Clinical Validation of a Ray-Casting Analytical Dose Engine for Spot Scanning Proton Delivery Systems.

To describe and validate the dose calculation algorithm of an independent second-dose check software for spot scanning proton delivery systems with full width at half maximum between 5 and 14 mm and with a negligible spray component. The analytical dose engine of our independent second-dose check software employs an altered pencil beam algorithm with 3 lateral Gaussian components. It was commissioned using Geant4 and validated by comparison to point dose measurements at several depths within spread-out Bragg peaks of varying ranges, modulations, and field sizes. Water equivalent distance was used to compensate for inhomogeneous geometry. Twelve patients representing different disease sites were selected for validation. Dose calculation results in water were compared to a fast Monte Carlo code and ionization chamber array measurements using dose planes and dose profiles as well as 2-dimensional-3-dimensional and 3-dimensional-3-dimensional γ-index analysis. Results in patient geometry were compared to Monte Carlo simulation using dose-volume histogram indices, 3-dimensional-3-dimensional γ-index analysis, and inpatient dose profiles. Dose engine model parameters were tuned to achieve 1.5% agreement with measured point doses. The in-water γ-index passing rates for the 12 patients using 3%/2 mm criteria were 99.5% ± 0.5% compared to Monte Carlo. The average inpatient γ-index analysis passing rate compared to Monte Carlo was 95.8% ± 2.9%. The average difference in mean dose to the clinical target volume between the dose engine and Monte Carlo was -0.4% ± 1.0%. For a typical plan, dose calculation time was 2 minutes on an inexpensive workstation. Following our commissioning process, the analytical dose engine was validated for all treatment sites except for the lung or for calculating dose-volume histogram indices involving point doses or critical structures immediately distal to target volumes. Monte Carlo simulations are recommended for these scenarios.