Purpose: To develop a fast and accurate in-house Monte Carlo (MC) based secondary MU check method for independent verification of VMAT treatment planning system dose calculations, that would be in accordance with TG-114 recommendations.

Methods: For a VMAT patient treatment plan created for a Varian Trilogy linac, DICOM information was exported from Eclipse. An open-source platform was used to generate input files for dose calculations using the EGSnrc and DOSXYZnrc framework. The full VMAT plan simulation employed 10 7 histories, and was parallelized to run on a computer cluster. A dose calibration factor was determined by performing an MC simulation of standard reference dosimetry conditions. The resulting 3D dose matrices were converted to the DICOM format using CERR and imported into Eclipse. The method was evaluated by applying it to 35 actual clinical VMAT plans of various treatment sites. For each plan, the doses calculated with the MC approach at four 3D reference points were compared to the corresponding Eclipse calculations, as well as calculations performed using the clinical software package, MUCheck.

Results: Each MC arc simulation of 107 particles required 13--25 minutes of total time, including processing and calculation. The average discrepancies in calculated dose values between the MC method and Eclipse were 2.03% (compared to 3.43% for MUCheck) for prostate cases, 2.45% (3.22% for MUCheck) for head and neck cases, 1.7% (5.51% for MUCheck) for brain cases and 2.84% (5.64% for MUCheck) for miscellaneous cases. 201 of 276 comparisons showed greater agreement between TPS and Monte Carlo vs. MUCheck. The largest discrepancies were found in regions of high dose gradients and heterogeneous densities.

Conclusion: We have developed a method to perform accurate secondary MU checks for VMAT plans using the EGS MC framework. By parallelizing the calculations, point dose accuracies of 2--6%, sufficient for clinical secondary checks, can be achieved in a reasonable amount of time. As computer clusters and/or cloud computing become more widespread, this method will be useful in most clinical setups.