<scp>GPUMCD</scp>: A new GPU‐oriented Monte Carlo dose calculation platform

Hissoiny, Sami; Ozell, Benoı̂t; Bouchard, Hugo; Després, Philippe

doi:10.1118/1.3539725

Cited by 194 publications

(205 citation statements)

References 52 publications

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“…Recently, a new commercial GPU‐based Monte Carlo dose calculation algorithm (GPUMCD) 10 , 11 has been proposed by the vendor Elekta (Elekta AB, Stockholm, Sweden) and is available in the research version of the Monaco TPS. The Monaco TPS currently has a clinical MC dose calculation algorithm called XVMC (12) for photons, which is founded on the voxel‐based MC algorithm (VMC) (13) for electron beams.…”

Section: Introductionmentioning

confidence: 99%

Experimental evaluation of a GPU‐based Monte Carlo dose calculation algorithm in the Monaco treatment planning system

Paudel

Kim

Sarfehnia

et al. 2016

J Applied Clin Med Phys

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A new GPU‐based Monte Carlo dose calculation algorithm (GPUMCD), developed by the vendor Elekta for the Monaco treatment planning system (TPS), is capable of modeling dose for both a standard linear accelerator and an Elekta MRI linear accelerator. We have experimentally evaluated this algorithm for a standard Elekta Agility linear accelerator. A beam model was developed in the Monaco TPS (research version 5.09.06) using the commissioned beam data for a 6 MV Agility linac. A heterogeneous phantom representing several scenarios — tumor‐in‐lung, lung, and bone‐in‐tissue — was designed and built. Dose calculations in Monaco were done using both the current clinical Monte Carlo algorithm, XVMC, and the new GPUMCD algorithm. Dose calculations in a Pinnacle TPS were also produced using the collapsed cone convolution (CCC) algorithm with heterogeneity correction. Calculations were compared with the measured doses using an ionization chamber (A1SL) and Gafchromic EBT3 films for 2×2 cm2,5×5 cm2, and 10×2 cm2 field sizes. The percentage depth doses (PDDs) calculated by XVMC and GPUMCD in a homogeneous solid water phantom were within 2%/2 mm of film measurements and within 1% of ion chamber measurements. For the tumor‐in‐lung phantom, the calculated doses were within 2.5%/2.5 mm of film measurements for GPUMCD. For the lung phantom, doses calculated by all of the algorithms were within 3%/3 mm of film measurements, except for the 2×2 cm2 field size where the CCC algorithm underestimated the depth dose by ∼5% in a larger extent of the lung region. For the bone phantom, all of the algorithms were equivalent and calculated dose to within 2%/2 mm of film measurements, except at the interfaces. Both GPUMCD and XVMC showed interface effects, which were more pronounced for GPUMCD and were comparable to film measurements, whereas the CCC algorithm showed these effects poorly.PACS number(s): 87.53.Bn, 87.55.dh, 87.55.km

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Section: Introductionmentioning

confidence: 99%

Experimental evaluation of a GPU‐based Monte Carlo dose calculation algorithm in the Monaco treatment planning system

Paudel

Kim

Sarfehnia

et al. 2016

J Applied Clin Med Phys

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“…Finally, in terms of computational time the current performance of the GaTE MCs platform is not compatible with a potential clinical use, even if one considers the use of pre-operative CT imaging and subsequent treatment planning. However, the necessary computational times are expected to be dramatically reduced in the future by using hybrid computing architectures, such as graphical card units (GPUs), including recently proposed implementations for Geant4 based MCss both in imaging and radiotherapy applications [23][24][25].…”

Section: Discussionmentioning

confidence: 99%

Monte-Carlo dosimetry for intraoperative radiotherapy using a low energy x-ray source

et al. 2015

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“…Monte Carlo methods are considered the gold standard for dose calculations in radiotherapy [20,37]. Their computation complexity is, however, an obstacle to the routine use of Monte Carlo in a clinical setting, although signicant advances have been made by using variance reduction techniques and taking advantage of the graphical processing unit (GPU) to speed up computations [31].…”

Section: Dose Calculationsmentioning

confidence: 99%

MRI based radiotherapy planning and pulse sequence optimization

Sjölund¹

2015

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Radiotherapy plays an increasingly important role in cancer treatment, and medical imaging plays an increasingly important role in radiotherapy. Magnetic resonance imaging (MRI) is poised to be a major component in the development towards more eective radiotherapy treatments with fewer side eects. This thesis attempts to contribute in realizing this potential.Radiotherapy planning requires simulation of radiation transport. The necessary physical properties are typically derived from CT images, but in some cases only MR images are available. In such a case, a crude but common approach is to approximate all tissue properties as equivalent to those of water. In this thesis we propose two methods to improve upon this approximation. The rst uses a machine learning algorithm to automatically identify bone tissue in MR. The second, which we refer to as atlas-based regression, can be used to generate a realistic, patient-specic, pseudo-CT directly from anatomical MR images. Atlas-based regression uses deformable registration to estimate a pseudo-CT of a new patient based on a database of aligned MR and CT pairs.Cancerous tissue has a dierent structure from normal tissue. This aects molecular diusion, which can be measured using MRI. The prototypical diusion encoding sequence has recently been challenged with the introduction of more general gradient waveforms. To take full advantage of their capabilities it is, however, imperative to respect the constraints imposed by the hardware while at the same time maximizing the diusion encoding strength. In this thesis we formulate this as a constrained optimization problem that is easily adaptable to various hardware constraints.

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GPUMCD: A new GPU‐oriented Monte Carlo dose calculation platform

Cited by 194 publications

References 52 publications

Experimental evaluation of a GPU‐based Monte Carlo dose calculation algorithm in the Monaco treatment planning system

Experimental evaluation of a GPU‐based Monte Carlo dose calculation algorithm in the Monaco treatment planning system

Monte-Carlo dosimetry for intraoperative radiotherapy using a low energy x-ray source

MRI based radiotherapy planning and pulse sequence optimization

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