Physics in medicine and biology | 2019

Preclinical voxel-based dosimetry through GATE Monte Carlo simulation using PET/CT imaging of mice.

 
 
 
 
 
 
 
 

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\u2009\u2009±\u2009\u20094.25\u2009g) 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.

Volume 64 9
Pages \n 095007\n
DOI 10.1088/1361-6560/ab134b
Language English
Journal Physics in medicine and biology

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