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Monte Carlo modeling in CT-based geometries: dosimetry for biological modeling experiments with particle beam radiation
The space radiation environment imposes increased dangers of exposure to ionizing radiation, particularly during a solar particle event (SPE). These events consist primarily of low energy protons that produce a highly inhomogeneous dose distribution. Due to this inherent dose heterogeneity, experime...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3951080/ https://www.ncbi.nlm.nih.gov/pubmed/24309720 http://dx.doi.org/10.1093/jrr/rrt118 |
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author | Diffenderfer, Eric S. Dolney, Derek Schaettler, Maximilian Sanzari, Jenine K. Mcdonough, James Cengel, Keith A. |
author_facet | Diffenderfer, Eric S. Dolney, Derek Schaettler, Maximilian Sanzari, Jenine K. Mcdonough, James Cengel, Keith A. |
author_sort | Diffenderfer, Eric S. |
collection | PubMed |
description | The space radiation environment imposes increased dangers of exposure to ionizing radiation, particularly during a solar particle event (SPE). These events consist primarily of low energy protons that produce a highly inhomogeneous dose distribution. Due to this inherent dose heterogeneity, experiments designed to investigate the radiobiological effects of SPE radiation present difficulties in evaluating and interpreting dose to sensitive organs. To address this challenge, we used the Geant4 Monte Carlo simulation framework to develop dosimetry software that uses computed tomography (CT) images and provides radiation transport simulations incorporating all relevant physical interaction processes. We found that this simulation accurately predicts measured data in phantoms and can be applied to model dose in radiobiological experiments with animal models exposed to charged particle (electron and proton) beams. This study clearly demonstrates the value of Monte Carlo radiation transport methods for two critically interrelated uses: (i) determining the overall dose distribution and dose levels to specific organ systems for animal experiments with SPE-like radiation, and (ii) interpreting the effect of random and systematic variations in experimental variables (e.g. animal movement during long exposures) on the dose distributions and consequent biological effects from SPE-like radiation exposure. The software developed and validated in this study represents a critically important new tool that allows integration of computational and biological modeling for evaluating the biological outcomes of exposures to inhomogeneous SPE-like radiation dose distributions, and has potential applications for other environmental and therapeutic exposure simulations. |
format | Online Article Text |
id | pubmed-3951080 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-39510802014-03-12 Monte Carlo modeling in CT-based geometries: dosimetry for biological modeling experiments with particle beam radiation Diffenderfer, Eric S. Dolney, Derek Schaettler, Maximilian Sanzari, Jenine K. Mcdonough, James Cengel, Keith A. J Radiat Res Physics The space radiation environment imposes increased dangers of exposure to ionizing radiation, particularly during a solar particle event (SPE). These events consist primarily of low energy protons that produce a highly inhomogeneous dose distribution. Due to this inherent dose heterogeneity, experiments designed to investigate the radiobiological effects of SPE radiation present difficulties in evaluating and interpreting dose to sensitive organs. To address this challenge, we used the Geant4 Monte Carlo simulation framework to develop dosimetry software that uses computed tomography (CT) images and provides radiation transport simulations incorporating all relevant physical interaction processes. We found that this simulation accurately predicts measured data in phantoms and can be applied to model dose in radiobiological experiments with animal models exposed to charged particle (electron and proton) beams. This study clearly demonstrates the value of Monte Carlo radiation transport methods for two critically interrelated uses: (i) determining the overall dose distribution and dose levels to specific organ systems for animal experiments with SPE-like radiation, and (ii) interpreting the effect of random and systematic variations in experimental variables (e.g. animal movement during long exposures) on the dose distributions and consequent biological effects from SPE-like radiation exposure. The software developed and validated in this study represents a critically important new tool that allows integration of computational and biological modeling for evaluating the biological outcomes of exposures to inhomogeneous SPE-like radiation dose distributions, and has potential applications for other environmental and therapeutic exposure simulations. Oxford University Press 2014-03 2013-12-05 /pmc/articles/PMC3951080/ /pubmed/24309720 http://dx.doi.org/10.1093/jrr/rrt118 Text en © The Author 2013. Published by Oxford University Press on behalf of The Japan Radiation Research Society and Japanese Society for Therapeutic Radiology and Oncology. http://creativecommons.org/licenses/by/3.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Physics Diffenderfer, Eric S. Dolney, Derek Schaettler, Maximilian Sanzari, Jenine K. Mcdonough, James Cengel, Keith A. Monte Carlo modeling in CT-based geometries: dosimetry for biological modeling experiments with particle beam radiation |
title | Monte Carlo modeling in CT-based geometries: dosimetry for biological modeling experiments with particle beam radiation |
title_full | Monte Carlo modeling in CT-based geometries: dosimetry for biological modeling experiments with particle beam radiation |
title_fullStr | Monte Carlo modeling in CT-based geometries: dosimetry for biological modeling experiments with particle beam radiation |
title_full_unstemmed | Monte Carlo modeling in CT-based geometries: dosimetry for biological modeling experiments with particle beam radiation |
title_short | Monte Carlo modeling in CT-based geometries: dosimetry for biological modeling experiments with particle beam radiation |
title_sort | monte carlo modeling in ct-based geometries: dosimetry for biological modeling experiments with particle beam radiation |
topic | Physics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3951080/ https://www.ncbi.nlm.nih.gov/pubmed/24309720 http://dx.doi.org/10.1093/jrr/rrt118 |
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