Overview

This research project aims to develop and validate a tool that uses artificial intelligence (AI) to automatically detect and quantify aortic regurgitation (AR). The clinical efficacy of this tool will be established by comparing it to manual diagnostic methods in a multicenter randomized controlled trial. By leveraging deep learning (DL) techniques, the AI system will automate aortic regurgitation (AR) detection, measurement, and diagnosis, addressing challenges like variability in echocardiographic interpretations and the need for specialized expertise. It will integrate multiple echocardiographic parameters to provide accurate, standardized, and efficient AR diagnoses, reducing human error and improving consistency. This tool will enhance diagnostic precision and accessibility, improving clinical outcomes and extending advanced diagnostic capabilities to a broader range of healthcare environments, including resource-limited settings.

Eligibility

Inclusion Criteria:

• Confirmed AR diagnosis via TTE and Doppler imaging per guidelines.
• Age ≥ 18 years.
• Adequate acoustic window for AR quantification.

Exclusion Criteria:

• Prior cardiac transplant or implanted cardiac devices.
• Poor image quality.
• Pregnancy or lactation.