Home»
ARCHERRT – A GPU-based and photon-electron coupled Monte Carlo dose computing engine for radiation therapy: Software development and application to helical tomotherapy
Accès à distance ? S'identifier sur le proxy UCLouvain
ARCHERRT – A GPU-based and photon-electron coupled Monte Carlo dose computing engine for radiation therapy: Software development and application to helical tomotherapy
Purpose: Using the graphical processing units (GPU) hardware technology, an extremely fast Monte Carlo (MC) code ARCHERRT is developed for radiation dose calculations in radiation therapy. This paper describes the detailed software development and testing for three clinical TomoTherapy cases: the prostate, lung, and head & neck. Methods: To obtain clinically relevant dose distributions, phase space files (PSFs) created from opti- mized radiation therapy treatment plan fluence maps were used as the input to ARCHERRT. Patient- specific phantoms were constructed from patient CT images. Batch simulations were employed to facilitate the time-consuming task of loading large PSFs, and to improve the estimation of statistical uncertainty. Furthermore, two different Woodcock tracking algorithms were implemented and their relative performance was compared. The dose curves of an Elekta accelerator PSF incident on a ho- mogeneous water phantom were benchmarked against DOSXYZnrc. For each of the treatment cases, dose volume histograms and isodose maps were produced from ARCHERRT and the general-purpose code, GEANT4. The gamma index analysis was performed to evaluate the similarity of voxel doses obtained from these two codes. The hardware accelerators used in this study are one NVIDIA K20 GPU, one NVIDIA K40 GPU, and six NVIDIA M2090 GPUs. In addition, to make a fairer compari- son of the CPU and GPU performance, a multithreaded CPU code was developed using OpenMP and tested on an Intel E5-2620 CPU. Results: For the water phantom, the depth dose curve and dose profiles from ARCHERRT agree well with DOSXYZnrc. For clinical cases, results from ARCHERRT are compared with those from GEANT4 and good agreement is observed. Gamma index test is performed for voxels whose dose is greater than 10% of maximum dose. For 2%/2mm criteria, the passing rates for the prostate, lung case, and head & neck cases are 99.7%, 98.5%, and 97.2%, respectively. Due to specific architecture of GPU, modified Woodcock tracking algorithm performed inferior to the original one. ARCHERRT achieves a fast speed for PSF-based dose calculations. With a single M2090 card, the simulations cost about 60, 50, 80 s for three cases, respectively, with the 1% statistical error in the PTV. Using the latest K40 card, the simulations are 1.7–1.8 times faster. More impressively, six M2090 cards could finish the simulations in 8.9–13.4 s. For comparison, the same simulations on Intel E5-2620 (12 hyperthreading) cost about 500–800 s. Conclusions: ARCHERRT was developed successfully to perform fast and accurate MC dose cal- culation for radiotherapy using PSFs and patient CT phantoms.
Fogliata Antonella, Vanetti Eugenio, Albers Dirk, Brink Carsten, Clivio Alessandro, Knöös Tommy, Nicolini Giorgia, Cozzi Luca, On the dosimetric behaviour of photon dose calculation algorithms in the presence of simple geometric heterogeneities: comparison with Monte Carlo calculations, 10.1088/0031-9155/52/5/011
Sterpin E., Tomsej M., De Smedt B., Reynaert N., Vynckier S., Monte Carlo evaluation of the AAA treatment planning algorithm in a heterogeneous multilayer phantom and IMRT clinical treatments for an Elekta SL25 linear accelerator : Monte Carlo evaluation of AAA in inhomogeneities, 10.1118/1.2727314
Yan Di, Vicini Frank, Wong John, Martinez Alvaro, Adaptive radiation therapy, 10.1088/0031-9155/42/1/008
Hansen Eric K., Bucci M. Kara, Quivey Jeanne M., Weinberg Vivian, Xia Ping, Repeat CT imaging and replanning during the course of IMRT for head-and-neck cancer, 10.1016/j.ijrobp.2005.07.957
Dawson Laura A., Jaffray David A., Advances in Image-Guided Radiation Therapy, 10.1200/jco.2006.09.9515
Martin William R., Brown Forrest B., Status of Vectorized Monte Carlo for Particle Transport Analysis, 10.1177/109434208700100203
Pratx Guillem, Xing Lei, GPU computing in medical physics: A review : GPU computing in medical physics, 10.1118/1.3578605
Shalf, High Performance Computing for Computational Science-VECPAR, 1 (2011)
http://www.top500.org/list/2012/11/
Jia Xun, Gu Xuejun, Graves Yan Jiang, Folkerts Michael, Jiang Steve B, GPU-based fast Monte Carlo simulation for radiotherapy dose calculation, 10.1088/0031-9155/56/22/002
Hissoiny Sami, Ozell Benoît, Bouchard Hugo, Després Philippe, GPUMCD: A new GPU-oriented Monte Carlo dose calculation platform : GPUMCD, 10.1118/1.3539725
Jahnke Lennart, Fleckenstein Jens, Wenz Frederik, Hesser Jürgen, GMC: a GPU implementation of a Monte Carlo dose calculation based on Geant4, 10.1088/0031-9155/57/5/1217
Su L, Liu T, Ding A, Xu X, WE-C-BRB-08: A GPU/CUDA Based Monte Carlo Code for Proton Transport: Preliminary Results of Proton Depth Dose in Water, 10.1118/1.4736101
Liu T, Ding A, Xu X, MO-F-213CD-01: GPU-Based Monte Carlo Methods for Accelerating Radiographic and CT Imaging Dose Calculations: Feasibility and Scalability, 10.1118/1.4735826
Zhou Bo, Yu Cedric X., Chen Danny Z., Hu X. Sharon, GPU-accelerated Monte Carlo convolution/superposition implementation for dose calculation : GPU-accelerated Monte Carlo convolution/superposition, 10.1118/1.3490083
Jia Xun, Gu Xuejun, Sempau Josep, Choi Dongju, Majumdar Amitava, Jiang Steve B, Development of a GPU-based Monte Carlo dose calculation code for coupled electron–photon transport, 10.1088/0031-9155/55/11/006
Jia Xun, Yan Hao, Gu Xuejun, Jiang Steve B, Fast Monte Carlo simulation for patient-specific CT/CBCT imaging dose calculation, 10.1088/0031-9155/57/3/577
Hissoiny Sami, D'Amours Michel, Ozell Benoît, Després Philippe, Beaulieu Luc, Sub-second high dose rate brachytherapy Monte Carlo dose calculations with
bGPUMCD
: HDR dose calculations with bGPUMCD, 10.1118/1.4730500
Townson Reid W, Jia Xun, Tian Zhen, Graves Yan Jiang, Zavgorodni Sergei, Jiang Steve B, GPU-based Monte Carlo radiotherapy dose calculation using phase-space sources, 10.1088/0031-9155/58/12/4341
T. Liu A. Ding W. Ji X. G. Xu C. Carothers F. B. Brown A Monte Carlo neutron transport code for eigenvalue calculations on a dual-GPU system and CUDA environment Proceedings of International Topical Meeting on Advances in Reactor Physics 2012
L. Su X. Du T. Liu X. G. Xu Monte Carlo electron-photon transport using GPUs as an accelerator: Results for a water-aluminum-water phantom Proceedings of the International Conference on Mathematics and Computational Methods Applied to Nuclear Science & Engineering 2013
Kim Wooyoung, Voss Michael, Multicore Desktop Programming with Intel Threading Building Blocks, 10.1109/ms.2011.12
Cuda C programming guide http://docs.nvidia.com/cuda/cuda-c-programming-guide/
F. B. Brown MCNP-A General Monte Carlo N-Particle Transport Code, Version 5
I. Kawrakow D. W. O. Rogers The EGSnrc code system: Monte Carlo simulation of electron and photon transport
F. Salvat J. M. Fernandez-Varea J. Sempau PENELOPE-2006: A code system for Monte Carlo simulation of electron and photon transport
Agostinelli S., Allison J., Amako K., Apostolakis J., Araujo H., Arce P., Asai M., Axen D., Banerjee S., Barrand G., Behner F., Bellagamba L., Boudreau J., Broglia L., Brunengo A., Burkhardt H., Chauvie S., Chuma J., Chytracek R., Cooperman G., Cosmo G., Degtyarenko P., Dell'Acqua A., Depaola G., Dietrich D., Enami R., Feliciello A., Ferguson C., Fesefeldt H., Folger G., Foppiano F., Forti A., Garelli S., Giani S., Giannitrapani R., Gibin D., Gómez Cadenas J.J., González I., Gracia Abril G., Greeniaus G., Greiner W., Grichine V., Grossheim A., Guatelli S., Gumplinger P., Hamatsu R., Hashimoto K., Hasui H., Heikkinen A., Howard A., Ivanchenko V., Johnson A., Jones F.W., Kallenbach J., Kanaya N., Kawabata M., Kawabata Y., Kawaguti M., Kelner S., Kent P., Kimura A., Kodama T., Kokoulin R., Kossov M., Kurashige H., Lamanna E., Lampén T., Lara V., Lefebure V., Lei F., Liendl M., Lockman W., Longo F., Magni S., Maire M., Medernach E., Minamimoto K., Mora de Freitas P., Morita Y., Murakami K., Nagamatu M., Nartallo R., Nieminen P., Nishimura T., Ohtsubo K., Okamura M., O'Neale S., Oohata Y., Paech K., Perl J., Pfeiffer A., Pia M.G., Ranjard F., Rybin A., Sadilov S., Di Salvo E., Santin G., Sasaki T., Savvas N., Sawada Y., Scherer S., Sei S., Sirotenko V., Smith D., Starkov N., Stoecker H., Sulkimo J., Takahata M., Tanaka S., Tcherniaev E., Safai Tehrani E., Tropeano M., Truscott P., Uno H., Urban L., Urban P., Verderi M., Walkden A., Wander W., Weber H., Wellisch J.P., Wenaus T., Williams D.C., Wright D., Yamada T., Yoshida H., Zschiesche D., Geant4—a simulation toolkit, 10.1016/s0168-9002(03)01368-8
Sempau Josep, Wilderman Scott J, Bielajew Alex F, DPM, a fast, accurate Monte Carlo code optimized for photon and electron radiotherapy treatment planning dose calculations, 10.1088/0031-9155/45/8/315
C. Everett E. D. Cashwell G. Turner A new method of sampling the Klein-Nishina probability distribution for all incident photon energies above 1 keV
M. J. Berger J. H. Hubbell S. M. Seltzer J. S. Coursey D. S. Zucker XCOM: Photon cross sections database
Berger, Methods in Computational Physics, 1, 135 (1963)
Goudsmit S., Saunderson J. L., Multiple Scattering of Electrons, 10.1103/physrev.57.24
Goudsmit S., Saunderson J. L., Multiple Scattering of Electrons. II, 10.1103/physrev.58.36
Kawrakow Iwan, Bielajew Alex F., On the representation of electron multiple elastic-scattering distributions for Monte Carlo calculations, 10.1016/s0168-583x(97)00723-4
International Commission on Radiation Units and Measurements Stopping powers for electrons and positions 1984
Zhao Ying-Li, Mackenzie M., Kirkby C., Fallone B. G., Monte Carlo calculation of helical tomotherapy dose delivery : Monte Carlo calculation of helical tomotherapy dose delivery, 10.1118/1.2948409
Sterpin E, Salvat F, Cravens R, Ruchala K, Olivera G H, Vynckier S, Monte Carlo simulation of helical tomotherapy with PENELOPE, 10.1088/0031-9155/53/8/011
Sterpin E, Salvat F, Olivera G H, Vynckier S, Analytical model of the binary multileaf collimator of tomotherapy for Monte Carlo simulations, 10.1088/1742-6596/102/1/012022
Verhaegen Frank, Devic Slobodan, Sensitivity study for CT image use in Monte Carlo treatment planning, 10.1088/0031-9155/50/5/016
Kawrakow I., Walters B. R. B., Efficient photon beam dose calculations using DOSXYZnrc with BEAMnrc : Efficient photon beam dose calculations with DOSXYZnrc/BEAMnrc, 10.1118/1.2219778
Walters B. R. B., Kawrakow I., Rogers D. W. O., History by history statistical estimators in theBEAMcode system, 10.1118/1.1517611
E. Woodcock T. Murphy P. Hemmings S. Longworth Techniques used in the GEM code for Monte Carlo neutronics calculations in reactors and other systems of complex geometry 1965
Kawrakow Iwan, Fippel Matthias, Investigation of variance reduction techniques for Monte Carlo photon dose calculation using XVMC, 10.1088/0031-9155/45/8/308
Phase-space database for external beam radiotherapy http://www-nds.iaea.org/phsp/phsp.htmlx
B. Walters I. Kawrakow D. W. O. Rogers DOSXYZnrc users manual 2011
Bibliographic reference
Su, Lin ; Yang, Youming ; Bednarz, Bryan ; Sterpin, Edmond ; Du, Xining ; et. al. ARCHERRT – A GPU-based and photon-electron coupled Monte Carlo dose computing engine for radiation therapy: Software development and application to helical tomotherapy. In: Medical Physics, Vol. 41, no.7, p. 071709 (2014)