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A Python package for fast GPU-based proton pencil beam dose calculation.

Mahasweta Bhattacharya1, Calin Reamy1, Heng Li1

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Summary
This summary is machine-generated.

A new Python package offers ultra-fast GPU-based proton dose calculation for intensity-modulated proton therapy (IMPT) research. This double Gaussian pencil beam (PB) method provides a simple, compatible solution, though accuracy may decrease in heterogeneous tissues.

Keywords:
dose calculationintensity modulated proton therapyproton therapy

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Area of Science:

  • Medical Physics
  • Computational Physics
  • Radiotherapy Research

Background:

  • Monte Carlo (MC) proton dose calculations offer high accuracy but are computationally intensive.
  • GPU-based pencil beam (PB) methods offer faster calculations but with some trade-off in physical accuracy.
  • Integrating advanced algorithms into research applications can be complex and time-consuming.

Purpose of the Study:

  • To develop and validate a GPU-based double Gaussian PB algorithm as a Python package.
  • To provide a simple, widely compatible, and ultra-fast proton dose calculation solution for intensity-modulated proton therapy (IMPT) planning research.
  • To enable rapid dose calculation for IMPT optimization research and development.

Main Methods:

  • Derived beam parameters from MC-generated pristine Bragg peaks for 98 energies.
  • Validated the PB algorithm against experimental measurements for pristine and spread-out Bragg peaks (SOBPs) in water.
  • Compared PB and MC calculations in a heterogeneous phantom and patient plans using gamma passing rates and dose metrics.

Main Results:

  • The PB algorithm achieved a computation time of 0.28 ± 0.07 seconds per patient plan, compared to 4.68 ± 2.68 seconds for MC.
  • Mean errors for sigma, R80, and SOBP dose were 0.05 ± 0.01, 0.0 ± 0.1 mm, and 0.4 ± 1.1%, respectively.
  • Accuracy degraded in heterogeneous regions like bone and lung due to inaccuracies in lateral proton scatter.

Conclusions:

  • A GPU-based proton PB algorithm was successfully implemented as a user-friendly Python package.
  • The developed package offers fast dose calculation suitable for IMPT planning research.
  • The algorithm's accuracy is limited in highly heterogeneous regions, similar to other PB methods.