Sub-second high dose rate brachytherapy Monte Carlo dose calculations with<b><tt>bGPUMCD</tt></b>

Hissoiny, Sami; DˈAmours, M; Ozell, Benoı̂t; Després, Philippe; Beaulieu, Luc

doi:10.1118/1.4730500

Cited by 20 publications

(13 citation statements)

References 30 publications

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“…Recently, accelerated MC computation using graphics processing units (GPUs) has been employed in radiotherapy research and clinical applications due to GPU’s tremendous parallel processing capability at a low cost (Jia et al ., 2014). Substantial acceleration factors over conventional CPU-based computations have been reported for photon, electron and proton dose calculations (Jia et al ., 2010a; Jia et al ., 2011; Hissoiny et al ., 2011; Jahnke et al ., 2012; Townson et al ., 2013; Bol et al ., 2012; Hissoiny et al ., 2012; Jia et al ., 2012a; Yepes et al ., 2010; Badal and Badano, 2009; Ma et al ., 2014; Tseung et al ., 2015). …”

Section: Introductionmentioning

confidence: 99%

Initial development of goCMC: a GPU-oriented fast cross-platform Monte Carlo engine for carbon ion therapy

et al. 2017

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Monte Carlo (MC) simulation is considered as the most accurate method for calculation of absorbed dose and fundamental physics quantities related to biological effects in carbon ion therapy. To improve its computational efficiency, we have developed a GPU-oriented fast MC package named goCMC, for carbon therapy. goCMC simulates particle transport in voxelized geometry with kinetic energy up to 450 MeV/u. Class II condensed history simulation scheme with a continuous slowing down approximation was employed. Energy straggling and multiple scattering were modeled. δ-electrons were terminated with their energy locally deposited. Four types of nuclear interactions were implemented in goCMC, i.e., carbon-hydrogen, carbon-carbon, carbon-oxygen and carbon-calcium inelastic collisions. Total cross section data from Geant4 were used. Secondary particles produced in these interactions were sampled according to particle yield with energy and directional distribution data derived from Geant4 simulation results. Secondary charged particles were transported following the condensed history scheme, whereas secondary neutral particles were ignored. goCMC was developed under OpenCL framework and is executable on different platforms, e.g. GPU and multi-core CPU. We have validated goCMC with Geant4 in cases with different beam energy and phantoms including four homogeneous phantoms, one heterogeneous half-slab phantom, and one patient case. For each case 3 × 107 carbon ions were simulated, such that in the region with dose greater than 10% of maximum dose, the mean relative statistical uncertainty was less than 1%. Good agreements for dose distributions and range estimations between goCMC and Geant4 were observed. 3D gamma passing rates with 1%/1 mm criterion were over 90% within 10%) isodose line except in two extreme cases, and those with 2%/1 mm criterion were all over 96%. Efficiency and code portability were tested with different GPUs and CPUs. Depending on the beam energy and voxel size, the computation time to simulate 107 carbons was 9.9–125 sec, 2.5–50 sec and 60–612 sec on an AMD Radeon GPU card, an NVidia GeForce GTX 1080 GPU card and an Intel Xeon E5-2640 CPU, respectively. The combined accuracy, efficiency and portability make goCMC attractive for research and clinical applications in carbon ion therapy.

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Section: Introductionmentioning

confidence: 99%

Initial development of goCMC: a GPU-oriented fast cross-platform Monte Carlo engine for carbon ion therapy

et al. 2017

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“…Compared with previous work on GPU-based fast MC dose calculation, [12][13][14][18][19][20] this study does better job on "fair comparison." Instead of comparing GPU code with serial CPU code, this study makes multithreaded CPU code and conducts a fairer comparison of GPU and CPU.…”

Section: B Comparison With Previous Workmentioning

confidence: 93%

“…19 Hissoiny et al reported a GPU based brachytherapy dose calculation tool using a precalculated phase space file (PSF) as input and achieved ∼2 s speed for a preoptimized plan. 20 However, electron transport was absent from their MC code and they did not consider external beam radiotherapy. Townson et al reported a GPU dose calculation engine for IMRT, 21 in which they used "phase-space-let" method to calculate dose distribution from a patient-independent PSF.…”

Section: Introductionmentioning

confidence: 99%

ARCHER_RT - A GPU-based and photon-electron coupled Monte Carlo dose computing engine for radiation therapy: Software development and application to helical tomotherapy

Yang

Bednarz

et al. 2014

Med. Phys.

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“…For example, MC calculation times have been reported that range from subminute to a few minutes for low-dose-rate brachytherapy applications, 32-34 from 2.5 to 17.0 min for 40 3 - 140 3 2-mm voxels, respectively, for an HDR rectal application, 35 and from subsecond for a single source to a couple of seconds for an HDR plus shield implant using graphics processing unit implementation. 36 …”

Section: The Monte Carlo Simulation Methodsmentioning

confidence: 99%

Current state of the art brachytherapy treatment planning dosimetry algorithms

Papagiannis¹,

Pantelis²,

Karaiskos³

2014

BJR

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Following literature contributions delineating the deficiencies introduced by the approximations of conventional brachytherapy dosimetry, different model-based dosimetry algorithms have been incorporated into commercial systems for 192 Ir brachytherapy treatment planning. The calculation settings of these algorithms are pre-configured according to criteria established by their developers for optimizing computation speed vs accuracy. Their clinical use is hence straightforward. A basic understanding of these algorithms and their limitations is essential, however, for commissioning; detecting differences from conventional algorithms; explaining their origin; assessing their impact; and maintaining global uniformity of clinical practice.Conventional, Task Group (TG)43-based 1 dosimetry marked an improvement over prior dose calculation formalisms for brachytherapy treatment planning by advocating the use of a source strength quantity traceable to international standards, the introduction of two-dimensional (2D) source anisotropy, and global uniformity in source characterization as well as clinical dosimetry practice. In the past decade, brachytherapy has progressed from the traditional surgical paradigm to modern three-dimensional (3D) image-based treatment planning systems (TPSs) and dose delivery. The information available through patient imaging, however, had not been fully exploited since TG43-based dosimetry relies on sourcespecific data pre-calculated in a standard homogeneous water geometry.1-3 Hence, it disregards patient-specific radiation scatter conditions and the radiological differences of tissue or applicator materials from water.In response to literature on the effect of these shortcomings, which has been reviewed in several recent publications, [4][5][6][7] TPSs have become commercially available that include improved dosimetry algorithms, collectively referred to as model-based dosimetry algorithms (MBDCAs). At the time of writing, these include a deterministic solver of the linear Boltzmann transport equation (LBTE) 8-10 and a collapsed cone superposition (CCS) algorithm 11-17 for 192 Ir high-doserate (HDR) applications.This work reviews the basic features of these algorithms and their clinical implementation and presents illustrative results of their performance. Monte Carlo (MC) simulation is also briefly discussed since, besides being a candidate MBDCA for clinical implementation, it is used for obtaining input data for MBDCAs, as well as for their testing. DOSIMETRY IN THE BRACHYTHERAPY PHOTON ENERGY RANGEThe vast majority of brachytherapy sources can be considered pure photon emitters.1-3 Figure 1 readily implies that mainly density heterogeneities affect dosimetry of higher photon energy-emitting sources like 192 Ir, since attenuation and energy absorption per unit mass is comparable for all materials except for bone. On the contrary, attenuation and energy absorption differences exist between different tissue compositions for lower photon energies. Literature on the effect...

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Sub-second high dose rate brachytherapy Monte Carlo dose calculations with`bGPUMCD`

Abstract: bGPUMCD has the potential to allow for fast MC dose calculation in a clinical setting for all phases of HDR treatment planning, from dose kernel calculations for plan optimization to plan recalculation.

Cited by 20 publications

References 30 publications

Initial development of goCMC: a GPU-oriented fast cross-platform Monte Carlo engine for carbon ion therapy

Initial development of goCMC: a GPU-oriented fast cross-platform Monte Carlo engine for carbon ion therapy

ARCHER_RT - A GPU-based and photon-electron coupled Monte Carlo dose computing engine for radiation therapy: Software development and application to helical tomotherapy

Current state of the art brachytherapy treatment planning dosimetry algorithms

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Sub-second high dose rate brachytherapy Monte Carlo dose calculations withbGPUMCD

Abstract: bGPUMCD has the potential to allow for fast MC dose calculation in a clinical setting for all phases of HDR treatment planning, from dose kernel calculations for plan optimization to plan recalculation.

Cited by 20 publications

References 30 publications

Initial development of goCMC: a GPU-oriented fast cross-platform Monte Carlo engine for carbon ion therapy

Initial development of goCMC: a GPU-oriented fast cross-platform Monte Carlo engine for carbon ion therapy

ARCHERRT - A GPU-based and photon-electron coupled Monte Carlo dose computing engine for radiation therapy: Software development and application to helical tomotherapy

Current state of the art brachytherapy treatment planning dosimetry algorithms

Contact Info

Product

Resources

About

Sub-second high dose rate brachytherapy Monte Carlo dose calculations with`bGPUMCD`

ARCHER_RT - A GPU-based and photon-electron coupled Monte Carlo dose computing engine for radiation therapy: Software development and application to helical tomotherapy