Journal of Medical Physics
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ORIGINAL ARTICLE
Year : 2022  |  Volume : 47  |  Issue : 2  |  Page : 181-188

Determination of dose distributions by monte-carlo simulation of 6 MV photon beam of varian vitalbeam accelerator using geant4 multithreaded code


1 Department of Physics, University of Dar es Salaam, Tanzania
2 Directorate of Radiation Control, Tanzania Atomic Energy Agency, Arusha, Tanzania

Correspondence Address:
Dr. Julius S Chiuyo
University of Dar es Salaam, P. O. Box 35063, Dar es Salaam
Tanzania
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/jmp.jmp_139_21

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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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