GPU-based fast Monte Carlo simulation for radiotherapy dose calculation

被引:145
作者
Jia, Xun [1 ]
Gu, Xuejun
Graves, Yan Jiang
Folkerts, Michael
Jiang, Steve B.
机构
[1] Univ Calif San Diego, Ctr Adv Radiotherapy Technol, La Jolla, CA 92037 USA
关键词
DEFORMABLE IMAGE REGISTRATION; ELECTRON-PHOTON TRANSPORT; GRAPHICS HARDWARE; PLAN OPTIMIZATION; RADIATION-THERAPY; CALCULATION TOOL; CODE; RECONSTRUCTION; ALGORITHM; DPM;
D O I
10.1088/0031-9155/56/22/002
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
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 similar to 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 similar to 39.6 s using gDPM.
引用
收藏
页码:7017 / 7031
页数:15
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