STOCKHOLM, May 10, 2017 – RayStation 6, the latest version of RaySearch’s innovative treatment planning system, introduces a Monte Carlo dose engine for proton pencil beam scanning (PBS) plans, which can be used in parallel with the existing pencil beam dose engine. The engine brings an additional level of precision without compromising on speed.
Monte Carlo dose planning is one of the important new proton therapy features that RaySearch will be demonstrating this week at the PTCOG conference in Yokohama, Japan.
Monte Carlo dose calculation is based on simulating the transport of individual particles. This makes it possible to fully account for the unaltered patient geometry, whereas analysis-based algorithms such as the pencil beam method require an approximate representation of the geometry. For the Monte Carlo method, accuracy is high, but speed was traditionally an issue until the advent of fast Monte Carlo algorithms. The dose engine in RayStation strikes the optimal balance between accurate physics modeling and speed, making it highly effective in clinical workflows.
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The Monte Carlo and pencil beam dose engines in RayStation are designed to be used in parallel, ensuring efficient and accurate dose calculation for all proton PBS planning needs. A single PBS machine model for a particular delivery system can support both the Monte Carlo and pencil beam dose calculations, and the beam-measurement data needed for commissioning is the same for both dose engines. The Monte Carlo and pencil beam dose engines can both be used for calculating spot dose distributions as input for optimization, with or without patient-specific block apertures, as well as for calculating a final dose distribution for plan approval.
Johan Löf, CEO of RaySearch, says: “Proton therapy is an important area of focus for RaySearch and we aim to be at the leading edge of developments to improve patient treatment. The unmatched speed of RayStation makes it possible to deliver the accuracy of Monte Carlo dose planning while maintaining a fast and efficient clinical workflow.”
