Literature DB >> 23128424

GPU-based fast Monte Carlo dose calculation for proton therapy.

Xun Jia1, Jan Schümann, Harald Paganetti, Steve B Jiang.   

Abstract

Accurate radiation dose calculation is essential for successful proton radiotherapy. Monte Carlo (MC) simulation is considered to be the most accurate method. However, the long computation time limits it from routine clinical applications. Recently, graphics processing units (GPUs) have been widely used to accelerate computationally intensive tasks in radiotherapy. We have developed a fast MC dose calculation package, gPMC, for proton dose calculation on a GPU. In gPMC, proton transport is modeled by the class II condensed history simulation scheme with a continuous slowing down approximation. Ionization, elastic and inelastic proton nucleus interactions are considered. Energy straggling and multiple scattering are modeled. Secondary electrons are not transported and their energies are locally deposited. After an inelastic nuclear interaction event, a variety of products are generated using an empirical model. Among them, charged nuclear fragments are terminated with energy locally deposited. Secondary protons are stored in a stack and transported after finishing transport of the primary protons, while secondary neutral particles are neglected. gPMC is implemented on the GPU under the CUDA platform. We have validated gPMC using the TOPAS/Geant4 MC code as the gold standard. For various cases including homogeneous and inhomogeneous phantoms as well as a patient case, good agreements between gPMC and TOPAS/Geant4 are observed. The gamma passing rate for the 2%/2 mm criterion is over 98.7% in the region with dose greater than 10% maximum dose in all cases, excluding low-density air regions. With gPMC it takes only 6-22 s to simulate 10 million source protons to achieve ∼1% relative statistical uncertainty, depending on the phantoms and energy. This is an extremely high efficiency compared to the computational time of tens of CPU hours for TOPAS/Geant4. Our fast GPU-based code can thus facilitate the routine use of MC dose calculation in proton therapy.

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Year:  2012        PMID: 23128424      PMCID: PMC4474737          DOI: 10.1088/0031-9155/57/23/7783

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


  32 in total

1.  Dose calculation models for proton treatment planning using a dynamic beam delivery system: an attempt to include density heterogeneity effects in the analytical dose calculation.

Authors:  B Schaffner; E Pedroni; A Lomax
Journal:  Phys Med Biol       Date:  1999-01       Impact factor: 3.609

2.  GPU-based fast cone beam CT reconstruction from undersampled and noisy projection data via total variation.

Authors:  Xun Jia; Yifei Lou; Ruijiang Li; William Y Song; Steve B Jiang
Journal:  Med Phys       Date:  2010-04       Impact factor: 4.071

3.  A particle track-repeating algorithm for proton beam dose calculation.

Authors:  J S Li; B Shahine; E Fourkal; C-M Ma
Journal:  Phys Med Biol       Date:  2005-02-17       Impact factor: 3.609

4.  GPU-based ultrafast IMRT plan optimization.

Authors:  Chunhua Men; Xuejun Gu; Dongju Choi; Amitava Majumdar; Ziyi Zheng; Klaus Mueller; Steve B Jiang
Journal:  Phys Med Biol       Date:  2009-10-14       Impact factor: 3.609

5.  Fast convolution-superposition dose calculation on graphics hardware.

Authors:  Sami Hissoiny; Benoît Ozell; Philippe Després
Journal:  Med Phys       Date:  2009-06       Impact factor: 4.071

6.  A pencil beam algorithm for proton dose calculations.

Authors:  L Hong; M Goitein; M Bucciolini; R Comiskey; B Gottschalk; S Rosenthal; C Serago; M Urie
Journal:  Phys Med Biol       Date:  1996-08       Impact factor: 3.609

7.  Accelerating Monte Carlo simulations of photon transport in a voxelized geometry using a massively parallel graphics processing unit.

Authors:  Andreu Badal; Aldo Badano
Journal:  Med Phys       Date:  2009-11       Impact factor: 4.071

8.  A technique for the quantitative evaluation of dose distributions.

Authors:  D A Low; W B Harms; S Mutic; J A Purdy
Journal:  Med Phys       Date:  1998-05       Impact factor: 4.071

9.  Implementation and evaluation of various demons deformable image registration algorithms on a GPU.

Authors:  Xuejun Gu; Hubert Pan; Yun Liang; Richard Castillo; Deshan Yang; Dongju Choi; Edward Castillo; Amitava Majumdar; Thomas Guerrero; Steve B Jiang
Journal:  Phys Med Biol       Date:  2010-01-07       Impact factor: 3.609

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

Authors:  Xuejun Gu; Dongju Choi; Chunhua Men; Hubert Pan; Amitava Majumdar; Steve B Jiang
Journal:  Phys Med Biol       Date:  2009-10-01       Impact factor: 3.609

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  40 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.  Robust optimization for intensity-modulated proton therapy with soft spot sensitivity regularization.

Authors:  Wenbo Gu; Dan Ruan; Daniel O'Connor; Wei Zou; Lei Dong; Min-Yu Tsai; Xun Jia; Ke Sheng
Journal:  Med Phys       Date:  2019-01-21       Impact factor: 4.071

3.  Experimental depth dose curves of a 67.5 MeV proton beam for benchmarking and validation of Monte Carlo simulation.

Authors:  Bruce A Faddegon; Jungwook Shin; Carlos M Castenada; José Ramos-Méndez; Inder K Daftari
Journal:  Med Phys       Date:  2015-07       Impact factor: 4.071

4.  Monte Carlo simulations will change the way we treat patients with proton beams today.

Authors:  H Paganetti
Journal:  Br J Radiol       Date:  2014-06-04       Impact factor: 3.039

Review 5.  Empowering Intensity Modulated Proton Therapy Through Physics and Technology: An Overview.

Authors:  Radhe Mohan; Indra J Das; Clifton C Ling
Journal:  Int J Radiat Oncol Biol Phys       Date:  2017-10-01       Impact factor: 7.038

6.  DICOM-RT Ion interface to utilize MC simulations in routine clinical workflow for proton pencil beam radiotherapy.

Authors:  Jungwook Shin; Hanne M Kooy; Harald Paganetti; Benjamin Clasie
Journal:  Phys Med       Date:  2020-05-07       Impact factor: 2.685

7.  Density overwrites of internal tumor volumes in intensity modulated proton therapy plans for mobile lung tumors.

Authors:  Pablo Botas; Clemens Grassberger; Gregory Sharp; Harald Paganetti
Journal:  Phys Med Biol       Date:  2018-01-30       Impact factor: 3.609

8.  A full-scale clinical prototype for proton range verification using prompt gamma-ray spectroscopy.

Authors:  Fernando Hueso-González; Moritz Rabe; Thomas A Ruggieri; Thomas Bortfeld; Joost M Verburg
Journal:  Phys Med Biol       Date:  2018-09-17       Impact factor: 3.609

9.  Recent developments and comprehensive evaluations of a GPU-based Monte Carlo package for proton therapy.

Authors:  Nan Qin; Pablo Botas; Drosoula Giantsoudi; Jan Schuemann; Zhen Tian; Steve B Jiang; Harald Paganetti; Xun Jia
Journal:  Phys Med Biol       Date:  2016-10-03       Impact factor: 3.609

10.  Site-specific range uncertainties caused by dose calculation algorithms for proton therapy.

Authors:  J Schuemann; S Dowdell; C Grassberger; C H Min; H Paganetti
Journal:  Phys Med Biol       Date:  2014-07-03       Impact factor: 3.609

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