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Development of Obese Hybrid Computational Pregnant Phantom Models for Radiotherapy Applications

R Makkia1*, K Nelson2 , M Dingfelder3 , H Zaidi4 , (1) East Carolina University, Greenville, NC, (2) Vidant Medical Center, Greeville, NC, (3) East Carolina University, Greeville, NC, (4) Geneva University Hospital, Geneva, CH


(Sunday, 7/29/2018) 3:00 PM - 6:00 PM

Room: Exhibit Hall

Purpose: To establish new complete sets of hybrid obese computational pregnant phantoms for patient undergo radiation therapy or diagnostic treatments.

Methods: Obese patients raise a potential health problem in the world. This project aims to create obese pregnant computational phantoms during pregnancy for many radiotherapy applications. All Radiological images in DICOM sets were obtained from Vidant Medical Center archive to conduct this study. The method starts as follows: (1) Three computational fetus phantom models were created using MRI and CT imaging data for each fetus model to construct a complete anatomically accurate fetus, gravid uterus, and placenta. All fetus volume organs are adjusting to match ICRP-89 data record after the major fetus organs were converted to 3D modeling object.(2) The next step is to construct an obese pregnant phantom model for the developed fetus models. We are planning to establish an obese pregnant phantom obtained from a real CT image set of the obese pregnant patient and the International Commission on Radiological Protection (ICRP-110) voxelized female.(3) Next is to add the fetus phantoms sets developed to the developed obese pregnant female phantom model using 3D-modeling software (Rhinoceros 5.0) to establish a complete set of obese pregnant phantoms. Many Researchers have created an ICRP pregnant computational models of computational fetus phantoms.However, no research has been done on any obese pregnant computational models for a patient who undergoes radiotherapy during pregnancy yet.

Results: Three sets of hybrid computational obese pregnant phantoms with realistic fetus phantoms are created to estimate the radiation dose to the fetus of an obese patient and evaluate the risk from radiation exposure due to a particular procedure.

Conclusion: This study provides hybrid computational obese pregnant model sets to representing pregnant obese patient and better estimate the radiation dose from a diagnostic procedure (CT) scan or therapeutic treatment (Linac).


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