The Echo-AVCS Study is an investigator-initiated, prospective, multicenter observational study designed to derive and validate an artificial intelligence (AI)-based echocardiographic aortic valve calcium score (Echo-AVCS) for confirming severe aortic stenosis (AS). Transthoracic echocardiography (TTE) is the standard imaging modality for assessing AS severity; however, discrepancies between valve area and transvalvular gradient measurements may complicate diagnosis, particularly in low-flow or discordant AS presentations. Cardiac computed tomography (CT)-derived aortic valve calcium scoring is currently used to resolve diagnostic uncertainty, but it involves additional cost and radiation exposure. This study will enroll consecutive adult patients undergoing clinically indicated TTE and cardiac CT with calcium scoring performed within 3 months. Standardized echocardiographic images will be centrally analyzed using dedicated AI-based image segmentation and machine learning methods to quantify aortic valve calcification directly from TTE images. CT-derived aortic valve calcium score will serve as the reference standard. The primary objective is to derive and validate the Echo-AVCS score for identifying severe AS. Secondary objectives include determination of sex-specific diagnostic thresholds, correlation with CT calcium volume, association with symptoms and NYHA class, and evaluation of prognostic associations with aortic valve replacement, heart failure hospitalization, cardiovascular events, and mortality at 1-year follow-up.
Age range
18 Years
Sex
ALL
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Derivation of Echo-AVCS
Timeframe: 6 months
Validation of Echo-AVCS
Timeframe: 6 months