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Development of An Age-Scalable Colon Model with Substructures for Colon Radiation Therapy Dosimetry in Large Pediatric Cohorts for Late-Effects Studies

C Owens1,2*, A Gupta1,2, S Shrestha1,2, S Smith1, C Lee3, C Peterson1,4, A Paulino5, S Kry1,2, D Followill1,2, R Howell1,2, (1) Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA, (2) The University of Texas Graduate School of Biomedical Sciences at Houston, Houston, TX, USA, (3) Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institute of Health, Bethesda, MD, USA, (4) Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA, (5) Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA

Presentations

(Sunday, 7/12/2020)   [Eastern Time (GMT-4)]

Room: AAPM ePoster Library

Purpose: To date, radiation therapy (RT)-related late-effects studies with colon have included prescribed pelvic dose or estimated the proximity of specific colon parts to the RT field, but have not included mean RT dose to the whole colon, colon substructure doses or dose-volume metrics. The purpose of this study was to develop a detailed age-scalable colon model with substructures for our late-effects phantom, which will allow calculation of these additional dose metrics for future studies on second colon cancers in childhood cancer survivors.

Methods: We used six whole-body CT-based phantoms (ages: 0.1, 1, 5, 10, 15 and 30 years) from the National Cancer Institute (NCI) computational human phantom series; each of which has a delineated colon with substructures. Since these phantoms are only available for select ages, we integrated the NCI colons into our in-house phantom which can be scaled to any age (infant-to-adult). First, we extracted the colon from each NCI phantom. Second, we rigidly registered each extracted colon to our in-house phantom scaled to the same age. Third, we created an age-based colon model selection process, whereby for a given individual, the colon model that is the closest in age is selected and scaled to their age at RT. Age-scaling is used because height and weight are not generally available in historic RT records.

Results: We successfully integrated six anatomically realistic CT-based colon models with substructures from an international phantom reference library into our in-house computational phantom. Uniquely, these colon models can be scaled to any age at RT.

Conclusion: We now have the capability to perform colon and colon substructure RT dosimetry for a study on RT-related late-effects in childhood cancer survivors. Incorporation of this detailed colon dosimetry could lead to more meaningful dose-response models that could be used to better inform survivorship care plans.

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Keywords

Radiation Effects, Radiation Dosimetry, Phantoms

Taxonomy

TH- Response Assessment: Radiation induced second cancers

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