Development of a mouse computational model for MCNPx based on Digimouse (r) images and dosimetric assays

Authors

  • Bruno Melo Mendes Universidade Federal de Minas Gerais; Programa de Pós-Graduação em Ciências e Técnicas Nucleares; Departamento de Engenharia Nuclear
  • Iassudara Garcia de Almeida Universidade Federal de Minas Gerais; Programa de Pós-Graduação em Ciências e Técnicas Nucleares; Departamento de Engenharia Nuclear
  • Bruno Machado Trindade Universidade Federal de Minas Gerais; Programa de Pós-Graduação em Ciências e Técnicas Nucleares; Departamento de Engenharia Nuclear
  • Telma Cristina Ferreira Fonseca Centro de Desenvolvimento da Tecnologia Nuclear
  • Tarcísio Passos Ribeiro de Campos Universidade Federal de Minas Gerais; Programa de Pós-Graduação em Ciências e Técnicas Nucleares; Departamento de Engenharia Nuclear

DOI:

https://doi.org/10.1590/s2175-97902017000116092

Keywords:

Dosimetry/assay, Mouse phantom/tests, MCNPx Monte Carlo code Computational studies.

Abstract

The aim of this study was to create and test a new mice 3D-voxel phantom named DM_BRA for mice and human first-estimation radiopharmaceutical dosimetry. Previously, the article reviews the state-of-art in animal model development. Images from Digimouse CT database were used in the segmentation and on the generation of the voxelized phantom. Simulations for validation of the DM_BRA model was performed at 0.015, 0.1, 0.5, 1 and 4 MeV photons with heart-source. Specific Absorbed Fractions (SAF) data were compared with literature data. The organ masses of DM_BRA correlated well with existing models based on the same dataset; however, few small organ masses hold significant variations. The SAF data in most simulated cases were statistically equal to a significant level of 0.01 to the reference data.

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Published

2017-01-01

Issue

Section

Articles

How to Cite

Development of a mouse computational model for MCNPx based on Digimouse (r) images and dosimetric assays. (2017). Brazilian Journal of Pharmaceutical Sciences, 53(1), e16092-. https://doi.org/10.1590/s2175-97902017000116092