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Session: Advanced Dosimetry and Monte Carlo Simulation [Return to Session]

A GPU-Accelerated Monte Carlo Dose Computation Engine for Precision Small Animal Radiotherapy

Z Liu, Y Yang*, University of Science and Technology of China, Hefei, China


WE-C930-IePD-F3-4 (Wednesday, 7/13/2022) 9:30 AM - 10:00 AM [Eastern Time (GMT-4)]

Exhibit Hall | Forum 3

Purpose: To develop a GPU-based Monte Carlo dose engine (GPUPT) for kV x-ray dose computation and evaluate its dose calculation accuracy in image-guided small animal radiation treatment.

Methods: The Woodcock algorithm and several acceleration techniques were adapted to develop the GPU-assisted dose computation algorithm. The depth-dose curves in both homogeneous water phantom and heterogeneous slab phantom were calculated using GPUPT and compared with that simulated using Geant4. Then, the GPUPT algorithm was further validated with dose distribution measured in a solid water phantom for radiation delivered on the iSMAART small animal radiotherapy platform. Finally, a conformal arc treatment plan was designed for a lung tumor to further evaluate the computation efficiency.

Results: The engine attained a speed-up of 1232 times in the homogeneous water phantom and 935 times in the bone-lung-water heterogeneous phantom when compared with Geant4. For different radiation field sizes, the depth-dose curves and cross-sectional beam profiles all showed decent matches between measurement and GPUPT computation. The computation time for an arc treatment plan delivered from 36 angles was just 7s when the voxel-based dose uncertainty was set to <1%.

Conclusion: The GPUPT can perform fast dose calculation in heterogeneous tissue environment, and is expected to play a vital role in image guided precision small animal radiation therapy.


Monte Carlo, Dose, Simulation


TH- Small Animal RT: Computational Dosimetry

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