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We have developed a fast and accurate in-house Monte Carlo (MC) secondary monitor unit (MU) check method, based on the EGSnrc system, for independent verification of volumetric modulated arc therapy (VMAT) treatment planning system dose calculations, in accordance with TG-114 recommendations. For a VMAT 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 framework. The full VMAT plan simulation employed 107 histories, and was parallelized to run on a computer cluster. The resulting 3ddose matrices were converted to the DICOM format using CERR and imported into Eclipse. The method was evaluated using 35 clinical VMAT plans of various treatment sites. For each plan, the doses calculated with the MC approach at four three-dimensional reference points were compared to the corresponding Eclipse calculations, as well as calculations performed using the clinical software package, MUCheck. Each MC arc simulation of 107 particles required 13-25 min 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. Of 276 comparisons, 201 showed greater agreement between the treatment planning system and MC vs MUCheck. The largest discrepancies between MC and MUCheck were found in regions of high dose gradients and heterogeneous densities. By parallelizing the calculations, point-dose accuracies of 2-7%, 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.
Pubmed ID: 31127699
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Multi paradigm numerical computing environment and fourth generation programming language developed by MathWorks. Allows matrix manipulations, plotting of functions and data, implementation of algorithms, creation of user interfaces, and interfacing with programs written in other languages, including C, C++, Java, Fortran and Python. Used to explore and visualize ideas and collaborate across disciplines including signal and image processing, communications, control systems, and computational finance.
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