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Development of a GPU-based dose calculation engine for MRI-guided proton therapy
Yue Gu1, Yuxiang Wang1,2, Meiqi Liu1
1Department of Engineering and Applied Physics, University of Science and Technology of China, Hefei, Anhui, China.
Medical Physics
|July 22, 2026
Summary
A new GPU-based dose engine, gPRIDE, provides fast and accurate calculations for MRI-guided proton therapy. It efficiently handles magnetic field effects, enabling clinical integration for improved cancer treatment.
Area of Science:
- Medical Physics
- Computational Science
- Radiotherapy Technology
Background:
- Magnetic resonance imaging (MRI)-guided proton therapy (MRPT) combines MRI's soft-tissue contrast with proton therapy's dose conformity.
- Clinical MRPT necessitates efficient and accurate dose calculation engines that account for magnetic field effects on proton beams.
Purpose of the Study:
- Develop a GPU-based proton and ion dose engine (gPRIDE) for rapid and precise dose calculations in MRPT.
- Enable realistic clinical configurations, including heterogeneous magnetic field effects.
Main Methods:
- Implemented a novel beam profile correction method to address magnetic focusing effects.
- Enhanced computational efficiency using region-of-interest calculations, linear ray tracing approximations, and hybrid GPU parallelization.
- Validated gPRIDE against Monte Carlo simulations in phantoms and patient cases with parallel and perpendicular magnetic field orientations.
Main Results:
- gPRIDE achieved >99% gamma passing rates (2%/2mm) in most cases, with >95% (3%/3mm) for challenging lung cases.
- Calculation times per plan ranged from 2.7 to 13.7 seconds on an NVIDIA GeForce RTX 3060 GPU.
- Demonstrated accuracy and efficiency across various patient anatomies and magnetic field configurations.
Conclusions:
- gPRIDE provides fast, accurate dose computations for MRPT under realistic 3D magnetic fields.
- The engine supports diverse beam orientations relative to the main magnetic field.
- gPRIDE's efficiency, accuracy, and versatility support its clinical integration into MRPT workflows.
