed to

proliferate (10). Since the monoclonal antibody alone is not

cytotoxic, it usually acts as a carrier of a more cytotoxic

radionuclide or toxin. This introduces a number of more

complicating factors and variables, which include the

combined physical, chemical, and biological properties of

the antibody and radiolabel. The following is a summary of

the variables directly linked with the production of the

radiolabeled tumor-associated antibody for imaging and

therapy (11):

1) Physical properties of radionuclides

a) Physical half-life
b) Gamma energies and abundances
c) Photon yield per absorbed radiation dose
d) Parent-daughter relationship-stable decay
products
e) Ratio of penetrating to nonpenetrating
components
f) Particle radiation (3-,9+,IC, and Auger
electrons)
g) Production mode (availability)

2) Chemical properties

a) Stability of radionuclide-protein bond
b) Specific activity-number of labels per molecule
obtainable
c) Retention of immunological activity versus
specific activity
d) Addition of nonradioactive carrier-metal ion
contamination
e) Sample pH





17

3) Biodistribution and biological half-life

a) Route of administration and activity of initial
dose
b) Vascularity: Blood flow and interstitial fluid
space
c) Uptake of protein-bound form of the isotope
d) Plasma and whole body clearance
e) Relative size of tumor model
f) Size of animal or human model
g) Cell proliferation
h) Capillary and cell permeability
i) Presence of inflammation

4) Target-nontarget time-dependent ratio: dose to
tumor, whole body, and other sensitive organs

5) Immunological purity of the antibody and its
relative specificity

6) Characteristics of imaging system with respect to
the radiolabel properties

7) Marketability, availability, convenience


This list, which is by no means all-inclusive, is

complicated by the fact that each variable seems to be

related to a number of the other variables.


Tumor Localization


The localization of radiolabeled antibodies at tumor

sites is dependent on a number of factors as reported by

several investigators (12-27). These include the tumor size,

radiolabeling method, choice of radiolabel, type of antibody

(whole vs fragment), route of administration, tumor biology

(blood flow, vascular permeability etc.), and the dose

administered. However, tumor uptake is ultimately dependent

upon its antigen content (13).







Choice of Radiolabel


The choice of a radiolabel is dependent upon its

intended use: diagnostic or therapeutic applications. For

diagnostic applications, one is more concerned with the

sensitivity and specificity of the test with the least

radiation dose. This is obtained by the use of radionuclides

with a low equilibrium absorbed dose constant. In therapy,

the objective is to attain the highest differential

radiation dose, which requires the use of radionuclides with

a high equilibrium absorbed dose constant. The goal of both

applications is to attain the highest radiation dose factor

for the target site in comparison to the normal tissue (28).

Ideally, radionuclides which are particularly suited

for imaging with radiolabeled antibodies should be

characterized by 1) physical half-life of 6 hr to 8 days, 2)

gamma energy range of 80-240 keV, 3) high single energy

gamma abundance per decay, 4) small abundances and low-

energy particulate radiation, and 5) reasonable

radiolabeling chemical properties and stability (11).

Similarly, radionuclides used for therapy should have

complementary properties to the antibody-bound radionuclides

used in imaging. However, their decay should be

characterized with a large component of particulate

radiation with little or no accompanying gamma radiation

such that a high localized dose may be delivered (11). Table

2-3 lists the various radionuclides that meet the required










Table 2-3. Selected Radionuclides for Radioimmunodetectiont

Nuclide Half-life Primary Decay Characteristics

9Tc 6 h IT (99%); 6 = 141 keV (89%)
123 13 h EC (100%); 6 = 159 keV (83%)

11In 68 h EC (100%); 6 = 171 keV (88%)
6 = 245 keV (94%)
131I1 193.2 h '" (100%); 6 = 364 keV

97Ru 69 h EC (100%); 6 = 216 keV (86%)

67Cu 62 h (100%); 6 = 91 keV (7%)
6 = 93 keV (17%)
6 = 184 keV (47%)

Selected Radionuclides for Radioimmunotherapyt

Nuclide Half-life Primary Decay Characteristics
131I1 193.2 h p'(100%); 0.608 MeV (86%)
6 = 364 keV (82%)

9Y 64 h P-(100%); 2.29 MeV (100%)

67Cu 62 h p'(100%); 6 = 91 keV (7%)
6 = 93 keV (17%)
6 = 184 keV (49%)

212Bi 1 h a (36%)
3' (64%) 212Po(0.3 g- sec T,,,
a = 8.78 MeV)
21At 7.2 h a (41%); 5.9 MeV (41%)
EC (59%)
125I 144.5 h EC (100%);6 = 35 keV
x-rays = 27 keV

t Adapted from Reference 29
Potentially useful in therapy as well
SPotentially useful in imaging also





20

specifications for diagnostic and therapeutic applications

of monoclonal antibodies. Table 2-4 lists the advantages and

disadvantages of the use of the radionuclides found in Table

2-3.

Technetium-99m, "'In, and 131I are examples of

radionuclides that are currently under extensive use in

medical imaging (29-34). They have the advantage of

availability, well-known chemistry, and optimal half-life

and gamma decay energy. Unfortunately, 131I suffers from

dehalogenation in vivo, which allows for nonspecific uptake

of free iodine in sites other than the tumor sites,

especially in the thyroid, liver and spleen (30,35). This

makes identifying tumors in these organs by imaging nearly

impossible. Iodine-131 also delivers a high radiation dose

to normal tissues due to its long half-life and medium gamma

energy (36). Indium-lll in vivo metabolism is relatively

unknown, although it has been shown to have good affinity

once in the tumor, but if it comes off the antibody, it will

relocate to the liver, spleen, and bone marrow (30).

Technetium-99m has a chemistry problem; i.e., it is

difficult to obtain a stable bond between it and the

antibody. Childs and Hnatowich (37) found increased

stability when "CTc was coupled directly to the chelate DTPA

(diethylenetriaminepentacetic acid). Rhodes et al. (38) used

a pretinning method to successfully label ""c directly to

antibody fragments, which showed increased stability against






21

Table 2-4. Advantages and Disadvantages of Selected
Radionuclides for Radioimmunodetectiont

Nuclide Advantages Disadvantages

"Tc Availability Short T.
Decay energy Chemistry problem

13I Decay energy Availability
Iodine chemistry Cost ($20/mCi)
Short T,

"'In Decay energy In vivo metabolism


Optimal T.
Chelation chemistry

Availability
Iodine chemistry
Optimal T2


Decay energy
In vivo de-iodination


97Ru Chelation chemistry In vivo metabolism
Availability
Decay Energy

67Cu Optimal T' Decay Energy

Advantages and Disadvantages of Selected Radionuclides for
Radioimmunotherapyt

Nuclide Advantages Disadvantages
131I Availability Long tissue path
Imaging
Cost
Y 90Sr-Generator Chemistry problems
Pure p decay In vivo metabolism?

67Cu Imaging In vivo metabolism?

212Bi High LET decay Short T,


High LET decay


High LET decay


Unknown chemistry

Short T
Unknown chemistry

Must be in nucleus to
kill tumor


Adapted from Reference 29


1311


1251


I Adapted from


Reference 29





22

transchelation. Recently, Goldenberg and associates (39)

have reported in vivo retentions of 98% immunoreactivity in

patients using anti-CEA murine monoclonal antibody (IMMU-4)

Fab' labeled directly with "9Tc. Chen and colleagues (40)

also have reported good results using 9"Tc labeled

antibodies in the confirmation of diagnosis of uveal

melanoma.

Several alpha- and beta-emitting radionuclides have

potential for radioimmunotherapy as seen in Table 2-3.

Iodine-131 has been most commonly used and is currently

being utilized in human clinical studies (35,41,42).

However, the choice of 1311 has not been because it is the

optimum for radioimmunotherapy; two-thirds of its absorbed

dose equivalent is due to penetrating radiation, which

usually escapes the primary tumors and their metastases (4).

The Auger electrons of iodine-125 may be effective for

therapy when used in conjunction with antibodies that are

internalized rather than remaining on the cell surface (9).

The appeal of alpha-particles for radioimmunotherapy is

their short range (-50-90 gm) and high linear energy

transfer (LET) (-80 keV/gm), which produces extreme

cytotoxicity. An alpha-particle traversing the diameter of a

10 im nucleus deposits an energy of 800 keV, equivalent to

an absorbed dose of approximately 0.25 Gy (4). Potential

alpha-emitting radionuclides for radioimmunotherapy are

astatine-211 and bismuth-212 (Table 2-3). Experimental





23

trials with 21At-conjugated antibodies on a murine lymphoma

system are in progress by Harrison (43) and Vaughan (44).

Perhaps the half-life of bismuth-212 is too short (60.6 min)

to fully capitalize on the longer antibody retention in the

tumor, although Macklis found it to be highly cytotoxic to

the murine Thy 1.2" EL-4 tumor cell line (45). More recently

Simonson et al. (46) showed 212Bi to be also cytotoxic to the

LS174T cell line. Few suitable alpha-sources are available

because most alpha-emitters are heavy elements (A > 82)

which decay to unstable daughters. The recoil alphas

produced in the decay of these daughters rupture the

radionuclide-antibody bond, which allows the daughter

product to diffuse away from the tumor (5).

Yttrium-90 offers another possibility for use in

radioimmunotherapy and has the advantage in that it is a

pure beta emitter and is easily available by production from

a strontium-90 generator (Table 2-4). Unfortunately, it has

no gamma emissions to allow for useful biokinetic studies in

the patient and, once detached from the antibody, it

deposits in the bone in sufficient quantities to give a high

radiation dose to the marrow. Yttrium-90 is currently under

investigation by several groups (24,47-52). Sally DeNardo

and colleagues (51,53) found copper-67 to be one of the most

promising radionuclides for radioimmunotherapy because of

its short half-life, abundance of beta particles, and the

presence of 93 and 184 keV gamma emissions.





24

A potential radionuclide for radioimmunotherapy,

palladium-109, a predominately beta-emitting radionuclide

(EMx= 1 MeV; half-life= 13.4 h) that is available carrier-

free, was investigated by Fawwaz et al. (54), who labeled

it to an antimelanoma monoclonal antibody. Unfortunately,

they found that at least 60% of the radiolabeled antibody

preparation failed to bind to melanoma cells. They believed

this was partly the result of inactivation of the antibody

during purification, storage, or radiolabeling and/or the

presence of carrier 1P08d in the '09Pd preparation. A new

radionuclide for radioimmunotherapy, rhenium-186 (1.07 MeV

maximum beta, 9% abundant 137 keV gamma), is being

extensively evaluated in patients by Schroff and associates

(55). Preliminary findings indicate it to have similar in

vivo properties to 9Tc and is very stable in vivo.


Tumor Size Effect


Several investigators have found that tumor uptake of

the radiolabeled monoclonal antibody is inversely related to

the tumor size; i.e., the per gram uptake of monoclonal

antibodies decreases as the tumor size increases (12-

15,56,57). Pimm and Baldwin (14) have found a multitude of

parameters that could potentially account for this

relationship. These include changes in blood flow, degree of

necrosis, levels of cellular and intratumor or extravascular

antigen, and the presence of circulating tumor-derived





25

antigen. However, this relationship could not be duplicated

by Cohen et al.(16). In fact, their findings contradicted

those by other investigators, in that they found the total

tumor uptake increased with increasing tumor size. No

satisfactory explanation has been offered to explain the

differences between the findings. Pedley et al. (57) found

that for tumor weights greater than 100 mg a strong positive

correlation exists between absolute uptake and tumor weight

but found a poor correlation for smaller tumors. They thus

concluded that specific uptake was inversely proportional to

tumor size regardless of the antibody.

At present, although still controversial, one may

conclude that the relationship between the tumor size and

the antibody uptake is an inverse one.


Fragment versus Whole Antibody


Antibody fragments (Figure 2-4) reach their maximum

accumulation faster and clear from the body faster than

whole antibodies (9,17-19,29,53). However, whole antibodies

remain in the tumor longer to achieve higher concentrations.

Thus, the choice of antibody type depends on the

application. Radioimmunoimaging would benefit most from the

use of fragments, because of their early maximum

accumulation and faster clearance, which results in a lower

background (nonspecific uptake) level. Radioimmunotherapy

would benefit most from the use of whole antibodies because





26

the cytotoxic effect could be delivered over a longer period

of time.

The difference in tumor localization between the

fragments and whole antibody has been attributed to the

smaller weight of the fragments (55,000 daltons and 110,000

daltons for IgG Fab and F(ab')2 respectively) compared to

that of the whole IgG antibody (160,000 daltons), which

allows them to transverse the intravascular and

extravascular space much more quickly (53). This effect also

may be the result of differences in the valency of the

antibodies (9). Since Fab fragments are monovalent, their

bonds to cell-bound antigens are weaker than those of the

divalent whole antibodies and because of this, they shed the

tumor and are rapidly cleared from the body via the kidneys

(9). F(ab')2 fragments, on the other hand, are divalent,

but demonstrate similar kinetics to the Fab fragments.

Ballou et al. (19) compared IgM F(ab')2, fragments to whole

IgM antibodies. The weight of the IgM F(ab')2 fragment was

130,000 daltons, which is not considerably less than that of

a whole IgG antibody (160,000 daltons). However, the IgM

F(ab')Z did weigh considerably less than the whole IgM

antibody, which weighed 900,000 daltons. The F(ab')2, showed

a 1.6-fold faster whole body clearance and reached its

maximum uptake earlier than that of the whole IgM antibody.

However, its total uptake was lower than the whole IgM

antibody. Ballou suggests that this may be caused in part by





27

differences in metabolism between the whole antibody and

fragment and also possible changes in the antigen-binding of

the fragments resulting from low pH digestion.

The choice of antibody type will depend upon its

application. For imaging, fragments will most likely be

used. The best choice seems to be F(ab')2 because it remains

in the blood longer than Fab fragments. This results from

its larger molecular weight, which reduces its loss through

the kidneys (58). For therapy, whole antibodies will

probably be used. Perhaps F(ab')2 fragments will prove

superior in all cases, because they offer the advantages of

fragments and the lack of immunogenicity of whole

antibodies.


Dose Administered Effect


Eger et al. (20) found dose-dependent kinetics in 12

human patients with melanoma. They found that as the amount

of injected antibody increased, the plasma half-life

increased, which eventually resulted in a higher tumor

uptake. They also found that the radioactivity levels in the

spleen and marrow decreased as the amount of antibody

increased. This dose dependent effect was also seen by

Hnatowich et al. (21). Pedley et al. (57) also studied the

effect of tumor weight on uptake with escalating amounts of

antibody. They found that there was decreased uptake with

escalating amounts of antibody in small tumors. This effect





28

was thought to be the result of steric hindrance in the

small tumors, even though the rate of diffusion into the

tumor may have increased.


Labeling Method Effect


The method used to attach the radionuclide to the

antibody will affect the antibody's localization. If the

method is inefficient, in that the radiolabel detaches from

the antibody in vivo or if the radiolabel's radiation

destroys or alters the properties of the antibody, all hope

of tumor localization is lost and radioimmunotherapy is

rendered useless.

Since most suitable radiolabels for therapy are metals

(Table 2-3), early methods of antibody labeling attempted to

attach them directly to the antibody. This proved to be

highly unstable and the radiolabel detached from the

antibody in vivo (9). However, nonmetals, such as iodine,

are currently being attached directly to the antibody by the

lodogen or Chloramine-T methods (22). These elements also

suffer from instabilities and tend to dehalogenate in vivo

(18). The latest methods employ the use of a coupling agent,

usually a chelate, to attach the metallic radiolabel to the

antibody (9,21,23,24). The most widely used chelate is

diethylenetriaminepentaacetic acid (DTPA). The antibody is

attached to the DTPA which, in turn, is attached to the

radiolabel. The bonds formed with the DTPA are much stronger





29

than those of the direct-attachment method (23); thus the

chelate-coupled antibodies are much more stable in vivo

(53). Another advantage to using a chelate such as DTPA is

that many different chelate substitution levels on the

antibody can be achieved by straightforward manipulation of

the relative amounts of reactants or time of reaction with

the antibody (53). Other chelates have also been used and

their effects on the antibody biodistribution are

continually being investigated (59-62).


Dose Administration Route


The site where the antibody is administered affects not

only how fast the antibody reaches the tumor, but also how

much eventually localizes in the tumor (17,25). Obviously,

if one is interested in localization in the lymphatic

system, intralymphatical administration will prove superior

to the other routes (25). If there are ascites in the

peritoneal cavity, intraperitoneal administration would

prove superior over the other routes. Hnatowich et al. (47)

concluded that the use of intraperitoneal rather than

intravenous administration may be important in the

application of yttrium-90 because it probably offers a means

of reducing radiation exposures to the bone marrow and the

critical organ without reducing exposure to the tumor within

the peritoneum. Larson (17) found that the concentration of

radiolabeled antibodies in human tumors is tenfold less





30

after administration via the intravenous route than after

injection either subcutaneously, intralymphatically, or

intraperitoneally.


Tumor Biology


Tumors grow radially from a central group of cells;

therefore as the tumor enlarges, the dividing cells form a

shell around a relatively hypoxic core. When these cells

outgrow their blood supply, they die and form a necrotic

central nest containing some viable cells that are highly

resistant to radiation (26). Blood flow in this situation is

low which makes delivery of the radiolabeled antibody to the

tumor very difficult. Studies by Gullino and Grantham found

that the average value of blood supply to tumors was 0.14

0.01 ml per hour per mg of nitrogen and the blood supply was

independent of the host (27). Solid tumors were also found

to be angiogenesis dependent by Folkman (63). The

radiolabeled antibody must reach the tumor through

circulation, crossing the capillary wall and diffusing

throughout the interstitial fluid to reach the tumor cells.

The rate of diffusion across these barriers is slowed by the

large size of the antibody molecule (64). This diffusion

rate has, according to Winchell (65), an 18 to 24 hour half-

life. Diffusion of the labeled antibody from the vascular

compartment into the tumor is caused by the concentration

gradient between the blood and the tumor (26). The higher





31

the concentration of radiolabeled antibody in the blood

compared with the tumor, the higher the diffusion rate will

be. Leichner et al.(66) found that external-beam

irradiation increased the permeability of tumor vascularity,

which resulted in increased tumor uptake of radiolabeled

antiferritin.


Other Factors


Other factors may influence the localization of

radiolabeled monoclonal antibodies in the tumor, such as the

amount of circulating antigens in the vascular system and

the metabolism and catabolism of the antibody in vivo.

Circulating antigens in the blood may combine with

circulating labeled antibodies. This complex could be

phagocytized by the reticuloendothelial system to reduce the

number of labeled antibodies that reach the tumor site

(67,68). Pimm and Baldwin (69) found that the average rate

of catabolism of 125I-labeled-IgG, anti-CEA monoclonal

antibody was 1.64% of the administered dose per gram per 24

hours and that this rate was higher for tumor bearing mice

as opposed to nontumor bearing mice. They also concluded

that tumor localization by the labeled antibody is a dynamic

process with simultaneous localization and degradation.

Gatenby et al. (70) have shown that the level of oxygen in

the tumor or tumor region also affects the antibody

localization. They found that tumors or tumor regions with a





32

mean oxygen pressure of 16 mm Hg or less had lower antibody

uptake, even when the presence of antigen was confirmed by

biopsy. This suggests that physiological factors other than

antigen expression may affect antibody uptake. In the past

few years a factor that has become increasingly important

because of the increase in the number of human studies is

the development of human anti-mouse antibodies (HAMAs). The

body, in response to the injection of murine antibodies,

produces antibodies (HAMAs) against the murine antibody

which it recognizes as being foreign. This response can be

detected within one week of exposure to the mouse protein

and is maximal within 2-3 weeks of exposure (71). The timing

and detection of the HAMAs are influenced by the dose of the

mouse antibody administered (71). HAMA clearly alters the

pharmacokinetics of subsequent murine antibody infusions

and, depending on the dose of the murine antibody and titer

of HAMA, can interfere with radioimaging and therapy and can

lead to toxicity because of the immune complexes and their

redistribution (71). Scannon (72) found a rapid clearance of

the infused murine antibodies from the blood which limited

further administration. It has been suggested that antibody

fragments be used instead of whole antibodies, because they

lack the Fc region (Figure 2-4), which most likely triggers

the allergic response. Other approaches to reducing HAMA

include the use of chimeric (human-mouse) monoclonal

antibodies, chemical alteration of the murine Fc portion,























33

ultrapheresis of human plasma to remove Ig, and chemical

suppression of the immune response.

From the above discussion, one may conclude that the

localization of radiolabeled monoclonal antibodies at the

tumor site is dependent upon a number of seemingly

interrelated variables which may vary from patient to

patient. Larson (25) also concluded that tumor localization

varied considerably from patient to patient.










CHAPTER 3

RADIATION DOSIMETRY



Before radioimmunotherapy can be implemented

successfully, it is necessary to know the amount of

radiation absorbed by the target and nontarget tissues. This

has proved to be difficult because of the lack of

appropriate methods to measure the amount of radiation

absorbed in the tissues; i.e., the absorbed dose, which was

deposited there by radiolabeled antibodies. The lack of an

appropriate method for correlating non-uniform dose with

effect has also hindered the efforts to assess the absorbed

dose. Assessment of the absorbed dose is complicated by the

large number of interrelated factors that affect the

localization of the radiolabeled antibodies in vivo (see

Chapter 2). These factors require that the calculated

absorbed dose be patient-specific. The current methods used

to calculate absorbed dose are based on assumptions that are

not valid when radiolabeled antibodies result in a

nonuniform distribution are used.





35

Current dosimetry methods can be divided on the basis

of the approach taken to calculate the absorbed-dose. There

are three basic approaches (73): (a) those that utilize the

conventional Medical Internal Radiation Dose Committee

(MIRD) formulation, a macroscopic approach which was

developed to cater mainly to diagnostic situations usually

involving gamma emitters and whole organs rather than

discrete targets (74); (b) those that utilize Berger's point

kernels, a semi-microdosimetry approach which considers

small size targets but not very low energy emissions at the

level of cell dimensions (75); and (c) those that take a

microdosimetric approach, which investigates doses from

short range emissions located near the cell surface or cell

nucleus (76).

Since absorbed dose is defined as the amount of energy

deposited per unit mass by ionizing radiation at the site of

interest (77), dosimetry calculations require a knowledge of

the physical properties of the radiolabel, length of time

the radioactivity remains in the various sites, and the

distribution of the radionuclide to the various sites in the

body (28,78,79). The physical properties of the radiolabel

are perhaps the easiest to determine accurately and will be

known in detail if conventional labels are used (80). The

residence time and spatial distribution of the radiolabeled

antibody in vivo are not usually known and must be

determined prior to radioimmmunotherapy. These parameters





36

are usually determined by sequential, timed quantitative

imaging. Several investigators (10,11,78) have suggested

that a diagnostic study, as such, be performed prior to

radioimmunotherapy. In this diagnostic study, the antibody

would be labeled with a small amount of the therapeutic

agent or a short-lived isotope of the therapeutic agent in

an effort to reduce the hazard to the patient (69).


Medical Internal Radiation Dose Committee (MIRD) Formulation


The MIRD Formula (74) is the most widely accepted

method for calculating radiation absorbed dose from

internally deposited radionuclides. This method was

recommended by the Medical Internal Radiation Committee of

the Society of Nuclear Medicine in 1968 and was later

adopted for standard use by the International Commission on

Radiation Units (ICRU) (81) in 1971. MIRD is based on the

dose rate equation developed by Loevinger et al. (82) in

1956 and is expressed as



Dose rate= K x activity in target x energy of x absorbed 1)
to target mass of target emission fraction


where K is a constant which depends on the units used.


Several assumptions are made in this approach, the most

important in the present context being that in applying this

method to humans, an anthropomorphic phantom is used, which

in calculating the absorbed dose, does not take into account





37

the nonuniformity of the activity distribution. Thus, source

homogeneity is assumed throughout the organs. Humm (4) gives

two reasons why this assumption may not necessarily be valid

in the case of radioimmunotherapy. First, the irregular

nature of the tumor vasculature will result in a complex

pattern of diffusion gradients guiding the antibodies

through the tumor. Second, immunohistochemical studies with

antibodies have shown that the tumor antigens may not be

expressed uniformly throughout the whole tumor cell

population.

For the application of radioimmunotherapy, and assuming

that the activity remaining in the body after organ uptake

is distributed uniformly, the mean dose to the target

(tumor) is the sum of three components: a) the dose from

nonpenetrating radiations (radiation pathlength is smaller

than the dimensions of the organ in which it resides)

emitted within the target organ, b) the dose from

penetrating radiations (radiation pathlength is greater than

the dimensions of the organ in which it resides) emitted

within the target organ, and c) the dose from penetrating

radiations emitted by the activity in the rest of the body

(41). The absorbed fraction for nonpenetrating radiations is

assumed to be unity; i.e., all the energy emitted by the

source organ is absorbed in the source organ. With this in

mind, one proceeds to calculate the various parameters of

the MIRD equation for each component. The effective half-





38

time can be calculated from exposure rate measurements and

activity measurements of the blood and urine as a function

of time. Decay constants are calculated from a least-squares

fit of the time-varied target organ count rates.

Compartmental modeling is often employed to calculate the

cumulated activity, decay constants, and the other

parameters needed for the MIRD equation. Tumor and critical

organ volumes are determined from Computed Tomography (CT)

or Single-Photon Emission Computed Tomography (SPECT)

images.

For conventionally employed radionuclides such as 131I,

32, or 9Y and for targets greater than a centimeter in

diameter, the MIRD method holds quite reasonably (73).


Berqer's Point Kernels


This method is based on Berger's Point Kernels for

calculating the absorbed dose from beta-rays (75). If the

medium is assumed to be uniform and unbounded, the beta-ray

dosimetry problem can be divided into two separate parts: a)

determination of the distribution of absorbed dose around a

point isotropic source, which is often referred to as a

point kernel, and b) appropriate integration over the point

kernel weighted by the source density to obtain absorbed-

dose distributions for extended sources (83). Part a)

contains all the physical aspects of the problem and part b)

is entirely geometric. Using the principles of





39

superposition, the absorbed dose from one source element can

be added independently to the contribution from another

source element. Thus, a distributed radionuclide source can

be considered as a collection of independently acting

isotropic sources (83).

The beta-ray dose rate is expressed in the form


Rp = 1.38E-05 Eg P A Gy d"' 2)


where Rg is the beta-ray dose rate in the tissue, E is the

average beta-ray energy per disintegration in Mev, is the

isotropic specific absorbed fraction, and A is the Activity

of the radionuclide in Bq.

Since the dose rate is proportional to the average

concentration, the total beta-particle dose is obtained by

integrating the concentration over the time the tissue is

exposed to the beta particles:



D (t) f RO(t)dt 1.38E-05 E t A(t)dt Gy




where E is in Mev, t is in days, and A is in Bq. Thus,

whenever the average activity A(t), is known as a function

of time, the absorbed dose can be computed by integration.

Loevinger et al. (82) states that for purposes of

dosimetry, the tissue distribution can be represented by a

stable system of separate compartments interconnected by

first-order reactions. First-order reactions imply that the





40

total amount of radioactivity leaving a given compartment

per unit time is proportional to the amount present. The

rate of change of the total radioactivity in the ith

compartment is described by the following differential

equation:

n
dgi = -pq ki0qo + Z(kjiqj kijqi) 4)
dt j=1

qi = total radioactivity in the ith compartment
kij = constant fraction of the radioactivity in the
ith compartment transferred to the jth
compartment, per unit time
ki = constant fraction of the radioactivity in the
ith compartment transferred to outside the
system (excretion)
Ip = radioactive decay constant
n = number of compartments


The first term on the right represents the loss due to

radioactive decay, the next term the loss from the system by

excretion or fixation, the first term inside the bracket

represents the contribution of the (n-1) other compartments

to the ith compartment, and the second term inside the

bracket represents the loss from the ith compartment to the

(n-1) other compartments. Integrating this equation for qi

(pCi) and then dividing by the mass (g) of compartment i

gives the average concentration of radioactivity in the ith

compartment:


C,(t) = 3.7 x 10' qi(t)/mi Bq g-1 5)


Thus, it is now possible, using Equation (5), to calculate

the total beta-particle dose from Equation (3). Spencer (84)





41

showed the applicability of this method in

radioimmunotherapy.

A whole range of electron energies from 10 keV to over

1000 keV, as well as tumor sizes from single cells to 107

cells (each having a millimeter diameter), can be

encompassed with this approach.


Microdosimetry


Microdosimetry is most applicable for evaluating dose-

effect relationships. It uses the microscopic distribution

of radiation interactions with biological systems to explain

the effects of radiation on the system (76). In some

instances, the distribution of specific energy in small

targets, individual tracks, or even individual energy

absorption events such as single ionizations may be needed

to obtain meaningful dose-effect relationships.

Microdosimetry takes into account the statistical aspects of

the particle tract structure, energy distribution patterns,

and radionuclide distribution within tissues and provides a

means for determining the number and frequency of cells

irradiated, the probability densities in specific energy,

and the average dose delivered to cells of interest (85).

Charged-particle radiation interacts with atomic electrons

of the matter through which it passes, and ionization and/or

excitation energy is imparted with each interaction. The

charge and mass of the particle, its initial energy, and the





42

matter through which it travels determine the pattern of

energy loss, the distance traveled, and the direction taken

by the particle. Ionizations and excitations are produced

when the energy is transferred from the particle to the

medium.

The basic quantity that describes the energy imparted

to matter is the absorbed dose, which actually is a mean

value. By definition, the absorbed dose D is the quotient of

de by dm, where de is the mean energy imparted by ionizing

radiation to matter of mass dm (86):


D = de/dm 6)


The specific energy, z, a stochastic quantity with units

similar to absorbed dose, is defined as the quotient of e by

m, where e is the energy imparted by ionizing radiation to

matter of mass m (86):


z = e/m 7)


The mean absorbed dose in a volume is equal to the mean

specific energy z, in the volume:


D= 8)


The ratio e/m is highly dependent upon target size. As the

target size gets smaller and smaller, the variations in the

local dose becomes increasingly greater, and the average

dose value becomes less and less indicative of the complete





43

dose distribution (85). Thus, for very small target sites,

the concept of absorbed dose becomes increasingly abstract,

and the dose is better represented by a distribution of

doses in "specific energy". For a given value of target size

mass, this distribution is called the "probability density

in specific energy" and is denoted by f(z). The probability

that the specific energy received by a target site lies in

the infinitesimal range dz containing the value z is f(z)dz.

Methods for calculating the probability densities in

specific energy can be divided into four steps (85). The

first step involves characterizing the geometrical

relationship between the radioactive source distribution and

the target sites. Second, the density in specific energy

must be determined for a target at any distance from the

radioactive source and with all possible angles of

intersection considered. Third, the probability that a point

source exists at any given distance from the target must be

determined from the spatial distribution of sources. And

fourth, the densities from all point sources are convolved

using Fourier transforms to construct a new specific energy

density for the target population.

The product of a microdosimetry calculation is a

statistical distribution of doses to small sites from which

an average dose could be determined. The precise

relationship between the specific energy density (average

dose) and the resulting biological effects is not known;





44

therefore, the results from this approach are not directly

applicable to the rather different conditions found in

radioimmunotherapy. However, several investigators (85,87-

91) have proceeded to utilize this method for radiolabeled

antibody dosimetric calculations.


Critical Organs


The maximum radiation doses that radiosensitive organs

can tolerate and still continue to function adequately to

support life are listed in Table 3-1 (10). With current

systemic approaches to therapy, bone marrow toxicity has

been the dose-limiting side-effect (92). However, as shown

by in vivo radiolabeled antibody biodistribution studies,

the dose-limiting organ is most likely to be the liver or

kidney.



Table 3-1. Sublethal Radiation Dosest


Organ System Dose (Gy)

Bone Marrow < 2
Intestinal Mucosa < 7
Kidney < 15
Liver < 25

t Adapted from Reference 10



Leichner et al. (41), using the MIRD methodology, found that

the 131I radiation dose for four patients ranged from four to

10 Gy for the liver and from 1.1 to 2.2 Gy for total-body





45

irradiation. Vaughan et al. (93), using Berger's Point

Kernels, found that a tumor dose of two Gy in one week with
131I was associated with a whole-body dose of 17 Gy. Bigler

et al. (87) utilized a microdosimetric approach to calculate

the mean dose to the red marrow for a number of different

radiolabels. The mean dose ranged from 1.6 Gy with "As to

17 Gy with 131I for a large cell size.

In recent years with the advent of new materials

technology, Griffith et al.(94-95) and Wessels (96) have

developed a method for the direct measurement of absorbed

radiation dose through the use of teflon-imbedded, CaSO4:Dy

thermoluminescent dosimeters (TLD)*, which have been

modified to fit inside a 20-gauge needle. The TLDs are

directly implanted into the tissue of interest and are

subsequently recovered for read-out. They measured an

absorbed dose of 8.1 Gy for the 1311 labeled B72.3 colorectal

carcinoma mouse system and 17.4 Gy for the 131I labeled LYM-1

Raji B-cell lymphoma mouse system, which correlated well

with autoradiography measurements (95). This method is not

appropriate for human dosimetry studies because of patient

discomfort and tissue trauma.

In order for radioimmunotherapy to be successful, the

radiation dose deposited in the tumor and other critical

organs must be known accurately. Current dosimetric methods

do not adequately address the unique features proposed by


Teledyne, Inc., NJ.



























46

the use of radiolabeled antibodies for the calculation of

absorbed dose. Therefore, new methods must be created. As

more clinical information using radiolabeled antibodies

becomes available, a better method may be defined, which can

be compared to direct measurements.








CHAPTER 4

MATERIALS AND METHODS



In this research, a foundation for a dosimetry

methodology to determine the absorbed dose in both target

and nontarget tissues using uniformly and nonuniformly

distributed activity has been developed. The calculation of

absorbed dose can be divided into two parts: 1) the

determination of the radionuclide concentration, and 2) the

determination of the amount of energy deposited in the

tissues of interest. This new dosimetry methodology uses

Single-Photon Emission Computed Tomography (SPECT) to

determine the radioactive uptake in the tissues and a Monte

Carlo method to determine the amount of energy deposited in

the tissues.

The research method utilized in this research is shown

in Figure 4-1. In this figure, the research method is

divided into three models: 1) the SPECT Model, 2) the Monte

Carlo Model, and 3) the Dosimetry Model. Results from the

SPECT and Monte Carlo Models are utilized in the Dosimetry

Model.



















































Figure 4-1. Research Methodology





49

SPECT Model


The SPECT Model employs the use of Single-Photon Computed

Tomography, a diagnostic imaging technique, to determine the

volume and radioactive uptake in the target and nontarget

tissues following injection of radiolabeled monoclonal

antibodies. A computer program, SPECTDOSE, was written to

calculate both target and nontarget tissue volumes and

radioactive uptake. SPECTDOSE uses edge detection and

contour tracing algorithms to determine the volume of the

various organs and tissues of interest. The SPECT image is

divided into several three-dimensional arrays of a

preselected size and number. Sixty-four arrays composed of

64 x 64 elements (pixels) are utilized in this research.

Each element of the array represents an image volume (voxel)

at a specified location. Each voxel contains an integer

value derived from the measured activity in the imaged

object. The total number of voxels and their location, image

intensity per voxel, and organ volume (total number of

voxels at a specified location) are determined in this

model. Results of this model are used in the Monte Carlo

Model.


Monte Carlo Model


This model uses a monte carlo method to calculate the

fraction of photon energy deposited per unit mass of target

and nontarget tissues (specific absorbed fraction). A monte








50

carlo computer program was obtained from Oak Ridge National

Laboratory, Oak Ridge, Tennessee (97). This program, called

ALGAMP, is a photon transport code which accurately

simulates the physical phenomena of the photon by the use of

the statistical nature of radioactivity. In ALGAMP, the

human body and organs are represented by a set of

mathematical equations known collectively as the Cristy

Parametized Phantom (98). The radioactive distribution

within each organ is assumed to be homogeneous in the Cristy

Parametized Phantom. ALGAMP was modified for use in this

research by the deletion of the Cristy Parametized Phantom

and the addition of a method which permits the direct use of

the voxel information created by the SPECT Model. The voxel

information generated by the SPECT Model defines the organ

volumes and locations of interest. In the dose calculation

each voxel value represents the heterogeneous radioactivity

distribution found in the organs following the use of

radiolabeled monoclonal antibodies. By use of the SPECT

image voxel information and the monte carlo simulation

method, the amount of photon energy deposited per tissue

mass, specific absorbed fractions, can be determined for

each organ volume and voxel. The specific absorbed fractions

are utilized in the Dosimetry Model.





51

Dosimetry Model


The Dosimetry Model uses the results of the SPECT and Monte

Carlo Models to determine the absorbed dose to both the

target and nontarget tissues. Voxel matrix values of the

tissue volumes determined in the SPECT Model are utilized in

the Monte Carlo Model to determine the specific absorbed

fractions in the tissues of interest. The Dosimetry Model

combines the specific absorbed fractions with the organs'

radioactive uptake determined in the SPECT Model to

calculate the absorbed dose. The absorbed dose is determined

for both the organ and organ voxels; i.e, the absorbed dose

can be calculated for each organ voxel also. The Dosimetry

Model retains the concepts of the MIRD Method in addition to

accounting for the heterogeneous distribution of

radioactivity exhibited in the organs and organ voxels

following the injection of radiolabeled monoclonal

antibodies into humans.


Single-Photon Emission Computed Tomography


Single-Photon Emission Computed Tomography (SPECT) is a

diagnostic imaging technique utilized in nuclear medicine,

in which, the differences in radioactive distribution of

internally administered radionuclides are exploited (99). In

SPECT, the detector, a gamma camera, rotates around the

patient while acquiring data (photon detection) (Figure 4-

2). With the use of a computer and several complicated
































Single-Head SPECT
Gamma Camera


Dual-Head SPECT
Gamma Camera


Single-Head SPECT Unit

















Multi-Detector Head
SPECT Unit


Figure 4-2. Single-Photon Emission Computed Tomography


Adapted from Reference 100





53

algorithms, the data is reprojected (reconstructed) into a

transverse section image (slice) of the activity

distribution. Basically, SPECT maps the three dimensional

concentration of a radionuclide by measuring the angular

distributions, or projections, of gamma ray intensities

emitted within the body. SPECT is also capable of

eliminating overlying and underlying source activities and

offers the potential for quantitating the radioactive uptake

in the patient (100)


SPECT Quantitation


SPECT quantitation of radionuclide activities in the

human body is affected by several physical and instrumental

factors including absorption attenuation of photons in the

patient, Compton scattered events, the system's finite

spatial resolution, and object size, finite number of

detected events, partial volume effects, the

radiopharmaceutical biokinetics, and patient and/or organ

motion. Other instrumentation factors such as calibration of

the center-of-rotation, sampling, and detector

nonuniformities will affect the SPECT measurement process

(100,101,102). Several of the major factors that affect

quantitation with SPECT systems are as follows (100):


1) Physical Factors:

a) Characteristic energy of the emitted photons
b) Radiation decay as a function of time





54

c) Attenuation of gamma photons within the
patient
d) Inclusion of scattered photons within pulse
height window

2) Anatomical/Physiological Factors:

a) Source size and location within the body
b) Patient and/or organ motion
c) Biokinetical behavior of radiopharmaceutical
within the body

3) SPECT System Factors:

a) Camera/collimator energy and spatial
resolutions
b) Detection efficiency
c) Changes in collimator geometric response with
distance from the collimator surface
d) Sensitivity variations across the camera
surface
e) Camera electronic variations, ADC errors, and
gantry mechanical variations with time and/or
position
f) Characteristics of reconstruction process
such as shape of filter function, linear and
angular sampling interval values, accuracy of
attenuation, nonuniformities, and scatter
compensation methods and accuracy of edge-
detection methods


Their relative importance depends on the type of

quantitative information desired and the biokinetic

properties of the radiopharmaceutical. The determination of

radionuclide concentration as a function of time for small

volume elements (voxels) within the body is affected most by

the factors listed above.


Photon Attenuation


The determination of the radionuclide concentration as

a function of time in the voxel elements is affected by the






55

absorption attenuation and scattering of photons. The effect

of attenuation results in a decrease in the measured gamma

ray intensity. There is self-attenuation in the source organ

and also attenuation in the surrounding body tissues. Most

attenuation compensation methods assume that the attenuation

coefficient, the fraction of the gamma-ray beam attenuated

per unit thickness of absorber (103), is constant. Although

this will provide a less accurate compensation within

regions where the value of the attenuation coefficient is

variable, it is the method utilized in this research. Other

attenuation compensation methods, those which do not assume

a constant attenuation coefficient, can be divided into

three classes: 1) Preprocessing Methods, 2) Intrinsic

Compensation Methods, and 3) Postprocessing Methods (100).

Preprocessing methods attempt to correct the projection

data prior to image reconstruction. These methods are

relatively easy to implement, however, they tend to generate

streak artifacts in the presence of noise. This method was

not used in this research because the antibody SPECT images

were very noisy.

Intrinsic compensation methods integrate attenuation

correction directly in the reconstruction algorithm. An

attenuation map is measured (by using a transmission source)

or assumed as part of the reconstruction algorithm. These

methods require the use of large computers and are time






56

consuming, thus preventing the use of this method in this

dissertation.

Postprocessing methods apply attenuation correction

after the image reconstruction has completed. This approach

is used most often in commercial SPECT systems and requires

the measurement or estimation of the patient's body contour.

In the human studies undertaken in this research, the

patient's body contour was not retained, which precluded the

use of this method in this research. The area of attenuation

compensation in SPECT is currently undergoing extensive

analysis and the reader is further directed to a number of

reports on this subject (104-119).


Photon Scatter


Compton scattering events degrade the image contrast

resulting in a major source of error in the quantification

of radionuclide concentrations. Scattered photons can

contribute as much as 50% of the total collected events in

SPECT (120). The use of a sodium iodine-thallium doped

detector in SPECT systems results in the inclusion of both

scattered and nonscattered photons in the photopeak energy

window. Several approaches have been attempted to compensate

for the scattered radiation, but none at this point have

proven to be of substantial value (100,101,102,121-130). No

scatter correction method was utilized in this research.





57

SPECT Camera System


SPECT was performed with a digital rotating gamma

camera* with a medium energy collimator and a 20% peak

energy window. A rotation of 360', 128 projections (2.81

apart), and a study of 26 minutes (12 s view'1) was used.

Data was acquired on a computer" in the 64 x 64 x 16 bit

mode (131). After acquisition, the raw image data is reduced

from 16 bits to 8 bits using the system software**. After

which, the data is prefiltered using a Gaussian filter of

the 24th order and a frequency cutoff of 0.20 (131). This

data is reconstructed using the high resolution

reconstruction algorithm, which is an iterative

reconstruction method (132,133), with one iteration and a

dampening factor of 0.5 (134). The dampening factor

indicates the level of contribution by the error image to

the production of the iterative transverse slices (135).

Sixty-four transaxial slices, one pixel thick, are created.

The size of the elemental voxel is one pixel in the x and y

axis (transaxial plane) and in the z direction (parallel to

the axis of rotation). One pixel was determined to be equal

to 6.9 mm in the patient studies.


Technicare Omega 500, Technicare Corporation,
Cleveland, OH 44139

ADAC DPS-3300, ADAC Laboratories, San Jose, CA 95138


ADAC Laboratories Version 4 System Software, San
Jose, CA 95138





58

Image Segmentation


Prior to determining the organ volumes, the SPECT image

must be segmented into the respective organs. Image

segmentation is the process of subdividing an image into its

constituent parts or objects. Segmentation algorithms are

generally based on two properties of the image gray-level

values: discontinuity and similarity. The gray-level value

is an integer that represents the image intensity. In the

discontinuity category, the image is partitioned on the

basis of abrupt changes in the gray level. Detection of

points, lines, and edges are of principle interest in this

category. In the similarity category, the image is divided

on the basis gray level similarities. Approaches to the

similarity category include thresholding and region growing

(136). Several segmentation or edge detection methods were

attempted prior to the selection of the Threshold

Segmentation Method in this research.

The Gradient Method, an approach that looks for

discontinuity, was attempted first. It is assumed in this

method that the regions of interest are homogeneous so that

the transition between two regions can be determined on the

basis of gray-level discontinuities alone. A local

derivative operator is determined, whereby the magnitude of

the first derivative indicates the presence of an edge and

the sign of the second derivative determines where the edge

pixel lies; the background or object side (137). Since the







59

first and second derivatives must be determined for each

image pixel, this method is computationally intensive.

A second approach, Histogram Segmentation Method, was

also attempted. This technique creates a histogram of the

gray-level contents of an image. The image is subdivided

into its constituents by use of the peaks and valleys in the

histogram, which represent the image object and background

regions respectively. Division between objects is difficult

when a deep valley or steep peak is not present (138). In

the presence of image noise, differentiation between peaks

and valleys is futile. Because of noisy SPECT images this

method was not used in this research.

The last approach attempted and used in this research

is the Threshold Segmentation Method. This technique

segments on the basis of gray-level similarity. A threshold

value is applied to the image, whereby any image pixel's

gray-level value that is greater than the threshold value is

considered to be a part of the object and any pixel with a

gray-level less than the threshold value is apart of the

background. Since the threshold depends only on each

pixel's gray-level, it is called global (139). This method

was selected because of its easy implementation, small

computation requirements, and excellent results when used

with noisy images.






60

Program SPECTDOSE


The Program SPECTDOSE was developed in this research to

calculate the necessary parameters proposed by the SPECT

Model; i.e., organ volumes and radioactive concentrations

(Figure 4-3). This program is written in Fortran-77 for a

VAX/VMS Operating System. The Program SPECTDOSE is divided

into a number subroutines (Figure 4-4). Before the SPECT

image could be utilized, its data format or the way the

image data was written to the file had to be determined. The

data format for the SPECT images was obtained with a promise

of confidentiality from the ADAC Corporation (140). The

reconstructed SPECT image data is stored in each voxel as

hexadecimal (base-16) numbers. The main program reads the

hexadecimal numbers into a logical array, where the values

(image count) are scaled between 0-255 intensity levels

(gray-levels) and read into an integer array. The resulting

reconstructed image data is represented as an interger which

has a value between 1 and 256. The image count can be

corrected for attenuation and radioactive decay at this

point by entering the appropriate linear attenuation

coefficient, radionulide half-life, and time of decay values

into the program. The image threshold value is entered and

the subroutine THOLD is called to segment the image into its

constituent objects. This process is repeated for each image

slice.
















































Figure 4-3. SPECT Model Flow Chart















































Figure 4-4. SPECTDOSE Program Subroutine Flow Chart







Subroutine THOLD


The subroutine THOLD segments the image into various objects

using the Threshold Segmentation method (139) (Figure 4-5).

The objects are separated from the background pixels by

comparing their intensity values with a global threshold

value; all pixels with an intensity value higher than the

threshold belong to the object. The subroutine CONTOUR is

called to extract the objects from the segmented image.


Subroutine CONTOUR


The subroutine CONTOUR extracts the objects from the

segmented image (Figure 4-6). The extracted object's

boundary is traced and the resulting object is stored in a

binary file called OBJECT#.DAT. This process is repeated for

all objects in the segmented image. Each object file is

assigned a consecutive identification number; i.e.,

Objectl.dat, Object2.dat etc. (Figure 4-7). The extracted

object's characteristics, which include the number of

voxels, total count, maximum and minimum indices, volume,

and area, are written to the file, OBJVAL.DAT.


Subroutine OBJSELECT


The subroutine OBJSELECT integrates the extracted objects of

each slice into a single object; i.e., organ. The extracted

object that best represents the shape of the organ of

interest is determined. This object's, the selected object,









































Objects are separated from the background in the
SPECT image using the Threshold Segementation
Method, which is implemented in Subroutine THOLD.




Figure 4-5. Illustration of Subroutine THOLD Object
Segmentation


w I


3





























1 2


3




Segemented objects are extracted and separated into
separate files by Subroutine CONTOUR


Figure 4-6. Subroutine CONTOUR Object Segmentation


1 2


3














SLICE 1


OBJECT

1




2




3




4



5


SLICE 2


SLICE N


- K


Segmented objects from each image slice is extracted and
separated into separate files and assigned file names
in consecutive order by Subroutine CONTOUR


Figure 4-7. Subroutine CONTOUR Object Assignment


[7:[ I


-aa








67

identification number is entered into the program. The

selected object is then compared with the rest of the

objects (Figure 4-8). If ninety percent of the object's

voxels are the same for each slice as the selected object's

voxels, the object is considered to be apart of the organ.

This process is repeated for all organs. The organ's voxel

indices, count, name, identification number, and volume are

stored in the file, VOXEL.DAT.


Subroutine CORGAN


The subroutine CORGAN creates an organ given its voxel

indices and identification parameters. Each pixel is

assigned an integer value which will represent the organ

volume desired. The number of image slices included in the

organ is also assigned. The organ created is used as a

photon reflector or sink; i.e., it either scatters or

absorbs the incident photons, and represents the areas of

the body not included in the SPECT image. If the whole body

is to be included in the SPECTDOSE Program, it is necessary

to create those areas of the body not seen in the SPECT

images due to the limited field-of-view of the SPECT camera

and the lack of availability of whole body SPECT images.

These areas are created using this subroutine.














Select Object 2
for Comparison:


OBJECT


SELECTED
OBJECT


K-1


Selected objects are compared to the remaining objects
for possible inclusion into one larger object (organ)




Figure 4-8. Illustration of Subroutine OBJSELECT Selected
Object Comparison







Subroutine VOXFIL


Once the organ files have been created; i.e., each organ's

voxel information has been stored in a VOXEL.DAT file, the

subroutine VOXFIL assembles the organs (each VOXEL.DAT file)

into one larger file called VOXPHAN.DAT. The number of

organs; i.e., the number of VOXEL.DAT files, is entered into

the program. This file contains the voxel indices, image

counts, weighting factors, identification numbers, and the

total number of voxels for all organs. The VOXPHAN.DAT file

is read directly by the program ALGAMP.


Program ALGAMP


The program ALGAMP is a point energy gamma-ray monte

carlo radiation transport code for calculating specific

absorbed fractions of energy and absorbed dose data from

internal and external sources (97). This program is written

in Fortran and was developed at Oak Ridge National

Laboratory in Oak Ridge, Tennessee (97). A flow chart of

this program can be seen in Figure 4-9. This program is

composed of 30 or more subroutines and initially utilized

the organs of the parametized phantom model from the Cristy

Phantom Series (98). In this Series, the organs were

represented by mathematical equations of various geometrical

shapes, such as, spheres and cylinders. The equations were

confined to a small number of ALGAMP subroutines (GEOM,SUM1,

SUM2, and RESULT), which hasten the modification process.


















































Figure 4-9. ALGAMP Flow Chart






71

The Cristy Phantom Series was not used in this research

because it assumes a homogeneous source distribution, which

is not valid in the case when radiolabeled monoclonal

antibodies are used; the organs were not patient specific;

and its inability to represent diseased organs, which are

most often found in nuclear medicine patients.

Since each human is uniquely different, it was the

desire of this research to make this new dosimetry method

patient specific; i.e., the organs of the imaged subject are

utilized in the calculation. This can be achieved by using

the actual SPECT image to define the organ volumes and

radioactive uptake. Each organ's voxel information was

determined and compiled into the file VOXPHAN.DAT by the

SPECT Model. The VOXPHAN.DAT file is read by ALGAMP. Each

voxel inherently, at the level of the camera system's

resolution, accounts for the heterogeneous source

distribution exhibited in the organs at that level following

the uptake of the radiolabled monoclonal antibodies. If the

activity is not distributed heterogeneously at the level of

the camera system's resolution, which is approximately one

half centimeter in this research, the voxels will reflect

this and the activity will be assumed to be homogeneously

distributed. For this homogeneous case, no additional

modifications to ALGAMP would be needed. Several ALGAMP

subroutines (INPUT, SOURCE, SEARCH, GEOM, SUM1, SUM2,





72

RESULT, and RANPOS) were modified to accommodate the

inclusion of the voxel information.

For sources distributed in energy, the cumulative

distribution function (cdf) for the source energy spectrum

is used. A detailed cross-section table is generated for the

source energies of interest. Each photon is weighted by a

weighting factor which describes the probability of photons

existing in a given voxel. The photon weighting factor is

computed for each voxel by dividing the voxel image count by

the average voxel count for a given organ. The source photon

location is chosen by randomly sampling the voxel locations

in the VOXPHAN.DAT file. Photon collisions are scored by

determining the voxel location given the photon direction

coordinates. Scoring is tallied for each voxel and organ.


Pixel and Slice Size Determination


In order to determine the organ volumes, it is

necessary to determine the size of each image pixel and

slice in physical dimensions. Since these values are

dependent upon the camera system's electronics, they must be

determined after each camera adjustment or change. A pixel

and slice size determination study was conducted prior to

the patient and phantom studies and in the case when the

camera system's electronics were changed. Two line sources

(small tubes containing ~"Tc) of known length and distance

apart are imaged in the planar (static) mode. The line





73

sources are imaged in both the parallel and perpendicular

positions relative to the camera system's axis-of-rotation

(AOR) to detect changes in the x and y planes, which would

indicate the camera system was working improperly. The

system software was used to return the number of pixels in a

line drawn between the two line source centers in the planar

imaged. The image pixel size in centimeters per pixel equals

the distance between the two line sources in centimeters

divided by the number of pixels in the line drawn between

the line source centers. The slice size is determined by

dividing the length of the line sources in centimeters by

the number of transverse slices that is required to

transverse the length of the line sources. The result is

reported in centimeters per slice.


Phantom Studies


Since the Threshold Segmentation Method is used in this

research, a threshold value which best relates the actual

objects of interest to the resulting SPECT image objects

must be determined. Three phantom studies were conducted to

determine the best threshold value for a given volume and

condition and to verify that the SPECT, Monte Carlo, and

Dosimetry models were working properly. The first phantom

study consisted of several cylinders of different volumes

filled with homogeneously distributed activity ("'In) imaged

in air. The second phantom study tested a torso phantom





74

containing three organ inserts under three experimental

conditions. First, the organ inserts were filled with

homogeneously distributed activity and placed in the cold

(no activity present) water filling the torso phantom.

Second, the organ inserts were filled with heterogeneously

distributed activity and placed in the cold water filling

the torso phantom. And last, the heterogeneously distributed

organ inserts were placed in the hot (activity present)

water filling the torso phantom. The last phantom study

consisted of a single cylindrical volume filled with

activity homogeneously and heterogeneously distributed and

thermoluminescent dosimetry devices for measuring absorbed

dose.


Phantom Study One


It is necessary to determine the best threshold value

which will result in the SPECTDOSE program calculating the

most accurate organ volume. A phantom study using objects of

a known volume can be conducted to determine the threshold

value which results in the SPECTDOSE program calculating a

volume which is closest to the known volume. In this study,

five cylinders of different sizes were SPECT imaged using

the same setup parameters as in the Clinical Studies (see

the previous section, SPECT Camera System) (Table 4-1). The

resulting images were read by the program SPECTDOSE to

calculate the phantom volume and activity concentration



















Table 4-1. Phantom Study One Acquisition Parameters


FIVE CYLINDERS OF TISSUE EQUIVALENT MATERIAL

SOURCE: INDIUM-111


VOLUME (ml)


30.56

438.71

496.17

616.39

6032.50


ACTIVITY (GBq)


1.13

16.28

18.36

22.86

229.33


ACQUISITION PARAMETERS:

360 degree rotation
128 views at 12 s view'
20% window over each peak
medium energy collimator
64 x 64 Matrix


PIXEL SIZE:

SLICE SIZE:


0.69 cm

0.71 cm


PHANTOM





76

using different threshold values. The results were analyzed

by linear regression to determine the correlation between

the threshold value, phantom volume, and activity

concentration. The threshold value that yielded the best

correlation between the actual phantom volume and SPECTDOSE

measured volume was used for that range of volumes and set

of conditions.


Phantom Study Two


This study was conducted to simulate the conditions in

which a patient has been injected with a radiolabeled

substance. A tissue-equivalent torso phantom with a liver,

spleen, and tumor insert was tested under several

experimental conditions. The study set up parameters can be

seen in Table 4-2. The tumor insert was placed 12 cm below

the liver insert and the spleen insert was placed right of

the tumor insert 2.5 cm below the liver insert (Figure 4-

10). In the first experiment, the organ inserts were filled

with homogeneously distributed "'In activity and placed

inside the torso phantom, which is filled with water with no

radioactivity in it. The amount of activity added to the

inserts and the acquisition parameters can be seen in tables

4-2 and 4-3. In the second experiment, the liver and spleen

inserts were filled with small glass beads (5 mm diameter)

and 11In. The beads were used to distribute the

radioactivity heterogeneously within those organs. This




















Table 4-2. Phantom Study Two Acquisition Parameters


TORSO BODY PHANTOM WITH ORGAN INSERTS

SOURCE: INDIUM-111

PHANTOM VOLUME (ml)

LIVER 1200.00

SPLEEN 166.31

TUMOR 0.26

BODY PHANTOM 13854.42


ACQUISITION PARAMETERS:

360 degree rotation
128 views at 12 s view"
20% window over each peak
medium energy collimator
64 x 64 matrix

PIXEL SIZE: 0.80 cm

SLICE SIZE: 0.82 cm







-- 30cm -


Liver Insert
Volume = 1200 cm 3


Spleen Insert
Volume = 166.31 cm3


/-0.25 cm
h-i
1.3 cm


Tumor Insert
Volume = 0.26 cm3


Figure 4-10. Phantom Study Two Torso Phantom and Organ Inserts













Table 4-3. Phantom Study Two Experiments


I. HOMOGENEOUS DISTRIBUTION/COLD BACKGROUND

Activity is uniformly distributed within organ
inserts with no activity in body phantom
(background).


VOLUME (ml)
1200.00
166.31
0.26


ACTIVITY (MBq)
38.48
5.74
2.37


II. HETEROGENEOUS DISTRIBUTION/COLD
BACKGROUND

Glass beads were added to the liver and spleen
inserts displacing 150 and 40 ml of liquid,
respectively. No activity in body phantom.


VOLUME (ml)
1200.00
166.31
0.26


ACTIVITY (MBq)
32.45
4.22
2.29


III. HETEROGENEOUS DISTRIBUTION/HOT
BACKGROUND

Glass beads were added to the liver and spleen
inserts displacing 150 and 40 ml of liquid,
respectively. Activity was added to the
body phantom.


PHANTOM
LIVER
SPLEEN
TUMOR
BACKGROUND


VOLUME (ml)
1200.00
166.31
0.26
12307.89


ACTIVITY (MBq)
31.45
4.14
2.26
5.81


PHANTOM
LIVER
SPLEEN
TUMOR


PHANTOM
LIVER
SPLEEN
TUMOR





80

experiment simulates the condition in which the patient's

organ(s) has a cold nonradioactivee) tumor within it. The

heterogeneously distributed radioactive organs and the

homogeneously distributed tumor insert were placed in the

cold nonradioactivee) water of the torso phantom and SPECT

imaged. The third experiment consisted of the

heterogeneously distributed radioactive liver and spleen

inserts and the homogeneously distributed tumor insert from

experiment two placed in the torso phantom which is filled

with radioactive water and SPECT imaged. Indium-lll (5.8

MBq) was added to the water of the torso phantom (Table 4-

3). Each experiment was SPECT imaged three times to detect

camera fluctuations. If the results varied from image to

image, this would indicate that the camera system was not

working properly and that the variation in results was due

to an improperly working camera system.


Phantom Study Three


This study was undertaken to verify the results of the

Dosimetry Model by comparing its results to direct measuring

devices placed in the phantom and to results calculated by

other methods. Indium-lll was placed homogeneously and

heterogeneously in the Jaszczak Phantom**** along with

several thermoluminescent dosimetry devices. The Jaszczak

Phantom is a cylinder made of tissue-equivalent material

Data Spectrum Corporation, High Point, NC 27514





81

with a volume of 6032.50 milliliters. In the first

experiment, 73 megabecquerels of "'In was added to the water

of the Jaszczak Phantom and six TLD cards of two chips each

were placed on the walls in various locations in the phantom

(Figure 4-11). The phantom was SPECT imaged using the same

camera setup parameters reported in the SPECT Camera System

section of this chapter. The TLDs were exposed to 11In for a

half an hour in the phantom. In the second experiment, a

cubed insert (7 cm x 6 cm x 7 cm) filled with air was added

to the radioactive water of the phantom to distribute the

activity heterogeneously. Six new TLD cards were added to

the walls of the phantom and the cubed insert (Figure 4-12).

The phantom was SPECT imaged using the same camera setup

parameters noted above. The TLD cards, once exposed, were

read by an automatic TLD reader *. The TLD reader was

calibrated using a Cesium-137 needle source; whereby, two

TLD cards were exposed to the 137Cs source for each of the

four exposure times (Appendix B). Once calibrated, the

experimental TLD readings can be converted to exposure and

absorbed dose. The TLD results calculated at time infinity

were compared to the results of the Dosimetry Model,

Geometric Factor Method (142), and the results calculated by

use of data in MIRD Pamphlet No. 3 (143) at time infinity.

It is assumed in each of these calculational methods



TLD System 4000, Harshaw/Filtrol Partnership, Solon,
OH 44139









h-- 21.6 cm-
I TOP I


BOTTOM


n-- BACK PANEL


RIGHT
SIDE
PANEL


TOP


Jaszczak Phantom


LEFT
PANEL


E


CARD 6


BACK
PANEL


RIGHT
PANEL


BOTTOM


Figure 4-11. Phantom Study Three Experiment One TLD Location


LEFT
SIDE
PANEL


I I It
I I I
I I I
II I I
II I I
I I II
I I II
















21.6 cm--
TOP I



E
Organ Insert 0
I,
00'


BOTTOM
Jaszczak Phantom


CARD


Organ Insert


TOP


Figure 4-12. Phantom Study Three Experiment Two TLD Location


BOTTOM





84

(Dosimetry Model, Geometric Factor Method, and MIRD Pamphlet

No. 3) that the activity in the source organs are removed

only by physical decay, the effective half-life is equal to

the physical half-life, and all non-penetrating radiation is

absorbed in the source organ.


Thermoluminescent Dosimeters (TLDs)


Ionizing radiation incident on a thermoluminescent

crystal elevates an electron from the valence band to the

conduction band to leave a hole in the valence band. The

electron and hole pair migrate throughout the crystal until

they are trapped at impurity sites. When the chip is heated,

energy is imparted to the electron which causes it to move

and to eventually recombine with its counterpart hole (or

electron). The recombination energy is released in the form

of visible light, which can be detected by a phototube. The

thermoluminescent crystal used in this research is lithium

fluoride, which is the most common thermoluminescent crystal

used today (142). The lithium fluoride chip has a useful

range that extends beyond 103 Sv and good linearity

response, which extends below 0.1 mSv. The dynamic range of

TLDs, in general, is large, with doses from a few mSv to 10

Sv. Two TLD-100 chips (0.318 cm x 0.318 cm x 0.009 cm)

placed in the Type G-l gamma card configuration *.... were

used in this research. Six Type G-l cards were used in each


Harshaw/Filtrol Partnership, Solon, OH 44139






85

experiment and were secured in place in the phantom with a

hot glue gun.


Clinical Studies


The results of Phase One, Two, and Three clinical

studies being conducted at Bay Pines Veterans Administration

Medical Center (VAMC) in Bay Pines, Florida, using indium-

111 labeled B72.3-GYK-DTPA directed against colorectal

cancer, will be utilized in this research. The goals of

Phase One, Two, and Three studies are similar to those of

this research, in that, they both seek to determine the

radiation absorbed dose. Phase One, Two, and Three studies

also seek to establish the radionuclide-antibody

biodistribution, dosage range, clearance half-life, critical

organs, and optimal imaging and sampling times in diseased

patients (143). The research at Bay Pines VAMC is being

sponsored by Cytogen Corporation of Princeton, New Jersey,

and is ongoing. The experimental protocol for these studies

is given below.


Patients


Sixteen male patients participating in a phase I-III study

using indium-lll labeled B72.3-GYK-DTPA were screened prior

to antibody infusion. The age of the patients ranged from

49-89 years with a mean age of 67 years. All subjects had





86

proven primary or were suspected of having recurrent

colorectal cancer.


Monoclonal Antibody


The antibody, B72.3, is a murine monoclonal antibody of the

IgGi subclass which detects a 200K-400K molecular weight

tumor-associated glycoprotein called Tag-72. The Tag-72

antigen has been found to be expressed on certain human

colon and human breast carcinoma cell lines. B72.3 is

coupled to In-ill by oxidation of the oligosaccharide

moieties on the constant region of the antibody molecule.

This provides a site for specific attachment of

radionuclides and other ligands, while retaining the

homogeneous antigen affinity and binding characteristics of

the antibody. B72.3 is conjugated with the linker complex,

glycyl-tyrosyl-(N-e-diethylenetriaminepentaacetic acid)-

lysine (GYK-DTPA) to produce B72.3-GYK-DTPA-In-111 (Figure

4-13).


Monoclonal Antibody Procedure


Each patient was given a pre-infusion diagnostic blood

screening workup prior to the antibody infusion. The

analyses included routine blood chemistries, hematology,

electrolyte, and urinalysis, serum TAG-72, HAMA and CEA

levels. Each patient was then given B72.3-GYK-DTPA in

randomly assigned doses of 0.5, 1 or 2 milligrams of




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