We report on the development of the open-source cross-platform radiation treatment planning toolkit matRad and its comparison against validated treatment planning systems. The toolkit enables three-dimensional intensity-modulated radiation therapy treatment planning for photons, scanned protons and scanned carbon ions.
matRad is entirely written in Matlab and is freely available online. It re-implements well-established algorithms employing a modular and sequential software design to model the entire treatment planning workflow. It comprises core functionalities to import DICOM data, to calculate and optimize dose as well as a graphical user interface for visualization. matRad dose calculation algorithms (for carbon ions this also includes the computation of the relative biological effect) are compared against dose calculation results originating from clinically approved treatment planning systems.
We observe three-dimensional γ-analysis pass rates ≥ 99.67% for all three radiation modalities utilizing a distance to agreement of 2mm and a dose difference criterion of 2%. The computational efficiency of matRad is evaluated in a treatment planning study considering three different treatment scenarios for every radiation modality. For photons, we measure total run times of 145 s - 1260 s for dose calculation and fluence optimization combined considering 4-72 beam orientations and 2608 - 13597 beamlets. For charged particles, we measure total run times of 63 s -993 s for dose calculation and fluence optimization combined considering 9963 - 45574 pencil beams. Using a CT and dose grid resolution of 0.3 cm(3) requires a memory consumption of 1.59GB - 9.07GB and 0.29GB - 17.94GB for photons and charged particles, respectively.
The dosimetric accuracy, computational performance and open-source character of matRad encourages a future application of matRad for both educational and research purposes. This article is protected by copyright. All rights reserved.
This research output has an Altmetric Attention Score of 11. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 28 January 2025.
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