Supplemental computational phantoms to estimate out-of-field absorbed dose in photon radiotherapy

Abstract

The purpose of this study was to develop a straightforward method of supplementing patient anatomy and estimating out-of-field absorbed dose for a cohort of pediatric radiotherapy patients with limited recorded anatomy. A cohort of nine children, aged 2-14 years, who received 3D conformal radiotherapy for low-grade localized brain tumors (LBTs), were randomly selected for this study. The extent of these patients' computed tomography simulation image sets were cranial only. To approximate their missing anatomy, we supplemented the LBT patients' image sets with computed tomography images of patients in a previous study with larger extents of matched sex, height, and mass and for whom contours of organs at risk for radiogenic cancer had already been delineated. Rigid fusion was performed between the LBT patients' data and that of the supplemental computational phantoms using commercial software and in-house codes. In-field dose was calculated with a clinically commissioned treatment planning system, and out-of-field dose was estimated with a previously developed analytical model that was re-fit with parameters based on new measurements for intracranial radiotherapy. Mean doses greater than 1 Gy were found in the red bone marrow, remainder, thyroid, and skin of the patients in this study. Mean organ doses between 150 mGy and 1 Gy were observed in the breast tissue of the girls and lungs of all patients. Distant organs, i.e. prostate, bladder, uterus, and colon, received mean organ doses less than 150 mGy. The mean organ doses of the younger, smaller LBT patients (0-4 years old) were a factor of 2.4 greater than those of the older, larger patients (8-12 years old). Our findings demonstrated the feasibility of a straightforward method of applying supplemental computational phantoms and dose-calculation models to estimate absorbed dose for a set of children of various ages who received radiotherapy and for whom anatomies were largely missing in their original computed tomography simulations.

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“…Computed tomography (CT) simulation images had been obtained for treatment planning from the top of the head to the neck. Missing anatomies in the CT image sets were supplemented with those of computational phantoms of matching height and weight from patients of the same sex [ 14 ]. Each patient's treatment planning data were exported to digital imaging and communications in medicine files [ 18 ] and deidentified [ 19 ].…”

“…The overall set of T comprised the thyroid, red bone marrow, skin, breast tissue, lungs, liver, stomach, uterus, ovaries, prostate, bladder, colon (including the rectum), and remainder tissues. Further information concerning the contours, the implementation of the supplemental phantoms, and the selection criteria were published previously [ 14 ].…”

“…The calculation and distribution of dose for photon therapy treatment plans in an LMIC country used in this study were published previously [ 14 ] and are briefly described here. In that study, some treatment plans had been adjusted slightly, and all were approved by an attending pediatric radiation oncologist.…”

“…In that study, some treatment plans had been adjusted slightly, and all were approved by an attending pediatric radiation oncologist. A clinically commissioned commercial TPS (version 5.01, Panther, Prowess Inc, Concord, California) calculated the therapeutic absorbed dose ( D ) (in grays), and an analytic model from the literature [ 21 ] was reparameterized with newly measured data to estimate the out-of-field dose [ 14 ]. Equivalent dose in each voxel ( H ; in sieverts) was calculated as the product of absorbed dose D and the radiation weighting factor ( w R ) for photons and electrons of 1 [ 22 ].…”

“…Other researchers concerned about radiogenic risk of SMNs in photon and proton therapy of intracranial tumors bypassed the need for large computational resources by neglecting stray radiation contributions and considering only in-field organs at risk [ 9 , 13 ]. For this reason, we decided to perform a comprehensive whole-body risk comparison between modalities for clinically realistic pediatric intracranial fields with computationally inexpensive dosimetric methods [ 14 – 16 ]. Further, no study had considered radiotherapy techniques that are used more globally, for example, in LMICs that are limited in their ability to implement the most advanced machinery, hardware, and software resources available in HICs.…”