A Monte-Carlo-based and GPU-accelerated 4D-dose calculator for a pencil beam scanning proton therapy system.

Purpose: The presence of respiratory motion during radiation treatment leads to degradation of the expected dose distribution, both for target coverage and healthy tissue sparing, particularly for techniques like pencil beam scanning proton therapy which have dynamic delivery systems. While tools exist to estimate this degraded four-dimensional (4D) dose, they typically have one or more deficiencies such as not including the particular effects from a dynamic delivery, using analytical dose calculations, and/or using nonphysical dose-accumulation methods. This work presents a clinically useful 4D-dose calculator that addresses each of these shortcomings.

Methods: To quickly compute the 4D dose, the three main tasks of the calculator were run on graphics processing units (GPUs). These tasks were (a) simulating the delivery of the plan using measured delivery parameters to distribute the plan amongst 4DCT phases characterizing the patient breathing, (b) using an in-house Monte Carlo simulation (MC) dose calculator to determine the dose delivered to each breathing phase, and (c) accumulating the doses from the various breathing phases onto a single phase for evaluation. The accumulation was performed by individually transferring the energy and mass of dose-grid subvoxels, a technique that models the transfer of dose in a more physically realistic manner. The calculator was run on three test cases, with lung, esophagus, and liver targets, respectively, to assess the various uncertainties in the beam delivery simulation as well as to characterize the dose-accumulation technique.

Results: Four-dimensional doses were successfully computed for the three test cases with computation times ranging from 4-6 min on a server with eight NVIDIA Titan X graphics cards; the most time-consuming component was the MC dose engine. The subvoxel-based dose-accumulation technique produced stable 4D-dose distributions at subvoxel scales of 0.5-1.0 mm without impairing the total computation time. The uncertainties in the beam delivery simulation led to moderate variations of the dose-volume histograms for these cases; the variations were reduced by implementing repainting or phase-gating motion mitigation techniques in the calculator.

Conclusions: A MC-based and GPU-accelerated 4D-dose calculator was developed to estimate the effects of respiratory motion on pencil beam scanning proton therapy treatments. After future validation, the calculator could be used to assess treatment plans and its quick runtime would make it easily usable in a future 4D-robust optimization system.