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A Gamma Analysis Approach to Determine Optimal Parameters for Monte Carlo Simulation of 6MV Varian Clinac iX Photon Beam
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作者 Roger Cai Xiang Soh lloyd kuan rui tan +4 位作者 Mark Sen Liang Goh Sitti Yani Freddy Haryanto Wen Siang Lew James Cheow Lei Lee 《Journal of Health Science》 2017年第1期36-43,共8页
Monte Carlo (MC) method is the gold standard dose calculation algorithm. Determination of the electron beam parameters for MC simulation is often estimated using trial and error methods. However, this can be tedious... Monte Carlo (MC) method is the gold standard dose calculation algorithm. Determination of the electron beam parameters for MC simulation is often estimated using trial and error methods. However, this can be tedious and time-consuming. This paper aims to validate MC simulated data using 1D gamma analysis for 6MV photon beam to obtain the optimal parameters. BEAMnrc codes were used to generate phase space files for conventional field sizes 10 × 10 cm^2, 6 × 6 cm^2, 4 × 4 cm^2 and small field sizes 2 ×2 cm^2, 1 ×1 cm^2, 0.5 ×0.5 cm^2. For conventional field sizes, simulations were benchmarked against Golden Beam Data (GBD). Simulations for small fields were benchmarked against measurements obtained using EDGE Detector and PTW Diode SRS detector in a Sun Nuclear 3D scanner. Dose profiles in water were calculated using DOSXYZnrc codes. Initial reference parameters were approximated using average percentage dose differences of different mean electron energy and electron beam radial distribution (Full Width at Half Maximum, FWHM). Subsequently, the optimal parameters were validated by 1D gamma analysis using varying gamma criteria from γ3%%/0.3mm to γ2.0%/2.0mm for depth dose and lateral dose profiles. Comparisons were performed along the central region at depth dose 1.6 cm . Optimal parameters were found to be unique for small field sizes. As field size decreases, smaller FWHM were required to match measured data. By using 95% passing rate, a generic set of optimal electron beam parameters in a MC model for all field sizes could be accurately determined. Our findings provide MC users a set of optimal parameters with sufficient accuracy for MC simulation work. 展开更多
关键词 Monte Carlo ID gamma analysis optimal parameters small fields.
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