Arrhythmia is often a significant challenge to acquiring diagnostic quality cardiac MRI. While discarding atypical cardiac cycles can exclude short-lived arrhythmic events, such as premature ventricular contractions (PVCs), this fails for atrial fibrillation (Afib), where subjects have an irregular cardiac cycle pattern. Harnessing the potential of the XD-GRASP MRI technique to reconstruct continuously acquired data with cardiac and respiratory phase as extra dimensions, we propose to additionally classify cardiac cycles for Afib patients according to their preload state, and simultaneously reconstruct the different types of arrhythmic cycles in a five-dimensional image space.
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