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Abstract #1703

Evaluating the impact of respiratory binning strategies on 4D-MRI reconstruction for an MR-Linac

Bastien Lecoeur1, Marco Barbone2, Sophie Alexander3, Jessica Gough3, Uwe Oelfke1, Wayne Luk2, and Andreas Wetscherek1
1Joint Department of Physics, The Institute of Cancer Research, London, United Kingdom, 2Department of Computing, Imperial College London, London, United Kingdom, 3The Royal Marsden NHS Fundation Trust, London, United Kingdom


In the context of MR-guided radiotherapy, 4D-MRI is of particular interest for lung and abdominal cancer treatment, as it enables quantifying the extent of respiratory motion at the time of treatment, facilitating time-efficient midposition treatments. To reduce long reconstruction times of iterative compressed sensing-based reconstructions involving algorithms, such as XD-GRASP, we used a fast C++ implementation. We evaluated the impact of using overlapping respiratory bins and different self-gating signals on image quality and reconstruction time in multiple patients with and without abdominal compression belts.

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