Real-time 3D MRI for low-latency volumetric motion tracking was successfully implemented on a 1.5T MR-Linac system using the MRSIGMA framework. A first scan was performed for offline learning to obtain a training dictionary of ten 3D motion states. A second scan with the same sequence parameters was performed to generate the motion signature in real-time for online matching and was also used as a reference for retrospective self-validation. The feasibility of the technique was demonstrated on a healthy volunteer and a patient with pancreatic cancer which presented high quantitative concordance between contours of real-time MRSIGMA matching and the reference.
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