Development and implementation in the Monte Carlo code PENELOPE of a new virtual source model for radiotherapy photon beams and portal image calculation

Overview & Synopsis

This work aims at developing a generic virtual source model (VSM) preserving all existing correlations between variables stored in a Monte Carlo pre-computed phase space (PS) file, for dose calculation and high-resolution portal image prediction. The reference PS file was calculated using the PENELOPE code, after the flattening filter (FF) of an Elekta Synergy 6 MV photon beam. Each particle was represented in a mobile coordinate system by its radial position (r(s)) in the PS plane, its energy (E), and its polar and azimuthal angles (phi(d) and theta(d)), describing the particle deviation compared to its initial direction after bremsstrahlung, and the deviation orientation. Three sub-sources were created by sorting out particles according to their last interaction location (target, primary collimator or FF). For each sub-source, 4D correlated-histograms were built by storing E, r(s), phi(d) and theta(d) values. Five different adaptive binning schemes were studied to construct 4D histograms of the VSMs, to ensure histogram efficient handling as well as an accurate reproduction of E, r(s), phi(d) and theta(d) distribution details. The five resulting VSMs were then implemented in PENELOPE. Their accuracy was first assessed in the PS plane, by comparing E, r(s), phi(d) and theta(d) distributions with those obtained from the reference PS file. Second, dose distributions computed in water, using the VSMs and the reference PS file located below the FF, and also after collimation in both water and heterogeneous phantom, were compared using a 1.5%-0 mm and a 2%-0 mm global gamma index, respectively. Finally, portal images were calculated without and with phantoms in the beam. The model was then evaluated using a 1%-0 mm global gamma index. Performance of a mono-source VSM was also investigated and led, as with the multi-source model, to excellent results when combined with an adaptive binning scheme.