Commissioning a fast Monte Carlo dose calculation algorithm for lung cancer treatment planning

A commercial Monte Carlo simulation package, NXEGS 1.12 (NumeriX LLC, New York, NY), was commissioned for photon‐beam dose calculations. The same sets of measured data from 6‐MV and 18‐MV beams were used to commission NXEGS and Pinnacle 6.2b (Philips Medical Systems, Andover, MA). Accuracy and efficiency were compared against the collapsed cone convolution algorithm implemented in Pinnacle 6.2b, together with BEAM simulation (BEAMnrc 2001: National Research Council of Canada, Ottawa, ON). We investigated a number of options in NXEGS: the accuracy of fast Monte Carlo, the re‐implementation of EGS4, post‐processing technique (dose de‐noising algorithm), and dose calculation time. Dose distributions were calculated with NXEGS, Pinnacle, and BEAM in water, lung‐slab, and air‐cylinder phantoms and in a lung patient plan. We compared the dose distributions calculated by NXEGS, Pinnacle, and BEAM. In a selected region of interest (7725 voxels) in the lung phantom, all but 1 voxel had a γ (3% and 3 mm thresholds) of 1 or less for the dose difference between the NXEGS re‐implementation of EGS4 and BEAM, and 99% of the voxels had a γ of 1 or less for the dose difference between NXEGS fast Monte Carlo and BEAM. Fast Monte Carlo with post‐processing was up to 100 times faster than the NXEGS re‐implementation of EGS4, while maintaining ± 2 % statistical uncertainty. With air inhomogeneities larger than 1 cm, post‐processing preserves the dose perturbations from the air cylinder. When 3 or more beams were used, fast Monte Carlo with post‐processing was comparable to or faster than Pinnacle 6.2b collapsed cone convolution. PACS numbers: 87.18.Bb, 87.53.Wz