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A fast GPU-accelerated Monte Carlo engine for calculation of MLC-collimated electron fields.

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This study developed a fast GPU-accelerated Monte Carlo engine for calculating electron beam doses collimated by multi-leaf collimators (MLCs). This advancement enables rapid dose calculations for advanced electron beam therapies.

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CUDAGPUMonte Carloelectron-beam therapy

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Area of Science:

  • Medical Physics
  • Radiation Oncology
  • Computational Science

Background:

  • Photon external beam therapies have advanced significantly, while electron beam therapy has lagged.
  • Modern linear accelerators offer potential for advanced electron treatments, but dose calculation methods for multi-leaf collimator (MLC) electron beams are lacking.
  • Clinical adoption requires dose calculation times comparable to current algorithms.

Purpose of the Study:

  • To develop a graphics processing unit (GPU)-accelerated Monte Carlo (MC) engine for rapid dose calculation of electron beams collimated by a conventional photon MLC.
  • To incorporate the Varian TrueBeam linear accelerator head geometry into the MC engine.
  • To achieve clinically relevant dose calculation speeds.

Main Methods:

  • Developed a compute unified device architecture (CUDA) framework for simulating particle transport (electrons and photons) through linac head and CT geometries, including various interactions.
  • Modeled the linac head collimating geometry using vendor specifications and phase-space files.
  • Benchmarked the MC engine against established codes (EGSnrc/DOSXYZnrc/GEANT) and validated dose distributions against experimental measurements in water and with radiochromic film.

Main Results:

  • The GPU-based MC engine achieved dose distributions in good agreement with benchmark codes and experimental measurements for both MLC and jaw-collimated electron beams.
  • Dose profiles showed average absolute differences of 1.1 mm (FWHM) and 1.9 mm (80%-20% penumbra) compared to measurements.
  • Achieved a dose uncertainty of <1% in approximately 2.5 minutes on an NVIDIA Tesla V100 GPU, demonstrating a speed improvement of ~300 times over single-CPU core methods.

Conclusions:

  • The developed GPU-based MC engine enables rapid and accurate dose calculation for electron beams collimated with conventional photon MLCs.
  • The accelerated computation times facilitate the rapid calculation of electron fields, paving the way for mixed photon and electron particle therapy.
  • This technology addresses a critical gap in electron beam therapy planning and clinical implementation.