Body Region-Specific 3D Age-Scaling Functions for Scaling Whole-Body Computed Tomography Anatomy for Pediatric Late Effects Studies

Purpose: Radiation epidemiology studies of childhood cancer survivors treated in the pre-computed tomography (CT) era reconstruct the patients’ treatment fields on computational phantoms. For such studies, the phantoms are commonly scaled to age at the time of radiotherapy treatment because age is the generally available anthropometric parameter. Several reference size phantoms are used in such studies, but reference size phantoms are only available at discrete ages (e.g.: newborn, 1, 5, 10, 15, and Adult). When such phantoms are used for RT dose reconstructions, the nearest discrete-aged phantom is selected to represent a survivor of a specific age. In this work, we (1) conducted a feasibility study to scale reference size phantoms at discrete ages to various other ages, and (2) evaluated the dosimetric impact of using exact age-scaled phantoms as opposed to nearest age-matched phantoms at discrete ages. Methods: We have adopted the University of Florida/National Cancer Institute (UF/NCI) computational phantom library for our studies. For the feasibility study, eight male and female reference size UF/NCI phantoms (5, 10, 15, and 35 years) were downscaled to fourteen different ages which included next nearest available lower discrete ages (1, 5, 10 and 15 years) and the median ages at the time of RT for Wilms’ tumor (3.9 years), craniospinal (8.0 years), and all survivors (9.1 years old) in the Childhood Cancer Survivor Study (CCSS) expansion cohort treated with RT. The downscaling was performed using our in-house age scaling functions (ASFs). To geometrically validate the scaling, Dice similarity coefficient (DSC), mean distance to agreement (MDA), and Euclidean distance (ED) were calculated between the scaled and ground-truth discrete-aged phantom (unscaled UF/NCI) for whole-body, brain, heart, liver, pancreas, and kidneys. Additionally, heights of the scaled phantoms were compared with ground-truth phantoms’ height, and the Centers for Disease Control and Prevention (CDC) reported 50th percentile height. Scaled organ masses were compared with ground-truth organ masses. For the dosimetric assessment, one reference size phantom and seventeen body-size dependent 5-year-old phantoms (9 male and 8 female) of varying body mass indices (BMI) were downscaled to 3.9-year-old dimensions for two different radiation dose studies. For the first study, we simulated a 6 MV photon right-sided flank field RT plan on a reference size 5-year-old and 3.9-year-old (both of healthy BMI), keeping the field size the same in both cases. Percent of volume receiving dose ≥ 15 Gy (V15) and the mean dose were calculated for the pancreas, liver, and stomach. For the second study, the same treatment plan, but with patient anatomy-dependent field sizes, was simulated on seventeen body-size dependent 5- and 3.9-year-old phantoms with varying BMIs. V15, mean dose, and minimum dose received by 1% of the volume (D1), and by 95% of the volume (D95) were calculated for pancreas, liver, stomach, left kidney (contralateral), right kidney, right and left colons, gallbladder, thoracic vertebrae, and lumbar vertebrae. A non-parametric Wilcoxon rank-sum test was performed to determine if the dose to organs of exact age-scaled and nearest age-matched phantoms were significantly different (p<0.05). Results: In the feasibility study, the best DSCs were obtained for the brain (median: 0.86) and whole-body (median: 0.91) while kidneys (median: 0.58) and pancreas (median: 0.32) showed poorer agreement. In the case of MDA and ED, whole-body, brain, and kidneys showed tighter distribution and lower median values as compared to other organs. For height comparison, the overall agreement was within 2.8% (3.9cm) and 3.0% (3.2cm) of ground-truth UF/NCI and CDC reported 50th percentile heights, respectively. For mass comparison, the maximum percent and absolute differences between the scaled and ground-truth organ masses were within 31.3% (29.8g) and 211.8g (16.4%), respectively (across all ages). In the first dosimetric study, absolute difference up to 6% and 1.3 Gy was found for V15 and mean dose, respectively. In the second dosimetric study, V15 and mean dose were significantly different (p<0.05) for all studied organs except the fully in-beam organs. D1 and D95 were not significantly different for most organs (p>0.05). Conclusion: We have successfully evaluated our ASFs by scaling UF/NCI computational phantoms from one age to another age, which demonstrates the feasibility of scaling any CT-based anatomy. We have found that dose to organs of exact age-scaled and nearest aged-matched phantoms are significantly different (p<0.05) which indicates that using the exact age-scaled phantoms for retrospective dosimetric studies is a bette

Advances in anthropomorphic thorax phantoms for radiotherapy: a review

A phantom is a highly specialized device, which mimic human body, or a part of it. There are three categories of phantoms: physical phantoms, physiological phantoms, and computational phantoms. The phantoms have been utilized in medical imaging and radiotherapy for numerous applications. In radiotherapy, the phantoms may be used for various applications such as quality assurance (QA), dosimetry, end-to-end testing, etc. In thoracic radiotherapy, unique QA problems including tumor motion, thorax deformation, and heterogeneities in the beam path have complicated the delivery of dose to both tumor and organ at risks (OARs). Also, respiratory motion is a major challenge in radiotherapy of thoracic malignancies, which can be resulted in the discrepancies between the planned and delivered doses to cancerous tissue. Hence, the overall treatment procedure needs to be verified. Anthropomorphic thorax phantoms, which are made of human tissue-mimicking materials, can be utilized to obtain the ground truth to validate these processes. Accordingly, research into new anthropomorphic thorax phantoms has accelerated. Therefore, the review is intended to summarize the current status of the commercially available and in-house-built anthropomorphic physical/physiological thorax phantoms in radiotherapy. The main focus is on anthropomorphic, deformable thorax motion phantoms. This review also discusses the applications of three-dimensional (3D) printing technology for the fabrication of thorax phantoms.

Virtual Igor: an analytical phantom for the simulation of the Saint Petersburg brick phantom in arbitrary layouts in MCNP

A computer code called Virtual Igor is presented. The code generates an analytical representation of the Saint Petersburg brick phantom family (Igor, Olga, Irina), which is frequently used for the calibration of whole-body counters, in arbitrary user-defined layouts for the use in the Monte-Carlo radiation transport code MCNP. The computer code reads a file in the ldraw format, which can easily be produced by simple freeware software with graphical user interfaces and which contains the types and coordinates of the bricks. Ldraw files with the canonical layouts of the brick phantom are provided with Virtual Igor. The code determines the positions of (2.75 cm)3 segments of the bricks, where 2.75 cm is the smallest length in the layout and, therefore, represents the spacing of the segment lattice. Each segment contains the exact geometry of the respective part of the brick, using cuboid and cylindrical surfaces. The user can define which rod source drill holes of which bricks contain the rod-type radionuclide sources. The method facilitates the comparison of different layouts of the Saint Petersburg brick phantom with each other and with anthropomorphic computational phantoms.

Simulation study on radiation exposure of emergency medical responders from radioactively contaminated patients

Emergency medical responders (EMRs) who treat victims during a radiation emergency are at risk of radiation exposure. In this study, the exposure dose to EMRs treating hypothetically contaminated patients was estimated using a Monte Carlo simulation, and the findings may be useful for educating EMRs and reducing their anxiety. The Monte Carlo simulation estimated radiation doses for adult computational phantoms based on radioactive contamination conditions and radiation dosages from previous studies. At contamination conditions below the typical upper limit of general Geiger–Müller survey meters, the radiation doses to EMRs were estimated to be less than 1 μSv per hour. In cases with greater contamination due to mishandling of an intense radioactive source (hundreds of GBq), the radiation doses to EMRs could reach approximately 100 mSv per hour. These results imply that a radiological accident with a highly radioactive source could expose EMR to significant radiation that exceeds their dose limit. Thus, authorities and other parties should ensure that EMRs receive appropriate education and training regarding measures that can be taken to protect themselves from the possibility of excessive radiation exposure. The results of this study may provide EMRs with information to take appropriate protective measures, although it is also important that they not hesitate to perform lifesaving measures because of concerns regarding radiation.

Simulation Study on Radiation Exposure of Emergency Medical Responders From Radioactively Contaminated Patients

Emergency medical responders (EMRs), who save victims in a radiation emergency, are at risk of radiation exposure. In this study, the exposure dose to EMRs assisting contaminated patients was estimated using a Monte Carlo simulation, and will produce data that contributes to EMR education and anxiety reduction. Using the Monte Carlo simulation, we estimated radiation doses for adult computational phantoms with radioactive contamination conditions radiation dosages were based on findings from previous studies. At the contamination condition corresponding to the typical upper limit of general GM survey meters, the radiation doses of EMRs were estimated to be less than μSv per hour. In case of a heavier contamination due to mishandling of an intense radioactive source with hundreds of GBq or more, their radiation doses would be close to 100 mSv per hour. The results have implied that the radiological accident with a highly radioactive source would expose EMR to the risk of significant radiation exposure exceeding the dose limit. It is thus crucial that the authority or other party who are responsible for the health of EMRs ensures that they shall have necessary education and training on the effective measures for protecting themselves from the possible, excessive radiation exposure.