Sub-second pencil beam dose calculation on GPU for adaptive proton therapy

被引:26
作者
da Silva, Joakim [1 ,2 ]
Ansorge, Richard [1 ]
Jena, Rajesh [2 ]
机构
[1] Univ Cambridge, Cavendish Lab, Cambridge CB3 0HE, England
[2] Univ Cambridge, Dept Oncol, Cambridge, England
关键词
proton therapy; dose calculation; GPU; graphics processing unit; pencil beam; adaptive radiotherapy; dose reconstruction; TREATMENT PLANNING SYSTEM; MONTE-CARLO SIMULATIONS; ALGORITHM; RADIOTHERAPY; IMPLEMENTATION;
D O I
10.1088/0031-9155/60/12/4777
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Although proton therapy delivered using scanned pencil beams has the potential to produce better dose conformity than conventional radiotherapy, the created dose distributions are more sensitive to anatomical changes and patient motion. Therefore, the introduction of adaptive treatment techniques where the dose can be monitored as it is being delivered is highly desirable. We present a GPU-based dose calculation engine relying on the widely used pencil beam algorithm, developed for on-line dose calculation. The calculation engine was implemented from scratch, with each step of the algorithm parallelized and adapted to run efficiently on the GPU architecture. To ensure fast calculation, it employs several application-specific modifications and simplifications, and a fast scatter-based implementation of the computationally expensive kernel superposition step. The calculation time for a skull base treatment plan using two beam directions was 0.22s on an Nvidia Tesla K40 GPU, whereas a test case of a cubic target in water from the literature took 0.14s to calculate. The accuracy of the patient dose distributions was assessed by calculating the gamma-index with respect to a gold standard Monte Carlo simulation. The passing rates were 99.2% and 96.7%, respectively, for the 3%/3 mm and 2%/2 mm criteria, matching those produced by a clinical treatment planning system.
引用
收藏
页码:4777 / 4795
页数:19
相关论文
共 30 条
  • [1] The FLUKA Code: Developments and Challenges for High Energy and Medical Applications
    Boehlen, T. T.
    Cerutti, F.
    Chin, M. P. W.
    Fosso, A.
    Ferrari, A.
    Ortega, P. G.
    Mairani, A.
    Sala, P. R.
    Smirnov, G.
    Vlachoudisl, V.
    [J]. NUCLEAR DATA SHEETS, 2014, 120 : 211 - 214
  • [2] An analytical approximation of the Bragg curve for therapeutic proton beams
    Bortfeld, T
    [J]. MEDICAL PHYSICS, 1997, 24 (12) : 2024 - 2033
  • [3] Da Silva J, 2015, EFFICIENT S IN PRESS
  • [4] Ferrari A., 2011, CERN-2005-10
  • [5] A Monte Carlo dose calculation algorithm for proton therapy
    Fippel, M
    Soukup, M
    [J]. MEDICAL PHYSICS, 2004, 31 (08) : 2263 - 2273
  • [6] GPU-based fast pencil beam algorithm for proton therapy
    Fujimoto, Rintaro
    Kurihara, Tsuneya
    Nagamine, Yoshihiko
    [J]. PHYSICS IN MEDICINE AND BIOLOGY, 2011, 56 (05) : 1319 - 1328
  • [7] A pencil beam algorithm for proton dose calculations
    Hong, L
    Goitein, M
    Bucciolini, M
    Comiskey, R
    Gottschalk, B
    Rosenthal, S
    Serago, C
    Urie, M
    [J]. PHYSICS IN MEDICINE AND BIOLOGY, 1996, 41 (08) : 1305 - 1330
  • [8] Proton therapy dose calculations on GPU: advances and challenges
    Jia, Xun
    Pawlicki, Todd
    Murphy, Kevin T.
    Mundt, Arno J.
    [J]. TRANSLATIONAL CANCER RESEARCH, 2012, 1 (03) : 207 - 216
  • [9] GPU-based high-performance computing for radiation therapy
    Jia, Xun
    Ziegenhein, Peter
    Jiang, Steve B.
    [J]. PHYSICS IN MEDICINE AND BIOLOGY, 2014, 59 (04) : R151 - R182
  • [10] GPU-based fast Monte Carlo dose calculation for proton therapy
    Jia, Xun
    Schuemann, Jan
    Paganetti, Harald
    Jiang, Steve B.
    [J]. PHYSICS IN MEDICINE AND BIOLOGY, 2012, 57 (23) : 7783 - 7797