Cardiac magnetic resonance (CMR) scanning provides a method to diagnose cardiac disease. For obtaining an effective image, the standard procedure of CMR requires patients to hold their breath during the scanning, but it is difficult for frail patients in clinic. Furthermore, standard CMR imaging depends upon averaging together regular cardiac cycles, which is disrupted by irregular heartbeats, this irregularity prevents visualization of arrhythmias. HeartSpeed software will introduce a new strategy to help frail patients, magnetic resonance technicians, and physicians, by enabling free-breathing CMR image post-processing that corrects the breathing motion. Closely related algorithms provide a new approach to visualize and explore the irregularities of heartbeats in real-time, unaveraged CMR scans. It includes focusing on the region of interest (ROI), such as a chamber or valve, identifying irregular cardiac cycles by PCA, and cluster analysis of heart beats to find and visualize irregularities, such as those of atrial fibrillation (AFib), which are common and increase with age. In scans of patients with AFib, I propose to reconstruct CMR movies that simplify the motions by grouping related beats. These image reconstructions will enable viewing of the blood flow in a valve and chamber and the motions of the wall of that chamber. These functions can be used for ultrafast, real-time CMR imaging of irregular heartbeats to extract the various components of the complex cardiac motion in patients with arrhythmias. The future work includes using statistics and data science methods to characterize patients with cardiac arrhythmias with novel imaging insight.
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