CMR-AI and Outcomes in AS

Materials \& Methods: In a current large-scale international, prospective, multi-center study ~1500 patients with severe AS underwent CMR imaging prior to aortic valve replacement (AVR). An AI-based algorithm, developed in the UK, was used for fully automated assessment of parameters of cardiac structure (end-diastolic volume, end-systolic volume, LV mass, maximum wall thickness) and function (EF, GLS, MAPSE, TAPSE). In this proposed follow-up project, we aim to associate these AI-based CMR parameters at baseline with mid-term clinical outcomes at 24-months post-AVR. A composite of all-cause mortality and heart failure hospitalization will serve as the primary endpoint. CMR-AI will be repeated at 24-months follow-up and trajectories from pre- to post-AVR will be assessed as a secondary endpoint.

Future Outlook: In severe AS, a novel AI-based algorithm allows immediate and precise measurements of ventricular structure and function on CMR imaging. Our goal is to identify early markers of cardiac dysfunction indicating adverse mid-term prognosis post-AVR. This has guideline-forming potential as the optimal timepoint for AVR in patients with AS is currently a matter of debate.