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ORIGINAL ARTICLE
Year : 2011  |  Volume : 7  |  Issue : 1  |  Page : 29-34

Monte Carlo study of dosimetric parameters and dose distribution effect of inhomogeneities and source position of GammaMed Plus source


1 Department of Radiotherapy, Pt. J.N.M. Medical College and Dr. B.R.A.M. Hospital, Raipur, Chhattisgarh, India
2 Department of Applied Physics, Bhilai Institute of Technology, Durg, Chhattisgarh, India
3 Department of Radiotherapy, C.S.M.M. University, Lucknow, Uttar Pradesh, India

Correspondence Address:
Rakesh M Chandola
Department of Radiotherapy, Pt. J.N.M. Medical College and Dr. B.R.A.M. Hospital, Raipur, Chhattisgarh
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/0973-1482.80453

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Background: The conventional treatment planning system (TPS) gives analytical calculations with approximately ±15?20% dose uncertainty, which may lead to over exposure of critical organs or under dose of target as well as the presence of inhomogeneities, and the position of source affects the exact dose calculation like in breast and intraluminal brachytherapy. Aim: To obtain dose distribution parameters of GammaMed Plus high dose rate (HDR) 192 Ir source using Monte Carlo (MC) EGSnrc and GEANT4 codes as well as to find the effect on dose distribution due to source position, and due to presence of air and cortical bone by using MC GEANT4 code, and to find the similarity of both studies with any past study of any HDR brachytherapy source for either as input to TPS or verification of TPS calculations. Settings and Design: It is done using different software of the computer, e.g., excel, MS word, etc. Materials and Methods: The source, source position for different studies, water phantom, water characteristics, points of measurements, air and cortical bone inhomogeneities, and position of inhomogeneities were simulated. Statistical Analysis Used: For uncertainties calculation, mean and probability are used. Results: The calculated dose rate constant, radial dose function, and 2D anisotropy function of the source show similarity with published data. Calculated dose distribution differences due to presence of air and cortical bone, and position of source in water phantom also show similarity with published data. Conclusion: These results can either be implemented in TPS or can be used for verification of TPS calculations.


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