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GPU-based ultra fast dose calculation using a finite pencil beam model

Xuejun Gu, Dongju Choi, Chunhua Men, Hubert Pan, Amitava Majumdar, Steve B. Jiang
Department of Radiation Oncology, University of California San Diego, La Jolla, CA 92037-0843
Physics in Medicine and Biology, Volume 54, Issue 20, pp. 6287-6297 (2009), arXiv:0908.4417 [physics.med-ph] (30 Aug 2009)

@article{gu2009gpu,

   title={GPU-based ultra-fast dose calculation using a finite size pencil beam model},

   author={Gu, X. and Choi, D. and Men, C. and Pan, H. and Majumdar, A. and Jiang, S.B.},

   journal={Physics in medicine and biology},

   volume={54},

   pages={6287},

   year={2009},

   publisher={IOP Publishing}

}

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Online adaptive radiation therapy (ART) is an attractive concept that promises the ability to deliver an optimal treatment in response to the inter-fraction variability in patient anatomy. However, it has yet to be realized due to technical limitations. Fast dose deposit coefficient calculation is a critical component of the online planning process that is required for plan optimization of intensity modulated radiation therapy (IMRT). Computer graphics processing units (GPUs) are well-suited to provide the requisite fast performance for the data-parallel nature of dose calculation. In this work, we develop a dose calculation engine based on a finite-size pencil beam (FSPB) algorithm and a GPU parallel computing framework. The developed framework can accommodate any FSPB model. We test our implementation on a case of a water phantom and a case of a prostate cancer patient with varying beamlet and voxel sizes. All testing scenarios achieved speedup ranging from 200~400 times when using a NVIDIA Tesla C1060 card in comparison with a 2.27GHz Intel Xeon CPU. The computational time for calculating dose deposition coefficients for a 9-field prostate IMRT plan with this new framework is less than 1 second. This indicates that the GPU-based FSPB algorithm is well-suited for online re-planning for adaptive radiotherapy.
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