Program Information

Development of a GPU-Based Dose Delivery System for Adaptive Pencil Beam Scanning

S Giordanengo

S Giordanengo¹*, G Russo¹ , F Marchetto¹ , V Monaco² , A Pella³ , M Varasteh² , A Attili¹ , (1) Istituto Nazionale di Fisica Nucleare, Section of Torino, Torino, Italy(2) University of Torino, Torino, Italy (3) Centro Nazionale di Adroterapia Oncologica, Pavia, Italy

Presentations

SU-E-T-107 Sunday 3:00PM - 6:00PM Room: Exhibit Hall

Purpose: A description of a GPU-based dose delivery system (G-DDS) to integrate a fast forward planning implementing in real-time the prescribed sequence of pencil beams. The system, which is under development, is designed to evaluate the dose distribution deviations due to range variations and interplay effects affecting mobile tumors treatments.

Methods: The Dose Delivery System (DDS) in use at the Italian Centro Nazionale di Adroterapia Oncologica (CNAO), is the starting point for the presented system. A fast and partial forward planning (FP) tool has been developed to evaluate in few seconds the delivered dose distributions using the DDS data (on-line measurements of spot properties, i.e. number of particles and positions). The computation is performed during the intervals between synchrotron spills and, made available at the end of each spill. In the interval between two spills, the G-DDS will evaluate the delivered dose distributions taking into account the real-time target positions measured by a tracking system. The sequence of prescribed pencil beams for the following spill will be adapted taking into account the variations with respect to the original plan due to the target motion.
In order to speed up the computation required to modify pencil beams distribution (up to 400 times has been reached), the Graphics Processing Units (GPUs) and advanced Field Programmable Gate Arrays (FPGAs) are used.

Results:An existing offline forward planning is going to be optimized for the CUDA architecture: the gain in time will be presented. The preliminary performances of the developed GPU-based FP algorithms will be shown.

Conclusion: A prototype of a GPU-based dose delivery system is under development and will be presented. The system workflow will be illustrated together with the approach adopted to integrate the three main systems, i.e. CNAO dose delivery system, fast forward planning, and tumor tracking system.

Funding Support, Disclosures, and Conflict of Interest: Supported by INFN Grant for Young Researchers


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