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A general-purpose Monte Carlo particle transport code based on inverse transform sampling for radiotherapy dose calculation
The Monte Carlo (MC) method is widely used to solve various problems in radiotherapy. There has been an impetus to accelerate MC simulation on GPUs whereas thread divergence remains a major issue for MC codes based on acceptance-rejection sampling. Inverse transform sampling has the potential to eli...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7300009/ https://www.ncbi.nlm.nih.gov/pubmed/32555530 http://dx.doi.org/10.1038/s41598-020-66844-7 |
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author | Liang, Ying Muhammad, Wazir Hart, Gregory R. Nartowt, Bradley J. Chen, Zhe J. Yu, James B. Roberts, Kenneth B. Duncan, James S. Deng, Jun |
author_facet | Liang, Ying Muhammad, Wazir Hart, Gregory R. Nartowt, Bradley J. Chen, Zhe J. Yu, James B. Roberts, Kenneth B. Duncan, James S. Deng, Jun |
author_sort | Liang, Ying |
collection | PubMed |
description | The Monte Carlo (MC) method is widely used to solve various problems in radiotherapy. There has been an impetus to accelerate MC simulation on GPUs whereas thread divergence remains a major issue for MC codes based on acceptance-rejection sampling. Inverse transform sampling has the potential to eliminate thread divergence but it is only implemented for photon transport. Here, we report a MC package Particle Transport in Media (PTM) to demonstrate the implementation of coupled photon-electron transport simulation using inverse transform sampling. Rayleigh scattering, Compton scattering, photo-electric effect and pair production are considered in an analogous manner for photon transport. Electron transport is simulated in a class II condensed history scheme, i.e., catastrophic inelastic scattering and Bremsstrahlung events are simulated explicitly while subthreshold interactions are subject to grouping. A random-hinge electron step correction algorithm and a modified PRESTA boundary crossing algorithm are employed to improve simulation accuracy. Benchmark studies against both EGSnrc simulations and experimental measurements are performed for various beams, phantoms and geometries. Gamma indices of the dose distributions are better than 99.6% for all the tested scenarios under the 2%/2 mm criteria. These results demonstrate the successful implementation of inverse transform sampling in coupled photon-electron transport simulation. |
format | Online Article Text |
id | pubmed-7300009 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-73000092020-06-22 A general-purpose Monte Carlo particle transport code based on inverse transform sampling for radiotherapy dose calculation Liang, Ying Muhammad, Wazir Hart, Gregory R. Nartowt, Bradley J. Chen, Zhe J. Yu, James B. Roberts, Kenneth B. Duncan, James S. Deng, Jun Sci Rep Article The Monte Carlo (MC) method is widely used to solve various problems in radiotherapy. There has been an impetus to accelerate MC simulation on GPUs whereas thread divergence remains a major issue for MC codes based on acceptance-rejection sampling. Inverse transform sampling has the potential to eliminate thread divergence but it is only implemented for photon transport. Here, we report a MC package Particle Transport in Media (PTM) to demonstrate the implementation of coupled photon-electron transport simulation using inverse transform sampling. Rayleigh scattering, Compton scattering, photo-electric effect and pair production are considered in an analogous manner for photon transport. Electron transport is simulated in a class II condensed history scheme, i.e., catastrophic inelastic scattering and Bremsstrahlung events are simulated explicitly while subthreshold interactions are subject to grouping. A random-hinge electron step correction algorithm and a modified PRESTA boundary crossing algorithm are employed to improve simulation accuracy. Benchmark studies against both EGSnrc simulations and experimental measurements are performed for various beams, phantoms and geometries. Gamma indices of the dose distributions are better than 99.6% for all the tested scenarios under the 2%/2 mm criteria. These results demonstrate the successful implementation of inverse transform sampling in coupled photon-electron transport simulation. Nature Publishing Group UK 2020-06-17 /pmc/articles/PMC7300009/ /pubmed/32555530 http://dx.doi.org/10.1038/s41598-020-66844-7 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Liang, Ying Muhammad, Wazir Hart, Gregory R. Nartowt, Bradley J. Chen, Zhe J. Yu, James B. Roberts, Kenneth B. Duncan, James S. Deng, Jun A general-purpose Monte Carlo particle transport code based on inverse transform sampling for radiotherapy dose calculation |
title | A general-purpose Monte Carlo particle transport code based on inverse transform sampling for radiotherapy dose calculation |
title_full | A general-purpose Monte Carlo particle transport code based on inverse transform sampling for radiotherapy dose calculation |
title_fullStr | A general-purpose Monte Carlo particle transport code based on inverse transform sampling for radiotherapy dose calculation |
title_full_unstemmed | A general-purpose Monte Carlo particle transport code based on inverse transform sampling for radiotherapy dose calculation |
title_short | A general-purpose Monte Carlo particle transport code based on inverse transform sampling for radiotherapy dose calculation |
title_sort | general-purpose monte carlo particle transport code based on inverse transform sampling for radiotherapy dose calculation |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7300009/ https://www.ncbi.nlm.nih.gov/pubmed/32555530 http://dx.doi.org/10.1038/s41598-020-66844-7 |
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