ORGAN DOSES FOR PATIENTS UNDERGOING COMPUTED TOMOGRAPHY EXAMINATIONS: VALIDATION OF MONTE CARLO CALCULATIONS USING ANTHROPOMORPHIC PHANTOMS

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1 ORGAN DOSES FOR PATIENTS UNDERGOING COMPUTED TOMOGRAPHY EXAMINATIONS: VALIDATION OF MONTE CARLO CALCULATIONS USING ANTHROPOMORPHIC PHANTOMS By DANIEL J. LONG A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE UNIVERSITY OF FLORIDA

2 2011 Daniel J. Long 2

3 To my beautiful wife, whose unending love makes every day a blessing To my parents, who taught me the importance of integrity and hard work To my friends and family, who have all helped bring me to where I am today 3

4 ACKNOWLEDGMENTS I thank Dr. Wesley Bolch for his guidance and for giving me the opportunity to pursue research about which I am passionate. I thank Dr. Choonsik Lee for his tremendous technical support and encouragement over the course of this project. I thank Dr. David Hintenlang and Dr. Manuel Arreola for the use of their equipment, their knowledge, and their input. I thank my wife, Nelia, my family, and my friends for all their love and encouragement. 4

5 TABLE OF CONTENTS page ACKNOWLEDGMENTS... 4 LIST OF TABLES... 6 LIST OF FIGURES... 7 LIST OF ABBREVIATIONS... 8 ABSTRACT... 9 CHAPTER 1 INTRODUCTION MATERIALS AND METHODS Computed Tomography (CT) Scanner Description Modeling of the CT Scanner X-ray Source Anthropomorphic Phantom Dose Measurements Computational Phantom Dose Measurements RESULTS AND DISCUSSION CONCLUSION LIST OF REFERENCES BIOGRAPHICAL SKETCH

6 LIST OF TABLES Table page 2-1 Summary of scan parameters used for each computed tomography (CT) protocol Measured and simulated organ dose results for the adult male phantom Measured and simulated organ dose results for the 9-month-old phantom Percent difference summary for all CT exam dose results

7 LIST OF FIGURES Figure page 2-1 Frontal view of the 9-month-old anthropomorphic phantom Axial cutaway of the 9-month-old anthropomorphic phantom with a fiber-optic coupled (FOC) dosimeter placed at a dose point in the lung Frontal view of the adult male anthropomorphic phantom Axial cutaway of the adult male anthropomorphic phantom with a fiber-optic coupled (FOC) dosimeter placed at a dose point in the right kidney

8 LIST OF ABBREVIATIONS CT ICRU MCNPX UF computed tomography International Commission on Radiation Units and Measurements Monte Carlo n-particle extended University of Florida 8

9 Abstract of Thesis Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science ORGAN DOSES FOR PATIENTS UNDERGOING COMPUTED TOMOGRAPHY EXAMINATIONS: VALIDATION OF MONTE CARLO CALCULATIONS USING ANTHROPOMORPHIC PHANTOMS Chair: Wesley Bolch Major: Biomedical Engineering By Daniel J. Long August 2011 The annual use of computed tomography (CT) examinations for medical diagnosis has increased twentyfold from 1980 to 2007; primarily due to the increasing diagnostic capabilities of the technology. However, CT scans deliver much greater radiation doses to patients as compared to other modalities, leading to concerns in the radiation protection and medical communities about increased radiation-induced cancer risks in the patient population, especially pediatric patients undergoing multiple exams. In order to better quantify these risks, radiation doses must be accurately calculated for these patients. One versatile and reliable method with which to perform these calculations is the Monte Carlo method. In this technique, the patient and CT scanner are simulated on the computer, and radiation transport calculations are performed to assess radiation doses. However, in order to ensure the accuracy of calculations, the Monte Carlo simulations must be benchmarked against physical measurements made on the actual CT scanners that the models represent. The purpose of this study was to validate the accuracy of a Monte Carlo model of a Siemens SOMATOM Sensation 16 CT scanner using radiation 9

10 dose measurements on anthropomorphic phantoms, which are physical representations of patients. The study consisted of taking radiation dose measurements on an adult male phantom and a 9-month-old male phantom during multiple types of CT scans, and replicating the same scans using the Monte Carlo method. The study found that for all CT scans for both phantoms, the results suggested excellent agreement between measured and simulated organ doses. For the adult male, the percent differences between simulated and measured organ doses for all scans were all within 15.5%. For the 9-month-old, the percent differences were all within 13.9%. These percent difference results were comparable to previous validation studies using anthropomorphic phantoms. Overall, the study validated the accuracy of the Monte Carlo model in accurately calculating radiation doses to patients. 10

11 CHAPTER 1 INTRODUCTION From 1982 to 2006, the average per capita annual background effective dose from all radiation sources in the United States rose from 3.6 to 6.2 msv. 1 This rise can mainly be attributed to the increased contribution of medical exposures, which rose from 15% of the total dose in 1982 to 48% in Additionally, computed tomography (CT) examinations accounted for 47% of the total annual medical exposures in The growing diagnostic capabilities of CT have led to the annual number of exams to increase from 3.6 million in 1980 to 72 million in This twentyfold increase in exams is of concern to the radiation protection and medical profession communities, due to the potential increase in cancer risks associated with the increased use of CT scans. 2-3 Therefore, the ability to accurately calculate patient radiation doses from CT exposures has become a pressing but challenging issue; especially when wanting to correctly assess patient-specific organ doses for retrospective epidemiological or prospective cancer risk estimation studies. Additionally, any future patient dose tracking efforts will require reliable dose estimates for a variety of CT examinations. Although there are a variety of methods by which to calculate patient organ doses from computed tomography examinations, Monte Carlo simulations have been reported to be the most accurate, reliable, and versatile in accomplishing this task In the Monte Carlo method, the patient and CT scanner are fully simulated on the computer using a computational phantom, an digital anatomic model of a patient, and an x-ray source term representing the scanner s beam output. However, to ensure accuracy of these calculations, these CT source terms must be benchmarked and validated against actual experimental measurements made on the scanners they 11

12 simulate. In the past, most validation studies were accomplished using standard CT dose index (CTDI) phantoms, but in more recent years, anthropomorphic phantoms have begun to be used. 10,11,21 Anthropomorphic phantoms, physical representations of patients, allow for more rigorous validation, as they include more complex and anatomically-realistic geometry and material heterogeneity as compared to standard CTDI phantoms. In previous work by Lee et al., a Monte Carlo CT source term had been validated against standard CTDI measurements. 22 The goal of this study was to further validate the same source term using organ dose measurements made on two different anthropomorphic phantoms for multiple axial and helical CT scanning protocols. 12

13 CHAPTER 2 MATERIALS AND METHODS Computed Tomography (CT) Scanner Description A SOMATOM Sensation 16 multi-detector CT scanner (Siemens Medical Solutions, Erlangen, Germany) was used as the basis for the Monte Carlo source term as well as used for all physical dose measurements. The scanner contained 16 rows of detectors that allowed beam collimations from mm, had the ability to scan in both axial and variable-pitch helical modes, and featured two settings of inherent filtration for head and body scanning along with a single bowtie beam-shaping filter. The fan beam angle was 52, with a focal-spot-to-isocenter distance of 57 cm. The operator could select tube potentials of 80, 100, 120, or 140 kvp along with varying tube current and gantry rotation speeds. The scanner also allowed for use of tube-current modulation during scanning, but this feature was not used for the measurements in this study. Modeling of the CT Scanner X-ray Source The source term of the scanner was created as a custom source file within a general-purpose Monte Carlo radiation transport code, MCNPX Material and thickness of the two inherent filters for head and body scanning was obtained from the manufacturer. This information, in conjunction with a commercial spectrum generation program, SPEC78 (Institute of Physics and Engineering in Medicine), was used to create x- ray spectra for the head and body filters for all beam energies. 24 These spectra were incorporated into the MCNPX source term through an input deck for energy sampling. To account for the effects of the bowtie filter on the shape of the fan beam for all beam energy/filter combinations, angular-dependent weighting factors were applied in the source term based on free-in-air lateral dose profile measurements made previously by 13

14 a pencil ion chamber while the x-ray tube was fixed at the 12 o clock position in service mode. 22 The effects of overbeaming on the true beam thicknesses for various collimation settings were previously quantified in studies using radiographic film, and were thus taken into account within the source term. 19 The custom source term allowed the user to simulate both axial exams and helical exams with varying pitch. For helical exams, this was accomplished by having the source first sample the location of the x-ray focal spot along a mathematically-described helix based on the pitch and scan length selected by the user as well as the previouslydefined focal-spot-to-isocenter distance of 57 cm. For axial exams, the focal spot location would be sampled along a series of circular rings of radius 57 cm spanning the total specified length of the scan that were spaced apart by the distance of the beam collimation selected. After selecting this starting location of the x-ray focal spot, the source sampled an angle within the 52 fan beam as well as within the beam collimation thickness, therefore selecting a directional path upon which the photon would initially travel. Finally, the photon energy was sampled based on the energy spectrum selected for the exam. This process would be repeated for the total number of particles to be transported as selected by the user. The final version of the source term allowed the user to select beam energy, head or body filtration, beam collimation, an axial or a helical exam with associated pitch, and starting angle of the beam for helical exams. Anthropomorphic Phantom Dose Measurements In order to validate the use of this Monte Carlo source in calculating patient organ doses, measurements were taken using two anthropomorphic phantoms, a pediatric nine-month-old phantom and an adult male phantom, shown in Figs. 2-1 and

15 Both phantoms were constructed at the University of Florida, and were each built as a set of individual 5mm axial slices. These axial slices were constructed from molds fabricated from simulated cross-sectional images of two computational phantoms using a computerized milling machine. 25 The adult male phantom was built as a replica of the UF adult male reference hybrid phantom, and the 9-month-old phantom was built as a replica of the UF series B 9-month-old voxel phantom 26,16 Both phantoms are made up of three types of materials developed at the University of Florida: soft tissue-equivalent, lung tissue-equivalent, and bone tissue-equivalent. Each of these materials closely match the reference densities and x-ray attenuation coefficients in the diagnostic energy range for their respective representative body tissues, as given by the International Commission on Radiation Units and Measurements (ICRU) in its Publication In lieu of molding organs individually, organ contours were instead traced on the large areas of soft tissue material at their correct axial slice locations. All dose measurements were done using a fiber-optic coupled (FOC) plastic scintillator dosimetry system developed at the University of Florida. 27 The dosimeters were placed along pre-cut channels in order to measure point doses within the phantom during CT examinations. Views of the dosimeters within these channels in both phantoms can be seen in Figs. 2-2 and 2-4. Each channel location corresponded to a measurement point within an organ. The point doses measured from these dosimeters were then averaged to estimate the average organ doses delivered to the phantom. Depending on the organ size, organs had anywhere from one to several points that were used to calculate the average organ dose. 15

16 The adult male anthropomorphic phantom was used to take organ dose measurements for six different CT scan protocols: three axial (head, chest, and abdomen/pelvis) and three helical (chest, abdomen, and pelvis. The number of organ doses measured for each scan ranged from four to eight. The pediatric phantom was used for measurements for two full-body scans, one axial and one helical, each with 13 organ doses measured. For each scan, the phantom was centered with respect to the central point of the bore s circular opening. A summary of scan parameters for each CT scan can be found in Table 2-1. Computational Phantom Dose Measurements Organ dose calculations using the Monte Carlo CT source term were performed using the UF reference adult male hybrid phantom and the UF series B 9-month-old voxel phantom. Since the anthropomorphic phantoms were built based on these two computational phantoms, the physical CT scans could be replicated such that the simulated scans would exactly match the physical scan setups. To do this, the arms of the computational phantoms were first removed to reflect the lack of arms on the physical phantoms when performing CT measurements. The phantoms were then voxelized to resolutions of 2 x 2 x 2 mm 3 for the adult male and 0.86 x 0.86 x 3 mm 3 for the 9-month-old for input into MCNPX for dose calculations. Within the Monte Carlo simulation setups, the voxelized phantoms were placed upon a model of the scanner s carbon-fiber patient table. The table was modeled as two concentric cylinders of different radii that were truncated to a width of 40 cm corresponding to the width of the patient table, with carbon fiber as its material composition. The source term was then set up to reflect the parameters of each physical scan. For all helical scans, the beam starting angle was assumed to be 0. Organ doses were then calculated using the F6 16

17 KERMA approximation tally in MCNPX; therefore, no secondary electrons were transported in the calculation. Considering the energy range of the CT x-ray spectra and the subsequent ranges of secondary electrons in tissue, the KERMA approximation offers an acceptably accurate approximation of average organ dose. For all computational calculations, 100 million particles were transported. Since MCNPX provides calculation results in dose per simulated photon, the number of photons delivered by the scanner per unit mas, called the Monte Carlo normalization factor, were multiplied to the MCNPX dose results to obtain organ doses in absolute units. The normalization factors were calculated based on the ratio of pencil ion chamber measurements in free-in-air (mgy/mas) to MCNPX-simulated free-in-air ion chamber doses (mgy/photon) made in previous studies. 22 Each unique beam energy, filter, and collimation combination required its own normalization factor. Absolute organ doses for each individual scan could then be calculated by multiplying the dose in mgy/mas by the total mas delivered during the exam. 17

18 Table 2-1. Summary of scan parameters used for each computed tomography (CT) protocol Scan Anatomical Extent Beam Energy (kvp) Filter Beam Collimation (mm) Effective mas Pitch Adult Male Axial Head Top of head to 2nd cervical vertebra 120 Head Axial Chest Clavicles to dome of diaphragm 120 Body Axial Abdomen/Pelvis Dome of diaphragm to femoral heads 120 Body Helical Chest Clavicles to tops of kidneys 120 Body Helical Abdomen Dome of diaphragm to iliac crests 120 Body Helical Pelvis Iliac crest to lesser trochanters 120 Body Month-Old Axial Full-Body Top of head to mid-thigh 120 Body Helical Full-Body Top of head to mid-thigh 120 Body

19 Figure 2-1. Frontal view of the 9-month-old anthropomorphic phantom. 19

20 Figure 2-2. Axial cutaway of the 9-month-old anthropomorphic phantom with a fiberoptic coupled (FOC) dosimeter placed at a dose point in the lung. 20

21 Figure 2-3. Frontal view of the adult male anthropomorphic phantom. During CT organ dose measurements, the arms of the phantom were removed and the bottom of the trunk containing the gonads was added. 21

22 Figure 2-4. Axial cutaway of the adult male anthropomorphic phantom with a fiber-optic coupled (FOC) dosimeter placed at a dose point in the right kidney. 22

23 CHAPTER 3 RESULTS AND DISCUSSION Tables 3-1 and 3-2 show the measured and simulated organ dose results for the adult male and pediatric CT scans, respectively. Upon inspection of the organ doses, one might notice a large discrepancy between the testes and prostate organ doses in the axial and helical pelvic exams of the adult male phantom. This is nothing more than a result of the organs being in-beam for the helical exams and out-of-beam for the axial exams due to slight differences in the inferior anatomical stopping point for each scan. For all CT scans for both phantoms, the results suggested excellent agreement between measured and simulated organ doses. For the adult male, the average percent difference between simulated and measured organ doses for all axial scans was 7.4%, and 8.4% for helical scans. For the 9-month-old, the average percent difference was 6.4% for the axial scan, and 5.4% for the helical scan. A summary of the percent difference results can be found in Table 3-3. The percent difference results were comparable to a study performed by Li et al, which detailed the first set of inphantom validation measurements for helical CT scans. 21 As mentioned in that study, percent differences within 20% are considered good matches due to the overall complexity of CT examinations and the large number of factors that influence both the measurement and simulation results. Such factors include uncertainties of Monte Carlo tally results, simulation and measurement scan setup discrepancies, starting angle and overranging considerations, and uncertainties in dosimeter dose readings. The success of this validation study can be attributed to the careful attention to detail used when creating the Monte Carlo source term. The majority of the x-ray source parameters were modeled based off of actual physical measurements on the CT 23

24 scanner, which better reflect actual scanner outputs than information provided in technical specifications. Another major contribution to the success of this work was the fact that our group had available multiple anthropomorphic phantoms that were exact replicas of computational phantoms. This allowed for a greater ability to accurately model CT scan setups as well as ensure dose results were being compared between identical organ locations. 24

25 Table 3-1. Measured and simulated organ dose results for the adult male phantom. Scan Organ Measured Dose (mgy) Simulated Dose (mgy) Percent Difference Axial Head Brain Salivary Glands Thyroid Eyeballs Axial Chest Thyroid Lungs Esophagus Heart Axial Abdomen/Pelvis Stomach Liver Kidneys Colon Small Intestines Bladder Testes Prostate Helical Chest Thyroid Lung Stomach Liver Esophagus Helical Abdomen Liver Stomach Kidneys Colon Small Intestine Helical Pelvis Colon Small Intestine Bladder Prostate Testes

26 Table 3-2. Measured and simulated organ dose results for the 9-month-old phantom. Scan Organ Simulated Dose (mgy) Measured Dose (mgy) Percent Difference Axial Full-Body Brain Thyroid Thymus Lungs Heart Liver Stomach Gall Bladder Pancreas Kidneys Adrenals Urinary Bladder Testes Helical Full-Body Brain Thyroid Thymus Lungs Heart Liver Stomach Gall Bladder Pancreas Kidneys Adrenals Urinary Bladder Testes Table 3-3. Percent difference summary for all CT exam dose results. 9-month-old Phantom Adult Male Phantom Axial Scan Helical Scan Axial Scans Helical Scans Range (-13.3%, 13.9%) (-12.3%, 12.8%) (-13.7%, 14.7%) (-7.4%, 15.5%) Average Magnitude 6.4% 5.4% 7.4% 8.4% 26

27 CHAPTER 4 CONCLUSION The goal of this study was to validate a Monte Carlo source term modeling a Siemens SOMATOM Sensation 16 CT scanner using organ dose measurements in anthropomorphic and computational phantoms. Overall, the results of this study have shown that the Monte Carlo source term can be used to accurately and reliably calculate organ doses for patients undergoing a variety of axial or helical CT examinations using anatomically-realistic computational phantoms. 27

28 LIST OF REFERENCES 1 NCRP, NCRP Report No. 160: Ionizing Radiation Exposure of the Population of the United States, NCRP Report No (National Council on Radiation Protection and Measurement, Bethesda, MD, 2009). 2 A. de Gonzalez, K. Kim, and J. Samet, "Radiation-induced cancer risk from annual computed tomography for patients with cystic fibrosis," American Journal of Respiratory and Critical Care Medicine 176, 970 (2007). 3 D. J. Brenner, and E. J. Hall, "Current concepts - Computed tomography - An increasing source of radiation exposure," New England Journal of Medicine 357, (2007). 4 E. Angel, C. V. Wellnitz, M. M. Goodsitt, N. Yaghmai, J. J. DeMarco, C. H. Cagnon, J. W. Sayre, D. D. Cody, D. M. Stevens, A. N. Primak, C. H. McCollough, and M. F. McNitt-Gray, "Radiation dose to the fetus for pregnant patients undergoing multidetector CT imaging: Monte Carlo simulations estimating fetal dose for a range of gestational age and patient size," Radiology 249, (2008). 5 E. Angel, N. Yaghmai, C. M. Jude, J. J. DeMarco, C. H. Cagnon, J. G. Goldin, C. H. McCollough, A. N. Primak, D. D. Cody, D. M. Stevens, and M. F. McNitt-Gray, "Dose to radiosensitive organs during routine chest CT: effects of tube current modulation," AJR Am J Roentgenol 193, (2009). 6 E. Angel, N. Yaghmai, C. M. Jude, J. J. Demarco, C. H. Cagnon, J. G. Goldin, A. N. Primak, D. M. Stevens, D. D. Cody, C. H. McCollough, and M. F. McNitt-Gray, "Monte Carlo simulations to assess the effects of tube current modulation on breast dose for multidetector CT," Physics in Medicine and Biology 54, (2009). 7 M. Caon, G. Bibbo, and J. Pattison, "A comparison of radiation dose measured in CT dosimetry phantoms with calculations using EGS4 and voxel-based computational models," Phys Med Biol 42, (1997). 8 M. Caon, G. Bibbo, and J. Pattison, "An EGS4-ready tomographic computational model of a 14-year-old female torso for calculating organ doses from CT examinations," Physics in Medicine and Biology 44, (1999). 9 M. Caon, G. Bibbo, and J. Pattison, "Monte Carlo calculated effective dose to teenage girls from computed tomography examinations," Radiation Protection Dosimetry 90, (2000). 10 P. Deak, M. van Straten, P. C. Shrimpton, M. Zankl, and W. A. Kalender, "Validation of a Monte Carlo tool for patient-specific dose simulations in multi-slice computed tomography," Eur Radiol 18, (2008). 28

29 11 J. J. DeMarco, C. H. Cagnon, D. D. Cody, D. M. Stevens, C. H. McCollough, J. O'Daniel, and M. F. McNitt-Gray, "A Monte Carlo based method to estimate radiation dose from multidetector CT (MDCT): cylindrical and anthropomorphic phantoms," Physics in Medicine and Biology 50, (2005). 12 J. J. DeMarco, C. H. Cagnon, D. D. Cody, D. M. Stevens, C. H. McCollough, M. Zankl, E. Angel, and M. F. McNitt-Gray, "Estimating radiation doses from multidetector CT using Monte Carlo simulations: effects of different size voxelized patient models on magnitudes of organ and effective dose," Physics in Medicine and Biology 52, (2007). 13 J. J. DeMarco, T. D. Solberg, and J. B. Smathers, "A CT-based Monte Carlo simulation tool for dosimetry planning and analysis," Medical Physics 25, 1-11 (1998). 14 J. Hausleiter, T. Meyer, M. Hadamitzky, E. Huber, M. Zankl, S. Martinoff, A. Kastrati, and A. Schomig, "Radiation dose estimates from cardiac multislice computed tomography in daily practice: impact of different scanning protocols on effective dose estimates," Circulation 113, (2006). 15 G. Jarry, J. J. DeMarco, U. Beifuss, C. H. Cagnon, and M. F. McNitt-Gray, "A Monte Carlo-based method to estimate radiation dose from spiral CT: from phantom testing to patient-specific models," Physics in Medicine and Biology 48, (2003). 16 C. Lee, C. Lee, R. J. Staton, D. E. Hintenlang, M. M. Arreola, J. L. Williams, and W. E. Bolch, "Organ and effective doses in pediatric patients undergoing helical multislice computed tomography examination," Medical Physics 34, (2007). 17 C. Lee, D. Lodwick, J. L. Williams, and W. E. Bolch, "Hybrid computational phantoms of the 15-year male and female adolescent: applications to CT organ dosimetry for patients of variable morphometry," Medical Physics 35, (2008). 18 H. Liu, J. Gu, P. F. Caracappa, and X. G. Xu, "Comparison of two types of adult phantoms in terms of organ doses from diagnostic CT procedures," Physics in Medicine and Biology 55, (2010). 19 R. J. Staton, C. Lee, C. Lee, M. D. Williams, D. E. Hintenlang, M. M. Arreola, J. L. Williams, and W. E. Bolch, "Organ and effective doses in newborn patients during helical multislice computed tomography examination," Physics in Medicine and Biology 51, (2006). 20 A. C. Turner, D. Zhang, H. J. Kim, J. J. DeMarco, C. H. Cagnon, E. Angel, D. D. Cody, D. M. Stevens, A. N. Primak, C. H. McCollough, and M. F. McNitt-Gray, "A method to generate equivalent energy spectra and filtration models based on measurement for multidetector CT Monte Carlo dosimetry simulations," Medical Physics 36, (2009). 29

30 21 X. Li, E. Samei, W.P. Segars, G.M. Sturgeon, J.G. Colsher, G. Toncheva, T.T. Yoshizumi, D.P. Frush, Patient-specific radiation dose and cancer risk estimation in CT: Part I. Development and validation of a Monte Carlo program, Medical Physics 38, (2011). 22 C. Lee, K.P. Kim, D. Long, R. Fisher, C. TIen, S.L. Simon, A. Bouville, W.E. Bolch, Organ doses for reference adult male and female undergoing computed tomography estimated by Monte Carlo simulations, Medical Physics 38, (2011). 23 D. B. Pelowitz, MCNPX user's manual Version 2.6.0, LA-CP (Los Alamos National Laboratory, 2008). 24 K. Cranley, B. Gilmore, G. Fogarty, and L. Desponds, "IPEM report 78: Catalogue of diagnostic X-ray spectra and other data," York: The Institute of Physics and Engineering in Medicine (1997). 25 J.F. Winslow, D.E. Hyer, R.F. Fisher, C.J. Tien, D.E. Hintenlang, Construction of anthropomorphic phantoms for use in dosimetry studies, Journal of Applied Clinical Medical Physics 10, (2009). 26 C. Lee, D. Lodwick, J. L. Hurtado, D. H. Pafundi, J. L. Williams, and W. E. Bolch, "The UF family of reference hybrid phantoms for computational radiation dosimetry," Physics in Medicine and Biology 55, (2010). 27 D.E. Hyer, R.F. Fisher, D.E. Hintenlang, Characterization of a water-equivalent fiberoptic coupled dosimeter for use in diagnostic radiology, Medical Physics 36, (2009). 30

31 BIOGRAPHICAL SKETCH Daniel Joseph Long was born in 1987 in Palm Harbor, Florida to Tom and Colleen Long. He has one older brother, Chris. He graduated from Palm Harbor University High School in 2005, and graduated cum laude with his Bachelor of Science in nuclear engineering from the University of Florida in May He graduated with his Master of Science in biomedical engineering with a specialty in medical physics at the University of Florida in August 2011, after which he began pursuit of a doctorate in the same field. Daniel enjoys many extracurricular activities, most of all playing sports and reading for pleasure. He has played organized baseball, soccer, and swam for his high school team. In addition, he has participated in intramural softball, indoor soccer, basketball, and football since his freshman year at the University of Florida. He also enjoys the occasional round of golf and tennis match. Daniel met his wife, Nelia, in his junior year of undergraduate studies on the day of his first nuclear engineering class. Three years later, they married in August 2010, and both began pursuit graduate studies in medical physics. 31