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Radiopharmaceutical Chemistry: Dosimetry/RadiobiologyDose Models and Estimates |
1 Vanderbilt University, Nashville, Tennessee; 2 Duke University, Durham, North Carolina
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Objectives: Anthropomorphic phantoms based on simple geometric structures have been used in radiation dose calculations for several decades. We have developed a series of anatomically realistic phantoms representing adults and children using body models based on non-uniform rational B-splines (NURBS), with organ and body masses based on the reference values given in ICRP Publication 89.
Methods: NURBS body and organ models were scaled and shaped to model the reference individuals described in ICRP 89 (male and female adults, newborns, 1-, 5-, 10- and 15-year-olds), using a software tool developed in Visual C++. Voxelized versions of these models were used in the GEANT4 radiation transport codes for calculation of specific absorbed fractions (SAFs) for internal sources. SAFs for discrete photon and electron sources were developed, using standard starting energy values.
Results: We scaled the models to within a few % of ICRP reference masses; physicians reviewed the models for anatomical realism. Development of individual phantoms was much faster than manual segmentation of medical images, and resulted in a very uniform standardized phantom series. SAFs were calculated on a multinode computing network (ACCRE). Photon and electron SAFs were calculated for all organs in all models, and were compared to values from similar phantoms developed by others. Agreement was very good in most cases; some differences were seen, due to differences in organ mass and geometry.
Conclusions: This realistic phantom series represents an update on the Cristy/Eckerman series of the 1980s. Both phantom sets will be included in the next release of OLINDA/EXM. The new phantoms will be made available for general use via the RPI Consortium of Computational Human Phantoms.
Research Support: This work is supported in part by grants 1R42CA115122-01, 5R01CA116743-03 and 5R01 EB001838 from the NIH.
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