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Geant4-based Monte Carlo simulations on GPU for medical applications.

Julien Bert1, Hector Perez-Ponce, Ziad El Bitar

  • 1LaTIM, UMR 1101 INSERM, CHRU Brest, Brest, France. julien.bert@univ-brest.fr

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Graphics processing units (GPUs) accelerate Monte Carlo simulations (MCS) for medical imaging and radiotherapy. This new framework achieves significant speedups, enabling faster clinical applications.

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Area of Science:

  • Medical Physics
  • Computational Science
  • Medical Imaging

Background:

  • Monte Carlo simulations (MCS) are crucial for medical applications like emission tomography and radiotherapy.
  • Long calculation times currently limit the clinical use of MCS.
  • Graphics processing units (GPUs) offer a cost-effective solution for high-performance computing.

Purpose of the Study:

  • To develop an efficient framework for implementing MCS on GPU architectures.
  • To leverage the Geant4 simulation engine for medical imaging and radiotherapy applications.
  • To accelerate complex simulations without compromising physics accuracy.

Main Methods:

  • Implemented a global strategy and data structures for GPU-based MCS.
  • Utilized the Geant4 toolkit as the core simulation engine.
  • Resolved photon and electron physics processes directly on the GPU without approximations.

Main Results:

  • Achieved a speedup factor of 80-90 for photon and electron physics processes compared to CPU-based Geant4.
  • Demonstrated acceleration factors of 400-800 for clinically realistic emission and transmission imaging simulations compared to GATE.
  • Validated the equivalence of physics processes between the GPU and Geant4 codes.

Conclusions:

  • The developed GPU-based framework significantly accelerates Monte Carlo simulations for medical applications.
  • This advancement facilitates the integration of high-fidelity simulations into routine clinical practice.
  • The approach maintains the accuracy of Geant4 physics while drastically reducing computation time.