Monte Carlo Commissioning of Low Energy Electron Radiotherapy Beams using NXEGS Software

Modeling the head of PRIMUS linear accelerator for electron-mode at 10 MeV for different applicators

OBJECTIVE

This study is to validate the utilization of Monte Carlo (MC) simulation to model the head of Primus linear accelerator, thereafter, using it to estimate the energy fluence distribution (EFD), the percentage depth dose (PDD), and beam profiles.

MATERIALS AND METHODS

The BEAMNRC code that is based on the EGSNRC code has been used for modeling the linear accelerator head for 10 MeV electron beam with different applicator sizes (10 × 10, 15 × 15, and 20 × 20 cm2 ). The phase space was acquired from BEAMNRC at the end of each applicator and then used as an input file to DOSXYZNRC and BEAMDP to calculate the EFD, PDD, and beam profiles.

RESULTS

There were a good consistency between the outcomes of the MC simulation and measured PDD and off-axis dose profiles that performed in a water phantom for all applicators. The PDD for the applicators proved to be favorable as a direct comparison of R100 , R90 , R80 , and R50 yielded results of < 2 mm, while it was 6 mm in R100 for the applicator 15 × 15 cm2 . The discrepancies in the surface doses (<3%) showed a quick decline in the build-up region and differences reached 0% within the first 2.4 mm. For the beam profiles comparison, the differences ranged from 2% (2 mm) to 3% (6 mm) for all applicators.

CONCLUSION

Our examination demonstrated that the MC simulation by BEAMNRC code was accurate in modeling the Primus linear accelerator head.

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