AI tool to detect and measure aortic regurgitation
Official title: Artificial Intelligence in Aortic Regurgitation: A Multicenter Randomised Controlled Trial
Run by Chinese University of Hong Kong · NCT07486271 · Data updated 2026-11-12
This project will test an AI-assisted echocardiography tool to detect and measure aortic regurgitation in adults and compare its results with standard manual measurements.
Quick facts
| Study type | Interventional |
|---|---|
| Ages | 18 Years and up |
| Sex | All |
| Enrollment | 540 (estimated) |
| Sponsor | Chinese University of Hong Kong Academic / other |
| Locations | 1 site (Hong Kong, New Territories) |
| Status | Recruiting |
| Started | December 1, 2025 |
| Main results expected | March 31, 2028 |
| Study ends | March 31, 2028 |
| Registry record updated | March 20, 2026 |
| Trial ID | NCT07486271 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Adults (age 18 and older) with a confirmed aortic regurgitation diagnosis on transthoracic echocardiography and an adequate acoustic window are ideal candidates.
✕Probably not a fit
Patients with poor image quality, prior cardiac transplant or implanted cardiac devices, or who are pregnant or breastfeeding are unlikely to benefit or be eligible.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
Deep learning algorithms will be trained to analyze echocardiographic images and integrate multiple Doppler and structural parameters to automatically detect and quantify aortic regurgitation. The AI system will be validated in a multicenter randomized controlled trial that assigns patients to AI-assisted interpretation or conventional manual measurement and compares diagnostic accuracy and consistency. Participating centers will use standardized image acquisition protocols with central adjudication to ensure comparability across sites. The approach aims to reduce inter-operator variability, speed diagnosis, and make advanced AR assessment more accessible, including in resource-limited settings.
Why it matters
Potential benefit: If successful, the AI tool could provide faster, more consistent AR diagnoses and extend specialist-level echo interpretation to more hospitals.
How similar studies have gone: Previous work has shown promising accuracy for AI in echocardiography and valvular disease, but large multicenter randomized comparisons specifically focused on AR quantification are still limited.
Who can join: the full rules
Show full inclusion / exclusion criteria
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.
Where it's running
-
Division of Cardiology, Department of Medicine and Therapeutics Faculty of Medicine, The Chinese University of Hong Kong
Hong Kong, New Territories, Hong Kong Recruiting
Study contacts
- Principal investigator: Alex PW Lee, Professor — Chinese University of Hong Kong
- Study coordinator: Xueting Wang
- Email: xueting@cuhk.edu.hk
- Phone: (852) 3505 3840
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How to take part
- Review the eligibility criteria above with your treating physician.
- Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
- Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.