Literature DB >> 22016026

GPU-based fast Monte Carlo simulation for radiotherapy dose calculation.

Xun Jia1, Xuejun Gu, Yan Jiang Graves, Michael Folkerts, Steve B Jiang.   

Abstract

Monte Carlo (MC) simulation is commonly considered to be the most accurate dose calculation method in radiotherapy. However, its efficiency still requires improvement for many routine clinical applications. In this paper, we present our recent progress toward the development of a graphics processing unit (GPU)-based MC dose calculation package, gDPM v2.0. It utilizes the parallel computation ability of a GPU to achieve high efficiency, while maintaining the same particle transport physics as in the original dose planning method (DPM) code and hence the same level of simulation accuracy. In GPU computing, divergence of execution paths between threads can considerably reduce the efficiency. Since photons and electrons undergo different physics and hence attain different execution paths, we use a simulation scheme where photon transport and electron transport are separated to partially relieve the thread divergence issue. A high-performance random number generator and a hardware linear interpolation are also utilized. We have also developed various components to handle the fluence map and linac geometry, so that gDPM can be used to compute dose distributions for realistic IMRT or VMAT treatment plans. Our gDPM package is tested for its accuracy and efficiency in both phantoms and realistic patient cases. In all cases, the average relative uncertainties are less than 1%. A statistical t-test is performed and the dose difference between the CPU and the GPU results is not found to be statistically significant in over 96% of the high dose region and over 97% of the entire region. Speed-up factors of 69.1 ∼ 87.2 have been observed using an NVIDIA Tesla C2050 GPU card against a 2.27 GHz Intel Xeon CPU processor. For realistic IMRT and VMAT plans, MC dose calculation can be completed with less than 1% standard deviation in 36.1 ∼ 39.6 s using gDPM.

Entities:  

Mesh:

Year:  2011        PMID: 22016026     DOI: 10.1088/0031-9155/56/22/002

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


  24 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.  New concept on an integrated interior magnetic resonance imaging and medical linear accelerator system for radiation therapy.

Authors:  Xun Jia; Zhen Tian; Yan Xi; Steve B Jiang; Ge Wang
Journal:  J Med Imaging (Bellingham)       Date:  2017-03-02

Review 3.  Monte Carlo systems used for treatment planning and dose verification.

Authors:  Lorenzo Brualla; Miguel Rodriguez; Antonio M Lallena
Journal:  Strahlenther Onkol       Date:  2016-11-25       Impact factor: 3.621

4.  A GPU tool for efficient, accurate, and realistic simulation of cone beam CT projections.

Authors:  Xun Jia; Hao Yan; Laura Cervino; Michael Folkerts; Steve B Jiang
Journal:  Med Phys       Date:  2012-12       Impact factor: 4.071

5.  Reconstructing cone-beam CT with spatially varying qualities for adaptive radiotherapy: a proof-of-principle study.

Authors:  Wenting Lu; Hao Yan; Xuejun Gu; Zhen Tian; Ouyang Luo; Liu Yang; Linghong Zhou; Laura Cervino; Jing Wang; Steve Jiang; Xun Jia
Journal:  Phys Med Biol       Date:  2014-09-26       Impact factor: 3.609

6.  A GPU-accelerated Monte Carlo dose calculation platform and its application toward validating an MRI-guided radiation therapy beam model.

Authors:  Yuhe Wang; Thomas R Mazur; Olga Green; Yanle Hu; Hua Li; Vivian Rodriguez; H Omar Wooten; Deshan Yang; Tianyu Zhao; Sasa Mutic; H Harold Li
Journal:  Med Phys       Date:  2016-07       Impact factor: 4.071

7.  Concurrent Monte Carlo transport and fluence optimization with fluence adjusting scalable transport Monte Carlo.

Authors:  Y M Yang; M Svatos; C Zankowski; B Bednarz
Journal:  Med Phys       Date:  2016-06       Impact factor: 4.071

8.  Metropolis Monte Carlo simulation scheme for fast scattered X-ray photon calculation in CT.

Authors:  Yuan Xu; Yusi Chen; Zhen Tian; Xun Jia; Linghong Zhou
Journal:  Opt Express       Date:  2019-01-21       Impact factor: 3.894

9.  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

10.  GPU-accelerated voxelwise hepatic perfusion quantification.

Authors:  H Wang; Y Cao
Journal:  Phys Med Biol       Date:  2012-08-14       Impact factor: 3.609

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.