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Program Information

Very Fast GPU-Based IMPT Dose Computation

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A Sullivan

A Sullivan*, M Brand , Mitsubishi Electric Research Lab, Cambridge, MA

Presentations

SU-E-T-806 (Sunday, July 12, 2015) 3:00 PM - 6:00 PM Room: Exhibit Hall


Purpose: Designing particle therapy treatment plans is a dosimetrist-in-the-loop optimization wherein the conflicting constraints of achieving a desired tumor dose distribution must be balanced against the need to minimize the dose to nearby OARs. IMPT introduces an additional, inner, numerical optimization step in which the dosimetrist’s current set of constraints are used to determine the weighting of beam spots. Very fast dose calculations are needed to enable the dosimetrist to perform many iterations of the outer optimization in a commercially reasonable time.

Methods: We have developed a GPU-based convolution-type dose computation algorithm that more accurately handles heterogeneities than earlier algorithms by redistributing energy from dose computed in a water volume. The depth dependence of the beam size is handled by pre-processing Bragg curves using a weighted superposition of Gaussian bases. Additionally, scattering, the orientation of treatment ports, and the non-parallel propagation of beams are handled by large, but sparse, energy-redistribution matrices that implement affine transforms.

Results: We tested our algorithm using a brain tumor dataset with 1 mm voxels and a single treatment port from the patient’s anterior through the sinuses. The resulting dose volume is 100 x 100 x 230 mm with 66,200 beam spots on a 3 x 3 x 2 mm grid. The dose computation takes <1 msec on a GeForce GTX Titan GPU with the Gamma passing rate for 2mm/2% criterion of 99.1% compared to dose calculated by an alternative dose algorithm based on pencil beams. We will present comparisons to Monte Carlo dose calculations.

Conclusion: Our high-speed dose computation method enables the IMPT spot weights to be optimized in <1 second, resulting in a nearly instantaneous response to user changes to dose constraints. This permits the creation of higher quality plans by allowing the dosimetrist to evaluate more alternatives in a short period of time.


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