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Determination of Dose Distributions by Monte-Carlo Simulation of 6 MV Photon Beam of Varian VitalBeam Accelerator Using Geant4 Multithreaded Code

BACKGROUND: Accuracy of dose delivery in radiation therapy is a primary requirement for effective cancer treatment. In practice, dose delivery accuracy of ±5% is desired. To achieve this accuracy level, an accurate method for calculating the dose distributions in the tumor volume is required. Monte-...

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Autores principales: Chiuyo, Julius S., Lugendo, Innocent J., Muhogora, Wilbroad E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Wolters Kluwer - Medknow 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9543005/
https://www.ncbi.nlm.nih.gov/pubmed/36212206
http://dx.doi.org/10.4103/jmp.jmp_139_21
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author Chiuyo, Julius S.
Lugendo, Innocent J.
Muhogora, Wilbroad E.
author_facet Chiuyo, Julius S.
Lugendo, Innocent J.
Muhogora, Wilbroad E.
author_sort Chiuyo, Julius S.
collection PubMed
description BACKGROUND: Accuracy of dose delivery in radiation therapy is a primary requirement for effective cancer treatment. In practice, dose delivery accuracy of ±5% is desired. To achieve this accuracy level, an accurate method for calculating the dose distributions in the tumor volume is required. Monte-Carlo method is one of the methods considered to be the most accurate for calculating dose distributions. MATERIALS AND METHODS: G4 linac-MT code was used to simulate a 6 MV photon beam. The initial electron beam parameters were tuned to validate the beam modeling from depth doses and beam profile. The dose distributions measured in water phantom were compared to the calculated dose distributions based on gamma index criterion. RESULTS: The beam tuning showed the initial electron energy, sigma and full width at half maximum of 6.2 MeV, 0.8 MeV, and 1.18 mm, respectively, best match the measured dose distributions. The gamma index tests showed the calculated depth doses and beam profile were generally comparable with measurements, passing the standard acceptance criterion of 2%/2 mm. The simulated photon beam was justified by the index of beam quality, which showed excellent agreement with measured doses with a discrepancy of 0.1%. CONCLUSION: The observed agreement confirm the accuracy of the simulated 6 MV photon beam. It can therefore be used as radiation source for calculating dose distributions and further investigations aimed at improving dose delivery and planning in cancer patients.
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spelling pubmed-95430052022-10-08 Determination of Dose Distributions by Monte-Carlo Simulation of 6 MV Photon Beam of Varian VitalBeam Accelerator Using Geant4 Multithreaded Code Chiuyo, Julius S. Lugendo, Innocent J. Muhogora, Wilbroad E. J Med Phys Original Article BACKGROUND: Accuracy of dose delivery in radiation therapy is a primary requirement for effective cancer treatment. In practice, dose delivery accuracy of ±5% is desired. To achieve this accuracy level, an accurate method for calculating the dose distributions in the tumor volume is required. Monte-Carlo method is one of the methods considered to be the most accurate for calculating dose distributions. MATERIALS AND METHODS: G4 linac-MT code was used to simulate a 6 MV photon beam. The initial electron beam parameters were tuned to validate the beam modeling from depth doses and beam profile. The dose distributions measured in water phantom were compared to the calculated dose distributions based on gamma index criterion. RESULTS: The beam tuning showed the initial electron energy, sigma and full width at half maximum of 6.2 MeV, 0.8 MeV, and 1.18 mm, respectively, best match the measured dose distributions. The gamma index tests showed the calculated depth doses and beam profile were generally comparable with measurements, passing the standard acceptance criterion of 2%/2 mm. The simulated photon beam was justified by the index of beam quality, which showed excellent agreement with measured doses with a discrepancy of 0.1%. CONCLUSION: The observed agreement confirm the accuracy of the simulated 6 MV photon beam. It can therefore be used as radiation source for calculating dose distributions and further investigations aimed at improving dose delivery and planning in cancer patients. Wolters Kluwer - Medknow 2022 2022-08-05 /pmc/articles/PMC9543005/ /pubmed/36212206 http://dx.doi.org/10.4103/jmp.jmp_139_21 Text en Copyright: © 2022 Journal of Medical Physics https://creativecommons.org/licenses/by-nc-sa/4.0/This is an open access journal, and articles are distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as appropriate credit is given and the new creations are licensed under the identical terms.
spellingShingle Original Article
Chiuyo, Julius S.
Lugendo, Innocent J.
Muhogora, Wilbroad E.
Determination of Dose Distributions by Monte-Carlo Simulation of 6 MV Photon Beam of Varian VitalBeam Accelerator Using Geant4 Multithreaded Code
title Determination of Dose Distributions by Monte-Carlo Simulation of 6 MV Photon Beam of Varian VitalBeam Accelerator Using Geant4 Multithreaded Code
title_full Determination of Dose Distributions by Monte-Carlo Simulation of 6 MV Photon Beam of Varian VitalBeam Accelerator Using Geant4 Multithreaded Code
title_fullStr Determination of Dose Distributions by Monte-Carlo Simulation of 6 MV Photon Beam of Varian VitalBeam Accelerator Using Geant4 Multithreaded Code
title_full_unstemmed Determination of Dose Distributions by Monte-Carlo Simulation of 6 MV Photon Beam of Varian VitalBeam Accelerator Using Geant4 Multithreaded Code
title_short Determination of Dose Distributions by Monte-Carlo Simulation of 6 MV Photon Beam of Varian VitalBeam Accelerator Using Geant4 Multithreaded Code
title_sort determination of dose distributions by monte-carlo simulation of 6 mv photon beam of varian vitalbeam accelerator using geant4 multithreaded code
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9543005/
https://www.ncbi.nlm.nih.gov/pubmed/36212206
http://dx.doi.org/10.4103/jmp.jmp_139_21
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