Evaluation of a commercial MRI Linac based Monte Carlo dose calculation algorithm with GEANT4.

Purpose: This paper provides a comparison between a fast, commercial, in-patient Monte Carlo dose calculation algorithm (GPUMCD) and geant4. It also evaluates the dosimetric impact of the application of an external 1.5 T magnetic field.

Fast GPU-based Monte Carlo simulations for LDR prostate brachytherapy.

The aim of this study was to evaluate the potential of bGPUMCD, a Monte Carlo algorithm executed on Graphics Processing Units (GPUs), for fast dose calculations in permanent prostate implant dosimetry. It also aimed to validate a low dose rate brachytherapy source in terms of TG-43 metrics and to use this source to compute dose distributions for permanent prostate implant in very short times. The physics of bGPUMCD was reviewed and extended to include Rayleigh scattering and fluorescence from photoelectric interactions for all materials involved.

Fast GPU-based computation of the sensitivity matrix for a PET list-mode OSEM algorithm.

During the last decade, studies have shown that 3D list-mode ordered-subset expectation-maximization (LM-OSEM) algorithms for positron emission tomography (PET) reconstruction could be effectively computed and considerably accelerated by graphics processing unit (GPU) devices. However, most of these studies rely on pre-calculated sensitivity matrices. In many cases, the time required to compute this matrix can be longer than the reconstruction time itself.

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

Purpose: To establish the accuracy and speed of bGPUMCD, a GPU-oriented Monte Carlo code used for high dose rate brachytherapy dose calculations. The first objective is to evaluate the time required for dose calculation when full Monte Carlo generated dose distribution kernels are used for plan optimization. The second objective is to assess the accuracy and speed when recalculating pre-optimized plans, consisting of many dwell positions.

Validation of GPUMCD for low-energy brachytherapy seed dosimetry.

Purpose: To validate GPUMCD, a new package for fast Monte Carlo dose calculations based on the GPU (graphics processing unit), as a tool for low-energy single seed brachytherapy dosimetry for specific seed models. As the currently accepted method of dose calculation in low-energy brachytherapy computations relies on severe approximations, a Monte Carlo based approach would result in more accurate dose calculations, taking in to consideration the patient anatomy as well as interseed attenuation. The first step is to evaluate the capability of GPUMCD to reproduce low-energy, single source, brachytherapy calculations which could ultimately result in fast and accurate, Monte Carlo based, brachytherapy dose calculations for routine planning.

GPUMCD: A new GPU-oriented Monte Carlo dose calculation platform.

Purpose: Monte Carlo methods are considered as the gold standard for dosimetric computations in radiotherapy. Their execution time is, however, still an obstacle to the routine use of Monte Carlo packages in a clinical setting. To address this problem, a completely new, and designed from the ground up for the GPU, Monte Carlo dose calculation package for voxelized geometries is proposed: GPUMCD.

A convolution-superposition dose calculation engine for GPUs.

Purpose: Graphic processing units (GPUs) are increasingly used for scientific applications, where their parallel architecture and unprecedented computing power density can be exploited to accelerate calculations. In this paper, a new GPU implementation of a convolution/superposition (CS) algorithm is presented.

Methods: This new GPU implementation has been designed from the ground-up to use the graphics card's strengths and to avoid its weaknesses.

Fast convolution-superposition dose calculation on graphics hardware.

The numerical calculation of dose is central to treatment planning in radiation therapy and is at the core of optimization strategies for modern delivery techniques. In a clinical environment, dose calculation algorithms are required to be accurate and fast. The accuracy is typically achieved through the integration of patient-specific data and extensive beam modeling, which generally results in slower algorithms.