Abstract

Monte Carlo simulations as well as analytical computations of proton transport in material media require accurate values of multiple Coulomb scattering (MCS) angles. High-quality experimental data on MCS angles in the energy range for proton therapy are, however, sparse. In this work, MCS modeling in proton transport was evaluated employing an experimental method to measure these angles on a medical proton beamline in clinically relevant materials. Results are compared to Monte Carlo simulations and analytical models. Aluminum, brass, and lucite (PMMA) scatterers of clinically relevant thicknesses were irradiated with protons at 100, 160, and 220MeV. Resulting spatial distributions of individual pencil beams were measured with a scintillating screen. The MCS angles were determined by deconvolution and a virtual point source approach. Results were compared to those obtained with the Monte Carlo codes PENH, TOPAS, and RayStation Monte Carlo, as well as the analytical models RayStation Pencil Beam Algorithm and the Molière/Fano/Hanson variant of the Molière theory. Experimental data obtained with the presented methodology agree with previously published results within 6%, with an average deviation of 3%. The combined average uncertainty of the experimental data yielded 1.8%, while the combined maximum uncertainty was below 4%. The obtained Monte Carlo results for PENH, TOPAS, and RayStation deviate on average for all considered energies, materials and thicknesses, by 2.5%, 3.4%, and 2.8% from the experimental data, respectively. For the analytical models, the average deviations amount to 4.5% and 2.9% for the RayStation Pencil Beam Algorithm and the Molière/Fano/Hanson model, respectively. The experimental method developed for the present work allowed to measure MCS angles in clinical proton facilities with good accuracy. The presented method permits to extend the database on experimental MCS angles which is rather limited. This work further provides benchmark data for lucite in thicknesses relevant for clinical applications. The data may serve to validate dose engines of treatment planning systems and secondary dose check software. The Monte Carlo and analytical algorithms studied are capable of reproducing MCS data within the required accuracy for clinical applications.

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