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

Magnetite Particle Presence in the Human Brain: A Computational Dosimetric Study to Emphasize the Need of a Complete Assessment of the Electromagnetic Power Deposition at 3.5 GHz

The growing evidence of increased magnetite nanoparticles (both endo- and exo-genic) in the human brain raises the importance of assessing the entire power deposition when electromagnetic waves at GHz frequencies propagate in such tissues. This frequency range corresponds to many popular portable communication devices that emit radiation close to a human's head. At these frequencies, the current dosimetric numerical codes can not accurately compute the magnetic losses part. This is due to the lack of an implemented computational algorithm based on solving the coupled Maxwell and Landau-Lifshitz-Gilbert equations, in the case of magneto-dielectrics, considering eddy currents losses and specific properties of magnetic sub-millimetric particles. This paper focuses on analyzing the limits and the inconsistencies when using commercial dosimetric numerical software to analyze the total absorbed power in brain models having ferrimagnetic content and being exposed to 3.5GHz electromagnetic waves. Magnetic losses computed using Polder’s permeability tensor as constitutive relation lead to unreliable results. However, using such software can provide a preliminary view of the electromagnetic impact of ultra- and super-high frequencies on magnetic-dielectric tissues.