Department of Radiation Oncology,National Cancer Center/Cancer Hospital,Chinese Academy of Medical Science,Peking Union Medical Collage,Beijing 100021,China
Abstract： Objective To obtain the high-resolution dose distribution for the single source channel of Leksell 4C gamma knife. Methods A parallel computing platform based on the Message Passing Interface (MPI) and Monte Carlo Code MCNPX was established. The ring-shaped detector and two pre-validated variance reduction techniques (emission direction-biased sampling of source and termination of electron tracking in partial structures) were adopted to derive the high-resolution dose distribution for the single source channel of Leksell 4C gamma knife. The effect of cut-off energy for both photon and electron on the accuracy of simulation outcomes was evaluated and statistically compared. Results Compared with previous findings,the spatial resolution of the dose distribution for the single source channel obtained in this study was higher (radial resolution=0.1 mm) with less statistical error (<1%).The calculation time was acceptable (approximately 24 h).For the 4-,8-,14-and 18-mm variable collimators,the penumbra and full width at the half maximum (FWHM) for single side were 1.0,1.1,1.2,1.3 mm and 2.2,4.3,7.3,9.3 mm,respectively,which were consistent with previous studies. The difference of the simulation results was extremely small between different cut-off energy for photon (1 keV vs.10 keV).However,the simulation results significantly differ between 1 and 521 keV electronic cut-off energy. Conclusions The MCNPX parallel computing platform based on the MPI environment can be utilized to derive highly accurate dose distribution with high resolution in acceptable calculation time. The cut-off energy of the photon and electron should be cautiously set up during simulation.
Tian Yuan,Xu Yingjie,Song Yixin et al. Monte Carlo simulation of accurate dose distribution with high resolution for the single source channel of Leksell 4C gamma knife[J]. Chinese Journal of Radiation Oncology, 2018, 27(8): 780-783.
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2018, Vol. 27 
