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A Monte Carlo Platform for Characterization of X-Ray Radiation Dose in CT Imaging
BACKGROUND: Computed tomography (CT) is currently known as a versatile imaging tool in the clinic used for almost all types of cancers. The major issue of CT is the health risk, belonging to X-ray radiation exposure. Concerning this, Monte Carlo (MC) simulation is recognized as a key computational t...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Shiraz University of Medical Sciences
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8236108/ https://www.ncbi.nlm.nih.gov/pubmed/34189115 http://dx.doi.org/10.31661/jbpe.v0i0.2012-1254 |
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author | Pakravan, Delaram Babapour Mofrad, Farshid Deevband, Mohammad Reza Ghorbani, Mahdi Pouraliakbar, Hamidreza |
author_facet | Pakravan, Delaram Babapour Mofrad, Farshid Deevband, Mohammad Reza Ghorbani, Mahdi Pouraliakbar, Hamidreza |
author_sort | Pakravan, Delaram |
collection | PubMed |
description | BACKGROUND: Computed tomography (CT) is currently known as a versatile imaging tool in the clinic used for almost all types of cancers. The major issue of CT is the health risk, belonging to X-ray radiation exposure. Concerning this, Monte Carlo (MC) simulation is recognized as a key computational technique for estimating and optimizing radiation dose. CT simulation with MCNP/MCNPX MC code has an inherent problem due to the lack of a fan-beam shaped source model. This limitation increases the run time and highly decreases the number of photons passing the body or phantom. Recently, a beta version of MCNP code called MCNP-FBSM (Fan-Beam Source Model) has been developed to pave the simulation way of CT imaging procedure, removing the need of the collimator. This is a new code, which needs to be validated in all aspects. OBJECTIVE: In this work, we aimed to develop and validate an efficient computational platform based on modified MCNP-FBSM for CT dosimetry purposes. MATERIAL AND METHODS: In this experimental study, a setup is carried out to measure CTDI(100) in air and standard dosimetry phantoms. The accuracy of the developed MC CT simulator results has been widely benchmarked through comparison with our measured data, UK’s National Health Service’s reports (known as ImPACT), manufacturer’s data, and other published results. RESULTS: The minimum and maximum observed mean differences of our simulation results and other above-mentioned data were the 1.5%, and 9.79%, respectively. CONCLUSION: The developed FBSM MC computational platform is a beneficial tool for CT dosimetry. |
format | Online Article Text |
id | pubmed-8236108 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Shiraz University of Medical Sciences |
record_format | MEDLINE/PubMed |
spelling | pubmed-82361082021-06-28 A Monte Carlo Platform for Characterization of X-Ray Radiation Dose in CT Imaging Pakravan, Delaram Babapour Mofrad, Farshid Deevband, Mohammad Reza Ghorbani, Mahdi Pouraliakbar, Hamidreza J Biomed Phys Eng Original Article BACKGROUND: Computed tomography (CT) is currently known as a versatile imaging tool in the clinic used for almost all types of cancers. The major issue of CT is the health risk, belonging to X-ray radiation exposure. Concerning this, Monte Carlo (MC) simulation is recognized as a key computational technique for estimating and optimizing radiation dose. CT simulation with MCNP/MCNPX MC code has an inherent problem due to the lack of a fan-beam shaped source model. This limitation increases the run time and highly decreases the number of photons passing the body or phantom. Recently, a beta version of MCNP code called MCNP-FBSM (Fan-Beam Source Model) has been developed to pave the simulation way of CT imaging procedure, removing the need of the collimator. This is a new code, which needs to be validated in all aspects. OBJECTIVE: In this work, we aimed to develop and validate an efficient computational platform based on modified MCNP-FBSM for CT dosimetry purposes. MATERIAL AND METHODS: In this experimental study, a setup is carried out to measure CTDI(100) in air and standard dosimetry phantoms. The accuracy of the developed MC CT simulator results has been widely benchmarked through comparison with our measured data, UK’s National Health Service’s reports (known as ImPACT), manufacturer’s data, and other published results. RESULTS: The minimum and maximum observed mean differences of our simulation results and other above-mentioned data were the 1.5%, and 9.79%, respectively. CONCLUSION: The developed FBSM MC computational platform is a beneficial tool for CT dosimetry. Shiraz University of Medical Sciences 2021-06-01 /pmc/articles/PMC8236108/ /pubmed/34189115 http://dx.doi.org/10.31661/jbpe.v0i0.2012-1254 Text en Copyright: © Journal of Biomedical Physics and Engineering https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 Unported License, ( http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) ) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Article Pakravan, Delaram Babapour Mofrad, Farshid Deevband, Mohammad Reza Ghorbani, Mahdi Pouraliakbar, Hamidreza A Monte Carlo Platform for Characterization of X-Ray Radiation Dose in CT Imaging |
title | A Monte Carlo Platform for Characterization of X-Ray Radiation Dose in CT Imaging |
title_full | A Monte Carlo Platform for Characterization of X-Ray Radiation Dose in CT Imaging |
title_fullStr | A Monte Carlo Platform for Characterization of X-Ray Radiation Dose in CT Imaging |
title_full_unstemmed | A Monte Carlo Platform for Characterization of X-Ray Radiation Dose in CT Imaging |
title_short | A Monte Carlo Platform for Characterization of X-Ray Radiation Dose in CT Imaging |
title_sort | monte carlo platform for characterization of x-ray radiation dose in ct imaging |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8236108/ https://www.ncbi.nlm.nih.gov/pubmed/34189115 http://dx.doi.org/10.31661/jbpe.v0i0.2012-1254 |
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