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...
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Autor*in:	Delaram Pakravan [verfasserIn] Farshid Babapour Mofrad [verfasserIn] Mohammad Reza Deevband [verfasserIn] Mahdi Ghorbani [verfasserIn] Hamidreza Pouraliakbar [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2021

Schlagwörter:	tomography, x-ray computed monte carlo method dosimetry fan-beam ct system performance

Übergeordnetes Werk:	In: Journal of Biomedical Physics and Engineering - Shiraz University of Medical Sciences, 2012, 11(2021), 3, Seite 271-280
Übergeordnetes Werk:	volume:11 ; year:2021 ; number:3 ; pages:271-280

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc Journal toc

DOI / URN:	10.31661/jbpe.v0i0.2012-1254

Katalog-ID:	DOAJ067558836

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520			\|a 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 CTDI100 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.
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allfields	10.31661/jbpe.v0i0.2012-1254 doi (DE-627)DOAJ067558836 (DE-599)DOAJ10bd6da791bc4c68b73907dab82ad136 DE-627 ger DE-627 rakwb eng R895-920 Delaram Pakravan verfasserin aut A Monte Carlo Platform for Characterization of X-Ray Radiation Dose in CT Imaging 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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 CTDI100 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. tomography, x-ray computed monte carlo method dosimetry fan-beam ct system performance Medical physics. Medical radiology. Nuclear medicine Farshid Babapour Mofrad verfasserin aut Mohammad Reza Deevband verfasserin aut Mahdi Ghorbani verfasserin aut Hamidreza Pouraliakbar verfasserin aut In Journal of Biomedical Physics and Engineering Shiraz University of Medical Sciences, 2012 11(2021), 3, Seite 271-280 (DE-627)720166152 (DE-600)2673599-4 22517200 nnns volume:11 year:2021 number:3 pages:271-280 https://doi.org/10.31661/jbpe.v0i0.2012-1254 kostenfrei https://doaj.org/article/10bd6da791bc4c68b73907dab82ad136 kostenfrei https://jbpe.sums.ac.ir/article_47529_783ec0238e5a39d892a1830f6cd8cea1.pdf kostenfrei https://doaj.org/toc/2251-7200 Journal toc kostenfrei https://doaj.org/toc/2251-7200 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 11 2021 3 271-280
spelling	10.31661/jbpe.v0i0.2012-1254 doi (DE-627)DOAJ067558836 (DE-599)DOAJ10bd6da791bc4c68b73907dab82ad136 DE-627 ger DE-627 rakwb eng R895-920 Delaram Pakravan verfasserin aut A Monte Carlo Platform for Characterization of X-Ray Radiation Dose in CT Imaging 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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 CTDI100 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. tomography, x-ray computed monte carlo method dosimetry fan-beam ct system performance Medical physics. Medical radiology. Nuclear medicine Farshid Babapour Mofrad verfasserin aut Mohammad Reza Deevband verfasserin aut Mahdi Ghorbani verfasserin aut Hamidreza Pouraliakbar verfasserin aut In Journal of Biomedical Physics and Engineering Shiraz University of Medical Sciences, 2012 11(2021), 3, Seite 271-280 (DE-627)720166152 (DE-600)2673599-4 22517200 nnns volume:11 year:2021 number:3 pages:271-280 https://doi.org/10.31661/jbpe.v0i0.2012-1254 kostenfrei https://doaj.org/article/10bd6da791bc4c68b73907dab82ad136 kostenfrei https://jbpe.sums.ac.ir/article_47529_783ec0238e5a39d892a1830f6cd8cea1.pdf kostenfrei https://doaj.org/toc/2251-7200 Journal toc kostenfrei https://doaj.org/toc/2251-7200 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 11 2021 3 271-280
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allfieldsSound	10.31661/jbpe.v0i0.2012-1254 doi (DE-627)DOAJ067558836 (DE-599)DOAJ10bd6da791bc4c68b73907dab82ad136 DE-627 ger DE-627 rakwb eng R895-920 Delaram Pakravan verfasserin aut A Monte Carlo Platform for Characterization of X-Ray Radiation Dose in CT Imaging 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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 CTDI100 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. tomography, x-ray computed monte carlo method dosimetry fan-beam ct system performance Medical physics. Medical radiology. Nuclear medicine Farshid Babapour Mofrad verfasserin aut Mohammad Reza Deevband verfasserin aut Mahdi Ghorbani verfasserin aut Hamidreza Pouraliakbar verfasserin aut In Journal of Biomedical Physics and Engineering Shiraz University of Medical Sciences, 2012 11(2021), 3, Seite 271-280 (DE-627)720166152 (DE-600)2673599-4 22517200 nnns volume:11 year:2021 number:3 pages:271-280 https://doi.org/10.31661/jbpe.v0i0.2012-1254 kostenfrei https://doaj.org/article/10bd6da791bc4c68b73907dab82ad136 kostenfrei https://jbpe.sums.ac.ir/article_47529_783ec0238e5a39d892a1830f6cd8cea1.pdf kostenfrei https://doaj.org/toc/2251-7200 Journal toc kostenfrei https://doaj.org/toc/2251-7200 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 11 2021 3 271-280
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callnumber-first	R - Medicine
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spellingShingle	Delaram Pakravan misc R895-920 misc tomography, x-ray computed misc monte carlo method misc dosimetry misc fan-beam ct misc system performance misc Medical physics. Medical radiology. Nuclear medicine A Monte Carlo Platform for Characterization of X-Ray Radiation Dose in CT Imaging
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topic	misc R895-920 misc tomography, x-ray computed misc monte carlo method misc dosimetry misc fan-beam ct misc system performance misc Medical physics. Medical radiology. Nuclear medicine
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title_auth	A Monte Carlo Platform for Characterization of X-Ray Radiation Dose in CT Imaging
abstract	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 CTDI100 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.
abstractGer	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 CTDI100 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.
abstract_unstemmed	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 CTDI100 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.
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title_short	A Monte Carlo Platform for Characterization of X-Ray Radiation Dose in CT Imaging
url	https://doi.org/10.31661/jbpe.v0i0.2012-1254 https://doaj.org/article/10bd6da791bc4c68b73907dab82ad136 https://jbpe.sums.ac.ir/article_47529_783ec0238e5a39d892a1830f6cd8cea1.pdf https://doaj.org/toc/2251-7200
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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. 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Nuclear medicine</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Farshid Babapour Mofrad</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Mohammad Reza Deevband</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Mahdi Ghorbani</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Hamidreza Pouraliakbar</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">In</subfield><subfield code="t">Journal of Biomedical Physics and Engineering</subfield><subfield code="d">Shiraz University of Medical Sciences, 2012</subfield><subfield code="g">11(2021), 3, Seite 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A Monte Carlo Platform for Characterization of X-Ray Radiation Dose in CT Imaging

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