Modeling of Radiotherapy Linac Source Terms Using ARCHER Monte Carlo Code: Performance Comparison for GPU and MIC Parallel Computing Devices

Lin, Hui-Ling; Li, Tianyu; Su, Lin; Bednarz, Bryan; Caracappa, Peter F.; Xu, X. George

doi:10.1051/epjconf/201715304010

Cited by 3 publications

(4 citation statements)

References 11 publications

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“…A number of authors describe the use of a graphics processing unit (GPU) to increase the parallelism of the computation. 41 This approach is pursued by Jia et al,who describe the implementation of the DPM code on GPU, with one to two orders of magnitude speedup compared to a single-thread implementation. 42,43 Townson et al 44 describe simplified phase-space models for this implementation, so as to avoid the time overhead associated with reading a large phase-space file.…”

Section: Discussionmentioning

confidence: 99%

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A phase space model of a Versa HD linear accelerator for application to Monte Carlo dose calculation in a real‐time adaptive workflow

Bedford

Nilawar

Nill

et al. 2022

J Applied Clin Med Phys

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This study aims to develop and validate a simple geometric model of the accelerator head, from which a particle phase space can be calculated for application to fast Monte Carlo dose calculation in real-time adaptive photon radiotherapy.With this objective in view,the study investigates whether the phase space model can facilitate dose calculations which are compatible with those of a commercial treatment planning system, for convenient interoperability. Materials and methods:A dual-source model of the head of a Versa HD accelerator (Elekta AB, Stockholm, Sweden) was created. The model used parameters chosen to be compatible with those of 6-MV flattened and 6-MV flattening filter-free photon beams in the RayStation treatment planning system (RaySearch Laboratories, Stockholm, Sweden). The phase space model was used to calculate a photon phase space for several treatment plans, and the resulting phase space was applied to the Dose Planning Method (DPM) Monte Carlo dose calculation algorithm. Simple fields and intensity-modulated radiation therapy (IMRT) treatment plans for prostate and lung were calculated for benchmarking purposes and compared with the convolution-superposition dose calculation within RayStation. Results: For simple square fields in a water phantom, the calculated dose distribution agrees to within ±2% with that from the commercial treatment planning system, except in the buildup region, where the DPM code does not model the electron contamination. For IMRT plans of prostate and lung, agreements of ±2% and ±6%, respectively, are found, with slightly larger differences in the high dose gradients. Conclusions:The phase space model presented allows convenient calculation of a phase space for application to Monte Carlo dose calculation, with straightforward translation of beam parameters from the RayStation beam model. This provides a basis on which to develop dose calculation in a real-time adaptive setting.

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Section: Discussionmentioning

confidence: 99%

“…A number of authors describe the use of a graphics processing unit (GPU) to increase the parallelism of the computation 41 . This approach is pursued by Jia et al., who describe the implementation of the DPM code on GPU, with one to two orders of magnitude speedup compared to a single‐thread implementation 42,43 .…”

Section: Discussionmentioning

confidence: 99%

A phase space model of a Versa HD linear accelerator for application to Monte Carlo dose calculation in a real‐time adaptive workflow

Bedford

Nilawar

Nill

et al. 2022

J Applied Clin Med Phys

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“…In this study, we combined GPU-accelerated MC simulations and organ autosegmentation techniques to evaluate rapidly the organ dose for a specific patient based on PET/CT images. In our previous work, a dedicated GPU-based MC code, ARCHER (Su et al 2014), has been validated for a wide range of medical physics applications, such as CT imaging and radiotherapy (Xu et al 2015, Adam et al 2020, Lin et al 2017. Here, ARCHER's capabilities are extended by adding a new NM module dedicated to internal dosimetry for patients undergoing PET/CT examination involving 18 F-FDG PET/CT imaging.…”

Section: Introductionmentioning

confidence: 99%

Development of a GPU-accelerated Monte Carlo dose calculation module for nuclear medicine, ARCHER-NM: demonstration for a PET/CT imaging procedure

Zhao¹,

Lu²,

Xu³

et al. 2022

Phys. Med. Biol.

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Objective: This paper describes the development and validation of a GPU-accelerated Monte Carlo (MC) dose computing module dedicated to organ dose calculations of individual patients undergoing nuclear medicine (NM) internal radiation exposures involving PET/CT examination. Approach: This new module extends the more-than-10-years-long ARCHER project that developed a GPU-accelerated MC dose engine by adding dedicated NM source-definition features. To validate the code, we compared dose distributions from the point ion source, including 18F, 11C, 15O and 68Ga, calculated for a water phantom against a well-tested MC code, GATE. To demonstrate the clinical utility and advantage of ARCHER-NM, one set of 18F-FDG PET/CT data for an adult male NM patient is calculated using the new code. Radiosensitive organs in the CT dataset are segmented using a CNN-based tool called DeepViewer. The PET image intensity maps are converted to radioactivity distributions to allow for MC radiation transport dose calculations at the voxel level. The dose rate maps and corresponding statistical uncertainties were calculated at the acquisition time of PET image. Main results：The water-phantom results show excellent agreement, suggesting that the radiation physics module in the new NM code is adequate. The dose rate results of the 18F-FDG PET imaging patient show that ARCHER-NM’s results agree very well with those of the GATE within -2.45% to 2.58% (for a total of 28 organs considered in this study). Most impressively, ARCHER-NM obtains such results in 22 seconds while it takes GATE about 180 minutes for the same number of 5×108 simulated decay events. Significance: This is the first study presenting GPU-accelerated patient-specific MC internal radiation dose rate calculations for clinically realistic 18F-FDG PET/CT imaging case involving autosegmentation of whole-body PET/CT images. This study suggests that the proposed computing tools —— ARCHER-NM —— are accurate and fast enough for routine internal dosimetry in NM clinics.

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“…To accelerate the simulation process, they simplified the transport physics or introduced GPU or multithread CPU techniques. Xu 18 adopted a GPU technique and developed an MC package called ARCHER to compute dose deposition under a magnetic field. Although the computational efficiency improved to some extent through aforementioned GPU or CPU acceleration or with variance reduction techniques, the high‐efficiency requirements of iterative invoking during plan optimization under the online treatment circumstance were hardly met.…”

Section: Introductionmentioning

confidence: 99%

Cross‐engine transformation‐based fast dose calculation for MRI‐Linac online treatment planning

Song

Zhou

2022

Medical Physics

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Purpose To propose a novel magnetic field dose calculation method based on transformation from pencil beam (PB) to Monte Carlo (MC) distribution for MRI‐Linac online treatment planning. Methods The novel magnetic field dose calculation algorithm was established by a PB dose engine and a magnetic field with tissue inhomogeneity influence correction network. The correction network was constructed with a Res‐UNet framework, including residual modules and an encoding–decoding path, by inputting three‐dimensional PB dose and patient electron density map, and outputting transformed dose distribution. The influences of magnetic fields and tissue heterogeneity were considered and corrected simultaneously in the correction model. A total of 110 clinically treated static beam IMRT plans were collected, including plans for brain, head‐and‐neck, lung, and rectum cases. A total of 90 cases were used and enhanced to train and validate the model, and the other 20 cases were for test. By comparing the proposed pipeline‐generated dose distribution with original input PB dose and corresponding MC dose, the feasibility and effectiveness of the method was evaluated. Results Results on both beam dose and plan dose accuracy comparisons on all investigated four tumor sites show great consistency between the cross‐dose‐engine transformation generations and the MC results, with averaged plan mean absolute error of 0.90% ± 0.13% for the voxel‐wise dose difference and 98.33% ± 1.07% gamma passing rate at the 2%/2 mm criteria. The whole PB calculation and transformation process can be completed within second. Conclusions We have successfully developed a fast novel magnetic field dose calculation pipeline based on transformation from PB distribution to MC distribution for MRI‐Linac online treatment planning.

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Modeling of Radiotherapy Linac Source Terms Using ARCHER Monte Carlo Code: Performance Comparison for GPU and MIC Parallel Computing Devices

Cited by 3 publications

References 11 publications

A phase space model of a Versa HD linear accelerator for application to Monte Carlo dose calculation in a real‐time adaptive workflow

A phase space model of a Versa HD linear accelerator for application to Monte Carlo dose calculation in a real‐time adaptive workflow

Development of a GPU-accelerated Monte Carlo dose calculation module for nuclear medicine, ARCHER-NM: demonstration for a PET/CT imaging procedure

Cross‐engine transformation‐based fast dose calculation for MRI‐Linac online treatment planning

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