Monte Carlo modelling of clinical accelerator beams and estimation of primary electron beam parameters

The accuracy of Monte Carlo simulations of clinical photon beams in radiation oncology is dependent on the linac head model accuracy and on parameters of the primary electron beam. While the internal composition and geometry of the accelerator head are known precisely, at least in principle, the energy spectrum and the spatial characteristics of the primary electron beam are unknown and immeasurable. The mean energy and FWHM of the electron beam are commonly estimated by comparing the simulation results with measured dosimetric data. Percentage depth doses (PDDs) and dose profiles are sensitive to changes in the electron beam parameters and are therefore in general used for the comparison. In the published studies which deal with parameter estimation, the determination of electron beam parameters is typically performed through a trial and error process. As to the parameter optimization, there is no unified methodology agreed upon, and the uncertainty of the resulting parameter values is usually not quantified by the authors. The aim of our work was not only to estimate the mean energy and the FWHM of the primary electron beam, but also to determine the confidence region of the optimized values in a defined and repeatable way. A model of Varian Clinac 2100C/D linear accelerator 6 MV photon beam was built in the EGSnrc/BEAMnrc Monte Carlo system. PDDs and dose profiles for different field sizes and different depths were obtained from water phantom measurements. We show that an approach based on a large number of simulations, each with a relatively low number of primary particles, in combination with non-linear regression methods allows to find both the optimized values of the electron beam parameters and their common 95% confidence region