129: Implementation of a GPU Monte Carlo protons transport code for dose calculations: methods and challenges

ICTR-PHE – 2014 internal motion is described by mesh vertex transformations. Figure 1 summarizes this approach of 4D dose calculation and PET reconstruction. For each organ of a patient with a lung tumour, the voxelized CT attenuation values were converted into tetrahedral density maps respecting the principle of mass conservation. Internal lung transformations were computed using non-linear FEA with a hyper elastic behavior. The Monte Carlo code GEANT4 [5] was used to simulate a proton passive beam targeting the lung tumour. The deposited energy was accumulated over each deforming tetrahedral element. In order to compensate for respiratory motion for PET the 4D List-Mode Maximum Likelihood Estimation (LM-MLEM) reconstruction algorithm was adapted to reposition the β+ radiation activity on tetrahedral meshes. A radioactive source was simulated inside a moving lung tumor using the GATE platform [6]. Results: First, we evaluated the dose calculated using the computed tetrahedral density map by comparing it to the dose calculated on the original CT image. The gamma test was performed with a distance-to-agreement criterion of 3 mm and a 3% dose difference [7] resulting in 98% of the gamma values lower than 1. Then, we were interested in evaluating the impact of the motion on the 4D PET reconstruction method by comparing the original simulated radiation activity with the reconstructed one using the Pearson Correlation Coefficient (PCC) [8]. The results are significantly improved when motion information is integrated with (PCC = 97%), compared to when no motion correction is applied (PCC =75%). Conclusions: We have presented a new approach to include respiratory motion in hadron therapy dose calculation and in PET reconstruction using a tetrahedral representation of the human anatomy. Before it can be used in clinical cases, this method needs to be validated and calibrated with real measurements using specific physical phantoms. Keywords: Dosimetry, Tetrahedron, 4D PET

Figure 3. Flowchart of the 4D dose calculation and PET reconstruction methods using tetrahedralized representation of the human anatomy. References: [1] Seppenwoolde Y, Shirato H, Kitamura K, Shimizu S, Van Herk M, Lebesque J, Miyasaka J, Precise and real-time measurement of 3d tumor motion in lung due to breathing and heartbeat, measured during radiotherapy, Int. J. Radiation Oncology Biol. Phys. 53(4), 822-834, 2002. [2] Saade J , Didier A.L, Villard P.F Buttin R , Moreau J.M , Beuve M, Shariat B, A preliminary study for biomechanical model of the respiratory system, VISAPP, 2010. [3] Al-Mayah A, Moseley J , Velec M, Brock K , Toward efficient biomechanical-based deformable image

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129 Implementation of a GPU Monte Carlo protons transport code for dose calculations: methods and challenges D. Maneval1, B. Ozell2, P. Després3 1 Université Laval, Quebec, Canada 2 École polytechnique de Montréal, Canada Hadrontherapy is an advanced technique of external radiotherapy. Ions have a finite path in matter with a maximum deposit energy in their distal range called Bragg peak. This allows a better ballistic treatment than conventional techniques with better sparing of organs at risk and healthy tissues. Currently, hadrontherapy uses low Linear Energy Transfer (LET) ions such as protons or high-LET ones such as carbon ions. The most accurate dose calculations in protontherapy stem from Monte Carlo algorithms. However, their clinical implementation remains problematic due to long computation times. Recently, Graphics Processing Units (GPU) were used to significantly accelerate dose calculation algorithms in external beam radiotherapy and brachytherapy. While GPUs offer unprecedented parallel computing capabilities, implementing a Monte Carlo code on these devices remains challenging. This work is aimed at presenting these challenges as well as implementation strategies used to address them in the context of Monte Carlo proton transport. It relies on GPUMCD, a validated GPU Monte Carlo code for photons and electrons. Proton physics was integrated into GPUMCD based on Geant4, which serves as a gold standard for comparison in the work we are presenting. Besides, Geant4 is also used to statistically quantify the thread divergence, paving the way for counteract this effect. Methods to reduce thread divergence and memory bandwidth problems will be presented, along with preliminary results of the accuracy and timing performances of the GPU code. The ultimate objective of this work is to allow the clinical use of Monte Carlo methods for dose calculations in order to improve the treatment control and quality in protontherapy. Keywords: GPU, Monte Carlo simulations, protontherapy