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

Jeff Craig,Jeff Chen,Eugene Wong,Adam Gladwish,Matt Mulligan,Mike Oliver

doi:10.1120/jacmp.v9i2.2702

Abstract

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

Highlights

84 Craig et al.: Commissioning a fast Monte Carlo dose calculation...materials with different densities, such as at the interface between lung and tissue.[13,14] A 5% difference is deemed unacceptable, given that an uncertainty of ±2% or better for dose distributions is usually sought to achieve an overall uncertainty of ±5% in delivering the dose to the patient.[15,16]Monte Carlo simulation consists using well-established interaction probability distributions to track individual interactions of electrons and photons through a representation of a patient’s anatomy
99% had a γ (3% and 3 mm thresholds) of 1 or less for the dose difference. These results indicate that FMC-NX is not as accurate as EGS4-NX, but that, overall, most of the dose distribution falls within ±0.03 cGy/monitor unit (MU) of BEAM
To provide a metric to compare the differences between FMC-NX and BEAM, we show in Fig. 7(a) the difference in dose distribution of a 10×10-cm, 18-MV beam calculated by collapsed cone convolution (CCC) in Pinnacle and by BEAM

Summary

Introduction

84 Craig et al.: Commissioning a fast Monte Carlo dose calculation...materials with different densities, such as at the interface between lung and tissue.[13,14] A 5% difference is deemed unacceptable, given that an uncertainty of ±2% or better for dose distributions is usually sought to achieve an overall uncertainty of ±5% in delivering the dose to the patient.[15,16]Monte Carlo simulation consists using well-established interaction probability distributions to track individual interactions of electrons and photons through a representation of a patient’s anatomy. For a given number of histories simulated, N, the standard deviation of the mean is proportional to 1 / N1/2, and for dose, D, within a scoring region, the relative statistical error is proportional to 1 / D1/2.(17) To eliminate all statistical uncertainties from the calculation, an infinite amount of time would have to be devoted to calculating the dose distribution, and so an acceptable level of random uncertainties must be accepted. Unlike the case with the CCC method, the time required to run a Monte Carlo simulation is independent of the number of beams used; instead, it depends on the number of histories. For multiple-field techniques such as intensity-modulated radiotherapy (IMRT), intensity-modulated arc therapy (IMAT),(18) and helical tomotherapy,(19) dose calculation time can be shortened by using Monte Carlo instead of CCC

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Discussion

Conclusion