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TRENDS IN EXTERNAL RADIATION EXPOSURE AMONG THE U.S NAVY MEDICAL PERSONNEL WORKING IN NUCLEAR MEDICINE DEPARTMENTS FROM

2

003

TO

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2020

A Thesis

submitted to the Faculty of the Graduate School of Arts and Sciences of Georgetown University

in partial fulfillment of the requirements for the degree of

Master of Science in Health Physics

By

TJahnensattudAennwt naarmSe. Almajed, B.S.

Washington, D.C. December 10, 2021

(
viii
)

CCooppyyrriigghhtt 2021 by Jannat Anwar S. Almajed All Rights Reserved

TRENDS IN EXTERNAL RADIATION EXPOSURE AMONG THE U.S NAVY MEDICAL PERSONNEL WORKING IN NUCLEAR MEDICINE DEPARTMENTS FROM 2003 TO 2020

SJatundneanttAnnamwear S. Almajed, B.S.

TThheessiissAAddvvisisoor rn:aLmueis Benevides, Ph.D.

ABSTRACT

Objectives: To assess trends in external occupational exposure of nuclear medicine (NM) workers from United States Navy (USN) medical centers from 2003 to 2020 and compare them with previously published data on NM workers from US civilian hospitals. Materials and methods: Analysis of the annual personal dose equivalents, deep dose equivalents Hp(10) (DDE) and shallow dose equivalents Hp(

0.07

) (skin dose) recorded using the DT-702/PD was conducted on

528

NM personnel working in USN medical centers. Also, analysis of 1,

35

7 annual shallow dose equivalents Hp(0.07) (extremity dose) recorded using DXT-RAD was conducted on

285

NM workers. The data used in the study was provided by the United States Navy Dosimetry Center (NDC). Summary statistics of the distributions of annual and cumulative DDE, skin doses and extremity doses are provided in this study. Annual doses of nuclear medicine personnel working in Navy hospitals/clinics that perform PET imaging besides general nuclear medicine studies were identified using publicly available websites’ information, analyzed and compared with those who work in nuclear medicine facilities that perform only general NM studies. Doses from the two groups were compared using a two-sample t-test with

95

% confidence interval. Results:

Median

annual doses of

0.38

mSv (IQR,

0.05

1.2

7

mSv; mean, 0.

82

mSv), 0.

37

mSv (IQR,

0.06

1.22

mSv; mean = 0.

80

mSv), and

2.89

mSv (IQR = 0.

76

7.86

mSv; mean =

6.65

mSv) for the DDE, skin dose and extremity dose, respectively, were observed in 2003–2020. Median cumulative

DDE, skin dose and extremity dose over 2003–2020 were

0.39

mSv (IQR = 0.05 –

3.18

mSv; mean =

2.96

mSv) and 0.39 mSv (IQR = 0.05 –

3.08

mSv; mean =

2.90

mSv), and

13

.0 mSv (IQR

=2.89 – 38.5 mSv; mean = 31.6 mSv), respectively. Median annual DDE, skin and extremity doses to workers from identified PET facilities were

0.44

mSv (IQR= 0.06 –

1.60

mSv; mean = 0.

99

mSv),

0.42

mSv (IQR = 0.06 –

1.58

mSv; mean = 0.

97

mSv) and

3.16

mSv (IQR =

0.73

9.51

mSv; mean =

8.74

mSv), respectively, against

0.29

mSv (IQR = 0.06 –

0.95

mSv; mean =

0.65

mSv),

0.30

mSv (IQR =0.06 – 0.95 mSv; mean = 0.

63

mSv) and

2.52

mSv (IQR =

0.76

6.19

mSv; mean =

4.72

mSv) to workers from non-PET facilities. The resultant p-value (p<0.05) of the two-sample t-test showed a significant difference between doses to NM workers from PET vs. non-PET facilities. Conclusions: All assessed values of the DDE, skin and extremity doses were well below the annual occupational limits established by the International Commissionon Radiological Protection. The median annual DDE to NM workers in the USN was lower than NM radiological technologists from US civilian hospitals. Our study’s mean annual skin dose was lower than NM technologists and NM physicians in Kuwait and NM technologists in Saudi Arabia. Moreover, our study’s mean annual extremity dose was half the lowest extremity exposure recorded among NM workers in Serbia. As expected, working in PET facilities was associated with increased radiation doses. This study provided new data useful for future exposure assessment in this population of radiation workers and improved radiation protection programs in medical centers.

ACKNOWLEDGEMENTS

The research and writing of this thesis is dedicated to

everyone who helped along the way. I would like to express my deepest appreciation to my thesis mentor Dr. Daphnée Villoing who helped me through all stages of planning and writing my thesis. Many thanks to my thesis advisor Dr. Luis Benevides, who made this work possible by helping in providing the data and contacting the NDC on my behalf. Thanks to Dr. Timothy Jorgensen for his continuous support and help to finish my degree. Thanks to Dr. Stanley Fricke for his advice and willingness to help every time I ask.

My completion of this degree could not have been accomplished without the support of my family. I am extremely grateful to my husband Ahmad Al Marzook for his sacrifices, love, and encouragement. Thanks to my daughter Julia for her love and patience and all the time she waited for me. Thanks to my parents, sisters, and my brother for their support and prayers.

TABLE OF CONTENTS

Chapter 1: Introduction 1
Chapter 2: Background… 4
Ionizing radiation in medicine 4
Biological effects of ionizing radiation 4
Overview of nuclear medicine 6
Nuclear medicine imaging… 8
Nuclear cardiovascular imaging 8
Positron Emission Tomography 9
Occupational exposure in nuclear medicine 10
History in radiation protection 12
Dosimetry Concepts 13
Dose Units 13
External radiation dosimetry in the US-Navy…

14

Chapter 3: Materials and Methods 17
Data Collection 17
Institutional Review Board 18
Dosimetry dose readings 18
Data cleansing – Inclusion and Exclusion criteria 19
Annual dose calculation… 21
Cumulative dose calculation… 21
Categorization 21
Statistical analysis 22
Chapter 4: Results 23
Annual doses 23
Annual deep dose equivalents distribution 23
Annual skin dose equivalents distribution… 26
Annual extremity doses distribution… 29
Cumulative dose 32
Cumulative deep dose and skin dose equivalents distribution. 32
Cumulative extremity doses distribution… 32
PET and non-PET 32
PET facilities distribution… 32
Non-PET facilities distribution… 32
PET vs. non-PET 33
Chapter 5: Discussion… 37
Conclusions 42
Bibliography 44
Appendix A:

Summary statistics of the annual deep dose equivalents for 528 nuclear medicine personnel working in the United States Navy medical facilities from 2003-2020

… 59
Appendix B:

Year

ly summary statistics of the annual deep dose equivalents for 528 nuclear medicine personnel working in the United States Navy medical facilities

60
Appendix C: Summary statistics of the annual shallow dose equivalents of the skin for 528 nuclear medicine personnel working in the United States Navy medical facilities from 2003-
2020…………………………………………………………………………………………..…..66
Appendix D: Yearly summary statistics of the annual shallow dose equivalents of the skin for 528 nuclear medicine personnel working in the United States Navy medical facilities

67

Appendix E:

Summary statistics of the annual shallow dose equivalents of the extremities for 285 nuclear medicine personnel working in the United States Navy medical facilities

73
Appendix F: Yearly summary statistics of the annual shallow dose equivalents of the extremities for 285 nuclear medicine personnel working in the United States Navy medical facilities 74
Appendix G: Summary statistics of the cumulative deep dose equivalents for 528 nuclear medicine personnel working in the United States Navy medical facilities from 2003-
2020……………………………………………………………………………………………….80
Appendix H: Summary statistics of the cumulative shallow dose equivalents of the skin for 528 nuclear medicine personnel working in the United States Navy medical facilities from 2003- 2020… 81
Appendix I: Summary statistics of the cumulative shallow dose equivalents of the extremities for 285 nuclear medicine personnel working in the United States Navy medical facilities from 2003- 2020… 82
Appendix G: Summary statistics of the annual deep dose equivalents corresponding to

221

NM personnel working in USN medical facilities identified as PET facilities 83
Appendix K: Summary statistics of the shallow deep dose equivalents of the skin corresponding to 221 NM personnel working in USN medical facilities identified as PET facilities 84
Appendix L: Summary statistics of the shallow deep dose equivalents of the extremities corresponding to

163

NM personnel working in USN medical facilities identified as PET facilities 85
Appendix M: Summary statistics of the annual deep dose equivalents corresponding to 3

61

NM personnel working in USN medical facilities identified as non-PET facilities 86
Appendix N: Summary statistics of the annual shallow dose equivalents of the skin corresponding to

361

NM personnel working in USN medical facilities identified as non-PET facilities 87
Appendix O: Summary statistics of the annual shallow dose equivalents of the extremities corresponding to

176

NM personnel working in USN medical facilities identified as non-PET facilities 88
Appendix P:

Two-sample t test’s result for the mean difference of the annual deep dose equivalents between non-PET and PET facilities

89
Appendix Q:

Two-sample t test’s result for the mean difference of the annual shallow dose equivalents of the skin between non-PET and PET facilities

90
Appendix R:

Two-sample t test’s result for the mean difference of the annual shallow dose equivalents of the extremities between non-PET and PET facilities

91

Appendix S: An example of a questionnaire could be used in future studies to help provide detailed information on the number of workers, workload, and radiation safety standards in the USN medical facilities

92

LIST OF FIGURES

Figure 1: DT-702 personal dosimeter 16

Figure 2: DXT-RAD finger dosimeter 16

Figure 3: Histogram of the distribution of

1,916

annual deep dose equivalents, Hp(10), previously collected and provided by the NDC for 528 workers from NM departments of the USN medical centers between 2003 and 2020. 24

Figure 4: Box-and-whisker plot of the trends in annual deep dose equivalents, Hp(10), to workers from NM departments of the USN medical centers between 2003 and 2020… 25

Figure 5: Histogram of the distribution of 1,916 annual shallow dose equivalents, Hp(0.07), previously collected and provided by the NDC for 528 workers from NM departments of the USN medical centers between 2003 and 2020… 27

Figure 6: Box-and-whisker plot of the trends in annual skin dose equivalents, Hp(0.07), to workers from NM departments of the USN medical centers between 2003 and 2020… 28

Figure 7: Histogram of the distribution of

1,357

annual shallow dose equivalents to the extremity, Hp(0.07), previously collected and provided by the NDC for 285 workers from NM departments of the USN medical centers between 2003 and 2020… 30

Figure 8: Box-and-whisker plot of the trends in annual shallow dose equivalents to the extremity, Hp(0.07), to workers from NM departments of the USN medical centers between 2003 and 2020… 31

Figure 9: Annual exposure of the personal dose equivalents Hp(10) in mSv for the USN personnel working NM facilities performing PET/CT vs. NM facilities that do not perform PET/CT 34

Figure 10: Annual exposure of the personal dose equivalents Hp(0.07), skin doses, in mSv for the USN personnel working in NM facilities performing PET/CT vs. NM facilities that do not perform PET/CT 35

Figure 11: Annual exposure of the personal dose equivalents Hp(0.07), extremity doses, in mSv for the USN personnel working in NM facilities performing PET/CT vs. NM facilities that do not perform PET/CT… 36

LIST OF TABLES

Table 1. Annual Occupational Dose Limits

52

Table 2. Categories and corresponding definitions in the first dataset provided by the Navy Dosimetry Center, for DT-702/PD data 52

Table 3. Categories and corresponding definitions in the second dataset provided by the Navy Dosimetry Center, for DXT-RAD 53

Table 4. Several annual records in 2003–2020 used the DT-702/PD 53

Table 5. A yearly number of annual records in 2003–2020, using the DXT-RAD 54

Table 6. PET versus non-PET data, using the DT-702/PD 54

Table 7. PET versus non-PET data, using the DXT-RAD 55

Table 8. The number of observations, several workers, median, mean,

Q1

,

Q3

, and

95th

percentiles, and the minimum to a maximum of various annual dose records for 2003-2020… 55

Table 9. Summary statistics of the annual dose records per year of the Hp(10). 55

Table 10. Summary statistics of the annual dose records per year of the skin dose equivalents, the Hp(0.07). 56

Table 11. Summary statistics of the annual dose records per year of the extremity dose equivalents, the Hp(0.07). 56

Table 12. The workers, median, mean, Q1, Q3, and 95th percentiles and minimum to a maximum of the cumulative deep dose equivalents, skin dose equivalents and extremity dose equivalents for 2003-2020… 57

Table 13. Summary statistics of the personal dose equivalents the Hp(10) and Hp(0.07) for the PET facilities’ skin and extremity records 57

Table 14. Summary statistics of the personal dose equivalents Hp(10) and Hp(0.07) for skin and extremity records in the non-PET facilities 58

CHAPTER 1. INTRODUCTION

Nuclear medicine (NM) is a specialized area of radiology that experienced significant developments in the second half of the 20th century (1). The evolution of instrumentation, a surge of new radiopharmaceuticals (2), and the advent of Single Photon Emission Computed Tomography (SPECT) and Positron Emission Tomography (PET) (3) have all contributed to the increased use of nuclear medicine worldwide and, more specifically in the United States (US) (2). The number of NM procedures performed worldwide increased from 23.5 million in 1980 (4) to 37 million in

2006

(5) and from 7 million in 1982 (6) to 17.2 million in 2006 in the United States (5). Hence, in 2006, about half of the worldwide NM procedures were performed in the United States (2). The tremendous increase in the performance of NM studies resulted in increasing the annual per-capita effective radiation dose to the US population (7), therefore increasing the occupational exposure among medical workers in NM departments (8).

Medical radiation workers are exposed to protracted low-level radiation for extended periods. In contrast to other medical radiation workers, NM technologists are in direct contact with the source of radiation by manipulating and handling radionuclides (9), which elevates their risk of certain cancers such as breast cancer and squamous cell carcinoma (SCC), and circulatory diseases such as myocardial infarction (10). Due to the possible risks from increased radiation exposure, the International Commission on Radiological Protection (ICRP) established recommendations to limit occupational doses and ensure the workers’ safety (11). It also emphasizes that the radiation exposure to the workers and patients should be kept As Low As Reasonably Achievable (ALARA) (12).

Previous studies of occupational doses to US radiologic technologists show that radiation doses have decreased since 1939 (13). Reducing these doses is likely due to improved radiation

(
10
)

safety practices (11,14). However, a recent study involving NM technologists from nine US medical institutions showed that the maximum values of the annual personal dose equivalents generally increased from 1992 to

2015

. In this study, the mean annual personal dose equivalent (2.69 mSv) was consistent with annual mean doses to NM technologists from other countries (1.5 to 3.5 mSv) and higher than the estimated annual mean effective dose to general medical workers worldwide (0.7 mSv) (15). Moreover, it was also higher than the mean annual dose to US radiologic technologists. Another recent study that examined dose trends among US radiologic technologists performing NM procedures or not over 36 years period showed that the annual dose records for US radiologic technologists performing NM procedures (median 1.2 mSv) were higher than for general radiologic workers (75th percentile= 0.40 mSv) (16). Finally, the study showed that higher doses were associated with performing more diagnostic NM procedures, specifically cardiac and PET procedures.

Variations in work practices and radiation safety techniques between institutions and countries can lead to heterogenous radiation exposure measurements among different groups of NM workers (14). For example, studies conducted in the US to examine the effect of the changes in NM practices on occupational doses included technologists from different medical institutions all over the country. Therefore, these studies are susceptible to heterogeneity and measurement biases due to the variations between NM departments regarding the radiation protection standards, the radiopharmaceuticals in use, and technology updates. The present study has the advantage of focusing specifically on exposures over time to a specific population of workers, all serving within the United States Navy (USN) — a group of NM workers subject to the same radiation safety programs and regulations. This should significantly mitigate the problem of exposure heterogeneity within the study group.

Using a USN cohort of NM workers, this thesis tests the hypothesis that NM workers’

annual personal dose equivalents in USN medical centers are lower than NM workers’ annual personal dose equivalents from civilian medical centers across the United States due to a stringent radiation protection program within the USN. Conclusions based on these results may help understand occupational exposure in nuclear medicine and improve radiation protection programs.

CHAPTER 2. BACKGROUND

1.1 Ionizing radiation in medicine

Radiation is energy; released from a source that travels through space in electromagnetic waves or particles. Radiation consists of ionizing radiation (IR) and non-ionizing radiation. This dissertation will focus on IR, a type of radiation with a short wavelength and enough energy to remove or relocate an electron from an atom. The whole population is naturally exposed to IR from the space, the earth, the air, and the radionuclides present in our bodies, such as Pottasium-

40. In the 1980s, eighty-two percent of the exposure to the U.S population was from natural background radiation (2).

In 1895, Wilhelm Roentgen accidentally discovered X-rays while experimenting on a cathode tube (17). Within a year of this discovery, X-rays were used in medicine for many applications, from finding a bullet in a patient’s leg to diagnosing kidney stones (17). Two years later, X-rays started to be used in military hospitals (18). At the same period of X-ray discovery, other scientists such as Pierre and Marie Curie or Henri Becquerel were studying natural radiation (17). The Curies discovered polonium and radium, first used in industrial applications (17). Later, in 19

46

, manufactured sources of gamma radiation were also available. These discoveries and the invention of technologies in the medical field resulted in a new radiation exposure source to the population (17). Nowadays, about half of the radiation exposure (48%) to the U.S population comes from diagnostic and therapeutic medical applications (2).

1.2 Biological effects of ionizing radiation

Widespread unregulated use of IR was observed in the early years following its discovery. The lack of understanding of radiation-related risks on health led to severe injuries. Due to the late manifestation of detrimental radiation effects, the need for radiation safety was not immediately

recognized (19). First dermatitis and skin cancers were observed one and six years after discovering X-rays, respectively (18). Most of our understanding of radiation hazards came from the study of Atomic Bomb survivors after World War II (17).

When radiation interacts with the human body, the damage occurs at the cellular level, making it hard to detect (17). Radiation can cause two biological effects: deterministic (non- stochastic) and stochastic. Deterministic effects have a threshold: the severity of the response increases with the radiation dose, and below a certain dose threshold, no biological effect can occur (19). Some examples include skin burn, radiation sickness, sterility, and acute radiation syndrome (19). These effects depend on different variables such as the dose, dose fractionation, and type of radiation (19). In contrast, stochastic effects are random, and there is no threshold dose (19). The probability of the effect is proportional to the radiation dose, but the severity is independent (19). Cancer and heritable or genetic changes are the two main types of stochastic effects (19). As far as cancer is concerned, most cancers have a 20 year latency period and can occur after many years of exposure. Due to the long latency period, it is challenging to know whether the cancer was caused by radiation exposure or other factors.

There are different types of theoretical dose-response models related to the use ofany carcinogen, including radiation (20). The first is the linear no-threshold model, which states that there is a risk at any level of radiation exposure, no matter how small (20). This model is based on biological responses at high radiation doses (20). Still, because no clinical effects are seen from radiation exposure below 0.5 Gray (Gy), it is best to be conservative and take the low doses cautiously (20). The second model is the linear threshold which consists of a known threshold below no clinical effects are seen, but at the threshold level (0.5 Gy), the effect will increase linearly (20). The third model is the linear-quadratic, used for overall human response (20). This

model states that the effect is linear at low doses, but the response becomes quadratic as the dose increases. The NRC accepts the linear no-threshold model since it is the most conservative. It likely does not underestimate the actual risk, thereby allowing maximum protection when setting risk-based dose limits.

1.3 Overview of nuclear medicine

Nuclear medicine is a multi-disciplinary modality that involves administering radiopharmaceuticals for diagnostic and therapeutic purposes. Diagnostic nuclear medicine uses radioactive tracers to measure the function of an organ (physiological) and the biochemical; images in the body; in therapeutic nuclear medicine, unsealed radioactive materials are used to treat various thyroid cancer and hyperthyroidism. In nuclear medicine, radioactive chemical elements (radionuclides) can be used without any biological vector, such as iodine-131, or labeled with drugs or particles, forming a radiopharmaceutical (21).

Radiopharmaceuticals are radionuclides bound to biological molecules, targeting specific organs or tissues (22). They can be administered to the patient by intravenous or peritumoral injection, orally, or inhalation (2). Each NM imaging study corresponds to a specific radiotracer distributed in a targeted region of interest (ROI). The radiotracer emits gamma rays with given energies that can be detected by a gamma camera positioned next to the patient.

Most NM procedures focus on diagnostic, while therapeutic procedures only account for a small percentage (2). Therapeutic NM procedures are performed with a lower frequency than diagnostic NM procedures but with higher administered activities of radiopharmaceuticals (5). For example, the administered activity of iodine-131 for thyroid uptake study (diagnostic) is 2.8- 4.4 megabecquerel (MBq) (23), but 185-555 MBq for hyperthyroidism treatment (therapy) (24). However, since 1985, therapeutic NM procedures in developed countries have almost doubled (5).

Diagnostic NM studies can provide functional and anatomical information, whereas other diagnostic studies such as radiography or Computing Tomography (CT) usually provide just anatomical information (2). Diagnostic NM procedures can be divided into two categories based on technology and instrumentation: general diagnostic nuclear medicine and positron emission tomography (PET). In general diagnostic nuclear medicine, a gamma camera is used to obtain either planar imaging (two-dimensional projection image) or single-photon emission computed tomography (SPECT) imaging. In both cases, detectors collect gamma rays emanating from the patient after administering a radiotracer. The gamma camera rotates around the patient for SPECT imaging to record photons from different angles. A three-dimensional projection image is then reconstructed. Radiotracers used for planar and SPECT imaging emit low to medium energy photons (80-200 keV)(2).

Positron emission tomography (PET) was introduced at the end of the 1970s. In the early 1980s, the clinical applications of PET emerged in the field of neurology (25). In the early 1990s, PET was implemented in cardiology clinics (25). In the late 1990s, the F-18 fluorodeoxyglucose (FDG) began to be used for the evaluation of oncology patients, leading to rapid growth in the number of performed NM studies worldwide since 2000 (25) (5). This imaging technology relies on the administration of positron-emitting radionuclides and the detection of coincidence photons (i.e., 511 keV photons simultaneously emitted in opposite directions after a positron-electron annihilation) (5). The average annual growth rate of PET studies was 80 % from 2000 to

2005

, against 9 % for non-PET NM diagnostic studies (21): the rapid growth in the PET studies was due to the introduction of the integrated PET/CT system in early 2000 and the use of F-18 FDG in oncology (25).

Hybrid imaging was introduced for both diagnostic and therapeutic applications (2). SPECT or PET imaging can be used in conjunction with conventional CT (SPECT/CT, PET/CT) (2), or more rarely, MRI (PET/MRI) (2), to obtain physiological images and to provide attenuation correction, which helps in improving the images by removing the effect of the artifact. Hybrid imaging techniques improve the accuracy of detecting and localizing disease and are increasingly used in recent years (2).

1.4 Nuclear medicine imaging

1.4.1 Nuclear cardiovascular imaging

Cardiac NM are non-invasive diagnostic procedures dedicated to assessing coronary artery disease and evaluating possible heart damage from cancer treatments such as radiotherapy and chemotherapy. NM cardiovascular studies have increased rapidly since 1979 and have become the most frequent procedure performed in nuclear medicine (1). In 2005, cardiac procedures accounted for 57% of the total completed NM studies in the US (5). The most common cardiac NM study is the myocardial perfusion stress test, which allows evaluation of the coronary arteries. Myocardial perfusion stress test performed in the US in

2014

accounted for 5.98 million studies (26).

Since the late 1960s, there have been few approved radiotracers used in nuclear cardiology (23). Nowadays, 59% of performed SPECT cardiac studies use Tc-99m Sestamibi (Tc-99m MIBI), 20% use Tc-99m Tetrofosmin, and 9% use Tl-201 Thallous Chloride (23). The amount of activity administered per procedure increased due to the reduction in the use of Tl-201 Thallous Chloride in myocardial NM studies. The typical administered amount of activity of Tl-201 Thallous Chloride before 2000 was

111

MBq and after 2000 is 148 MBq, while the administered amount of activity of Tc-99m MIBI and Tc-99m Tetrofosmin is 1110 MBq for one day protocol (23).

Furthermore, cardiac NM studies account for 8

5%

of the effective dose to the NM patient population (5).

In

2011

, a Turkish study estimated radiation doses to technologists per NM procedure (27). It showed that cardiac studies performed using Tc-99m MIBI delivered higher doses toNM technologists than whole-body bone scans, thyroid scans, and renal scans (27). The cumulative radiation exposure to technologists performing cardiac NM scans increased over time, which might be due to an increased frequency of cardiac procedures (1). Moreover, the myocardial perfusion stress test usually includes two injections, and technologists spend a longer time with the patient during injection, stress test, and camera positioning, contributing to increased occupational exposure (1).

1.4.2 Positron Emission Tomography

Positron emission tomography (PET) is a more recent NM technology. The science behind PET imaging started early in 1929 (28). Still, it was not clinically applicable until Ter-Pogossian et al. developed in 1975 a PET whole-body camera that provides high contrast images of positron- emitting organs (29). PET imaging relies on detecting photons emitted from the patient’s body after the injection of a positron-emitting radioisotope (29). When the emitted positron has lost its energy, it annihilates with an electron within the body to create two 511 keV photons (28). The PET camera is composed of scintillation crystals that absorb the photons and convert them into light photons. When two 511 keV photons are detected in coincidence (at 180° and simultaneously), the light is converted into an electrical signal (30).

Recently, the number of performed PET procedures increased from less than 2% to 15% due to several factors: the advent of the hybrid PET/CT system after 2000, an increasing number of cyclotrons for the production of short-lived positron-emitting radioisotopes (most positron

emitters have half-lives measured in minutes), and a decrease in the cost of PET cameras (2). Moreover, malignant tumors metabolize glucose faster than benign tumors, making F-18 FDG useful in oncology (28). The high demand for PET in oncology is also a leading cause of the increase in PET scans annually (31).

The annihilation photons from the radionuclides used in PET have a higher energy (511 keV) than the energy of the photons from radionuclides typically used in general NM studies. Accordingly, the annihilation photons have a greater ability to penetrate deeper tissues, which causes a higher internal organ risk to workers (31). An Australian study compared the radiation doses to technologists working in general NM with doses to those working in PET and showed that technologists rotating through PET received higher whole-body doses than those who only performed general NM procedures (31).

1.5 Occupational exposure in nuclear medicine

With ionizing radiation in medicine, medical workers are sometimes exposed. Those working in NM departments, including NM technologists, physicians, nurses, health/medical physicists, are more or less exposed to ionizing radiations depending on their occupationand workload. Occupational exposure occurs from any procedure that requires the worker to stand near a radioactive source during the shipping, preparation, or administration of the radiopharmaceutical. Furthermore, standing near the patient after the administration can also lead to radiation exposure (8). In the earliest years of nuclear medicine, scientists focused on improving the instrumentation, interpreting the medical images, and conducting clinical trials to approve new radiopharmaceuticals, with little attention to monitoring occupational exposure (8).

The US National Cancer Institute conducted a cohort study on 90,000 US radiologic technologists employed in the twentieth century (32) that showed increased risks of leukemia (33),

melanoma and non-melanoma skin cancer (34-35), and breast cancer (36), for these technologists. Another study showed a statistically significant increase in cancer mortality among British radiologists who had been working for more than 40 years in the twentieth century (37). A recent study of radiation-monitored workers employed in the nuclear industry in France, the United Kingdom, and the US showed a positive association between cumulative dose of ionizing radiation and death caused by leukemia among workers exposed to low doses of radiation (38). Compared with the nuclear industry, the medical field’s lack of historical dosimetry data made it more challenging to estimate radiation risk among those workers (39). Starting in the 19

50

s, scientists became more aware of radiation’s health hazards and gave more attention to occupational exposure. This awakening led to increasing the awareness of NM workers’ monitoring (8).

NM workers are potentially exposed to radiation internally and externally. Internal radiation exposure can occur after inhalation, ingestion, or skin contamination with radionuclides (39). Individual monitoring for internal exposure to radiation is usually achieved by body activity assessment or air sampling (39). Doses from internal exposure during routine work in the NM department are much lesser than the external exposure (39). Therefore, the dose assessment for internal exposure to NM workers is only performed when an unanticipated event has possibly internally exposed the worker. Otherwise, NM workers are externally exposed to ionizing radiations during a typical workday due to the proximity with radioactive materials during transportation, manipulation, injection, and patients’ transportation, positioning, or imaging (39). For that reason, NM workers are regularly monitored for external radiation exposure by wearing two dosimeters: a whole-body dosimeter on the chest and an extremity dosimeter on the finger.

1.6 History in radiation protection

In the 1896s, the American engineer Wolfram Fuchs established the first radiation protection recommendations: time, distance, and shielding (18). In 1925, the first meeting of the International Congress of Radiology (ICR) was held in London, and the International Commission on Radiation Units and Measurements (ICRU) was established (18). In 1928, the International X- ray and Radium Protection Committee (IXRPC) provided its first recommendation, emphasizing the importance of shielding to protect against superficial injuries and changes in the blood, and set a limit of working hours (18). In 1934, the first set of exposure limits was established for X-ray irradiation (18). This recommendation (0.2 roentgen per day) can result in an annual effective dose of about

500

mSv (18). In 1938, the same exposure limits and regulations were adopted for gamma radiation as had previously been established for X-rays (18). After world war II, in 1951, the International Commission on Radiological Protection (ICRP) was established, and this commission issued a recommendation of a maximum permissible dose of 0.5 roentgens/week and

1.5 roentgen/week for both X-ray and gamma radiation for whole-body exposure and hand exposure, respectively (18).

For the first 60 years of using ionizing radiation in industry and medicine, the main goal in radiological protection was to avoid any deterministic effects on workers (18). During this time, the ICRU started to replace roentgen ( a unit of exposure) with rem ( a unit of dose equivalence), and the limit from 1951 became 0.3 rem /week, resulting in annual occupational effective dose of

150

mSv (18). In 1954, the commission provided the first recommendation that encourages limiting the exposure from IR to the lowest possible level (18). In 1958, following the Geneva meeting, the commission published its recommendation in publication 1, including a limit of accumulated dose equivalent corresponding to an average annual occupational effective dose of

50 mSv (18). The 1954 recommendation was replaced by as low as practicable in publication 9 in the 1966’s report, and the limit of accumulated dose equivalent was replaced by an annual occupational limit of 50 mSv (18). In 1977, the ICRP established a dose limitation system and introduced the three principles of protection: justification, optimization, and the application of annual occupational dose limits (the total effective dose equivalents and the dose equivalents). In 1990, the ICRP provided more specified numerical limits to protect workers (Table 1)(11). In the United States, the Nuclear Regulatory Commission (NRC) was created by congress in 1974 to regulate the use of nuclear materials and to ensure the safe use of radioactive materials for beneficial civilian purposes while protecting the environment and people. The current Navy radiation protection standards are consistent with or more stringent than those of the NRC.

1.7 Dosimetry concepts

1.7.1 Dose Units

The quantities used in radiation dosimetry are divided into three categories: physical quantities, which describe the interactions between the radiation and matter (40), protection quantities, and operational quantities, both used in radiation protection dosimetry (

41

). The ICRP has supported a system for radiological protection for more than 50 years (42). In

2007

, the most recent protection quantities were recommended by the ICRP in publication

103

, which include the mean absorbed dose, the equivalent dose, HT, and the effective dose, E (42). The equivalent dose is based on the mean absorbed dose multiplied by a radiation-weighting factor, which depends on the biological effectiveness of the type of radiation (43). After applying tissue-weighting factors, the effective dose is the sum of all exposed tissues’ equivalent doses. The effective dose is used for protective dose assessment (43). It is calculated for a reference male or female but never for a specific individual.

Protection quantities are impossible to measure directly; therefore, equivalent doses and effective doses cannot be used directly in radiation monitoring but can be assessed using operational quantities (43). The ICRP and the ICRU defined operational quantities as replacing the protection quantities to ensure compliance with regulations and exposure limits to workers (44). Accordingly, many countries have used operational quantities for individual external radiation monitoring purposes (42). Although the operational quantities generally provide a conservative estimate for the protection quantities (42), the ICRU stated that they should be used as estimates for the protection quantities when doses are below dose limits (44).

Operational quantities consist of area monitoring quantities and a personal dose equivalent used for individual monitoring (42). For the present study, only the personal dose equivalent will be discussed. The personal dose equivalent, Hp (d), is a dose equivalent at an appropriate depth, d, below a specified point of the body (43). A depth of d= 10 mm is used for the deep dose equivalent (DDE-whole body), while a depth of d= 0.07 mm is used for the assessment of the shallow dose equivalent (SDE) to the skin and extremities (43). The relationship betweenthe effective dose and Hp(10) is based on a uniform whole-body irradiation (44). The deep dose equivalent Hp(10) is estimated for photons and electrons using a single detector whose output signals are proportional to the absorbed dose (44). The shallow dose equivalent Hp(0.07) is estimated using a thin detector material whose output signals are proportional to the absorbed dose to tissue and used for low-energy photons and beta particles monitoring (44).

1.7.2 External radiation dosimetry in the US-Navy

The US Navy (USN) specifies acceptable dosimetry devices for monitoring Navy radiation workers (45). All NM personnel working in the USN medical centers are required by the Navy regulations to wear personnel dosimeters (PDs). PDs are used to monitor DDE and SDE.

Simultaneously, some NM workers, such as NM technologists, must wear extremity dosimeters (45).

In 1973, the Navy introduced thermo-luminescent dosimeters (TLD) for gamma exposure monitoring. Since 2002, the Navy has been using a DT-702 manufactured by Saint Gobain (Harshaw 8840) for personnel dosimetry. It uses a high-sensitivity LiF doped with magnesium (Mg), copper (Cu), and phosphorus (P) (LiF: Mg, Cu, P) (45). The DT-702/PD is composed of a TLD card and a holder. The TLD includes four lithium fluoride (LiF) pellets of different thicknesses and compositions mounted between two Teflon sheets on an aluminum card (45).

Elements 1 and 2 are 0.381 mm thick of LiF-700H, element 3 is a thinner

0.25

4 mm of LiF-700H, and element 4 is 0.381 mm of LiF-

600

H (45) . LiF-700H can measure photon and beta radiation, while LiF-600H is useful for measuring photon, beta, and neutron radiation (45). The holder consists of filters that provide variable radiation absorption thicknesses to assess DDE and SDE (45). Element 1 is placed behind 242 mg/cm2 plastic combined with 91 mg/ cm2 copper and discriminates gamma radiation energy levels (46). Element 2 is placed behind 1,000 mg/cm2 of plastic and is used for determining the deep dose Hp(10) (46). Element 3 is covered by a 17 mg/cm2 Mylar window for shallow dose equivalent estimation (46). Element 4 is placed behind a combination of 242 mg/cm2 of plastic and 240 mg/ cm2 of Tin and used to provide neutron information as well as medium energy photon discrimination (46) (Figure 1). The NDC provides NM workers with Thermo scientific DXTRAD finger ring dosimeter for extremity monitoring. DXTRAD is a single element LiF TLD used to monitor photon and beta radiation and mounted in an adjustable ring (45) (Figure 2).

(
Figure

4:

DT-702

personal

dosimeter.
Cardholder
Filter 2:

Plastic
Filter 3:
Mylar
window
Filter 4:
Plastic and
Tin
Filter

1:

Plastic

and
Copper
LiF Card
)

Figure 5: DXT-RAD finger dosimeter.

*Image from (NAVMED P-5055, Radiation Health Protection Manual)

CHAPTER 3. MATERIALS AND METHODS

This study is designed to examine the changes in annual occupational exposure among a study population of NM personnel working in USN medical centers, using personal dose equivalents (deep and shallow) recorded from personnel passive dosimeters and shallow doses recorded from extremity dosimeters. A dosimetry dataset was received from the United States Navy, Naval Dosimetry Center (NDC), the centralized dosimetry processing laboratory for US Navy. NDC distributes, receives, processes, and archives exposures from the USN occupational workers deployed worldwide.

2.1 Data Collection

The NDC is a large-scale processor responsible for sending dosimeters to over250 locations worldwide (47) and preparing summary radiation exposure reports to the Navy and Marine Corps personnel (45). It provided two datasets that include dose records of NM personnel working in the USN medical centers over almost 20 years. The first dataset contains the radiation exposure obtained from personal dosimeters over 2002-2020. The second dataset contains radiation exposure obtained from extremity dosimeters over 2003-2020. The two datasets were provided as Microsoft Excel spreadsheets. Data used in this study are explained in Table 2-3.

Moreover, the Navy provides a 2-digit occupational code that identifies Navy employers’ occupation: the assigned code is 32 for NM occupation (45). For this study, code 32 was usedby the NDC to extract Navy personnel working in NM departments. Radiation exposure monitoring data of NM personnel working in Naval medical centers from 2003 to 2020 were included in this study. The data collection period was set to 2000-2020, corresponding to the years when the exposure to NM workers was expected to increase due to the advent of PET/CT imaging. It also matches an increased use of Tc-99m in myocardial studies, which require higher administered

activities, as previously described (Background). However, as the USN transitioned to a new dosimeter in 2002, the NDC did not provide any data collected before that year.

2.2 Institutional Review Board

An institutional review board (IRB) is a group that a research center has formally designated to review and monitor research involving human subjects (48). They work to protect the rights and safety of humans who participate in the research. Georgetown University’s IRB reviewed this study’s proposal under ID: STUDY00003615 and was determined as exempt (non- human research). As defined by the US Department of Health and Human Subjects under 45 CFR 26.101(b) (48) from 45 CFR part 46 requirements, an exempt study may include existing data, but the subjects cannot be identified from the information presented in the study. To fulfill this condition, the NDC deidentified data: name, age, gender, date of birth, or any other identifiers were not used in this study.

2.3 Dosimetry dose readings

The operational quantities Hp(d) (mSv) have been used in the applicable regulations of many countries for individual external monitoring to ensure workers’ compliance with radiation safety (49). Collected dosimetry information for external radiation monitoring to radiation workers generally includes two dose quantities: Hp(10) and Hp(0.07), which are obtained from personal and extremity monitoring devices, respectively (15). The USN requires NM workers to wear the dosimeter at the waist/chest level for photon and beta radiation monitoring and a DXT-RAD finger ring dosimeter for extremity monitoring (45).

NM personnel working in Naval medical centers have been routinely monitored using TLD dosimeters since 1973 (45). Since 2002, the NDC has issued a personnel monitor (DT-702/PD) quarterly (95 days maximum) to monitor their radiation workers (45). Still, they monitored

monthly (35 days maximum) any NM technologist and other NM worker expected to receive an annual effective dose equivalent of 5 mSv (45).

The Navy does not keep the exact job title of their workers in records. In nuclear medicine, NM workers can be either technologists, nurses, physicians, or health/medical physicists, and this distinction could not be made in our data. No further investigation could be conducted to obtain this information for the sake of anonymity. Therefore, the monitoring time of the dose records varied based on the variation in the occupations in the NM department. Although, in the data, we observed monitoring times that exceeded 95 days in 360 records corresponding to 154 individuals working in 12 USN medical centers. Dosimetry data corresponding to extended periods of 95+ days was considered acceptable in this study; they were not excluded and believed to have no detrimental effect on our study.

The lower limit of detection (LLD) of the dosimeter DT-702/PD is 0.03 mSv for DDE and SDE for photon and beta monitoring and 0.05 mSv for DDE for neutron monitoring (50). As confirmed by NDC workers, the US Navy keeps all the recorded doses, including the doses below the LLD levels, for use in retrospective studies. Therefore, annual dose equivalents below and above the LLD level were included in the data analysis in this study.

2.4 Data cleansing – Inclusion and Exclusion criteria

The NDC provided whole-body exposure (deep dose equivalent, DDE) and skin exposure (shallow dose equivalent, SDE) data for 528 individuals working in NM departments of 16 Naval medical centers over 2002-2020: these data were recorded using the DT-702/PD. Besides, the NDC provided extremity exposure (SDE) data for 305 individuals working in NM departments of 15 Naval medical centers over 2003-2020: these data were recorded using DXT-RAD finger rings.

Henceforth, the SDE from personal dosimeters will be referred to as “skin dose,” and the SDE from extremity dosimeters as “extremity dose.”

Records

before 2002 were excluded from this study because of a dosimetry technology transition and change in the Lower Limit of Detection in the Navy. NDC provided the data with a unique anonymized individual code to link each individual’s data. These unique individual codes ensured anonymity of the individual workers. The data included from NDC included the issue date and the collection date of the dosimeters, which was used to convert period doses to annual doses, as explained in the next paragraph.

The initial dataset received from NDC included 7,641 records of each DDE and skin dose and 4,789 records of extremity doses. Duplicates were first identified in Excel using the following variables: unique code, issue date, and collection date. After the data cleansing, 7,578 records remained for DDE and skin doses and 4,747 for extremity doses. Overlaps between years were then tracked to avoid overestimating, and doses were recalculated by calendar year. For example, if the issue date was at the end of 2003 and the dosimeter was collected early in

2004

, the total monitoring duration for this dosimeter was calculated by subtracting the issue date from the collection date. Then, the total number of days with a dose was derived for each calendar year. An average daily dose was then calculated by dividing the recorded dose by the total monitoring duration and eventually multiplied by the total number of days of that calendar year. 1,201 and 830 records were found to overlap between two years in the data from DT-702/PD and DXT-RAD dosimeters, respectively, which led to as many more new records in the datasets of these respective dosimeters. A total of 161 records of extremity doses from 20 individuals were excluded for not being linked to any individual from the whole-body data.

2.5 Annual dose calculation

The unique code and the issue year converted period doses to annual doses. All the available DDE values for each worker and each year were summed to obtain annual doses. The same step was taken to calculate annual skin and extremity doses. Doses provided in Roentgen equivalent man (rem) by the US Navy were converted into millisieverts (mSv). Yearly numbers of annual records are provided in Table 4-5.

2.6 Cumulative dose calculation

The cumulative personal dose equivalents were calculated by summing the annual records for each individual over the period a worker was exposed to radiation in USN NM departments. Five hundred twenty-eight cumulative doses of each DDE and skin records and 285 cumulative doses of extremity records were included in the analysis.

2.7 Categorization

The NDC provided the mailing address associated with each issued dosimeter, including the Navy medical center name, city, state, and zip codes. Data from DT-702/PD records corresponded to 16 locations, while data from DXT-RAD records corresponded to 15 sites. These addresses were used to discriminate PET and non-PET facilities, using publicly available Navy hospitals/clinics’ websites. Our research was focused on NM and PET features in the presentations of radiology departments. If the website mentioned both NM and PET, we categorized the facility as a PET facility; otherwise, it was categorized as a non-PET facility. More detailed information is provided in Tables 6-7. For 140 dose records corresponding to 78 individuals, all from 2003, dose data were excluded from our PET vs. non PET analysis due to the absence of a mailing address.

2.8 Statistical analysis

The statistical software STATA version 16 was used to analyze the data. The distributions of annual and cumulative dose records of NM personnel working in Naval medical centers from 2003-2020 were described using summary statistics (e.g., 25th, 50th, 75th, and 95th percentiles) and graphical methods (e.g., histograms and box-and-whisker plots). Owing to the large observation number within the PET and non-PET facilities, a parametric test was conducted without the necessity to perform a normality test. The F-ratio test for the equality of the variances was served with a

95%

confidence interval (CI). It showed significant differences between the variances of the two groups: annual exposure of the personnel working in the USN NM facilities perform PET/CT vs. the annual exposure of personnel working in the USN NM facilities that do not perform PET/CT of all variables DDE, skin doses and extremity doses (p= < 0.05). Therefore, the DDE, skin doses, and extremity doses were statistically analyzed between both groups using the two-sample t-test, assuming unequal variance. For all statistical tests, p< 0.05 was considered statistically significant. The null hypothesis (i.e., the hypothesis to be tested) was no difference in the annual radiation exposure of personnel working in the USN NM facilities performing PET/CT vs. the annual exposure of personnel working in the USN NM facilities that do not perform PET/CT. The alternate hypothesis was a difference in the annual radiation exposure of personnel working in the USN NM facilities performing PET/CT vs. the annual exposure of personnel working in the USN NM facilities not performing PET/CT. (Rejection of the null hypothesis implies that the alternative hypothesis is correct).

CHAPTER 4. RESULTS

Summary statistics of annual dose records to NM workers from medical centers of the US Navy between 2003 and 2020 are presented in Table 8. A total of 1,916 and 1,357 annual dose records were obtained from 2003 to 2020 using the DT-702/PD and the DXT-RAD, respectively (Table 4-5). The numbers of annual records varied over time, with average values of 106 (37 –

159

) and 75 (35 – 103) for DT-702/PD and DXT-RAD, respectively. The average number of annual records per NM worker were 3.63 and 4.76 for DT-702/PD and DXT-RAD, respectively.

3.1 Annual doses

3.1.1 Annual deep dose equivalents distribution

A total of 1,916 annual deep dose equivalents (Hp(10)) – recorded between 2003 and 2020 for 528 individuals – were included in the analysis. These annual Hp(10) varied from 0.00 mSv to

7.18

mSv, with a median value of 0.38 mSv (interquartile range [IQR], 0.05-1.27 mSv; mean,

0.82

mSv). Seventeen percent of the annual Hp(10) were below the LLD of the DT-702/PD but were included in the analysis. More than 95% of the annual Hp(10) received by NM workers in our cohort were below three mSv [95.3% (1827 of 1916])(Figure 3). Median annual Hp(10) remained relatively constant from 2003 to 2020 (range,

0.12

-0.82 mSv) (Table 9). The distribution of the maximum value of annual Hp(10) fluctuated over time (range, 1.87-7.18 mSv), with the highest value observed in 2015 (Figure 4). No correlation was found between the number of individuals monitored each year and the maximum value.

Figure 3: Histogram of the distribution of 1,916 annual deep dose equivalents, Hp(10), previously collected and provided by the NDC for 528 workers from NM departments of the USN medical centers between 2003 and 2020.

Figure 4: Box-and-whisker plot of the trends in annual deep dose equivalents, Hp(10), to workers from NM departments of the USN medical centers between 2003 and 2020.

*The upper and lower whiskers represent the maximum and minimum values.

3.1.2 Annual skin dose equivalents distribution

A total of 1,916 annual skin dose equivalents (Hp(0.07)) recorded between 2003 and 2020 for 528 individuals were also included in the analysis. These annual Hp(0.07) varied from 0.00 mSv to

7.12

mSv, with a median value of

0.37

mSv (IQR =0.06 – 1.22 mSv; mean =

0.80

mSv). Sixteen percent of the annual Hp(0.07) were below the LLD of the DT-702/PD but were included in the analysis. More than 95% of the annual Hp(0.07) received by NM workers in our cohort were below three mSv [95.6% (1831 of 1916)] (Figure 5). Median annual Hp(0.07) remained relatively constant from 2003 to 2020 (range, 0.12-0.81 mSv) (Table 10). The distribution of the maximum value of annual Hp(0.07) fluctuated over time (range, 1.96-7.12 mSv), with the highest value observed in 2015 (Figure 6). No correlation was found between the number of individuals monitored each year and the maximum value.

Figure 5: Histogram of the distribution of 1,916 annual shallow dose equivalents, Hp(0.07), previously collected and provided by the NDC for 528 workers from NM departments of the US-Navy between 2003 and 2020.

Figure 6: Box-and-whisker plot of the trends in annual skin dose equivalents, Hp(0.07), to workers from NM departments of the USN medical centers between 2003 and 2020.

*The upper and lower whiskers represent the maximum and minimum values.

3.1.3 Annual extremity doses distribution

A total of 1,357 annual extremity dose equivalents (Hp(0.07)) recorded between 2003 and 2020 for 285 individuals were included in the analysis. These annual Hp(0.07) varied from 0.00 mSv to

121

mSv, with a median value of 2.89 mSv (IQR = 0.76 – 7.86 mSv; mean = 6.65 mSv). Almost eighty-two percent of the annual Hp(0.07) received by NM workers in our cohort were below ten mSv [81.7% (1109 of 1357)] (Figure 7). Median annual Hp(0.07) remained relatively constant from 2003 to 2020 (range,

1.34

-5.26 mSv) (Table 11). The distribution of the maximum value of annual Hp(0.07) doubled in 2005 (120 mSv), then fluctuated in 2006 – 2014, and decreased again after 2015 to reach a minimum value of 12.7 mSv in 2020 (Figure 8). No correlation was found between the number of individuals monitored each year and the maximum value for the annual extremity doses.

Figure 7: Histogram of the distribution of 1,357 annual shallow dose equivalents to the extremity, Hp(0.07), previously collected and provided by the NDC for 285 workers from NM departments of the USN medical centers between 2003 and 2020

Figure 8: Box-and-whisker plot of the trends in annual shallow dose equivalents to the extremity, Hp(0.07), to workers from NM departments of the USN medical centers between 2003 and 2020.

*The upper and lower whiskers represent the maximum and minimum values.

3.2 Cumulative doses

3.2.1 Cumulative deep dose and skin dose equivalents distribution

For the 528 individuals monitored with the DT-702/PD, the cumulative deep dose equivalents (DDE) and cumulative skin dose equivalents ranged from 0.00 to 46.6 mSv and 0.00 to 44.3 mSv, respectively. Cumulative DDE and skin doses had median values of 0.39 mSv (IQR

= 0.05 – 3.18 mSv; mean = 2.96 mSv) and 0.39 mSv (IQR = 0.05 – 3.08 mSv; mean = 2.90 mSv), respectively (Table 12 a-b).

3.2.2 Cumulative extremity dose equivalents distribution

For the 285 individuals monitored with the DXT-RAD, the cumulative extremity dose equivalents ranged from 0.11 to 529 mSv and had a median value of

13.0

mSv (IQR= 2.89 – 38.5 mSv; mean = 31.6 mSv) (Table 12c).

3.3 PET and non-PET dose

3.3.1 PET facilities distribution

The analysis of the two facilities with a PET department included 221 individual and

787

annual dose records of both values the DDE and the skin dose equivalents, respectively, and 163 individual and 600 annual dose record of the extremity dose equivalents. DDE, skin dose equivalents and extremity dose equivalents had median values of 0.44 mSv (IQR= 0.06 – 1.60 mSv; mean =

0.99

mSv), 0.42 mSv (IQR = 0.06 – 1.58 mSv; mean =

0.97

mSv) and 3.16 mSv (IQR = 0.73 – 9.51 mSv; mean = 8.74 mSv), respectively (Table 13).

3.3.2 Non-PET facilities distribution

The analysis of the 14 and 13 facilities corresponding to the data from DT-702/PD and DXT-RAD dosimeters, respectively, were collected on 361 individuals, corresponding to

1,207

annual dose records of each the DDE and the skin dose equivalents, and 176 individuals, corresponding to

800

annual dose records of the extremity dose equivalents. DDE, skin dose equivalents and extremity dose equivalents had median values of 0.29 mSv (IQR = 0.06 – 0.95 mSv; mean = 0.65 mSv), 0.30 mSv (IQR= 0.06 – 0.95 mSv; mean =

0.63

mSv) and 2.52 mSv

(IQR = 0.76 – 6.19 mSv; mean = 4.72 mSv), respectively (Table 14).

3.3.3 PET vs non-PET

An independent two samples t-test was conducted to compare the annual radiation exposure of personnel working in the USN NM facilities perform PET/CT (group 1) (N=787 and N=600) vs. the annual exposure of personnel working in the USN NM facilities that do not perform PET/CT (group 2) (N= 1,207 and N= 800) for the data recorded using the DT-702/PD and the DXT-RAD, respectively.

The result showed that there is significant difference ( p= <0.001 ) in the annual DDE for group 1 with higher mean (M= 0.99 , SD=

1.24

) than group 2 (M=0.65, SD=

0.85

). The magnitude of the differences in the mean (mean difference= –

0.34

, 95% CI : – 0.44 to –

0.24

) was significant. Also, it showed that there is significant difference ( p= <0.001 ) in the annual skin doses for group 1 with higher mean (M= 0.97 , SD= 1.2 ) than group 2 (M=0.63, SD= 0.82). The magnitude of the differences in the mean (mean difference= - 0.34, 95% CI : - 0.44 to - 0.24) was significant. Moreover, the test’s result showed that there is significant difference ( p= <0.001 ) in the annual extremity doses for group 1 with higher mean (M= 8.74 , SD= 14.7 ) than group 2 (M=4.72, SD= 6.38). The magnitude of the differences in the mean (mean difference= - 4.02, 95% CI : - 5.28 to

– 2.76) was significant Figure 9, 10, and 11.

Figure 9: Annual exposure of the personal dose equivalents Hp(10) in mSv for the USN personnel working in NM facilities performing PET/CT vs. NM facilities that do not perform PET/CT.
*The upper and lower whiskers represent the maximum and minimum values.

Figure 10: Annual exposure of the personal dose equivalents Hp(0.07), skin doses, in mSv for the USN personnel working NM facilities performing PET/CT vs. NM facilities that do not perform PET/CT.
*The upper and lower whiskers represent the maximum and minimum values.

Figure 11: Annual exposure of the personal dose equivalents Hp(0.07), extremity doses, in mSv for the USN personnel working in NM facilities performing PET/CT vs. NM facilities that do not perform PET/CT.
*The upper and lower whiskers represent the maximum and minimum values.

CHAPTER 5. DISCUSSION

In our record of 528 and 285 USN NM workers assessed using the DT-702/PD and the DXT-RAD from 2003-2020, respectively, we observed a median annual radiation dose of 0.38 mSv (IQR, 0.05-1.27 mSv; mean, 0.82 mSv), 0.37 mSv (IQR, 0.06 – 1.22 mSv; mean = 0.80 mSv),

and 2.89 mSv (IQR = 0.76 – 7.86 mSv; mean = 6.65 mSv) for the DDE, skin doses and extremity doses, respectively. More than 95% of the annual DDE and skin doses were below three mSv: this is less than the average annual exposure from natural background radiation in the US. Almost 82% of the annual extremity doses were less than ten mSv. These values are significantly below the annual occupational limit of 50 mSv for the effective dose equivalent and 500 mSv for the dose equivalent to the skin and extremities established by the ICRP and recommended by the NRC. These DDE, skin doses, and extremity doses spread over a wide range, which could be related to the variability of NM workers’ occupations and tasks within NM departments.

Our study focuses on analyzing the data for the period when the occupational exposure of NM workers was expected to increase due to increased use of Tc-99m in myocardial studies, for instance, and decreased use of Tl-201 thallous chloride. This period also corresponded to the advent of PET/CT imaging, possibly leading to increased radiation exposure to the workers. However, the median value of annual personal dose equivalents (Hp(10)) appeared to be lower in our study (0.38 mSv in 2003 – 2020) than the median dose value for NM technologists working at civilian U.S. hospitals (

2.07

mSv in 1979 – 2015) (15). Moreover, our result of the median annual DDE was lower than that of a recent study, including data from NM technologists working in civilian U.S. hospitals in 1980-2015 (1.2 mSv) (16). We computed summary statistics for easier comparison with other studies when excluding any annual dose below 0.03 mSv—the abovementioned studies recorded as minimal any annual dose below the LLD. After exclusion,

our dataset’s median annual DDE was higher than without exclusion, with 0.62 mSv against 0.38 mSv, but still about half the median dose values from studies performed on workers from civilian hospitals. This result supports the hypothesis that the annual exposure to NM workers in the Navy is lower than to NM workers from civilian hospitals. These lower radiation doses to US Navy workers might be due to stringent radiation protection programs within the Navy. However, this dose difference could also be linked to a variation in workload between civilian and Navy hospitals. Our mean value of annual DDE was slightly lower than that of a cohort of 588 NM technologists from Saudi Arabia, monitored between 2015 and

2019

, with 0.82 mSv against 1.22 mSv, respectively (51). Moreover, our mean annual DDE matched the estimated average annual effective dose to NM workers monitored worldwide in 1990-19

94

(

0.79

mSv). However, it was slightly higher than the estimated mean annual effective dose to general medical workers worldwide in 2000-2002 (0.70 mSv) (52).
To our knowledge, no published data reports annual occupational exposure to the skin and extremities for U.S. NM workers. Therefore, we only could compare skin doses from the present study with published skin doses from other countries. The mean annual skin dose in our study (0.80 mSv) was lower than the mean skin doses in Kuwait for NM technologists (0.94 mSv in

2009

) and NM physicians (

0.96

mSv in 2009) (53). Moreover, it was lower than the mean annual skin dose reported for 588 NM technologists in Saudi Arabia (

1.23

mSv) in 2015-2019 (51).
On the other hand, the operational quantity for extremity doses was compared with the reported values in a study that evaluated the extremity exposure among NM workers in Serbia, using DXT-RAD finger ring (

2010

-2014) (54). The lowest mean annual value was recorded among radiographers in 2014 (12 mSv), thus almost twice the average annual value recorded in our study (6.65 mSv). It is recommended to wear ring dosimeters where the highest exposure is expected.

However, no information was provided on how workers wore their dosimeters in the present study, nor whether these recommendations were followed.

Because no information was available to identify NM facilities performing PET/CT in addition to general NM studies, we used the mailing addresses provided by the NDC and publicly available information from the Navy hospitals’ website to discriminate dose records for workers performing PET/CT procedures. Our results matched those from a recent study that showed an association of higher doses for NM technologists regularly performing PET/CT in the U.S. (16). The statistical analysis of doses to workers from facilities mentioning PET/CT on their website, compared with doses to workers from non-PET facilities, showed a statistically significant difference of mean annual dose between the two groups. However, in the absence of verified information on the regular performance of PET/CT procedures for each worker in our cohort, and due to the absence of a time specification on the implementation of PET in each facility, this result should be taken with caution when interpreting these results.

A major strength of this study is the consistency in the dosimeter type and the calibration method – using a single radiation protection program –, which prevents uncertainties related to variation in dosimetry practices. Moreover, previous studies conducted on occupational radiation exposure only included NM technologists. In contrast, the present study involves all possible workers from NM departments exposed to radiation, including NM technologists, physicians, nurses, and health/medical physicists: this means a more exhaustive evaluation of occupational exposure in NM departments. Lastly, our study is the first to report dose equivalents to the skin and extremities among NM workers in the US, and this type of data is now available for comparison with future studies.

A major limitation of this study is the absence of work history, such as the frequency of performed diagnostic and therapeutic procedures, the radionuclides in use, and the radiation safety procedures. The lack of such information limited our analysis of the dose results and trends. The absence of information on each worker’s occupation or job title was a major inconvenience, making it very complex to separate dose analysis based on the occupation.

A second limitation is an assumption that doses recorded by the dosimeters reflect doses received by the workers. Based on the documentation obtained from the Navy’s radiation health protection program, the DT-702/PD dosimeter should be worn at the chest level to detect the exposure received by the body at the point where the highest exposure could occur (45). Some uncertainty arises from the obligation level each worker has toward these regulations. In addition, the data obtained from the NDC were doses per issued dosimeter. Due to overlap between years of some issued dosimeters, we recalculated doses by year, resulting in an over-or underestimation of some doses. The last limitation of our study is a common issue in radiation dosimetry: occupational exposure is assessed based on the personal dose equivalents, measured using personal dosimeters. These operational quantities are surrogates for the effective dose, which cannot be directly measured. However, report 160 from the European Commission of radiation protection on technical recommendations for monitoring individuals occupationally exposed to external radiation stated that the operational quantity Hp(10) generally overestimates the effective dose (55). Therefore, comparisons between personal dose equivalents and effective doses should be taken with caution.

Overall, a prospective study on the same group of workers or a simple survey could help

get the missing information in this study and better link the dose trends with the occupation, the workload, radiation safety program, and the performance of specific procedures such as

myocardial studies or PET/CT. A questionnaire has been drafted, and the dose analysis in the present study and could be used in future studies. It is provided as an Appendix.

CHAPTER 6. CONCLUSIONS

Nuclear medicine workers are exposed to protracted low-level radiation for extended periods, elevating their risk of breast cancer, SCC, and circulatory disease. Due to the possible risks from increased radiation exposure, the ICRP established recommendations to limit occupational doses and emphasized the ALARA principle. Previous studies conducted in the US to assess the trends of occupational exposure among NM workers included technologists from different medical institutions, which makes these studies susceptible to heterogeneity and measurement biases due to variations in work practices and radiation safety techniques between institutions. Although previous studies of occupational doses among the US radiologic technologists show that doses have decreased since 1939, which is likely due to improved radiation safety practices, a recent study of occupational doses among NM technologists in the US medical institutions showed that the maximum values of the annual personal dose equivalents among those workers generally increased from 1992 to 2015. Therefore, the present study was conducted to mitigate the problem of exposure heterogeneity within the study group and to test the hypothesis that NM workers’ annual personal dose equivalents in USN medical centers are lower than the annual personal dose equivalents of NM workers from civilian medical centers across the United States due to a stringent radiation protection program within the USN.

Our study showed that the annual DDE, skin, and extremity doses of 528 and 285 NM

personnel working at the USN medical facilities and assessed using the DT-702/PD and the DXT- RAD from 2003-2020, respectively, were well below the annual occupational limits established by the ICRP (50 mSv for the total effective dose equivalents, and 500 mSv for the dose equivalents to the skin and extremities). The median annual DDE to NM workers in the USN is lower than NM workers from US civilian hospitals, supporting our hypothesis. Also, the mean value of annual

DDE was slightly lower than that for NM technologists from Saudi Arabia (2015-2019). Our study’s mean annual skin dose was lower than the average for NM technologists andNM physicians in Kuwait and lower than for NM technologists in Saudi Arabia. The mean of annual DDE in the present study matched the estimated average annual effective dose to NM workers monitored worldwide (1990-1994), but slightly higher than the estimated mean annual effective dose to general medical workers worldwide (2000-2002).

Moreover, our study’s mean annual extremity dose was half the lowest extremity exposure recorded among NM workers in Serbia. As expected, our mean annual exposure among workers in PET facilities was significantly higher than for non-PET facilities. The present study provided new data for future radiation monitoring among those workers and should help improve radiation protection programs in medical centers. We recommend a prospective data collection or a survey to provide detailed information on the USN workload and radiation protection programs for future studies.

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Table 1. Annual Occupational Dose Limits

500

500

500

Measurement

Type

(a) ICRP- Dose Limit

(mSv)

(b)

NRC-

Dose

Limits

(mSv)

Total effective dose equivalent

20*

50

Lens equivalent dose

20**

150

Extremity equivalent dose

500

Shallow dose (Dose equivalent to the skin)

*Effective dose of 20 mSv/ year, averaged over five years with no single year exceeding 50 mSv

** This annual limit was lowered by ICRP in April 2011 from 150 mSv to 20 mSv, with the further provision that the dose should not exceed 50 mSv in any single year.

(
Source: Reference 11.
)

Table 2. Categories and corresponding definitions in the first dataset provided by the Navy Dosimetry Center, for DT-702/PD data.

Column

Definition

SDE_RPT

Shallow Dose Equivalent : the external exposure to the skin. The dose is equivalent at a tissue depth of 0.007 centimeters (cm) over an

area of 10 cm2.

PDE_RPT

Photon Dose Equivalent or what is referred to in the text as Deep

Dose Equivalent (DDE): the photon external whole-body exposure equivalent at a depth of 1 cm.

IndCode

Individual Code: anonymized codes assigned by the NDC to help identify each’s data.

Issue_Date

Date the dosimeter was issued to an individual. (Year Month Date)

Collect_Date

Date the dosimeter was collected from an individual. (Year Month Date)

CommAddr

Command Address : mailing address associated with the issued dosimeter.

( Name, City, State, Zip-Code)

Table 3. Categories and corresponding definitions in the second dataset provided by the Navy Dosimetry Center for DXT-RAD.

Column

Definition

IndCode

Issue_Date

See Table 2.

Collect_Date

See Table 2.

See Table 2.

CommAddr

See Table 2.

EDE_RPT

Extremity Dose Equivalent: the extremity exposure measured using extremity dosimeter at tissue depth of 0.007 cm.

See Table 2.

Occ_Code

Table 4. Several annual records in 2003–2020 used the DT-702/PD.

Year

Number

of

annual records

2003

152

2004

143

2005

159

2006

133

2007

112

2008

99

2009

92

2010

91

2011

80


2012


103

2013

111

2014

127

2015

117

2016

107

2017

115

2018

97

2019

41

2020

37

Table 5. A yearly number of annual records in 2003–2020, using the DXT-RAD.

2003

2004

2005

99

2006

2007

2008

2009

50

2010

2011

82

2013

2014

92

2015

2016

95

2017

103

2018

80

2019

37

2020

Year

Number

of

annual

records

82

100

76

67

63

46

61

2012

95

94

35

Table 6. PET versus non-PET data, using the DT-702/PD.

PET

Non-PET

Number of facilities

2 14

Number of individuals

221 361

Number of annual records

787

1,207

Table 7. PET versus non-PET data, using the DXT-RAD.

PET

Non-PET

Number of facilities

2

Number of individuals

Number of annual records

13
163 176

600

800

Table 8. The number of observations, several workers, median, mean, Q1, Q3, and 95th percentiles, and the minimum to a maximum of various annual dose records for 2003-2020.

# of

1,916

528

An

nual Dose Recor

ds (mSv)

# of

Median

Mean

Q1 Q3 95th

Minimum

Annual Dose
Records
Workers

Percentile

to

Maximum

Deep Dose

Equivalents

1,916

528

0.38

0.82

0.05 1.27

2.94

0.00-7.18

Skin Dose

Equivalents

0.37 0.80 0.06 1.22

2.86

0.00- 7.12

Extremity

Dose

Equivalents

1,357

285

2.89 6.65 0.76 7.86

26.5

0.00-121

Table 9. Summary statistics of the annual dose records per year of the Hp(10).

Annual Dose Records (mSv)

Year

Median

Mean

Q1

Q3

Maximum

2003

0.35

0.60

0.06

0.87

3.46

2004

0.82 0.99 0.10

1.42

4.64

2005

0.61

0.96 0.07

1.43

5.51

2006

0.28

0.95

0.07

1.41

6.44

2007

0.35

0.95

0.04

1.23

6.50

2008

0.26

0.83

0.04

1.34

4.64

2009

0.20

0.84

0.06

1.23

4.80

2010

0.12

0.78

0.02

0.88

6.05

2011

0.59

0.96

0.09

1.46

4.36

2012

0.55

0.91

0.05

1.53

5.01

2013

0.48

0.79

0.07

1.32

3.27

2014

0.34

0.72

0.04

1.33

3.87

2015

0.28

0.85

0.05

1.35

7.18

2016

0.45

0.72

0.04

1.20

3.68

2017

0.29

0.77

0.05

1.30

6.26

2018

0.18

0.51

0.05

0.82

2.88

2019

0.43

0.77

0.07

1.51

2.87

2020

0.26

0.53

0.05

0.90

1.87

Table 10. Summary statistics of the annual dose records per year of the skin dose equivalents, the Hp(0.07).

Annual Dose Records (mSv)

Year

Median

Mean

Q1

Q3

Maximum

0.37

0.60

0.06

0.84

0.12

1.43

4.64

0.55

0.90

0.06

1.33

0.90

0.07

1.27

0.35

0.95

0.04

0.28

0.84

0.04

1.33

0.83

0.06

0.78

0.02

0.05

0.43

0.77

0.08

1.24

0.72

0.06

1.33

0.84

0.06

0.72

0.04

0.30

0.05

1.20

0.18

0.05

0.78

0.07

0.07

0.92

2003

3.65

2004

0.81

1.00

2005

5.36

2006

0.25

6.11

2007

1.24

6.47

2008

5.00

2009

0.22

1.2

4.73

2010

0.12

0.86

5.86

2011

0.56

0.92

0.08

1.40

4.38

2012

0.58

0.89

1.52

4.89

2013

3.12

2014

0.31

3.84

2015

0.30

1.50

7.12

2016

0.44

1.15

3.57

2017

0.73

6.12

2018

0.49

2.70

2019

0.42

0.75

1.36

2.77

2020

0.24

0.54

1.96

Table 11. Summary statistics of the annual dose records per year of the extremity dose equivalents, the Hp(0.07).

Annual Dose Records (mSv)

Year

Median

Mean

Q1

Q3

Maximum

2003

2004

2005

3.57

2006

1.42

10.1

2007

11.5

2008

3.15

7.24

1.44

9.91

48.3

4.57 10.1

2.15

11.3

68.8

11.5

1.31

12.9

121

4.45

9.28

92.3

5.26

11.0

1.45

114

3.73

7.31

1.10

8.05

48.7

2009

0.82

2010

0.84

6.47

2011

2012

2013

0.38

2014

2015

0.48

2016

0.61

2017

2018

1.42

2019

3.12

2020

4.07

8.08

10.0

63.6

3.23

7.88

53.8

2.71

5.06

1.21

7.71

34.8

3.95

7.59

0.93

12.3

42.4

2.35

6.02

8.94

36.6

1.34

5.07

0.23

5.65

59.8

2.07

4.69

6.84

38.3

2.13

3.78

5.32

27.1

1.56

3.41

0.50

4.33

20.1

3.04

0.39

4.31

21.3

4.12

1.03

6.24

15.4

1.49

2.62

0.74

3.51

12.7

Table 12. The workers, median, mean, Q1, Q3, and 95th percentiles and minimum to a maximum of the cumulative deep dose equivalents, skin dose equivalents, and extremity dose equivalents for 2003-2020.

Median

Mean

Q1

Q3

95th

528

0.39

0.05

528

0.39

0.05

285

2.89

Cumulative

Dose

Records

(mSv)

# of workers

Minimum

to Maximum

a- Deep Dose Equivalents

2.96 3.18

14.22

0.00 – 46.6

b- Skin Dose Equivalents

2.90 3.08

14.39

0.00 – 44.3

c-

Extremity

Dose

Equivalents

13.0

31.64

38.51

134.10

0.11 – 529

Table 13. Table 13. Summary statistics of the personal dose equivalents the Hp(10) and Hp(0.07) for the PET facilities’ skin and extremity records.

Median

Mean

Q1

Q3

95th

Maximum

Deep Dose

Equivalents

0.44

0.99

0.06

7.18

Skin Dose

Equivalents

0.42

0.06

7.12

Extremity

Dose

Equivalents

0.73

121

PET Facilities (mSv)

1.60

3.47

0.97 1.58

3.40

3.16 8.74 9.51

37.2

Table 14. Summary statistics of the personal dose equivalents Hp(10) and Hp(0.07) for skin and extremity records in the non-PET facilities.

Median

Mean

Q1

Q3

95th

Maximum

Deep Dose

Equivalents

0.29

0.06

0.95

Skin Dose

Equivalents

0.30

0.06

0.95

Extremity

Dose

Equivalents

0.76

59.8

Non-PET Facilities (mSv)

0.65

2.38

6.13

0.63

2.27

6.18

2.52 4.72 6.19

16.5

APPENDIX A

Summary statistics of the annual deep dose equivalents for 528 nuclear medicine personnel working in the United States Navy medical facilities from 2003-2020

0

0

0

0

1,916

Mean

Percentiles

Smallest

1%

0

5%

.0053735

10%

.0149745

Obs 1,916

25%

.0548624

Sum of Wgt.

50%

.3754083

.8160365

75%

1.267237

Largest

6.259352

Std. Dev.

1.053848

90%

2.271212

6.439745

Variance

1.110597

95%

2.940099

6.49072

Skewness

1.939169

99%

4.558464

7.176692

Kurtosis

7.569551

APPENDIX B

Yearly summary statistics of the annual deep dose equivalents for 528 nuclear medicine personnel working in the United States Navy medical facilities

2003

Percentiles

Smallest

1%

0

0

5%

0

10%

Obs

25%

Sum of Wgt.

152

50%

Mean

75%

Std. Dev.

90%

Variance

95%

Skewness

99%

2.751594

Kurtosis

.0158069

.0193887

.0017403

152

.0558003

.0032977

.3533911

.5954048

.8666915

Largest

2.556723

.6878873

1.557385

2.65008

.4731889

2.237326

2.751594

1.587392

3.45546

5.384345

2004

Percentiles

Smallest

1%

0

5%

.0012822

10%

Obs

25%

Sum of Wgt.

143

50%

Mean

75%

Std. Dev.

90%

Variance

95%

Skewness

99%

3.93676

Kurtosis

.0012822

.0106438

.0308526

.003324

143

.1048888

.004826

.8155563

.9941114

1.423938

Largest

3.386387

.9653986

2.361793

3.416775

.9319945

2.84205

3.93676

1.14879

4.63605

4.045049

2005

Percentiles

Smallest

1%

.0012822

0

5%

.0106438

.0012822

10%

.0308526

.003324

Obs

143

25%

.1048888

.004826

Sum of Wgt.

143

50%

.8155563

Mean

.9941114

75%

1.423938

Largest
3.386387

Std. Dev.

.9653986

90%

2.361793

3.416775

Variance

.9319945

95%

2.84205

3.93676

Skewness

1.14879

99%

3.93676

4.63605

Kurtosis

4.045049

2006

Percentiles

Smallest

1%

5%

.004466

10%

Obs

25%

Sum of Wgt.

133

50%

Mean

75%

Std. Dev.

90%

Variance

95%

Skewness

99%

4.257892

6.439745

Kurtosis

.004466

.0036347

.0203855

.0342862

.0070844

133

.0680952

.0101563

.2762672

.9519001

1.412995

Largest

4.144266

1.274838

3.029637

4.187002

1.625213

3.806939

4.257892

1.655794

5.352752

2007

Percentiles

Smallest

1%

5%

.0061564

10%

Obs

25%

Sum of Wgt.

112

50%

Mean

75%

Std. Dev.

90%

Variance

95%

Skewness

99%

6.130999

6.49072

Kurtosis

.0061564

.0049375

.013367

.0194603

.0074532

112

.0374651

.0085283

.3508754

.9498236

1.233454

Largest

5.223693

1.387288

2.606879

5.88709

1.924567

4.051319

6.130999

2.145686

7.557846

2008

Percentiles

Smallest

1%

0

0

5%

0

0

10%

0

Obs

25%

0

Sum of Wgt.

99

50%

Mean

75%

Std. Dev.

90%

Variance

95%

Skewness

99%

4.635402

Kurtosis

.0080472

99

.0398241

.261023

.8314757

1.341586

Largest

3.732991

1.147634

2.900131

3.970333

1.317064

3.636149

4.168913

1.592871

4.635402

4.595665

2009

Percentiles

Smallest

1%

.0001528

5%

10%

Obs

25%

Sum of Wgt.

92

50%

Mean

75%

Std. Dev.

90%

Variance

95%

4.558464

Skewness

99%

4.799671

Kurtosis

.0001528

.0046363

.0006318

.0317041

.0006845

92

.0611961

.0007781

.1988361

.8411406

1.234413

Largest

3.45946

1.135638

2.563417

3.898583

1.289673

3.302218

1.644283

4.799671

5.069683

2010

Percentiles

Smallest

1%

.0003796

5%

10%

Obs

25%

Sum of Wgt.

91

50%

Mean

75%

Std. Dev.

90%

Variance

95%

Skewness

99%

6.049545

Kurtosis

.0003796

.0070811

.001003

.009816

.0027117

91

.0240745

.0050217

.1151427

.7796714

.8781401

Largest

3.858491

1.317878

2.486832

5.077831

1.736803

3.747566

5.798368

2.240975

6.049545

7.76719

2011

Percentiles

Smallest

1%

0

0

5%

10%

Obs

25%

Sum of Wgt.

80

50%

Mean

75%

Std. Dev.

90%

Variance

95%

Skewness

99%

4.355334

Kurtosis

.0053148

.0020422

.0129835

.0030358

80

.0885018

.0037949

.5875151

.955201

1.456991

Largest

3.442358

1.047137

2.545557

3.555289

1.096496

3.369639

4.103434

1.395265

4.355334

4.438917

2012

Percentiles

Smallest

1%

0

5%

.0008358

10%

Obs

25%

Sum of Wgt.

103

50%

Mean

75%

Std. Dev.

90%

Variance

95%

Skewness

99%

4.436441

Kurtosis

.0008358

.0053168

.0122175

.0010657

103

.0506676

.0015669

.5462941

.910614

1.528687

Largest

3.092861

1.021356

2.121116

3.320576

1.043167

2.716112

4.436441

1.449513

5.005732

5.332718

2013

Percentiles

Smallest

1%

0

0

5%

0

10%

0

Obs

25%

Sum of Wgt.

111

50%

Mean

75%

Std. Dev.

90%

Variance

95%

Skewness

99%

3.244384

Kurtosis

.0032804

.0140443

111

.0713282

.000541

.4788338

.7891131

1.321705

Largest

2.980606

.8829734

2.038877

2.986499

.779642

2.931366

3.244384

1.20218

3.274509

3.521907

2014

Percentiles

Smallest

1%

0

0

5%

0

10%

Obs

25%

Sum of Wgt.

127

50%

Mean

75%

Std. Dev.

90%

Variance

95%

Skewness

99%

3.498989

Kurtosis

.0041658

.0140761

.0002244

127

.0422195

.000234

.3374017

.7205666

1.334441

Largest

2.930588

.8674197

1.917927

2.990605

.7524169

2.398999

3.498989

1.380122

3.872853

4.334483

2015

Percentiles

Smallest

1%

0

5%

.0009826

10%

Obs

25%

Sum of Wgt.

117

50%

Mean

75%

Std. Dev.

90%

Variance

95%

Skewness

99%

5.767288

7.176692

Kurtosis

.0009826

.0050809

.011369

.0017945

117

.0514741

.0040815

.2835386

.8453923

1.346161

Largest

3.547054

1.19854

2.487023

4.048561

1.436498

2.715241

5.767288

2.382416

10.58892

2016

Percentiles

Smallest

1%

0

0

5%

0

10%

Obs

25%

Sum of Wgt.

107

50%

Mean

75%

Std. Dev.

90%

Variance

95%

Skewness

99%

3.399453

Kurtosis

.0007151

.0044666

.0003958

107

.0369615

.0004923

.452927

.7210969

1.195336

Largest

2.894889

.8832121

1.925686

2.97426

.7800637

2.841493

3.399453

1.445903

3.678466

4.389815

2017

Percentiles

Smallest

1%

5%

.0020566

10%

Obs

25%

Sum of Wgt.

115

50%

Mean

75%

Std. Dev.

90%

Variance

95%

Skewness

99%

3.959037

6.259352

Kurtosis

.0020566

.0007266

.0047266

.0094334

.002233

115

.0459444

.003271

.2865726

.7652477

1.296422

Largest

3.422184

1.047726

2.182504

3.560056

1.097731

2.765138

3.959037

2.150577

9.124552

2018

Percentiles

Smallest

1%

.0000456

5%

10%

Obs

25%

Sum of Wgt.

97

50%

Mean

75%

Std. Dev.

90%

Variance

95%

Skewness

99%

2.877304

Kurtosis

.0000456

.0004132

.0001181

.0088668

.0001385

97

.0500798

.0002033

.1790895

.5077409

.8227307

Largest

1.950156

.6401801

1.560979

2.171966

.4098306

1.887049

2.355326

1.512951

2.877304

4.711528

2019

Percentiles

Smallest

1%

.0079081

5%

10%

.0134662

Obs

25%

Sum of Wgt.

41

50%

Mean

75%

Std. Dev.

90%

Variance

95%

2.313535

Skewness

99%

2.870684

Kurtosis

.0079081

.0134662

.0097465

.0211412

41

.0714212

.0137174

.4256934

.7709586

1.510869

Largest

2.18502

.8307606

2.078768

2.313535

.6901632

2.337713

.9017106

2.870684

2.520716

2020

Percentiles

Smallest

1%

.0010885

5%

.0066906

10%

Obs

25%

.0240003

Sum of Wgt.

37

50%

Mean

75%

Std. Dev.

90%

1.521588

Variance

95%

1.698638

Skewness

99%

1.870278

Kurtosis

.0010885

.0066906

.0240003

.0081717

37

.0511697

.2559418

.5342347

.8983554

Largest

1.521588

.5847211

1.551218

.3418987

1.698638

.9076189

1.870278

2.378766

APPENDIX C

Summary statistics of the annual shallow dose equivalents of the skin for 528 nuclear medicine personnel working in the United States Navy medical facilities from 2003-2020

Percentiles

Smallest

1%

0

0

5%

0

10%

0

Obs

1,916

25%

0

Sum of Wgt.

1,916

50%

Mean

75%

Std. Dev.

90%

Variance

95%

Skewness

99%

Kurtosis

.0070037

.0182813

.0556798

.3725173

.7994701

1.215276

Largest

6.119405

1.026777

2.210767

6.181241

1.05427

2.864718

6.473961

1.968534

4.635141

7.118781

7.846537

APPENDIX D

Yearly summary statistics of the annual shallow dose equivalents of the skin for 528 nuclear medicine personnel working in the United States Navy medical facilities

2003

Percentiles

Smallest

1%

0

0

5%

0

10%

Obs

152

25%

Sum of Wgt.

152

50%

Mean

75%

Std. Dev.

90%

Variance

95%

Skewness

99%

2.84054

Kurtosis

.0084649

.0232357

.0034345

.0619117

.0035827

.3734783

.6024175

.8353235

Largest

2.54432

.6952061

1.607193

2.594654

.4833115

2.239701

2.84054

1.656896

3.64907

5.817352

2004

Percentiles

Smallest

1%

0

0

5%

0

10%

0

Obs

143

25%

Sum of Wgt.

143

50%

Mean

75%

Std. Dev.

90%

Variance

95%

Skewness

99%

3.887628

4.635141

Kurtosis

.0180982

.0352173

.1165865

.0004867

.8086973

1.001939

1.433539

Largest

3.395016

.9594585

2.380001

3.553425

.9205606

2.818681

3.887628

1.125757

4.004581

2005

Percentiles

Smallest

1%

0

5%

.0003918

10%

Obs

25%

Sum of Wgt.

159

50%

Mean

75%

Std. Dev.

90%

Variance

95%

Skewness

99%

4.925521

Kurtosis

.0003918

.0075263

.026471

.0004055

159

.0558806

.0019618

.5540211

.9012122

1.335968

Largest

4.501707

1.115336

2.477835

4.719437

1.243974

3.467109

4.925521

1.738235

5.361388

5.993091

2006

Percentiles

Smallest

1%

5%

.0038637

10%

Obs

133

25%

Sum of Wgt.

133

50%

Mean

75%

Std. Dev.

90%

Variance

95%

Skewness

99%

4.13113

Kurtosis

.0038637

.0000145

.0186963

.0384645

.0046722

.0704271

.0118052

.251845

.8992895

1.267874

Largest

4.028935

1.205549

2.887704

4.130642

1.453349

3.45397

4.13113

1.69271

6.117428

5.526514

2007

Percentiles

Smallest

1%

5%

.0045778

10%

Obs

112

25%

Sum of Wgt.

112

50%

Mean

75%

Std. Dev.

90%

Variance

95%

6.181241

Skewness

99%

6.181241

6.473961

Kurtosis

.0045778

.000824

.0098852

.0218932

.0059951

.0369207

.0072682

.3476557

.9470057

1.244687

Largest

5.136432

1.386328

2.608834

6.098285

1.921905

3.781629

2.166295

7.734419

2008

Percentiles

Smallest

1%

0

0

5%

10%

Obs

99

25%

Sum of Wgt.

99

50%

Mean

75%

Std. Dev.

90%

Variance

95%

Skewness

99%

5.007534

Kurtosis

.0081023

.000813

.0152435

.0048934

.0398511

.0052773

.2818285

.8394228

1.329703

Largest

3.590305

1.167257

2.842191

3.867624

1.362488

3.585802

4.691899

1.686533

5.007534

5.143531

2009

Percentiles

Smallest

1%

0

0

5%

0

10%

0

Obs

92

25%

Sum of Wgt.

92

50%

Mean

75%

Std. Dev.

90%

Variance

95%

Skewness

99%

4.728184

Kurtosis

.0024876

.0318315

.0592

.0020215

.2181594

.8260686

1.19651

Largest

3.39449

1.120429

2.543737

3.792108

1.255362

3.215777

4.587036

1.656993

4.728184

5.130683

2010

Percentiles

Smallest

1%

0

0

5%

0

10%

Obs

91

25%

Sum of Wgt.

91

50%

Mean

75%

Std. Dev.

90%

Variance

95%

Skewness

99%

5.85675

Kurtosis

.0010832

.0129185

.000339

.0209081

.000655

.1152964

.7778495

.8557506

Largest

4.029578

1.308913

2.380189

5.08658

1.713252

3.853779

5.661973

2.188447

5.85675

7.424417

2011

Percentiles

Smallest

1%

0

0

5%

10%

Obs

80

25%

Sum of Wgt.

80

50%

Mean

75%

Std. Dev.

90%

Variance

95%

Skewness

99%

4.384409

Kurtosis

.006398

.0016755

.0105388

.0033417

.0819527

.0050043

.5637543

.9188706

1.399775

Largest

3.246475

1.015724

2.454417

3.396849

1.031694

3.12352

4.110482

1.460607

4.384409

4.76502

2012

Percentiles

Smallest

1%

0

5%

.0008805

10%

Obs

103

25%

Sum of Wgt.

103

50%

Mean

75%

Std. Dev.

90%

Variance

95%

Skewness

99%

4.789417

Kurtosis

.0008805

.0103226

.0153127

.0027984

.0469969

.005133

.5842557

.8881484

1.518886

Largest

3.005121

1.001568

2.067253

3.184366

1.003139

2.620567

4.789417

1.564144

4.886204

6.014499

2013

Percentiles

Smallest

1%

0

0

5%

0

10%

Obs

111

25%

Sum of Wgt.

111

50%

Mean

75%

Std. Dev.

90%

Variance

95%

Skewness

99%

2.986268

Kurtosis

.0036849

.0163677

.0015644

.0766911

.0015753

.4301052

.7664876

1.241447

Largest

2.896818

.844135

2.01359

2.957707

.7125639

2.76489

2.986268

1.17474

3.119043

3.423309

2014

Percentiles

Smallest

1%

0

5%

.0003335

10%

Obs

127

25%

Sum of Wgt.

127

50%

Mean

75%

Std. Dev.

90%

Variance

95%

Skewness

99%

3.45275

Kurtosis

.0003335

.0111018

.0200854

.0003343

.0565306

.00072

.3108966

.7162428

1.331176

Largest
2.864718

.8510828

1.876407

2.91954

.7243419

2.480283

3.45275

1.362852

3.840094

4.31162

2015

Percentiles

Smallest

1%

0

0

5%

0

10%

0

Obs

117

25%

Sum of Wgt.

117

50%

Mean

75%

Std. Dev.

90%

Variance

95%

Skewness

99%

5.842677

7.118781

Kurtosis

.0056502

.0143271

.0594046

.0032522

.3000902

.8405839

1.49064

Largest

3.366111

1.158529

2.349617

3.762578

1.342189

2.660555

5.842677

2.46023

11.57388

2016

Percentiles

Smallest

1%

5%

.000943

10%

Obs

107

25%

Sum of Wgt.

107

50%

Mean

75%

Std. Dev.

90%

Variance

95%

Skewness

99%

3.376464

Kurtosis

.000943

.0005591

.0043598

.0104486

.0012348

.0362867

.001927

.4361207

.717801

1.150011

Largest

2.811715

.8608956

2.037004

2.833677

.7411413

2.727755

3.376464

1.404647

3.571377

4.272691

2017

Percentiles

Smallest

1%

0

0

5%

0

10%

Obs

115

25%

Sum of Wgt.

115

50%

Mean

75%

Std. Dev.

90%

Variance

95%

Skewness

99%

3.965399

6.119405

Kurtosis

.0065132

.0132471

.0042236

.0455055

.0057532

.2939483

.7275742

1.200172

Largest

3.24128

1.004895

1.952452

3.502958

1.009813

2.699834

3.965399

2.28546

9.97769

(
72
)

2018

Percentiles

Smallest

1%

0

0

5%

0

10%

Obs

97

25%

Sum of Wgt.

97

50%

Mean

75%

Std. Dev.

90%

Variance

95%

Skewness

99%

2.699398

Kurtosis

.0002111

.00628

5.68e-06

.0478902

.0000862

.1792101

.4868667

.7786379

Largest

1.795226

.6123164

1.571636

2.047335

.3749314

1.752032

2.441648

1.528986

2.699398

4.777551

2019

Percentiles

Smallest

1%

.0028523

5%

10%

.0113948

Obs

41

25%

Sum of Wgt.

41

50%

Mean

75%

Std. Dev.

90%

Variance

95%

2.245001

Skewness

99%

2.774321

Kurtosis

.0028523

.0113948

.0110024

.0343229

.0699882

.0257073

.420664

.7523692

1.356327

Largest

2.082096

.8038705

2.04069

2.245001

.6462078

2.266349

.9159093

2.774321

2.541419

2020

Percentiles

Smallest

1%

.000199

5%

.0041498

10%

Obs

37

25%

.0242334

Sum of Wgt.

37

50%

Mean

75%

Std. Dev.

90%

1.578964

Variance

95%

1.745904

Skewness

99%

1.961328

Kurtosis

.000199

.0041498

.0242334

.0130043

.0651802

.2393117

.5449339

.9173883

Largest

1.578964

.6009547

1.619356

.3611466

1.745904

.9475189

1.961328

2.48645

APPENDIX E

Summary statistics of the annual shallow dose equivalents of the extremities for 285 nuclear medicine personnel working in the United States Navy medical facilities

Percentiles

Smallest

1%

5%

10%

Obs

25%

Sum of Wgt.

1,357

50%

Mean

75%

Std. Dev.

90%

Variance

95%

Skewness

99%

Kurtosis

.0217029

.0022509

.1368456

.0030824

.2482247

.0039535

1,357

.7627603

.0039845

2.88947

6.646006

7.857769

Largest

77.51325

11.12562

15.82636

92.3313

123.7794

26.47331

114.2635

4.206948

59.76435

120.6773

28.40237

(
73
)

APPENDIX F

Yearly summary statistics of the annual shallow dose equivalents of the extremities for 285 nuclear medicine personnel working in the United States Navy medical facilities

2003

Percentiles

Smallest

1%

.1100384

5%

10%

Obs

25%

Sum of Wgt.

82

50%

Mean

75%

Std. Dev.

90%

Variance

95%

Skewness

99%

48.31822

Kurtosis

.1100384

.3955024

.2269577

.547952

.3153768

82

1.443871

.3639799

3.151708

7.236618

9.913731

Largest

30.2099

9.158629

18.51997

30.57057

83.88048

29.75217

31.43298

2.117284

48.31822

7.800717

2004

Percentiles

Smallest

1%

5%

10%

Obs

25%

Sum of Wgt.

100

50%

Mean

75%

Std. Dev.

90%

Variance

95%

Skewness

99%

Kurtosis

.1592758

.1457507

.3156808

.1728009

.7206655

.1781174

100

2.150729

.2141979

4.572249

10.05775

11.26102

Largest

52.39859

14.58192

23.38075

60.15455

212.6323

49.70239

64.61112

2.492539

66.71343

68.81573

8.726595

2005

Percentiles

Smallest

1%

.0411071

5%

10%

Obs

99

25%

Sum of Wgt.

99

50%

Mean

75%

Std. Dev.

90%

Variance

95%

Skewness

99%

120.6773

120.6773

Kurtosis

.0411071

.1988184

.0841144

.3893005

.1151264

1.308954

.1585269

3.566083

11.52021

12.86205

Largest

63.17491

19.31912

30.22922

70.35617

373.2283

60.81975

74.73264

3.127999

14.27773

2006

Percentiles

Smallest

1%

.0633888

5%

10%

Obs

25%

.2682183

Sum of Wgt.

76

50%

Mean

75%

Std. Dev.

90%

Variance

95%

33.65672

Skewness

99%

92.3313

92.3313

Kurtosis

.0633888

.2682183

.1158227

.4955065

.1946463

76

1.423433

4.453853

9.275897

10.07067

Largest

33.65672

14.96471

24.68233

35.90947

223.9426

74.88283

3.611937

18.24488

2007

Percentiles

Smallest

1%

.0979249

5%

10%

Obs

25%

.3140229

Sum of Wgt.

67

50%

Mean

75%

Std. Dev.

90%

Variance

95%

36.24613

77.51325

Skewness

99%

114.2635

114.2635

Kurtosis

.0979249

.3140229

.1758117

.4655808

.2421001

67

1.445213

5.258824

11.02538

11.53873

Largest

36.24613

18.22

26.59136

43.48446

331.9683

3.65816

18.92618

2008

Percentiles

Smallest

1%

.0404472

5%

10%

Obs

25%

.1100654

Sum of Wgt.

63

50%

Mean

75%

Std. Dev.

90%

Variance

95%

31.75814

Skewness

99%

48.65779

Kurtosis

.0404472

.1100654

.075621

.1668186

.0995994

63

1.096516

3.728353

7.314512

8.045874

Largest

31.75814

10.00344

17.47653

32.47658

100.0689

40.23872

2.328275

48.65779

8.404312

2009

Percentiles

Smallest

1%

.0149458

5%

10%

.2620834

Obs

25%

Sum of Wgt.

50

50%

Mean

75%

Std. Dev.

90%

Variance

95%

27.81606

Skewness

99%

63.55399

Kurtosis

.0149458

.2620834

.091006

.5227313

50

.8151155

.327626

4.074058

8.077372

9.955929

Largest

26.61095

12.48456

20.92142

27.81606

155.8641

53.52279

2.937633

63.55399

12.15962

2010

Percentiles

Smallest

1%

.2067398

5%

10%

.2430426

Obs

25%

Sum of Wgt.

46

50%

Mean

75%

Std. Dev.

90%

Variance

95%

40.62265

Skewness

99%

53.8362

Kurtosis

.2067398

.2430426

.209037

.3298148

46

.8380799

.271205

3.228703

7.881159

6.465068

Largest

30.45856

12.79693

28.44971

40.62265

163.7614

50.89484

2.422633

53.8362

8.085803

2011

Percentiles

Smallest

1%

.0565581

5%

10%

Obs

25%

.1538275

Sum of Wgt.

61

50%

Mean

75%

Std. Dev.

90%

Variance

95%

14.66929

Skewness

99%

34.77391

Kurtosis

.0565581

.1538275

.1202071

.3509958

.1516559

61

1.209168

2.745102

5.060928

7.709274

Largest

14.66929

5.981541

10.47628

17.68077

35.77883

20.64693

2.530651

34.77391

11.77437

2012

Percentiles

Smallest

1%

.0140712

5%

10%

Obs

82

25%

Sum of Wgt.

82

50%

Mean

75%

Std. Dev.

90%

Variance

95%

Skewness

99%

42.42496

Kurtosis

.0140712

.1567765

.1003516

.3125843

.1214804

.9313893

.1472311

3.952852

7.587485

12.33601

Largest

29.93611

9.411401

19.17125

30.04114

88.57448

28.86268

42.21157

1.807286

42.42496

6.235459

2013

Percentiles

Smallest

1%

.0446474

5%

10%

Obs

25%

Sum of Wgt.

95

50%

Mean

75%

Std. Dev.

90%

Variance

95%

Skewness

99%

36.60241

Kurtosis

.0446474

.1099062

.0456403

.1542054

.0667088

95

.3843837

.1017152

2.347798

6.024351

8.939804

Largest

24.71736

8.073399

16.54802

32.49219

65.17977

21.61152

34.88761

1.860972

36.60241

6.328581

2014

Percentiles

Smallest

1%

.0078511

5%

10%

Obs

92

25%

Sum of Wgt.

92

50%

Mean

75%

Std. Dev.

90%

Variance

95%

Skewness

99%

59.76435

59.76435

Kurtosis

.0078511

.0721064

.0268371

.1169482

.0601499

.2289982

.0614876

1.376333

5.065321

5.654953

Largest

28.87495

9.347452

11.97626

33.22704

87.37487

25.31287

40.4018

3.461458

17.12187

2015

Percentiles

Smallest

1%

.083957

5%

10%

Obs

25%

Sum of Wgt.

94

50%

Mean

75%

Std. Dev.

90%

Variance

95%

Skewness

99%

38.25689

Kurtosis

.083957

.1347093

.1053502

.1680737

.1099917

94

.4778297

.1179634

2.066357

4.687912

6.83713

Largest

21.58343

6.455334

10.69378

23.77067

41.67134

18.08842

27.04418

2.578411

38.25689

11.37067

2016

Percentiles

Smallest

1%

.0127261

5%

10%

Obs

95

25%

Sum of Wgt.

95

50%

Mean

75%

Std. Dev.

90%

Variance

95%

Skewness

99%

27.05575

Kurtosis

.0127261

.1215181

.0170917

.1840531

.0242604

.6108225

.0443757

2.127224

3.779112

5.322699

Largest

14.35394

4.794174

9.018718

19.57408

22.98411

13.89317

19.86312

2.329099

27.05575

9.515051

2017

Percentiles

Smallest

1%

5%

.1135154

10%

Obs

103

25%

Sum of Wgt.

103

50%

Mean

75%

Std. Dev.

90%

Variance

95%

Skewness

99%

18.6359

Kurtosis

.1135154

.016183

.1908533

.2781078

.1318665

.5008725

.1502714

1.563737

3.4084

4.332285

Largest

16.53289

4.401668

9.935368

16.76095

19.37468

13.77273

18.6359

1.963701

20.04729

6.465768

(
78
)

2018

Percentiles

Smallest

1%

.0022509

.0022509

5%

.0030824

10%

.0039535

Obs

80

25%

.0039845

Sum of Wgt.

80

50%

Mean

75%

Std. Dev.

90%

Variance

95%

Skewness

99%

21.30811

Kurtosis

.0079435

.1510461

.3947382

1.419367

3.04302

4.308156

Largest

11.63484

3.76643

8.480438

12.56597

14.18599

10.68836

12.67641

2.19236

21.30811

9.132303

2019

Percentiles

Smallest

1%

.0119237

5%

.0159467

10%

Obs

37

25%

.1066185

Sum of Wgt.

37

50%

Mean

75%

Std. Dev.

90%

10.62188

Variance

95%

11.95496

Skewness

99%

15.37549

Kurtosis

.0119237

.0159467

.1066185

.0572418

1.025548

3.116429

4.137128

6.238679

Largest

10.62188

3.869094

11.3914

14.96989

11.95496

1.052625

15.37549

3.551712

2020

Percentiles

Smallest

1%

.0879792

5%

.1268238

10%

Obs

25%

.2356016

Sum of Wgt.

35

50%

Mean

75%

Std. Dev.

90%

6.481418

Variance

95%

10.20442

Skewness

99%

12.65337

Kurtosis

.0879792

.1268238

.2356016

.1519402

35

.7384854

1.487486

2.616966

3.513096

Largest

6.481418

3.101258

9.822086

9.6178

10.20442

1.816878

12.65337

5.564647

APPENDIX G

Summary statistics of the cumulative deep dose equivalents for 528 nuclear medicine personnel working in the United States Navy medical facilities from 2003-2020

Percentiles

Smallest

1%

.0010657

0

5%

0

10%

0

Obs

25%

0

Sum of Wgt.

528

50%

Mean

75%

Std. Dev.

90%

Variance

95%

Skewness

99%

Kurtosis

.0105749

.0202651

528

.0510137

.385507

2.961223

3.177992

Largest

35.69023

5.967875

10.05622

43.95685

35.61553

14.21984

44.11264

3.719745

29.33472

46.6182

20.76875

(
80
)

APPENDIX H

Summary statistics of the cumulative shallow dose equivalents of the skin for 528 nuclear medicine personnel working in the United States Navy medical facilities from 2003-2020

Percentiles

Smallest

1%

.0032522

0

5%

0

10%

0

Obs

528

25%

0

Sum of Wgt.

528

50%

Mean

75%

Std. Dev.

90%

Variance

95%

Skewness

99%

Kurtosis

.0135532

.0207912

.0511209

.3863496

2.901108

3.082477

Largest

34.54876

5.82575

9.535597

43.16834

33.93936

14.38533

43.27398

3.697068

28.47435

44.32508

20.42743

APPENDIX I

Summary statistics of the cumulative shallow dose equivalents of the extremities for 285 nuclear medicine personnel working in the United States Navy medical facilities from 2003-2020

Percentiles

Smallest

1%

.1100384

5%

.1099062

10%

.1100384

Obs

25%

.1318665

Sum of Wgt.

285

50%

Mean

75%

Std. Dev.

90%

Variance

95%

Skewness

99%

202.7736

Kurtosis

.1052364

.3404641

.6788423

285

2.889666

12.99507

31.64432

38.50785

Largest

193.6166

56.06953

82.82853

202.7736

3143.792

134.0991

487.4695

5.003586

528.6354

38.91941

APPENDIX J

Summary statistics of the annual deep dose equivalents corresponding to 221 NM personnel working in USN medical facilities identified as PET facilities

Percentiles

Smallest

1%

0

0

5%

.002233

0

10%

.0094334

0

Obs

25%

0

Sum of Wgt.

787

50%

Mean

75%

Std. Dev.

90%

6.439745

Variance

95%

6.49072

Skewness

99%

7.176692

Kurtosis

787

.0552446

.4414652

.9909822

1.602285

Largest
6.259352

1.237229

2.805705

1.530736

3.471585

1.651442

5.253173

5.913189

APPENDIX K

Summary statistics of the shallow deep dose equivalents of the skin corresponding to 221 NM personnel working in USN medical facilities identified as PET facilities

Percentiles

Smallest

1%

0

0

5%

0

10%

.0129185

0

Obs

787

25%

.0558806

0

Sum of Wgt.

787

50%

Mean

75%

Std. Dev.

90%

6.119405

Variance

95%

3.395016

6.473961

Skewness

99%

5.136432

7.118781

Kurtosis

.0052731

.4244372

.974075

1.576345

Largest
6.117428

1.211676

2.699954

1.468158

1.670658

6.043804

APPENDIX L

Summary statistics of the shallow deep dose equivalents of the extremities corresponding to 163 NM personnel working in USN medical facilities identified as PET facilities

Percentiles

Smallest

1%

.0022509

5%

.0030824

10%

.0039535

Obs

25%

.0039845

Sum of Wgt.

600

50%

Mean

75%

Std. Dev.

90%

92.3313

Variance

95%

114.2635

Skewness

99%

120.6773

Kurtosis

.0129868

.1224643

.2322271

600

.7295181

3.155826

8.740191

9.51468

Largest
77.51325

14.68307

23.83935

215.5926

37.1934

3.420971

72.5444

18.26929

APPENDIX M

Summary statistics of the annual deep dose equivalents corresponding to 361 NM personnel working in USN medical facilities identified as non-PET facilities

Percentiles

Smallest

1%

0

5%

.0088668

0

10%

0

Obs

25%

0

Sum of Wgt.

1,207

50%

.2865726

Mean

75%

Std. Dev.

90%

Variance

95%

5.767288

Skewness

99%

3.872853

6.130999

Kurtosis

.0004604

.0201419

1,207

.0552063

.6492319

.9536016

Largest
5.005732

.8499088

1.742694

5.507882

.722345

2.381172

2.186277

9.328157

APPENDIX N

Summary statistics of the annual shallow dose equivalents of the skin corresponding to 361 NM personnel working in USN medical facilities identified as non-PET facilities

Percentiles

Smallest

1%

0

0

5%

0

10%

0

Obs

1,207

25%

0

Sum of Wgt.

1,207

50%

Mean

75%

Std. Dev.

90%

5.361388

Variance

95%

2.266349

5.842677

Skewness

99%

3.781629

6.181241

Kurtosis

.0101224

.0212507

.0556345

.2956524

.6339584

.9462707

Largest
4.789417

.8202126

1.702806

.6727487

2.210261

9.792458

APPENDIX O

Summary statistics of the annual shallow dose equivalents of the extremities corresponding to 176 NM personnel working in USN medical facilities identified as non-PET facilities

Percentiles

Smallest

1%

.0119237

5%

.0127261

10%

.0149458

Obs

25%

.0159467

Sum of Wgt.

800

50%

Mean

75%

Std. Dev.

90%

40.4018

Variance

95%

42.21157

Skewness

99%

59.76435

Kurtosis

.0336422

.1502192

.2597432

800

.7570839

2.518783

4.718144

6.193541

Largest
40.23872

6.379942

11.98545

40.70366

16.49016

3.081133

31.26666

16.93102

APPENDIX P

Two-sample t test’s result for the mean difference of the annual deep dose equivalents between non-PET and PET facilities

APPENDIX Q

Two-sample t test’s result for the mean difference of the annual shallow dose equivalents of the skin between non-PET and PET facilities

APPENDIX R

Two-sample t test’s result for the mean difference of the annual shallow dose equivalents of the extremities between non-PET and PET facilities

APPENDIX S

An example of a questionnaire could be used in future studies to help provide detailed information on the number of workers, workload, and radiation safety standards in the USN medical facilities.

Section One: General

This section will include general information on your nuclear medicine (NM) department.

Q1. Is your NM department located in the United States?

YES NO

Q2. How many NM technologists, physicians, nurses, and health/ medical physicists worked in your department in the following years?

Table #1

Year

# of

NM Technologist

# of NM Physicians

# of Nurses

# of Health/Medical Physicist

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

2018

2019

2020

Section Two: Diagnostic (non-PET)

This section will focus on your department’s nuclear medicine (NM) diagnostic procedures. PET

procedures are not included.

Q1. Overall, how many diagnostic NM procedures were performed in your department in the following years?

Table #2

Year

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

# of diagnostic NM procedures

2016

2017

2018

2019

2020

Q2. On average, how many diagnostic NM procedures are performed per week in your department?

Answer:

Q3. How many were cardiac NM procedures performed in your department in the following years?

Table #3

Year

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

2018

2019

2020

# of cardiac NM procedures

Q4. Do you use Tc-99m to perform cardiovascular studies? If yes, in which year did you start using Tc-99m in your department?

YES NO Year :

Q5. Do you use Tl-201 to perform cardiovascular studies? If yes, in which year did you start using Tl-201 in your department?

(
:
)YES NO Year

Q6. Do you have CZT cameras for cardiac imaging?

YES NO

Section Three: Therapy

This section will focus on therapeutic nuclear medicine (NM) procedures performed in your

department. Please skip this section if your department does not perform therapeutic NM

procedures.

Q1. Overall, how many therapeutic NM procedures were performed in your department in the following years?

Table #4

Year

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

# of therapeutic NM procedures

2016

2017

2018

2019

2020

Q2. On average, how many therapeutic NM procedures are performed per month in your department?

Answer:

Q3. Who is responsible for the preparation of radiopharmaceuticals for therapy?

NM Technologist

NM Physician

Other ………………

Q11. Who is responsible for the administration of radiopharmaceuticals for therapy?

NM Technologist
NM Physician
Other ………………

Section Four: PET

This section will focus on PET procedures. If your department does not perform PET procedures,

please skip this section.

Q1. When did you start performing PET or PET/CT procedures in your department?

Year:

Q2. Do you use a PET/CT camera?

YES NO

Q3. How many PET and PET/CT procedures did you perform in your NM department in the following years?

Table#5

Year

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

2018

2019

2020

# of PET or PET/CT Procedures

Q4. Does your department require NM technologists to rotate between general NM and PET?

YES NO

Q5. Do you have Intego or any other PET infusion system?

YES NO

Q6. On average, how many PET procedures are performed per week in your department? Answer:

Section Five: Radiation Protection

This section will focus on radiation safety practices in your department.

Q1. How many body dosimeters are NM technologists required to wear in your department?

One Two

Q2. Where do NM workers usually wear the body dosimeter in your department?

Chest Level Other

Q3. Are NM physicians required to wear a body dosimeter?

YES NO

Q4. Are NM technologists required to wear a ring dosimeter?

YES NO

Q5. Are NM physicians required to wear a ring dosimeter?

YES NO

Q6. Are NM technologists required to wear a lead apron?

YES NO

Q7. Are NM technologists required to use a syringe shield during the manipulation of the radiopharmaceuticals?

YES NO

Q8. Are NM technologists required to use a syringe shield during the injection of the radiopharmaceuticals?

YES NO

Q9. Do you receive single doses of radiopharmaceuticals from radiopharmacy?

YES NO

Q10. How often are NM technologists, NM physicians, nurses, and health/medical physicists monitored in your department? (Please, use a ✓ to assign your answer in table #6).

Table#6

Title of the workers in the

NM department

Monthly

Quarterly

NM Technologists

NM Physicians

NM Nurses

Medical/Health physicists

GEORGETOWN UNIVERSITY GRADUATE SCHOOL
GUIDELINES FOR DISSERTATION, DOCTORAL PROJECT

AND THESIS WRITERS

The Graduate School of Arts and Sciences
3520 Prospect St NW, Car Barn Suite 140

gradstudentservices@georgetown.edu

PREPARATION OF THE THESIS ……………………………………………………………………………………………. 2

Style Manuals ………………………………………………………………………………………………………………………… 2

Pagination ……………………………………………………………………………………………………………………………… 2

Fonts ……………………………………………………………………………………………………………………………………… 2

ORDER AND CONTENT OF THE THESIS ……………………………………………………………………………… 3

Order of the Pages …………………………………………………………………………………………………………………. 3

Title Page ………………………………………………………………………………………………………………………………. 3

Your Name …………………………………………………………………………………………………………………………….. 3

The Date ………………………………………………………………………………………………………………………………… 4

Copyright Page ………………………………………………………………………………………………………………………. 4

Abstract …………………………………………………………………………………………………………………………………. 4

Table of Contents …………………………………………………………………………………………………………………… 4

Page Margins …………………………………………………………………………………………………………………………. 5

Schema of Headings and Subheadings and Hierarchy of Font Treatments ……………………………….. 5

SUBMISSION OF THE THESIS TO THE GRADUATE SCHOOL ……………………………………………. 6

Electronic Submission of Work ………………………………………………………………………………………………. 6

The Main Issues……………………………………………………………………………………………………………………… 7

Common Mistakes to Avoid ……………………………………………………………………………………………………. 9

Using a Template………………………………………………………………………………………………………………….. 11

Frequently Asked Questions …………………………………………………………………………………………………. 11

  • ADVICE FOR . . . .
  • …………………………………………………………………………………………………………………. 12

    Advice for Long Dissertations ……………………………………………………………………………………………….. 12

    Advice for LaTeX Users ……………………………………………………………………………………………………….. 12

    Advice for APA Users …………………………………………………………………………………………………………… 12

    Advice for Multi-Article Dissertations …………………………………………………………………………………… 12

    Advice for Figure Titles ………………………………………………………………………………………………………… 13

    Advice on Placement of Figures and Tables …………………………………………………………………………… 14

    APPENDIX: SAMPLE THESIS………………………………………………………………………………………………….. i

    2

    INTRODUCTION

    The thesis you are writing is a significant step in the pursuit of your graduate degree. A well-
    written and well-formatted work will reflect favorably upon you, your department, and
    Georgetown University. When completed, your thesis will be a lasting contribution to your field
    of knowledge. Therefore, your thesis must follow a format and style that are acceptable, readily
    understandable, and consistent with your field of knowledge. This document will use the term
    ‘thesis’ to refer to all three types of scholarly work.

    PREPARATION OF THE THESIS

    Style Manuals
    Every thesis must follow a style manual or style sheet that has been approved by your Thesis
    Advisor or by your department or program. Some examples include:

    • A Manual for Writers of Term Papers, Theses, and Dissertations by Kate Turabian
    • The Chicago Manual of Style · MLA Style Manual
    • Publication Manual of the American Psychological Association

    The Lauinger Library website has information on these on the Citation Guides tab on
    https://www.library.georgetown.edu/citations

    Pagination
    The pagination must meet the following guidelines:

    • Title page — No page number
    • The pages that follow — Copyright page, Abstract, Table of Contents, etc. — are

    numbered with lower-case Roman numerals: ii, iii, etc.
    • All page numbers, including lower-case Roman numerals, at the bottom center of the

    page
    • The remainder of the thesis, beginning with the Introduction or Chapter One, must be

    numbered consecutively using Arabic numerals (1, 2, etc.)
    • Pages in each section must be numbered consecutively from beginning to end. The lower

    case Roman numerals and the Arabic numerals form two separate numeric series, the
    former beginning with ii, and the latter with 1.

    • Blank pages are not permitted.
    • The page number for any page printed in horizontal or “landscape” mode must still

    appear at the bottom of the page when the page is held vertically.
    Fonts
    The fonts used in the thesis must meet the following guidelines:
    • Times New Roman 12 point or Arial 10 point.
    • Italics may not be used in the Table of Contents unless it is used for a foreign word.
    • The font size requirement applies to all prefatory material (title page, Acknowledgments,
    Table of Contents, , etc.), the body of the text, page numbers, all footnotes or endnotes, and all
    concluding material (Appendices and Bibliography). Some charts, graphs, or tables may contain
    type that is one point smaller.

    3

    ORDER AND CONTENT OF THE THESIS
    Order of the Pages

    Page Page Numbering

    Title Page Not numbered (but counts as i)

    Copyright Page ii (Roman numeral)

    Abstract (not required for theses) Next consecutive Roman numeral(s)

    Acknowledgments, Dedication (if used) Next consecutive Roman numeral(s)

    Table of Contents with dot leaders and page Next consecutive Roman numeral(s)
    numbers

    List of Figures (if document has figures) with Next consecutive Roman numeral(s)
    numbers, titles and dot leaders and page numbers

    List of Tables (if document has tables) with Next consecutive Roman numeral(s)
    numbers, titles and dot leaders and page numbers

    Text, beginning with the Introduction Arabic numerals ( 1, 2, 3, 4, etc.) for the
    remainder of the work

    Appendices (if used) Next consecutive Arabic numeral(s)

    Bibliography Next consecutive Arabic numeral(s)

    Specially bound or packaged Addenda Not numbered, but included in the Table of
    Contents (e.g. maps or digital media)
    Title Page
    The title page should include the title, the submission statement (A Thesis or A Dissertation…),
    the degree, the name of your department or program, your name, highest previous degree, the
    location (“Washington, D.C.”), and the date. The title page is not numbered. An example title
    page appears in the Appendix. Note that department is not necessary on Public Policy theses
    because the program is included in the degree.

    Your Name
    The format of your name must appear as it appears on your transcript in MyAccess on the title
    page, copyright page and abstract page. The name must match exactly in each location.

    On the title page of your thesis, your name should be followed by the SINGLE highest degree
    you have previously received, not a list of all the degrees you have received. You should list
    only the initials of the degree itself, for example: B.A., B.S., M.S., M.A., J.D., Ed.M., etc. Do
    not list the majors, concentrations, specialties, or the institution where the prior degree was
    earned. Following are two examples of the correct format for your name on the thesis title page:

    Jamie Doe Smith, M.S. John D. Smith, Jr., B.A.

    4

    The Date
    At the bottom of the title page of your thesis, underneath “Washington, D.C.,” type the date you
    defended your thesis or dissertation. If no defense was required, you should insert the date your
    advisor signed the cover sheet to approve the thesis. DO NOT allow MSWord to add a
    superscript st, nd or th to the date. Samples of date notation can be found in the Appendix below.

    Copyright Page
    You possess the copyright to your thesis from the time you record it in some tangible form. If
    you claim copyright, either informally or through a formal application, the appropriate notice
    should be printed on its own numbered page immediately following the title page of the thesis.
    For example:

    Copyright 2020 by Jamie Doe Student
    All Rights Reserved

    Abstract
    The purpose of the abstract is to provide a brief summary of the contents of the thesis. The
    abstract, must be written in English. The maximum permissible length of the abstract is 350
    words (2,450 characters). The abstract is optional for a Master’s thesis.

    See the Appendix at the end of this document for an example of how your Abstract page should
    be formatted. The abstract should start with the title of the thesis (in ALL CAPS, centered),
    followed by your name and highest degree (centered), followed by the word “Advisor:” and the
    name and highest degree of your Thesis Advisor (centered). The word ABSTRACT appears
    (centered, in caps), followed by the text of the abstract itself

    Table of Contents

    • Each chapter or section heading in the body of text, appendices and bibliography or
    references section must be shown with corresponding page numbers for each item.

    • The numbering of chapters or sections in the Table of Contents—whether written out as
    words, or shown as Roman or Arabic numerals—must be shown in the same way in the
    text.

    • The items must appear in plain typeface without stylistic treatments such as bold,
    underlining, italicization, size variations, etc.

    • You must list all main section or chapter headings, and may choose to include
    subheadings as well. If you choose to include subheadings, you must show all instances
    of a given level, for example first-level but not second-level subheadings or first-level
    AND second-level subheadings, for all chapters that have subheadings at that level.

    • Headings and subheadings must appear in the Table of Contents word-for-word as
    they appear in the body of text including capitalization.

    • Note: Do not use MS Word’s built-in Table of Contents formatting options, but rather
    use Custom Table of Contents.

    • Page numbers must also be right-aligned along the right margin. Instructions on how to
    do this in MS Word appear on page 9.

    • Page numbers in the Table of Contents must be the page numbers where the item
    actually appears in the text.

    5

    Page Margins
    Page margins must be 1” on all sides.

    Considerations for Formatting Subheadings in the Text

    • Subheadings at a given level must be formatted in the same way throughout the
    document. A common schema has first-level subheadings centered in ALL CAPS,
    second-level subheadings in bolded mixed case at the left margin, and third-level
    subheadings in un-bolded mixed case at the left margin.

    • The formatting reviewer will assume that the formatting of the first section or chapter
    will be the formatting for the entire document. Pay close attention to the Introduction to
    make sure that its formatting schema matches that of the rest of the document.

    • Make sure that each section or chapter has the SAME formatting schema.
    • Subheadings must not be left orphaned at the bottom of a page with no text below them.
    • Spacing must be consistent between paragraphs, above and below subheadings, above

    and below figures and tables. The top line of a page should not be blank.

    Schema of Headings and Subheadings and Hierarchy of Font Treatments
    The formatting of each level of subheading must be the same through all chapters or sections of
    the document. An example schema, excluding consideration of numbering, would be:

    Chapter or section heading ALL CAPS, bold,

    centered

    First-level subheading Mixed Case, bold, at the left

    margin

    Second-level subheading Mixed Case, plain text, at the left margin
    Third-level subheading Mixed Case, italics, at the left margin

    Examples of this schema would look like:

    ASSOCIATIONAL FREEDOM AND EQUAL ACCESS
    (Chapter/Section Heading)

    Introduction
    (First-level subheading)

    The Value of Associations
    (Second-level subheading)

    Associational Freedom and the Right to Exclude
    (Third-level subheading)

    Your document need not have all these levels. The point is that all chapters or sections with
    multiple levels of subheading must follow the same schema—which can mirror this schema or
    can be a schema of your own choosing.

    The level of headings and subheadings that appear in the Table of Contents must be the same for
    all sections/chapters.

    The schema of the first section will be assumed to be the schema for the whole document.

    6

    SUBMISSION OF THE THESIS TO THE GRADUATE SCHOOL

    Electronic Submission of Work
    The Graduate School requires electronic submission of all theses via the ProQuest website.
    Please refer to the Graduate School websites for information on the submission process:
    https://grad.georgetown.edu/info-for/current-students/submission-of-thesis/
    https://grad.georgetown.edu/info-for/current-students/submission-of-dissertation-or-doctoral-
    project

    There is no cost associated with publishing your work. There is a cost if you elect certain
    publishing or copyright options in ProQuest or order copies of your thesis from ProQuest. Refer
    to the Lauinger Library website for more information.

    Review of the Thesis by the Graduate School
    The Graduate School reviews all theses submitted to ProQuest. We ensure that the works are
    formatted according to Graduate School standards and are ready for publication. The care you
    take to prepare your work according to these guidelines generally determines the amount of time
    we will need to review your thesis, and the number and nature of any changes you may be
    required to make.

    Formatting of the Introduction will be assumed to be the formatting for each section or chapter of
    the entire document. Pay close attention to the Introduction to make sure that its formatting
    schema matches that of the rest of the document

    https://grad.georgetown.edu/info-for/current-students/submission-of-thesis/

    https://grad.georgetown.edu/info-for/current-students/submission-of-dissertation-or-doctoral-project

    https://grad.georgetown.edu/info-for/current-students/submission-of-dissertation-or-doctoral-project

    7

    FORMATTING GUIDANCE

    The Main Issues
    Initial Section

    • There must be no page number on the title page
    • Pages prior to the Introduction must use Roman numerals rather than Arabic numerals
    • Sections prior to the Introduction DO NOT appear in the Table of Contents

    Table of Contents

    • Do not use MS Word’s built-in Table of Contents formatting options. Use Custom Table
    of Contents instead.

    • All Table of Contents items should appear in plain typeface and not include stylistic
    treatment such as bold, color, underlining, italicization or size variations.

    • With the exception of the most commonly recognized abbreviations and acronyms, like
    HIV, abbreviations and acronyms must be written out in words in all headings and
    subheadings.

    • DO NOT include the items that have Roman numeral page numbers, including the
    Abstract, Acknowledgements, Table of Contents and List of Figures.

    • If a given level of subheading appears in the Table of Contents, all subheadings at the
    same level (and all higher levels) must appear for EACH section or chapter.

    • Page numbers in the Table of Contents must be the page where the item actually appears
    in the text. Check all page numbers before uploading.

    • The page number for the first page of the Introduction or Chapter One must be 1.
    • Page numbers for each item must appear with dot leaders, . . . ., and be right-justified on

    the right margin.
    • If any items wrap to a second line, add a hard return before a word in the first line so that

    the second line does not begin with dot leaders ……..

    • In all headings and subheadings, major words should be capitalized.
    • Items in the Table of Contents must match the corresponding items in the text word-for-

    word–and in terms of capitalization and punctuation.
    • Appendices (if the document has one or more) and the Bibliography or References

    section must appear in the Table of Contents.

    List of Figures / List of Tables

    • If the document has five or more figures or tables, it requires a List of Figures and List of
    Tables.

    • The word Figure or Table, the number and the title presented in mixed case. The words
    through the first period are considered the title and ONLY they appear here. Do not show
    the entire title and caption.

    • Items in the List of Figures and List of Tables must match those items in the text word-
    for-word–and in terms of capitalization and punctuation.

    • To the greatest extent possible, abbreviations should be written out in words.
    • Page numbers for figures or titles must be right-justified with dot leaders.
    • If any items wrap to a second line, add a hard return before a word in the first line so that

    the second line does not begin with dot leaders ……..

    8

    • The List of Figures and List of Tables must be separate lists. If they are short enough to
    fit on one page, the two separate lists can appear on a single page. Otherwise, the List of
    Figures must appear on its own page with the List of Tables on the next page.

    • Page numbers listed in the List of Figures and List of Tables must reflect the page where
    the figures and tables appear in the text. Check all page numbers before uploading.

    Text

    • The organizing schema for all headings and subheadings and their formatting must be
    consistent both within and across chapters

    • Headings, subheadings, figure titles and table titles must appear in the text word-for-word
    as they appear in the Table of Contents/List of Figures/List of Tables.

    • All headings at a given level must be formatted in the same way, in terms of
    capitalization, bolding, italics, punctuation, spacing, etc., throughout the document.

    • Where the page is presented in landscape orientation rather than portrait, the page number
    must appear on the left side of the page turned 90 degrees so that it would be readable if
    the page appeared in a book with the page number at the bottom of the page.

    • All figures and tables in the text require numbers and titles.
    • Figure and table numbers and titles must appear without italics and in bold face.

    Additional caption text should not be bolded.
    • Figure and tables numbers and titles must be the same size as the font in the body of the

    document.
    • Table titles must appear ABOVE the table.
    • Figure titles must appear BELOW the figure.
    • Figures and tables MUST fit within the regular 1-inch page margins.
    • Figures must be centered along with their titles (and captions).
    • Tables must appear on a single page wherever possible.
    • When a table goes onto a second page, the column headers must be added to the top of

    the second page. Above the table, add a notation of Table # (Cont.) Do not include the
    table title.

    • The text in figures and tables must be large enough as to be legible, with text no more
    than 1 point smaller than the main text.

    • Subheadings must not be orphaned at the bottom of a page. Move them to the top of the
    following page.

    • Be sure that the heading or text for each page–first page of a chapter possibly aside–
    appear at the top line of the page

    9

    Common Mistakes to Avoid
    Mistake: Your name used in the document does not match your transcript. The name that
    appears on your signed cover sheet must be your name as it appears on your transcript in
    MyAccess. The same format of your name must be used on your thesis. If you have recently had
    a name change, take steps to update it with the Registrar’s Office using the form at
    https://georgetown.app.box.com/s/yt90bx3gdcds7mwuz67yhv6knh4v5nm7

    Mistake: Formatting such as bold, color, italics, underlining and size variations appears in
    the Table of Contents. The words in the Table of Contents must appear in plain typeface.

    Mistake: Headings in the document do not match the headings in the Table of Contents. All
    of the headings in your Table of Contents must appear word-for-word the same as the headings
    used in your document. For example, if the title of your third chapter appears in the document as
    “Chapter Three: Writing a Thesis at Georgetown University,” the heading in your table of
    contents cannot be “Chapter 3: Writing a Paper at GU.” They must match exactly. The same rule
    applies for the titles of figures and tables and the respective items listed in your List of Figures,
    List of Tables.

    Mistake: Page numbers shown in the Table of Contents do not match the location in the
    text. If a subheading is listed as appearing on page 10 in the Table of Contents, it must appear on
    page 10 in the text, not page 11. This holds true for figures and tables as well.

    Mistake: Page numbers do not appear right-justified at the right margin in the Table of
    Contents, List of Figures and List of Tables. Due to modern proportional fonts, it is not
    possible to just type periods and have the justification come out right. In MSWord, the Tabs
    dialog box allows you set a right tab at the right margin and then choose the style of dot leader.

    1) Highlight the items–the words and the page numbers–in the table/list and open the
    Tabs menu, Home->Paragraph->Tabs is in the bottom left of the dialog box.
    2) For Tab stop location, enter the location of the right margin most likely 6.5.
    a) For Alignment, select Right
    b) For Leader, choose 2 ……
    c) Returning to your document, place your cursor at the end of the words for the table/list
    entry before the page number and hit Tab. The page number should jump to the right
    margin with a series of dot leaders

    Mistake: Sections with Roman numeral page numbers (like the Abstract and
    Acknowledgements) appear in the Table of Contents. The Introduction or first chapter should
    be the first item in the Table of Contents. Other pages prior to the introduction or first chapter are
    not be included in the Table of Contents.

    Mistake: The document is missing a List of Figures and List of Tables. A thesis with five or
    more tables must include a List of Figures and List of Tables formatted like Tables of Contents
    on the page after the Tables of Contents.

    https://georgetown.app.box.com/s/yt90bx3gdcds7mwuz67yhv6knh4v5nm7

    10

    Mistake: Entries wrap to a second line that begins ……… at the left margin in the Table of
    Contents, List of Figures or List of Tables. To avoid this, add a hard return at about 80% of the
    first line on the subheading or figure/table title.

    Mistake: Figures and tables have no titles. ALL figures and tables require titles whether or not
    there is a List of Figure and List of Table. Figure titles, must appear BELOW the figure. Table
    titles must appear ABOVE the table. Examples of properly formatted figure and table titles:
    Figure 1. Map of sectarian neighborhoods in Belfast, 1982.
    Table 1. Monthly output of widgets by company, 2010-2015.

    Mistake: Figures titles appear within the figure box. Crop the title from the top of the figure
    box or go back to Excel and remove the title from within the figure box. Re-type the title as a
    properly numbered and formatted figure title below the figure box.

    Mistake: Tables appear on more than one page. Look for extra white space in the table that
    can be removed or columns that can be narrowed so that the table fits on one page. When a
    second page is necessary, the second page should be identified as such for instance as Table 3.
    (Cont.)

    Mistake: Sections of the document (title page, table of contents, list of figures, list of tables,
    appendix, and bibliography) are not in the correct order. The Graduate School requires the
    sections of your document follow a specific order. The template provided by the Graduate
    School (available on our forms website at: https://grad.georgetown.edu/academics/dissertation-
    thesis-information#. You can also refer to page 3 of the “Guidelines for Thesis Writers”
    document to see the correct order.

    Mistake: A subheading appears alone at the bottom of a page. Move the subheading to the
    top of the following page.

    Mistake: Appendix figures and tables are missing from the List of Figures and List of
    Tables. Number Appendix items as Figure A.1, A.2, Table A.1, A.2, etc., add descriptive titles
    and include them in the List of Figures and List of Tables.

    Mistake: Incomplete upload to the ProQuest site after making edits. Do not email the
    revised document. Be sure to click the “confirm” button after you upload your revised document
    to the ProQuest website. Students sometimes overlook this step and upload a revised draft
    without officially submitting it. The Graduate School will not see your submission on the
    ProQuest site until it is officially submitted. At one point, you will see:

    “Your revisions have been made, but still need to be submitted to your graduate school for
    review.”
    “I’m done – submit my changes.”

    On that page, click “I’m done – submit my changes.”, but continue to the next screen where you will see a
    Submit Revisions button. Click the Submit Revisions button to ensure that Graduate School staff receive
    the submission.

    Mistake: Page numbers not aligned at the bottom of the document after conversion to PDF.
    Note that the PDF converter on the ProQuest site should not be used.

    https://www.etdadmin.com/cgi-bin/student/revpayment?siteId=163;revId=465605

    https://www.etdadmin.com/cgi-bin/student/revpayment?siteId=163;revId=465605

    11

    Mistake: Edits not submitted by the deadline. You must submit the edits and the document
    accepted by the Graduate School by deadline posted online. If edits that are not completed on
    time, your graduation will be delayed until the next available graduation date.

    Using a Template
    The Graduate School provides three different templates to help format your thesis. They are
    available at: http://grad.georgetown.edu/academics/dissertation-thesis-information/

    • MS-Word on a PC
    • Word for Mac
    • LaTeX markup language

    Note that use of these templates is not a guarantee of a smooth review process. The PC and
    Mac templates are unlocked and can be edited by you. The LaTeX template requires additional
    steps to remove the Roman numeral items from the Table of Contents. The Graduate School
    cannot provide technical support related to the use of these templates. Use of the template is not
    required; you may format the work on your own based on these guidelines.

    Frequently Asked Questions
    What style guide should I use? This is a question for your academic department (advisor and/or
    thesis committee members).

    Does the Graduate School have a template I can use to format my work? Templates are
    linked from the Graduate School forms website on:
    http://grad.georgetown.edu/academics/dissertation-thesis-information/

    How soon will my thesis be reviewed after I submit it to the Graduate School? The Graduate
    School works to review all works submitted within three business days. We receive an
    automated system email when a PDF is uploaded or updated. There is no need to notify the
    Graduate School that you have uploaded a new version.

    Are the edits identified by the Graduate School required? Yes.

    What is the deadline for submitting my edits? In August, the deadline to submit any required
    edits is the final working day of the month. There are different deadlines for May and December
    graduates (see https://grad.georgetown.edu/academics/dissertation-thesis-information/submit-
    dissertation/#).

    How can I order bound copies of my thesis? You can order bound copies of your work via the
    ProQuest website.

    What publishing option should I choose? Lauinger Library has produced a set of videos that
    lay out the options you can select on the ProQuest site,
    https://www.library.georgetown.edu/scholarly-communication/etds-videos.

    https://www.library.georgetown.edu/scholarly-communication/etds-videos

    12

    ADVICE FOR . . . .

    Advice for Long Dissertations
    Dissertations are written over the course of months a chapter at a time. We often see that the
    structure and formatting within each chapter is consistent, but they are not consistent across
    chapters. The Introduction and Conclusion are often written last–with a different structure.

    When reviewing a document, we take the organizational structure and formatting of subheadings
    of the first section as the pattern for the whole document and identify edits in the subsequent
    sections by comparing them to the standard of the first section. (See the Schema of Headings and
    Subheadings and Hierarchy of Font Treatments section on page 5.) As a result, it is especially
    important that the Introduction use the formatting scheme that you will use for the entire
    document.

    Advice for LaTeX Users
    The complexity of the LaTeX template can give the impression that there is no need to pay
    attention to formatting. Unfortunately, there are several things that it does not take into account.

    The template does not control for capitalization in headings and subheadings. Even though items
    in the Table of Contents, headings and subheadings appear in SMALL CAPS, capitalization of the
    words still matters. All subheadings at each level and across chapters must be capitalized in the
    same way.

    Figure numbers and titles must be placed UNDER the figures. Table numbers and titles must be
    placed ABOVE the tables.

    Advice for APA Users
    The APA Style Guide uses un-numbered subheadings. This can make is seem like it imposes
    little structure. In fact, the five levels of subheadings are very specifically prescribed. Whether
    your thesis has two levels of subheadings, three or five, each level must adhere to the schema.

    Level Number and Format
    1 Centered, Boldface, Title Case Heading
    2 At the Left Margin, Boldface, Title Case Heading with a hard return at the end
    3 At the Left Margin, Boldface Italics, Title Case Heading with a hard return at the end
    4 Indented, Boldface Title Case Heading Ending with a Period. The text continues on the
    same line as the subheading.
    5 Indented, Boldface Italics, Title Case Heading Ending With a Period. The text
    continues on the same line as the subheading.

    Advice for Multi-Article Dissertations
    Dissertations in the sciences are often a collection of journal articles–often ones submitted to
    different publications each with their own formatting requirements. A dissertation is a unitary
    academic work with a single abstract at the beginning of the document and consistent formatting
    of headings and subheadings throughout the document.

    13

    Advice for Figure Titles

    Figure 1. Simple Histogram of Proficiency.

    Figure 1. Simple Histogram of Proficiency.

    Figure titles must be bolded

    All figures and tables
    need numbers whether
    or not you have a List of

    Figures and List of
    bl

    WRONG

    RIGHT

    14

    Advice on Placement of Figures and Tables

    WRONG: Extends beyond the right margin

    WRONG: Extends beyond both margins

    At left margin: GOOD

    Centered: ALSO GOOD

    Pa
    ge

    M
    ar

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    APPENDIX: SAMPLE THESIS

    STARTLING BRILLIANCE: DIAMONDS MAY BE FOREVER BUT WHAT IS THEIR
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    A Thesis
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    Asian Studies

    By

    Jamie Doe Student, B.A.

    Washington, DC
    October 7, 2019

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    STARTLING BRILLIANCE: DIAMONDS MAY BE FOREVER BUT WHAT IS THEIR
    AFFECT ON MARRIAGE RATES?

    Jamie Doe Student, M.A.

    Thesis Advisor: Name O. Professor, Ph.D.

    ABSTRACT

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    TABLE OF CONTENTS

    Chapter 1. Introduction …………………………………………………………………………………………………. 1

    Chapter 2. Literature Review ………………………………………………………………………………………….. 6

    Chapter 3. Material and Methods ……………………………………………………………………………………. 8

    Chapter 4. Data ………………………………………………………………………………………………………….. 11

    Chapter 5. Results ………………………………………………………………………………………………………. 16

    Chapter 6. Policy Discussion ………………………………………………………………………………………. 20

    Chapter 7. Conclusion ………………………………………………………………………………………………….. 27

    Appendix: Supplementary Tables ………………………………………………………………………………….. 30

    References ………………………………………………………………………………………………………………….. 32

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    LIST OF TABLES

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    Table 3. Title for Table 3 …………………………………………………………………………………………………14

    Table 4. Title for Table 4 …………………………………………………………………………………………………18

    Table 5. Title for Table 5 …………………………………………………………………………………………………19

    Table A1. Title for Table A1 ……………………………………………………………………………………………30

    Table A2. Title of Tables A2 ……………………………………………………………………………………………31

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    CHAPTER 1. INTRODUCTION

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    Estimation of Peak Skin Dose and Its Relation to the Size Specific Dose Estimate

    Abdullatif Abdullah

    1

    , *, Matthew Williams

    2

    , *

    1

    3

    700 O St NW, Washington, DC, 20057

    23800 Reservoir Rd NW, Washington, DC, 20007

    Received December 10, 2021, amended month date year, accepted month date year

    Abstract:

    The research aims to test the concept that the size specific dose estimete (SSDE) has a significantly higher linear relationship with the peak skin dose (PSD). To determine the connection between the two measurements, a NEMA phantom and ACR phantom were provided with a peak skin dose measured using the external dosimeters (Nanodots) to measure the level of delivered radiation. For the experiment’s success, different measuring techniques and methods were utilized in the research. Nanodots dosimeters which use optically stimulated luminescence (OSL) technology, were used to determine peak skin dose. The findings revealed a somewhat favorable connection in both PA and lateral regions, suggesting that the PSD and SSDE may be related. Posterior and Lateral angles have some potential since, in most projections, the greater the PSD, the higher the SSDE. The measured PSD and SSDE revealed that a physicist can predict the PSD within 80% of the actual dose estimates with considerable some uncertainties.

    1
    2
    3

    Introduction

    The Federal Drug Administration (FDA) states that the Peak Skin Dose is the highest radiation dose accruing actually at a single site on a patient’s skin (1). Knowing the appropriate highest dosage is vital so that no harm is caused to the patient. The United States has regulated that the fluoroscopic system provides a display of the irradiation time, dose rate at the interventional reference point during irradiation, and the cumulative dose for the procedure upon completion of irradiation (2). In preparation for actual patients, technologists and physicists would revert to the manufactured dose estimation which is called the Computed Tomography Dose Index (CTDI). The CTDI is generally utilized for quality control including the radiation output of CT machines (2). Specifically, the volume CTDI is shown on the control center of all CT machines and is promptly accessible to the administrator. In any case, the CT Dose Index (CTDIvol) was originally designed as an index of dose associated with various CT diagnostic procedures, not as a direct dosimetry method for individual patient dose assessments (3).

    Moreover, CTDIvol is reported in two units: a 16-cm phantom for head exams or 32-cm phantom or body exams. The relationship between the CTDIvol and skin dose entrance depends on various factors, one of which is the patient size (5). CTDIvol is displayed on the console of CT scanners, and it gives genuine estimates of the dose being delivered to a phantom,

    which can over or under estimate dose to an actual patient. For instance, report 204 was generated to help better estimate the dose to a patient based on the patient size and shape that differs from size and shape of phantoms used to generate CTDIvol (4).

    CTDIvol is a measurement taking with an ion chamber inserted into a phantom but not laying on outside of a phantom at the point of skin entrance. Specifically, estimating Peak Skin Dose is ideal since it is a surely known dosimetric amount that directly identifies with radiation-incited skin injures. For example, radiation directly damages the skin as well as its deep tissue cells, causing dryness, loss of elasticity, pigmentation, soft tissue fibrosis, capillary dilatation, and radiation dermatitis in irradiated areas. Therefore, there is a threshold range for transient erythema and temporary epilation is 2-5 Gray (Gy) peak skin dose, prolonged erythema and permanent partial epilation have threshold ranges of 5-10 Gy peak skin dose and severe skin injury is associated with larger values of peak skin dose (5).

    Besides, estimates of PSD values, utilizing appropriate phantoms can be made across all types of CT units and scan protocols accessible in clinics (6). This is significant for comparing doses for a similar CT examination in different facilities, which can change fundamentally. More recently, modifications to the original CTDI concept have attempted to convert it into to patient dosimetry method, but have mixed results in terms of accuracy (7).

    Nonetheless, CTDI-based dosimetry is the current worldwide standard for estimation of patient dose in CT (8). Therefore, CTDIvol is often used to enable medical physicists to compare the dose output between different CT scanners (8). Also, since CTDIvol estimates the patient’s radiation exposure from the CT procedure, the exposures are the same regardless of

    patient size, but the size of the patients is a factor in the overall patient’s absorbed dose (SSDE) (4). The size-specific dose estimate (SSDE) is measured in mGy, and it is a method of estimating CT radiation dose that takes a patient’s size into account (4).

    From a radiation protection point of view, determining the maximum dose delivered to the skin would allow deriving quantities that can be compared with dose reference levels set by national and international standards. The most important outcome from a radiation safety perspective is evaluating if a radiation injury had occurred quickly (10). In this research, the peak skin dose delivered to a patient was estimated experimentally by measuring the dose delivered to the surface of a NEMA phantom and an ACR phantom using external dosimeters (11). These dosimeters provided PSD values for a given protocol and its related CTDIvol. From this, a relationship was evaluated between both quantities. The aim of this project was to test the hypothesis that the size-specific dose estimate (SSDE) has a sufficiently strong linear relationship with PSD to allow direct calculation of the PSD directly from the SSDE. Comment by ,Abdullatif abdullah: Prof. Jorgensen note “What are you saying here? Do you mean that dose rate is the most important parameter determining skin injury? Or do you mean that shorter latency means higher doses? I don’t understand why this sentence is stuck in here.”

    MATERIALS AND METHODS

    The measurements were performed with a Siemens 64 slices, Biograph mCT. A comparison was made between the CTDIvol value displayed on the CT console and the measured CTDIvol value using the AAPM protocol. For every examined scanner, the CTDIvol was obtained from scans in an axial mode for head scans and helical mode of the routine pelvis, cervical spine, abdomen, and thoracic scans using the scan parameters. The corresponding CTDIvol displayed on the console was recorded as shown in Table 1.

    Peak Skin Dose was estimated by using Nanodots dosimeters (12) (International Specialty Products, Inc., Wayne, NJ, USA) which have optically stimulated luminescence (OSL) technology which is a single point radiation monitoring dosimeter. It is a useful tool in measuring the patient dose, and it is an ideal solution in multiple settings, including diagnostic radiology, nuclear medicine, interventional procedures and radiation oncology (12).

    Nanodots dosimeters also have minimal angular or energy dependencies with appropriate calibration which can be used to measure skin dose at a point of interest. Moreover, LANDAUER provides a set of calibration dosimeters exposed at a beam quality of 80 kVp on a PMMA phantom at normal incidence for conventional (non-mammography) diagnostic radiology applications (12). For radiation oncology applications, LANDAUER provides a set of screened, unexposed calibration dosimeters that can be irradiated using a radiation therapy beam quality. Another way for calibration is to request a dosimeter set exposed to a 662 keV beam quality (Cs-137) (12).

    The Nanodot dosimeters were placed on three different locations (Anterior-Posterior, Lateral (LAT) and Posterior-Anterior) as shown in figure 1, and the dose to the skin was measured at these locations.

    1

    2
    3

    CT TABLE

    Figure1. (a) a set-up used for the Peak Skin Dose measurements with placing the Nanodots on the three locations (Anterior, Posterior and lateral) with using the NEMA phantom. The cylindrical phantom was placed in the center of the CT scan. (b) The Peak Skin Dose measurements with using the ACR phantom which was placed in the center of the CT scan. Comment by ,Abdullatif abdullah: I will change this figure once I am back on campus. I will place both phantoms we used in the center of the scanner and upload the pictures here instead.

    Experimental set-up and procedure:

    The CTDIvol displayed by the scanner was validated to the true CTDIvol following the ACR testing guidelines (13). A correction factor was used to correct the inaccuracies in the displayed value. This correction was applied to the DLP displayed by the scanner.

    Peak skin dose and its relation were measured by the 2 phantoms, and the phantoms were aligned at the isocenter of the scanner and a single axial CT scan was made. After placing the Nanodot dosimeters on the AP, LAT and PA locations, the phantoms were scanned over the scan length for a fixed value of the tube current. The measurement was repeated several times using various scanning techniques (with varying energy, current) as shown in table 1. Size conversion factors used were based on the dimension of the phantom being scanned. These K-factors with the CTDIvol produced the size-specific dose estimates (SSDEs), and since the CT dose index was provided at the CT scanner too, the size-specific dose estimate for the phantoms was calculated. Also testing if the correlation between the size-specific dose estimate and the measurement of the peak skin dose match was done, and since such a relationship exists, finding that factor was achieved.

    RESULTS

    To determine the connection between the Peak Skin Dose and Size Specific Dose Estimates, a comparison was done using the NEMA phantom and ACR phantom with a peak skin dose measured using the Nanodots. After testing if the correlation between the size-specific dose estimate and the measurement of the peak skin dose, the SSDE was calculated using the corresponding k-factor based on the AP and lateral dimension from AAPM Report 204. The Size Specific Dose estimate values as shown in table 1, are based on the CTDIvol value which was displayed on the console. (effective diameter = ), the effective diameter represented the diameter of the phantom at a given location along the z-axis of the phantom (4). The anterior (AP) in the NEMA phantom was 22.37 cm whereas the lateral (LAT) in the same phantom was 29.27 cm. The effective diameter for the NAMA phantom was 26 cm.

    (SSDE = CTDIvol x K factor), this formula was used to solve for the Size Specific Dose Estimates. Report 204, has tables with different conversion factors based on the use of the NEMA phantom. Table 1D in the report, provided conversion factors as a function of the

    Tables 1 illustrates the difference kilovoltage peaks, milliampere-seconds, CTDIvol in mGy, the Peak Skin Dose of all the Nanodot dosimeters that were used in the specific locations and the measured size specific dose estimate.

    effective diameter. The data on the report are used when the CTDIvol is known. In this study, the conversion factor for 26 cm effective diameter NEMA phantom in all the projections besides head was 1.43. For head scans, different protocol was used which was similar to the protocol used with the ACR phantom. The effective diameter for the ACR phantom was 19 cm. The AAPM Report 204 stated that the conversion

    factor based on the use of the ACR phantom with 19 cm effective diameter was 0.90. The SSDE was calculated and measured in mGy as shown in table 1.

    Table 1 includes a comparison between the peak skin dose that was measured by the Nanodots in the three locations. The measured PSD values varied between

    0.13

    and

    70.77

    mGy. The highest PSD was measured using the ACR phantom with head projection at the anterior location and the lowest was Peak Skin Dose was measured at the anterior location of the NEMA phantom with abdomen projection.

    120

    120

    12.55

    100

    Thoracic

    100

    ABD

    120

    Pelvis

    120

    C-Spine

    100

    Head

    100

    NEMA Phantom

    Scans:

    kVp

    mAs

    CTDIvol

    (mGy)

    PSD in Dosimeter A, (mGy)

    PSD in Dosimeter Lat, (mGy)

    PSD in Dosimeter P, (mGy)

    SSDE (mGy)

    ABD

    120

    155

    8.76

    0.13

    0.19

    0.39

    12.53

    Head

    916

    158

    0.68

    1.09

    2.62

    142.2

    Thoracic

    100

    125

    5.56

    9.52

    9.64

    11.69

    7.95

    Pelvis

    113

    8.78

    9.88

    10.80

    12.55

    C-Spine

    535

    23.86

    27.33

    30.05

    32.27

    34.12

    ACR Phantom

    46

    2.06

    6.21

    5.

    50

    4.88

    1.85

    50

    3.81

    7.50

    5.97

    7.12

    3.43

    99

    3.77

    27.83

    6.17

    5.94

    3.39

    408

    18.23

    36.86

    27.16

    30.54

    16.41

    856

    87.69

    70.77

    62.76

    56.43

    78.92

    Figure 2: The graph illustrates the relationship between Peak Skin Dose in AP location and the Size Specific Dose Estimates in AP location in the NEMA phantom and the ACR phantom.

    Figure 2, illustrates the measured PSD in AP location against the SSDE in AP location with using 2 different phantoms (NEMA phantom and ACR phantom). For both phantoms, there was a linear relationship between the size specific dose estimates and the peak skin dose. In this study, the R-squared value was 0.75 which indicate that 75% of the variance of the dependent variable being studied is explained by the variance of the independent variable (14). Therefore, the relationship between the PSD in AP location and the SSDE in AP location has a positive correlation.

    Figure 3: The graph demonstrates the relationship between Peak Skin Dose in PA location and the Size Specific Dose Estimates in PA location in the NEMA phantom and the ACR phantom.

    The third figure demonstrates the measured PSD in PA location against the SSDE in PA location. For both phantoms, there was linear relationship between the size specific dose estimates and the peak skin dose. In this graph, the R-squared value was 0.85. Therefore, the relationship between the PSD in PA location and the SSDE has a positive relationship and high correlation.

    Figure 4: The graph illustrates the relationship between Peak Skin Dose in Lateral location and the Size Specific Dose Estimates in Lateral location in the NEMA phantom and the ACR phantom.

    Figure 4, illustrates the measured PSD in the lateral location against the SSDE in Lateral location. For both phantoms, there was linear relationship between the

    size specific dose estimates and the peak skin dose. In this graph the R-squared value was 0.78 which indicated that there was a positive linear relationship between the PSD in lateral location and the SSDE in lateral location.

    In all the plots, linear relationship between the PSD and SSDE was found, and the linear fitting equation was calculated. Peak Skin Dose can be predicted in the anterior location with knowing the CTDIvol which is shown on the console. (SSDE = 0.8373 x (PSD) – 2.3412), this was the fitting equation for the AP location graph (1st graph).

    (SSDE = 0.6833 x (PSD) + 4.9856), this was the linear fitting equation for the posterior location graph (2nd graph) which indicates that PSD can be measured with knowing the SSDE value.

    (SSDE = 0.9384 x (PSD) – 3.084), this was the linear fitting equation for the lateral location graph (3rd graph).

    The three equations have a high positive relationship, so predicting the value of SSDE or PSD will be possible but not 100% accurate. With using these data and fitting equations, a physicist can estimate the PSD, but with some limitations.

    The physicist would be within 80% the true dose estimates and a large error would be there as well. The regression was almost 80% in the three locations, so roughly 80% of the data points will fall close to the linear line.

    DISCUSSION

    The regression of the Peak Skin Dose was different in the AP and LAT locations comparison with the lateral location which is because the thickness of the phantom. Considering that examination is performed in the lateral location of the body which has the highest x-ray attenuation, thus requiring higher beam energy to penetrate. With increasing the patient average diameter, the peak skin dose was higher. According to the data that was measured, the measured PSD was higher in all the lateral location than the AP and PA locations. The bigger the phantom (more tissue to penetrate), the more dose was required to attenuate and reached the dosimeter.

    In the is study the AP, PA and lateral dimensions of the phantom were used to measure the SSDE which is a factor that is used to estimate the absorbed dose. This could’ve been an error in measuring the peak skin dose since the SSDE was not measured at that time. Also, there was a linear relationship between the PSD and the SSDE because the Size Specific Dose Estimates dictate the patient’s dose and this could be one of the reasons that the linear relationship occurred. Also, there could be better modifications to the K-factors in order to dictate the patient’s more accurately.

    When calculating how much radiation dose a patient is actually receiving, it’s best to consider their actual size. CTDIvol and DLP are common methods to estimate a patient’s radiation dose from a CT procedure. The dose is the same regardless of patient size, but the size of the patients is a factor in the overall patient’s absorbed dose. Therefore, SSDE measured in mGy, would allow the physicists to use the patient’s size as a factor in order to estimate the radiation dose. In the other hand the PSD is the maximum absorbed dose in mGy to the most heavily exposed region of the skin in specific location. In this study, the measured values of the PSD and SSDE had a linear relationship in most projections (C-spine, thoracic and pelvis). The higher the PSD was, the higher the SSDE which was due to the measured CTDIvol which displayed in the console (the higher the CTDIvol was, the higher SSDE was calculated).

    There is a difference between the CTDIvol that was shown on the console and the actual CTDIvol. The CTDIvol or its derivative the DLP, as seen on consoles and outputted, do not represent the actual absorbed or effective dose for the patient. They should be taken as an index of radiation output by the system for comparison purposes. In this study, it is not possible to compare the true CTDIvol to the displayed because the phantoms that were used were not CTDI phantoms, so it is not possible to place a CTDI probe.

    However, nowadays many modifications to original CTDI concept have attempted to make it more accurate patient dosimetry method, with mixed results. Body CTDIvol reported by the CT scanner, or measured on a CT scanner, is a dose index that results from air kerma measurements at two locations, to a very cylinder of plastic phantom with a density of 1.19 g/cm3 (15).

    CTDIvol is primary affected by kVp and mAs, so parameters which were used in most of the previous researches such as (Auto-kVp and dose reduction initiative parameters) were not used in this research because in a normal system as the tube rotate around the phantom, the thickness of the phantom varies, LAT location usually requires more dose so more kVp and mAs than AP location, so the kVp and mAs values will fluctuate which will lead to change the CTDIvol as well. Therefore, fixed kVp and mAs values were used in order to have a continuous CTDIvol for the entire process, and for a different phantom a different parameter was used in different exam so an abdomen phantom had different parameter than the one for the cervical spine.

    According to the measured data, some scan projections such as abdomen had high PSD and high SSDE due to the high measured CTDIvol and DLP caused out wire and low regression. Taking out the abdomen PSD and SSDE from the graphs make the regression higher (more positive) which means correlation could exist. Therefore, some projections such as an abdomen and head might make the data points and graphs not clear and hard to be read.

    When graphing the measured PSD and SSDE in each phantom separately, a higher regression (more positive correlation) was found (close to 90%) in all the three locations. This means that the closer the patient to become cylindrical, the better relationship between PSD and SSDE will be and more accurate doses will be measured. It fails at very large effective circumferences with perfectly cylindrical patients.

    In this study, only two phantoms were used (NEMA and ACR phantoms) with specific thicknesses, so other phantoms such as anthropomorphic phantoms and fake human phantoms with different thickness styles could be used to get better data and correlation.

    In this study, only 9 measurements were taken in the three different location due to the limitation of the Nanodots. More measurements could have been taken and a better data points would have been measured. With more data testing that the SSDE has a sufficiently strong linear relationship with PSD could be proven.

    CONCLUSION

    In this study a measured value of the dose was delivered to two different phantoms (NEMA and ACR phantoms) during a CT examination. The Peak Skin Dose values were calibrated and reported by LANDAUER labs. The Size Specific Dose estimates was calculated using the CTDIvol that was shown in the console and the corresponding k-factor based on the AP and lateral dimension from AAPM Report 204. The results showed there was a positive linear relationship in AP, PA and lateral locations, and there was a sufficiently strong linear relationship between the PSD and SSDE. The higher the PSD was, the higher the SSDE was in almost all the projections. The measured PSD and SSDE showed that a physicist can estimate the PSD within 80% the true dose estimates with a small error. The R-squared value was around 0.80 in all the locations which indicated that there was a positive linear relationship.

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    Jones, A. K., Kisiel, M. E., Rong, X. J., & Tam, A. L. (2021). Validation of a method for estimating peak skin dose from CT‐guided procedures. Journal of applied clinical medical physics.

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    Tack, D., & Gevenois, P. A. (2018). Radiation dose from adult and pediatric Multidetector computed tomography. Springer Science & Business Media.

    McCollough, C. H., Leng, S., Yu, L., Cody, D. D., Boone, J. M. and McNitt-Gray, M. F. CT dose index and patient dose: they are not the same thing. Radiology 259(2), 311 – 316 (2011).

    Bauhs, J. A., Vrieze, T. J., Primak, A. N., Bruesewitz, M. R. and McCollough, C. H. CT dosimetry: Comparison of measurement techniques and devices. Radiographics 28, 245 – 253 (2008).

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    Beganovic, A., Sefic-Pasic, I., Skopljak-Beganovic, A., Kristic, S., Sunjic, S., Mekic, A., Gazdic-Santic, M., Drljevic, A. and Samek, D. Doses to skin during dynamic perfusion computed tomography of the liver. Radiat. Prot. Dosim. 153(1), 106–111 (2013).

    NanoDot™. LANDAUER. (n.d.). Retrieved November 19, 2021, from https://www.landauer.com/product/nanodot.

    ACR–sar–SPR practice parameter for the performance of … (n.d.). Retrieved November 19, 2021, from https://www.acr.org/-/media/ACR/Files/Practice-Parameters/CT-Entero .

    Frost, J. (2021). How To Interpret R-squared in Regression Analysis. Retrieved 1 December 2021, from

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    Morgan, M. (2021). Size specific dose estimate | Radiology Reference Article | Radiopaedia.org. Retrieved 1 December 2021, from

    https://radiopaedia.org/articles/size-specific-dose-estimate?lang=us

    McCollough, C., Leng, S., Yu, L., Cody, D., Boone, J., & McNitt-Gray, M. (2011). CT Dose Index and Patient Dose: They AreNotthe Same Thing. Radiology, 259(2), 311-316. doi: 10.1148/radiol.11101800

    NEMA phantom 12.53 7.95 12.55 34.119999999999997 1.85 3.43 3.39 16.41 78.92 0.39 11.69 12.55 32.270000000000003 4.88 7.12 5.94 30.54 56.43 ACR phantom 1.85 3.43 3.39 16.41 78.92 4.88 7.12 5.94 30.54 56.43

    Peak Skin Dose (mGy)

    Size Specific Dose Estimates (mGy)

    NEMA phantom 12.53 7.95 12.55 34.119999999999997 1.85 3.43 3.39 16.41 78.92 0.13 9.52 9.8800000000000008 27.33 ACR phantom 12.53 7.95 12.55 34.119999999999997 1.85 3.43 3.39 16.41 78.92 6.21 7.5 27.83 36.86 70.77

    Peak Skin Dose (mGy)

    Size Specific Dose Estimates (mGy)

    NEMA phantom 12.53 7.95 12.55 34.119999999999997 1.85 3.43 3.39 16.41 78.92 0.19 9.64 10.8 30.05 ACR phantpm 12.53 7.95 12.55 34.119999999999997 1.85 3.43 3.39 16.41 78.92 5.5 5.97 6.17 27.16 62.76

    Peak Skin Dose (mGy)

    Size Specific Dose Estimates (mGy)

    Thesis / Doctoral Project / Dissertation Proposal

    Student Information:

    Student GUID Number:

    8

    3

    3

    1

    68318

    Student Name: (As it appears on your transcript)

    Abdullatif Abdullah

    Address:

    1850 Columbia Pike Apt 406, Arlington, Virginia,

    2

    2204

    E-Mail Address:

    aa2388@georgetown.edu

    Phone Number:

    571-340-6065

    Degree:

    Masters in

    Health Physics

    Expected Graduation Month/Year

    05 / 2022

    Dept./Major:

    Health Physics

    I. Title:

    Estimation of Peak Skin Dose and Its Relation to the Size Specific Dose Estimate

    II. Problem or Hypothesis:

    The CT Dose Index (CTDIvol) was originally designed as an index of dose associated with various CT diagnostic procedures not as a direct dosimetry method for individual patient dose assessments. There is no current method for calculating peak skin dose (PSD) using the key metrics provided from the radiation dose structure report of a CT scanner. Every CT study is required to output the kVp and mAs that were used, the dose length product and CT dose index volume which will all be shown on the CT console, but there is no direct method to go straight to the PSD. This project will test the hypothesis that the SSDE has a sufficiently strong linear relationship with PSD to allow direct calculation of the PSD directly from the SSDE.

    III. Review of Related Literature:

    The highest radiation dose accruing at a single site on a patient’s skin is referred to as the peak skin dose (PSD) which is related to the Computed Tomography dose index (CTDIvol) that is displayed on the console of CT scanners. However, the CT Dose Index was originally designed as an index not as a direct dosimetry method for patient dose assessment. More recently, modifications to original CTDI concept have attempted to convert it into to patient dosimetry method, but have with mixed results in terms of accuracy. Nonetheless, CTDI-based dosimetry is the current worldwide standard for estimation of patient dose in CT. Therefore, CTDIvol is often used to enable medical physicists to compare the dose output between different CT scanners.

    Fearon, Thomas (2011) explained that current estimation of radiation dose from CT scans on patients has relied on the measurement of Computed Tomography Dose Index (CTDI) in standard cylindrical phantoms, and calculations based on mathematical representations of “standard man.” The purpose of this study was to investigate the feasibility of adapting a radiation treatment planning system (RTPS) to provide patient-specific CT dosimetry. A radiation treatment planning system was modified to calculate patient-specific CT dose distributions, which can be represented by dose at specific points within an organ of interest, as well as organ dose-volume (after image segmentation) for a GE Light Speed Ultra Plus CT scanner. Digital representations of the phantoms (virtual phantom) were acquired with the GE CT scanner in axial mode. Thermoluminescent dosimeter (TLDs) measurements in pediatric anthropomorphic phantoms were utilized to validate the dose at specific points within organs of interest relative to RTPS calculations and Monte Carlo simulations of the same virtual phantoms. Congruence of the calculated and measured point doses for the same physical anthropomorphic phantom geometry was used to verify the feasibility of the method. The advantage of the RTPS is the significant reduction in computation time, yielding dose estimates within 10%–20% of measured values.

    De las Heras (2013) elaborated on the concept of CT scanners and their critical implementation in diagnostic imaging. His method was based on estimating the peak skin dose delivered by CT scanners by measuring the PSD values related to the volume CT dose index (CTDIvol), a parameter that is displayed on the console of modern CT scanners. He obtained the PSD measurement estimates in CT units by placing radio-chromic film on the surface of a CTDI head phantom, and different x-ray tube currents were then used to irradiate the phantom. The PSD and the CTDIvol were independently measured and later related to the CTDIvol value that was displayed on the console. They found that there was a relationship between the measured PSD and the associated CTDIvol displayed on the console, and the measured PSD values varied among all scanners when the routine head scan parameters were used. This work showed the widely used CTDIvol could be used to accurately estimate an actual radiation dose delivered to the skin of a patient. Also, the method and the analysis provided valuable information to patients, radiological technologists, medical physicists, and physicians to relate the displayed CTDIvol to an actual measured dose delivered to the skin of a patient.

    Jones, A. Kyle (2021) recently developed a new method to estimate the peak skin dose from CTDIvol. The objective of this study was to validate the methodology during CT-guided ablation procedures. Radio-chromic film was calibrated and used to measure PSD as well. Real patients, rather than phantoms, were used in the study. CTDIvol stratified by axial and helical scanning was used to calculate an estimate of PSD, and both calculated PSD and total CTDIvol were compared to measured PSD. The calculated PSD were significantly different from the measured PSD, but the measured PSD were not significantly different from total CTDIvol which prove that the CTDI can help in measuring the patient dose. Considering that CTDIvol was reported on the console of all CT scanners, is not stratified by axial and helical scanning modes, and is immediately available to the operator during CT-guided interventional procedures.

    Each of the methodologies mentioned above represents a reasonably accurate approach for computing the patient dose from CT procedures. Reassuringly, estimation of the dose to either phantoms or actual patients yielded comparable doses. However, all the methodologies used to obtaine the PSD measurement were based on the same experimental approach. They estimated in CT units by placing a radio-chromic film on the surface of a CTDI phantom. This research project will use a completely different approach — it will make patient dose estimates by means of Nanodots dosimeters. Nanodots have optically stimulated luminescence (OSL) technology which is a single point radiation monitoring dosimeter. It is a useful tool in measuring the patient dose, and it is an ideal solution in multiple settings, including diagnostic radiology, nuclear medicine, interventional procedures and radiation oncology. These dosimeters have the technical advantage that they can be placed anywhere on the body or phantom and the nondestructive readout supports reanalysis and electronic data archiving.

    IV. Procedure or Method:

    The CTDIvol displayed by the scanner will be validated to the true CTDIvol following the ACR testing guidelines. A correction factor will be used to correct any inaccuracies in the displayed value. This correction will also be applied to the DLP displayed by the scanner.

    Peak skin dose and its relation will be measured by various phantoms such as NEMA phantoms, 16 cm CTDI and 32 cm CTDI phantoms. The phantoms will be aligned at the isocenter of the scanner with the chamber in the center hole of the phantom. The longitudinal axis of the chamber and cylindrical phantom will be aligned parallel to the longitudinal axis of the CT gantry. With using those different phantoms, the dosimeter will be placed serially in center hole ad peripheral hole. Those measurements are combined to produce the weighted CTDI, so a 100-mm-long cylindrical (pencil) chamber, approximately 9 mm in diameter, inserted into either the center or a peripheral hole of a phantom as shown in figure 1, and with the pencil chamber located at the center (in the z-dimension) of the phantom and also at the center of the CT gantry, a single axial CT scan is made. An ionization chamber can only produce an accurate dose estimate if its entire sensitive volume is irradiated by the x-ray beam. Therefore, for the partially irradiated 100-mm CT pencil chamber, the nominal beam width which is the total collimated x-ray beam width as indicated on the CT console, is used to correct the chamber reading for the partial volume exposure. The 100-mm chamber length is useful for x-ray beams of thin slices such as 5 mm to thicker beam collimations such as 40 mm. The correction for partial volume is essential and is calculated using the correction for partial volume is essential and is calculated using which B can be either the total collimated beam width, in mm, for a single axial scan or the width of an individual CT detector (T) number of active detectors (n)

    Then the CTDI will be calculated as CTDI100 = (1/3) x CTDIcenter + (2/3) x CTDIperiphery. Combining the center and peripheral measurements using a 1/3 and 2/3 weighting scheme provides a good estimate of the average dose to the phantom at the central CT slice along z, giving rise to the weighted CTDI, CTDIw. The CTDI100, which is the amount of radiation delivered to one slice of the body over a long CT scan and it is also known as CTDI weighted. The scanner scans the entire volume in a helical trajectory. Thus, there isn’t really a true ‘slice’, as the z-position of the scanner is different at each angle. Also, the spacing between successive revolutions of the CT tube represents the pitch of the scan. In fact, the wider the helix, the less dose the patient will receive because the same portion of tissue is being irradiated at fewer angles, so the larger the pitch the lower the dose. Therefore, CTDIvol represent the dose for a specific scan protocol which considers gaps and overlaps between the radiation dose profile from consecutive rotations of the x-ray source and it can be calculated; CTDIvol = (1/pitch) x CTDIw. The CTDIw represents the average radiation dose over the x and y direction whereas CTDIvol represents the average radiation dose over the x, y and z directions.

    Nanodot dosimeters will be placed on the LAT and AP locations as shown in figure 2, the dose to the skin will be measured at these locations. Then, the phantoms will be scanned over the scan length for a fixed value of the tube current. The measurement will be repeated several times using various scanning techniques (with varying energy, current). Size conversion factors used will be based on the dimension of the phantom being scanned used. These K-factors with the CTDIvol can produce size specific dose estimates (SSDEs), and since the CT dose index will be provided at the CT scanner too, the size specific dose estimate for the phantoms will be calculated. Also testing if the correlation between the size specific dose estimate and the measurement of the peak skin dose match will be done, and if such a relationship exists, trying to find that factor will be the aim.

    Finally, in null hypothesis significance testing, the p-value is the probability of obtaining test results at least as extreme as the results observed under the assumption that the null hypothesis is correct. Since reporting the p-values of statistical tests is common practice in academic publication of many quantitative fields, then calculating the p-value will be done and looking for very small p-value will be the hope. Because small p-value (p-value <0.05) means that such an extreme observed outcome would be very unlikely under the null hypothesis and regression analyses and correlation coefficients are statically significant.

    Phantom

    Phantom

    Figure1: a 100-mm-long cylindrical (pencil) chamber, approximately 9 mm in diameter, inserted into either the center or a peripheral hole of a phantom.

    1

    CT TABLE

    3
    2

    Figure2: a phantom in the middle of the CT scan and 1 is the AP location, 2 is the LAT location and 3 is the PA location.

    V. Selected Bibliography:

    Andersson, J., Bednarek, D. R., Bolch, W., Boltz, T., Bosmans, H., Gislason-Lee, A. J., … & Zamora, D. (2021). Estimation of patient skin dose in fluoroscopy: summary of a joint report by AAPM TG357 and EFOMP. Medical physics (Lancaster).

    da Silva, E. H., Baffa, O., Elias, J., & Buls, N. (2021). Conversion factor for size specific dose estimation of head CT scans based on age, for individuals from 0 up to 18 years old. Physics in Medicine & Biology, 66(8), 085011.

    Fleury, A. S., Durand, R. E., Cahill, A. M., Zhu, X., Meyers, K. E., & Otero, H. J. (2021). Validation of computed tomography angiography as a complementary test in the assessment of renal artery stenosis: a comparison with digital subtraction angiography. Pediatric Radiology, 1-14.

    Greffier, J., Hamard, A., Berny, L., Snene, F., Perolat, R., Larbi, A., … & Beregi, J. P. (2021). A retrospective comparison of organ dose and effective dose in percutaneous vertebroplasty performed under CT guidance or using a fixed C-arm with a flat-panel detector. Physica Medica, 88, 235-241.

    Jauhari, A., Anam, C., Ali, M. H., Rae, W. I. D., Akbari, S., & Meilinda, T. (2021). The effect on CT size-specific dose estimates of mis-positioning patientsfrom the iso-centre. European Journal of Molecular & Clinical Medicine, 8(3), 155-164.

    Jones, A. K., Kisiel, M. E., Rong, X. J., & Tam, A. L. (2021). Validation of a method for estimating peak skin dose from CT‐guided procedures. Journal of applied clinical medical physics.

    Loose, R. W., Vano, E., Mildenberger, P., Tsapaki, V., Caramella, D., Sjöberg, J., … & Damilakis, J. (2021). Radiation dose management systems—requirements and recommendations for users from the ESR EuroSafe Imaging initiative. European Radiology, 31(4), 2106-2114.

    Mohamed, A. I. A. (2021). Estimation of Effective Dose for Pediatric Patients During Computed Tomography Examinations (Doctoral dissertation, Sudan University of Science and Technology).

    Okamoto, H., Kito, S., Tohyama, N., Yonai, S., Kawamorita, R., Nakamura, M., … & Shioyama, Y. (2021). Radiation protection in radiological imaging: a survey of imaging modalities used in Japanese institutions for verifying applicator placements in high-dose-rate brachytherapy. Journal of Radiation Research, 62(1), 58-66.

    Saeed, M. K. (2021). Comparison of estimated and calculated fetal radiation dose for a pregnant woman who underwent computed tomography and conventional X-ray examinations based on a phantom study. Radiological Physics and Technology, 14(1), 25-33.

    Steuwe, A., Weber, M., Bethge, O. T., Rademacher, C., Boschheidgen, M., Sawicki, L. M., … & Aissa, J. (2021). Influence of a novel deep-learning based reconstruction software on the objective and subjective image quality in low-dose abdominal computed tomography. The British Journal of Radiology, 94(1117), 20200677.

    Sundell, V. M., Kortesniemi, M., Siiskonen, T., Kosunen, A., Rosendahl, S., & Büermann, L. (2021). Patient-Specific Dose Estimates In Dynamic Computed Tomography Myocardial Perfusion Examination. Radiation Protection Dosimetry, 193(1), 24-36.

    Tabari, A., Li, X., Yang, K., Liu, B., Gee, M. S., & Westra, S. J. (2021). Patient-level dose monitoring in computed tomography: tracking cumulative dose from multiple multi-sequence exams with tube current modulation in children. Pediatric Radiology, 1-9.

    Thierry-Chef, I., Ferro, G., Le Cornet, L., Dabin, J., Istad, T. S., Jahnen, A., … & Simon, S. L. (2021). Dose estimation for the european epidemiological study on pediatric computed tomography (EPI-CT). Radiation Research, 196(1), 74-99.

    De las Heras, H., Minniti, R., Wilson, S., Mitchell, C., Skopec, M., Brunner, C. C., & Chakrabarti, K. (2013). Experimental estimates of peak skin dose and its relationship to the CT dose index using the CTDI head phantom. Radiation protection dosimetry, 157(4), 536-542.

    V. Use of Human Subjects:

    Does your research involve the use of human subjects? No

    Yes |_|

    No

    If yes, you must obtain approval from the appropriate University Institutional Review Board before your proposal can be submitted to the Graduate School. Submit a copy of the IRB Approval Memo for your research along with this form.

    IRB Number:

         

    VII. Student Signature:

    Abdullatif Abdullah October, 29th 2021

    Signature Date

    VIII. Faculty Approvals:

    Committee Member

    Committee Member

    COMMITTEE ROLE:

    MEMBER NAME: (typed)

    SIGNATURE:

    DATE:

    Thesis Advisor

    Matthew Williams

    11/5/2021

    Committee Member

    Stanley Thomas Fricke

    11/14/2021

    Committee Member

    Director

    of Graduate Studies

    Completed form should be returned to:

    BGE students should return the form to:

    Graduate School of Arts & Sciences

    Biomedical Graduate Education Office

    Car Barn 207, 3520 Prospect Street, NW
    gradstudentservices@georgetown.edu

    SE109 Medical Dental Building
    bgestudentservices@georgetown.edu

    5

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