Fast GPU-based Monte Carlo simulations for LDR prostate brachytherapy

Abstract

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. The radial and anisotropy functions were obtained for the Nucletron SelectSeed in TG-43 conditions. These functions were compared to those found in the MD Anderson Imaging and Radiation Oncology Core brachytherapy source registry which are considered the TG-43 reference values. After appropriate calibration of the source, permanent prostate implant dose distributions were calculated for four patients and compared to an already validated Geant4 algorithm. The radial function calculated from bGPUMCD showed excellent agreement (differences within 1.3%) with TG-43 accepted values. The anisotropy functions at r = 1 cm and r = 4 cm were within 2% of TG-43 values for angles over 17.5°. For permanent prostate implants, Monte Carlo-based dose distributions with a statistical uncertainty of 1% or less for the target volume were obtained in 30 s or less for 1 × 1 × 1 mm(3) calculation grids. Dosimetric indices were very similar (within 2.7%) to those obtained with a validated, independent Monte Carlo code (Geant4) performing the calculations for the same cases in a much longer time (tens of minutes to more than a hour). bGPUMCD is a promising code that lets envision the use of Monte Carlo techniques in a clinical environment, with sub-minute execution times on a standard workstation. Future work will explore the use of this code with an inverse planning method to provide a complete Monte Carlo-based planning solution.

egs_brachy: a versatile and fast Monte Carlo code for brachytherapy

“…With the goal of reducing differences between calculated and delivered doses, momentum is growing for adoption of model-based dose calculation algorithms (MBDCAs) in brachytherapy. A number of codes have been developed to carry out advanced model-based dose calculations for brachytherapy; see the report of AAPM Task Group 186 (Beaulieu et al 2012) and references therein, Chibani and Williamson (2005), Taylor et al (2007), Thomson et al (2010), Afsharpour et al (2012), Chibani and Ma (2014) and Bonenfant et al (2015). Two MBDCA options are available in commercial treatment planning systems: Acuros (a gridbased Boltzmann equation solver) in Brachy Vision 1 and ACE (a collapsed cone superposition/convolution method) in Oncentra Brachy 2 (Papagiannis et al 2014).…”

Embedding expertise knowledge into inverse treatment planning for low‐dose‐rate brachytherapy of hepatic malignancies

“…Monte Carlo‐based calculations are time‐consuming, with the computation time being primarily influenced by voxel size and the number of events. Typically, one simulation can take anywhere between 1 and 20 min 17 . In contrast, the TG‐43 formalism requires less than 50 ms for a single calculation in our specific case, utilizing an Intel I9 CPU.…”

DVH-Based Inverse Planning Using Monte Carlo Dosimetry for LDR Prostate Brachytherapy

“…Such computational time is in good agreement with alternative GPU-enabled dose engines. 34 Despite the fast dose map generation, the plan's dose map requires several thousand modifications during inverse planning. Thus, to avoid computational overhead, we decoupled the dose calculation from inverse planning.…”