| Literature DB >> 30913544 |
Arun Gupta1, Min Sun Lee, Joong Hyun Kim, Sohyeon Park, Hyun Soo Park, Sang Eun Kim, Dong Soo Lee, Jae Sung Lee.
Abstract
Internal dosimetry is of critical importance to obtain an accurate absorbed dose-response relationship during preclinical molecular imaging and targeted radionuclide therapy (TRT). Conventionally, absorbed dose calculations have been performed using organ-level dosimetry based on the Medical Internal Radiation Dose (MIRD) schema. However, recent research has focused on developing more accurate voxel-level calculation methods. Geant4 application for emission tomography (GATE) Monte Carlo (MC) is a simulation toolkit gaining attention in voxel-based dosimetry. In this study, we used PET/CT images of real mice to estimate the absorbed doses in sensitive organs at voxel-level to evaluate the suitability of GATE MC simulation for preclinical dosimetry. Thirteen normal C57BL/6 mice (male, body weight: 27.71 ± 4.25 g) were used to acquire dynamic positron emission tomography/computed tomography (PET/CT) images after IV injection of 18F-FDG. GATE MC toolkit was applied to estimate the absorbed doses in various organs of mice at voxel-level using CT and PET images as voxelized phantom and voxelized source, respectively. In addition, mean absorbed dose at organ-level was calculated using MIRD schema for comparison purposes. The differences in the respective absorbed doses (mGy MBq-1) between GATE MC and MIRD schema for brain, heart wall, liver, lungs, stomach wall, spleen, kidneys, and bladder wall were 1.36, 12.3, -22.4, -11.2, -16.9, -2.87, -4.29, and 3.71%, respectively. Considering that the PET/CT data of real mice were used for GATE simulation, the absorbed doses estimated in this study are mouse-specific. Therefore, the GATE-based Monte Carlo is likely to allow for more accurate internal dosimetry calculations. This method can be used in TRT for personalized dosimetry because it considers patient-specific heterogeneous tissue compositions and activity distributions.Entities:
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Year: 2019 PMID: 30913544 DOI: 10.1088/1361-6560/ab134b
Source DB: PubMed Journal: Phys Med Biol ISSN: 0031-9155 Impact factor: 3.609