Literature DB >> 23732697

GPU-based Monte Carlo radiotherapy dose calculation using phase-space sources.

Reid W Townson1, Xun Jia, Zhen Tian, Yan Jiang Graves, Sergei Zavgorodni, Steve B Jiang.   

Abstract

A novel phase-space source implementation has been designed for graphics processing unit (GPU)-based Monte Carlo dose calculation engines. Short of full simulation of the linac head, using a phase-space source is the most accurate method to model a clinical radiation beam in dose calculations. However, in GPU-based Monte Carlo dose calculations where the computation efficiency is very high, the time required to read and process a large phase-space file becomes comparable to the particle transport time. Moreover, due to the parallelized nature of GPU hardware, it is essential to simultaneously transport particles of the same type and similar energies but separated spatially to yield a high efficiency. We present three methods for phase-space implementation that have been integrated into the most recent version of the GPU-based Monte Carlo radiotherapy dose calculation package gDPM v3.0. The first method is to sequentially read particles from a patient-dependent phase-space and sort them on-the-fly based on particle type and energy. The second method supplements this with a simple secondary collimator model and fluence map implementation so that patient-independent phase-space sources can be used. Finally, as the third method (called the phase-space-let, or PSL, method) we introduce a novel source implementation utilizing pre-processed patient-independent phase-spaces that are sorted by particle type, energy and position. Position bins located outside a rectangular region of interest enclosing the treatment field are ignored, substantially decreasing simulation time with little effect on the final dose distribution. The three methods were validated in absolute dose against BEAMnrc/DOSXYZnrc and compared using gamma-index tests (2%/2 mm above the 10% isodose). It was found that the PSL method has the optimal balance between accuracy and efficiency and thus is used as the default method in gDPM v3.0. Using the PSL method, open fields of 4 × 4, 10 × 10 and 30 × 30 cm(2) in water resulted in gamma passing rates of 99.96%, 99.92% and 98.66%, respectively. Relative output factors agreed within 1%. An intensity modulated radiation therapy patient plan using the PSL method resulted in a passing rate of 97%, and was calculated in 50 s (per GPU) compared to 8.4 h (per CPU) for BEAMnrc/DOSXYZnrc.

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Year:  2013        PMID: 23732697     DOI: 10.1088/0031-9155/58/12/4341

Source DB:  PubMed          Journal:  Phys Med Biol        ISSN: 0031-9155            Impact factor:   3.609


  9 in total

1.  Initial development of goCMC: a GPU-oriented fast cross-platform Monte Carlo engine for carbon ion therapy.

Authors:  Nan Qin; Marco Pinto; Zhen Tian; Georgios Dedes; Arnold Pompos; Steve B Jiang; Katia Parodi; Xun Jia
Journal:  Phys Med Biol       Date:  2017-01-31       Impact factor: 3.609

2.  ARCHERRT - a GPU-based and photon-electron coupled Monte Carlo dose computing engine for radiation therapy: software development and application to helical tomotherapy.

Authors:  Lin Su; Youming Yang; Bryan Bednarz; Edmond Sterpin; Xining Du; Tianyu Liu; Wei Ji; X George Xu
Journal:  Med Phys       Date:  2014-07       Impact factor: 4.071

Review 3.  GPU-based high-performance computing for radiation therapy.

Authors:  Xun Jia; Peter Ziegenhein; Steve B Jiang
Journal:  Phys Med Biol       Date:  2014-02-03       Impact factor: 3.609

4.  GPU-accelerated Monte Carlo simulation of MV-CBCT.

Authors:  Mengying Shi; Marios Myronakis; Matthew Jacobson; Dianne Ferguson; Christopher Williams; Mathias Lehmann; Paul Baturin; Pascal Huber; Rony Fueglistaller; Ingrid Valencia Lozano; Thomas Harris; Daniel Morf; Ross I Berbeco
Journal:  Phys Med Biol       Date:  2020-12-02       Impact factor: 4.174

5.  A rapid, accurate image simulation strategy for mega-voltage cone-beam computed tomography.

Authors:  Mengying Shi; Marios Myronakis; Matthew Jacobson; Mathias Lehmann; Dianne Ferguson; Paul Baturin; Pascal Huber; Rony Fueglistaller; Thomas Harris; Ingrid Valencia Lozano; Christopher Williams; Daniel Morf; Ross I Berbeco
Journal:  Phys Med Biol       Date:  2020-07-06       Impact factor: 4.174

6.  Moving GPU-OpenCL-based Monte Carlo dose calculation toward clinical use: Automatic beam commissioning and source sampling for treatment plan dose calculation.

Authors:  Zhen Tian; Yongbao Li; Nima Hassan-Rezaeian; Steve B Jiang; Xun Jia
Journal:  J Appl Clin Med Phys       Date:  2017-02-16       Impact factor: 2.102

7.  A high-resolution dose calculation engine for X-ray microbeams radiation therapy.

Authors:  Sarvenaz Keshmiri; Sylvan Brocard; Raphaël Serduc; Jean-François Adam
Journal:  Med Phys       Date:  2022-04-12       Impact factor: 4.506

8.  A phase space model of a Versa HD linear accelerator for application to Monte Carlo dose calculation in a real-time adaptive workflow.

Authors:  James L Bedford; Rahul Nilawar; Simeon Nill; Uwe Oelfke
Journal:  J Appl Clin Med Phys       Date:  2022-06-14       Impact factor: 2.243

9.  A fast jaw-tracking model for VMAT and IMRT Monte Carlo simulations.

Authors:  Reid Townson; Hilary Egglestone; Sergei Zavgorodni
Journal:  J Appl Clin Med Phys       Date:  2018-05-09       Impact factor: 2.102

  9 in total

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