Monte Carlo-based treatment planning system calculation engine for microbeam radiation therapy.

PURPOSE: Microbeam radiation therapy (MRT) is a synchrotron radiotherapy technique that explores the limits of the dose-volume effect. Preclinical studies have shown that MRT irradiations (arrays of 25-75-μm-wide microbeams spaced by 200-400 μm) are able to eradicate highly aggressive animal tumor models while healthy tissue is preserved. These promising results have provided the basis for the forthcoming clinical trials at the ID17 Biomedical Beamline of the European Synchrotron Radiation Facility (ESRF). The first step includes irradiation of pets (cats and dogs) as a milestone before treatment of human patients. Within this context, accurate dose calculations are required. The distinct features of both beam generation and irradiation geometry in MRT with respect to conventional techniques require the development of a specific MRT treatment planning system (TPS). In particular, a Monte Carlo (MC)-based calculation engine for the MRT TPS has been developed in this work. Experimental verification in heterogeneous phantoms and optimization of the computation time have also been performed.
METHODS: The penelope/penEasy MC code was used to compute dose distributions from a realistic beam source model. Experimental verification was carried out by means of radiochromic films placed within heterogeneous slab-phantoms. Once validation was completed, dose computations in a virtual model of a patient, reconstructed from computed tomography (CT) images, were performed. To this end, decoupling of the CT image voxel grid (a few cubic millimeter volume) to the dose bin grid, which has micrometer dimensions in the transversal direction of the microbeams, was performed. Optimization of the simulation parameters, the use of variance-reduction (VR) techniques, and other methods, such as the parallelization of the simulations, were applied in order to speed up the dose computation.
RESULTS: Good agreement between MC simulations and experimental results was achieved, even at the interfaces between two different media. Optimization of the simulation parameters and the use of VR techniques saved a significant amount of computation time. Finally, parallelization of the simulations improved even further the calculation time, which reached 1 day for a typical irradiation case envisaged in the forthcoming clinical trials in MRT. An example of MRT treatment in a dog's head is presented, showing the performance of the calculation engine.
CONCLUSIONS: The development of the first MC-based calculation engine for the future TPS devoted to MRT has been accomplished. This will constitute an essential tool for the future clinical trials on pets at the ESRF. The MC engine is able to calculate dose distributions in micrometer-sized bins in complex voxelized CT structures in a reasonable amount of time. Minimization of the computation time by using several approaches has led to timings that are adequate for pet radiotherapy at synchrotron facilities. The next step will consist in its integration into a user-friendly graphical front-end.