Purpose: 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. Methods: matRad is entirely written in Matlab and is freely available online. It re-implements wellestablished 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. Results: We observe three-dimensional c-analysis pass rates ≥ 99.67% for all three radiation modalities utilizing a distance to agreement of 2 mm 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 1.59 GB-9.07 GB and 0.29 GB-17.94 GB for photons and charged particles, respectively. Conclusion: The dosimetric accuracy, computational performance and open-source character of matRad encourages a future application of matRad for both educational and research purposes.

Motion and uncertainty in radiotherapy is traditionally handled via margins. The clinical target volume (CTV) is expanded to a larger planning target volume (PTV), which is irradiated to the prescribed dose. However, the PTV concept has several limitations, especially in proton therapy. Therefore, robust and probabilistic optimization methods have been developed that directly incorporate motion and uncertainty into treatment plan optimization for intensity modulated radiotherapy (IMRT) and intensity modulated proton therapy (IMPT). Thereby, the explicit definition of a PTV becomes obsolete and treatment plan optimization is directly based on the CTV. Initial work focused on random and systematic setup errors in IMRT. Later, inter-fraction prostate motion and intra-fraction lung motion became a research focus. Over the past ten years, IMPT has emerged as a new application for robust planning methods. In proton therapy, range or setup errors may lead to dose degradation and misalignment of dose contributions from different beams -a problem that cannot generally be addressed by margins. Therefore, IMPT has led to the first implementations of robust planning methods in commercial planning systems, making these methods available for clinical use. This paper first summarizes the limitations of the PTV concept. Subsequently, robust optimization methods are introduced and their applications in IMRT and IMPT planning are reviewed.Abstract. Motion and uncertainty in radiotherapy is traditionally handled via 31 margins. The clinical target volume (CTV) is expanded to a larger planning target 32 volume (PTV), which is irradiated to the prescribed dose. However, the PTV 33 concept has several limitations, especially in proton therapy. Therefore, robust and 34 probabilistic optimization methods have been developed that directly incorporate 35 motion and uncertainty into treatment plan optimization for intensity modulated 36 radiotherapy (IMRT) and intensity modulated proton therapy (IMPT). Thereby, the 37 explicit definition of a PTV becomes obsolete and treatment plan optimization is 38 directly based on the CTV. Initial work focused on random and systematic setup errors 39 in IMRT. Later, inter-fraction prostate motion and intra-fraction lung motion became 40 a research focus. Over the past 10 years, IMPT has emerged as a new application for 41 robust planning methods. In proton therapy, range or setup errors may lead to dose 42 degradation and misalignment of dose contributions from different beams a problem 43 Robust radiotherapy planning 2 that cannot generally be addressed by margins. Therefore, IMPT has led to the first 44 implementations of robust planning methods in commercial planning systems, making 45 these methods available for clinical use. This paper first summarizes the limitations 46 of the PTV concept. Subsequently, robust optimization methods are introduced and 47 their applications in IMRT and IMPT planning are reviewed. 48 1. Introduction 49Radiotherapy aims at delivering curative doses of radiation ...

The authors' study reconfirms the dosimetric benefits of noncoplanar irradiation of nasopharyngeal tumors. Both SnS using optimized noncoplanar beam ensembles and VMAT using an optimized, arbitrary, noncoplanar trajectory enabled dose reductions in organs at risk compared to coplanar SnS and VMAT. Using great circles or simple couch rotations to implement noncoplanar VMAT, however, was not sufficient to yield meaningful improvements in treatment plan quality. The authors estimate that noncoplanar VMAT using arbitrary optimized irradiation trajectories comes at an increased delivery time compared to coplanar VMAT yet at a decreased delivery time compared to noncoplanar SnS IMRT.