A Novel GPU-based Fast Monte Carlo Photon Dose Calculating Method for Accurate Radiotherapy Treatment Planning

M Karbalaee, D Shahbazi-Gahrouei, M B Tavakoli


Objective: This work aimed to create a novel GPU-based fast Monte Carlo Photon Dose Code (called MCPDC in this work) as a fast and accurate tool in dose calculation for radiotherapy treatment planning.

Materials and Methods: MCPDC was written to implement photon Monte Carlo simulation for energies in the range of 0.01–20 MeV and run on an NVIDIA GTX970. The code was validated using DOSXYZnrc results and experimental measurements, performed by a Mapcheck dosimeter. Using the innovative definition of photon and electron interactions, the average calculation time for the MCPDC was 5.4 sec for 5e7 source particle history, significantly less than that of DOSXYZnrc which was 400 min.

Results: Considering the simulations in the anthropomorphic phantom with bone and lung inhomogeneity, in all cases, 96.1% or more of all significant voxels passed the gamma criteria of 3%-3 mm. Compared to the experimental dosimetry results, 97.6% or more of all significant voxels passed the acceptable clinical gamma index of 3%-3 mm.

Conclusion: Very fast calculation speed and high accuracy in dose calculation may allow the MCPDC to be used in routine radiotherapy clinics as a central component of a treatment plan verification system and also as the dose calculation engine for MC-based planning. MCPDC is currently being developed for electron dose calculation module and graphic user interface. In addition, future work on the applicability of the improved version of the MCPDC in transit dosimetry of megavoltage CT is in process.


Radiotherapy Treatment Planning, Dosimetry, Fast Monte Carlo, Parallel Processing, DOSXYZnrc, GPU, CUDA

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DOI: https://doi.org/10.22086/jbpe.v0i0.716

eISSN: 2251-7200        JBPE NLM ID: 101589641

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                                                                        Chairman and Editor in Chief

                                                                              Dr. Alireza Mehdizadeh

This work is licensed under a Creative Commons Attribution-NonCommercial 3.0 Unported License.

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