Parallelized Monte-Carlo dosimetry using graphics processing units to model cylindrical diffusers used in photodynamic therapy: From implementation to validation.

Abstract

The Monte-Carlo method is the standard method for computing the dosimetry of both ionizing and non-ionizing radiation. Because this technique is highly time-consuming in conventional implementations, several improvements have recently been developed to speed-up simulations. Among the improvements, the use of graphics processing units (GPU) to parallelize algorithms provides a cost-efficient solution to accelerate the Monte-Carlo method. Parallel implementation of Monte-Carlo using GPU technology is described in the context of photodynamic therapy (PDT) dosimetry. This algorithm has been optimized to compute light emitted from optical fibers with cylindrical diffusers that are used in interstitial PDT applications. A comparison of the experimental measurements used to assess the results of the Monte-Carlo method is detailed. Illumination profiles of several commercially available diffusers are measured using an optical phantom that mimics the optical properties of the brain. Additionally, this Monte-Carlo method is compared to ex-vivo measurements made by a device dedicated to intraoperative PDT treatment of brain tumors. The results of the GPU Monte-Carlo validation are in accordance with the recommendations of the American Association of Physicists in Medicine. The acceleration obtained with the GPU implementation is in accordance with the literature and is sufficiently fast to be integrated in a treatment planning system dedicated to planning routine clinical interstitial PDT treatments.