Enhancing Real-Time Cardiac MRI with Image-Domain Diffusion Model for Arrhythmia Patient

Motivation: Persistent premature ventricular obscure left ventricle (LV) function assessment. Current imaging lacks temporal resolution and methods for effective differentiation of beat morphologies. Goal(s): To enhance real-time MRI scans of arrhythmia patients, targeting high temporal resolution for discerning arrhythmia beats. Approach: We trained an image-domain diffusion model on a public database, optimizing transferability to arrhythmia scans. The model employs prior images during the reverse sampling to impose image-domain constraints. Results: Achieved a 62% increase in LV signal-to-noise ratio and a 150% increase in LV-to-myocardium contrast-to-noise ratio across 10 real-time scans. Also facilitated direct beat morphology analysis, paving the way for PVC-induced cardiomyopathy studies. Impact: The trajectory-agnostic diffusion model offers clinicians and patients clearer visualization of real-time arrhythmia scans, potentially assisting the early detection and study of PVC-induced cardiomyopathies. Future research may explore its applicability to other rapid-cycle cardiac phenomena.