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A Series of Computational Human Phantoms in DICOM-RT Format for Normal Tissue Dose Reconstruction in Epidemiological Studies

A Pyakuryal

A Pyakuryal1*, B Moroz2 , C Lee3 , C Pelletier4 , J Jung5 , C Lee6 , (1) National Cancer Institute, National Institutes of Health, Rockville, MD, (2) National Cancer Institute, National Institutes of Health, Rockville, MD, (3) University of Michigan, Ann Arbor, MI, (4) East Carolina University Greenville, NC, (5) East Carolina University Greenville, NC, (6) National Cancer Institute, Rockville, MD


SU-F-J-174 (Sunday, July 31, 2016) 3:00 PM - 6:00 PM Room: Exhibit Hall

Purpose: Epidemiological studies of second cancer risk in radiotherapy patients often require individualized dose estimates of normal tissues. Prior to 3D conformal radiation therapy planning, patient anatomy information was mostly limited to 2D radiological images or not even available. Generic patient CT images are often used in commercial radiotherapy treatment planning system (TPS) to reconstruct normal tissue doses. The objective of the current work was to develop a series of reference size computational human phantoms in DICOM-RT format for direct use in dose reconstruction in TPS.

Methods: Contours of 93 organs and tissues were extracted from a series of pediatric and adult hybrid computational human phantoms (newborn, 1-, 5-, 10-, 15-year-old, and adult males and females) using Rhinoceros software. A MATLAB script was created to convert the contours into the DICOM-RT structure format. The simulated CT images with the resolution of 1x1x3 mm3 were also generated from the binary phantom format and coupled with the DICOM-structure files. Accurate volumes of the organs were drawn in the format using precise delineation of the contours in converted format. Due to complex geometry of organs, higher resolution (1x1x1 mm3) was found to be more efficient in the conversion of newborn and 1-year-old phantoms.

Results: Contour sets were efficiently converted into DICOM-RT structures in relatively short time (about 30 minutes for each phantom). A good agreement was observed in the volumes between the original phantoms and the converted contours for large organs (NRMSD<1.0%) and small organs (NRMSD<7.7%).

Conclusions: A comprehensive series of computational human phantoms in DICOM-RT format was created to support epidemiological studies of second cancer risks in radiotherapy patients. We confirmed the DICOM-RT phantoms were successfully imported into the TPS programs of major vendors.

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