3 March 2017 Open-source software for collision detection in external beam radiation therapy
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Abstract
PURPOSE: Collision detection for external beam radiation therapy (RT) is important for eliminating the need for dryruns that aim to ensure patient safety. Commercial treatment planning systems (TPS) offer this feature but they are expensive and proprietary. Cobalt-60 RT machines are a viable solution to RT practice in low-budget scenarios. However, such clinics are hesitant to invest in these machines due to a lack of affordable treatment planning software. We propose the creation of an open-source room’s eye view visualization module with automated collision detection as part of the development of an open-source TPS. METHODS: An openly accessible linac 3D geometry model is sliced into the different components of the treatment machine. The model’s movements are based on the International Electrotechnical Commission standard. Automated collision detection is implemented between the treatment machine’s components. RESULTS: The room’s eye view module was built in C++ as part of SlicerRT, an RT research toolkit built on 3D Slicer. The module was tested using head and neck and prostate RT plans. These tests verified that the module accurately modeled the movements of the treatment machine and radiation beam. Automated collision detection was verified using tests where geometric parameters of the machine’s components were changed, demonstrating accurate collision detection. CONCLUSION: Room’s eye view visualization and automated collision detection are essential in a Cobalt-60 treatment planning system. Development of these features will advance the creation of an open-source TPS that will potentially help increase the feasibility of adopting Cobalt-60 RT.
Conference Presentation
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Vinith M. Suriyakumar, Renee Xu, Csaba Pinter, Gabor Fichtinger, "Open-source software for collision detection in external beam radiation therapy", Proc. SPIE 10135, Medical Imaging 2017: Image-Guided Procedures, Robotic Interventions, and Modeling, 101351G (3 March 2017); doi: 10.1117/12.2255644; https://doi.org/10.1117/12.2255644
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