Internal exposure rate conversion coefficients and absorbed fractions of mouse for 137Cs, 134Cs and 90Sr contamination in body.

The aim of this study was to determine parameters for estimating the internal exposure of all organs in mouse experiments from the radioactivity concentration in organs. The estimation of internal exposure rate conversion coefficients and absorbed fractions for 137Cs, 134Cs and 90Sr by the Particle and Heavy Ion Transport code System (PHITS) with a voxel-based mouse phantom is presented. The geometry of the voxel phantom is constructed from computer tomography images of a mouse 9 cm in length weighing 23.9 g. The voxel-based mouse phantom has the following organs: brain, skull, heart, lungs, liver, stomach, spleen, kidneys, bladder, testis and tissue (tissue and other organs). Gamma- and beta-rays from 137Cs, 134Cs and 90Sr sources in each source organ are generated and scored for every target organ. The internal exposure rate conversion coefficients and absorbed fractions are calculated from deposition energies in each target organ from each source organ and are used to generate an internal exposure rate conversion coefficient matrix and an absorbed fraction matrix. The absorbed fractions of beta-rays in the source organs are roughly 0.5-0.8 for 137Cs and 134Cs, and the absorbed fractions of gamma-rays are <0.04 for 137Cs and <0.03 for 134Cs. The internal exposure rate conversion coefficient matrix is defined using the absorbed fractions. The calculated internal exposure rate coefficient matrix is tested under a uniform radioactivity concentration of 1 Bq/kg for 137Cs, 134Cs and 90Sr. The estimated internal exposure rates in the mouse whole body for 137Cs, 134Cs and 90Sr are 3.28 × 10-3, 2.55 × 10-3 and 1.20 × 10-2 μGy/d, respectively. These values are very similar to those for an ellipsoid frog (31.4 g) and an ellipsoid crab egg mass (12.6 g) reported in ICRP Publication 108. Published by Oxford University Press on behalf of The Japanese Radiation Research Society and Japanese Society for Radiation Oncology 2020.