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NCT Number: NCT07486271

Artificial Intelligence in Aortic Regurgitation

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.

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Key information

Conditions

Aortic Regurgitation Disease Aortic Valve Disease Aortic Valve Insufficiency Cardiovascular Diseases Heart Diseases Heart Valve Diseases

Age range

18 year and older

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

Division of Cardiology, Department of Medicine and Therapeutics Faculty of Medicine, The Chinese University of Hong Kong

Hong Kong, New Territories, Sha Tin

Location status: Recruiting

Location contact

Xueting PW Wang, Professor

CONTACT

[email protected]

(852) 3505 3840

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

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.

Treatment and study plan

AI-Assisted Group

Diagnostic Test

Participants in this group will undergo aortic regurgitation assessment using an advanced artificial intelligence tool.

Manual measurement group

Other

Participants in this group will receive a traditional diagnostic assessment for aortic regurgitation, performed by trained sonographers following standard protocols.

Primary outcomes

  1. Study Outcomes

    Time frame: This will be recorded from baseline to study completion (20 months)

    To compare the accuracy of the AI group and the manual group in distinguishing severe from non-severe AR, using expert cardiologists' (ASE level III or equivalent) assessments as the reference standard.

Secondary outcomes

  1. Comparing Accuracy in Differentiating AR Severity Levels

    Time frame: This will be recorded from baseline to study completion (20 months)

    To compare the accuracy of the AI group and the manual group in differentiating trace, mild, moderate, and severe aortic regurgitation, using cardiologists' assessments as the reference standard.

  2. Assessing deviations in Effective Regurgitant Orifice Area (EROA)

    Time frame: This will be recorded from baseline to study completion (20 months)

    The Effective Regurgitant Orifice Area (EROA) assesses the size of a valve opening that leads to backward blood flow in the heart. It is an important metric for evaluating valvular regurgitation and will be measured during echocardiography.

  3. Assessing deviations in Vena Contracta (VC)

    Time frame: This will be recorded from baseline to study completion (20 months)

    The Vena Contracta (VC) is an important measurement in echocardiography used to evaluate how severe mitral regurgitation is and will be measured during echocardiography.

  4. Assessing deviations in Proximal Isovelocity Surface Area (PISA)

    Time frame: This will be recorded from baseline to study completion (20 months)

    Proximal Isovelocity Surface Area (PISA) is a method used in echocardiography to evaluate mitral regurgitation and will be measured during echocardiography.

  5. Assessing deviations in jet width

    Time frame: This will be recorded from baseline to study completion (20 months)

    The jet width is a critical measurement used to assess the severity of aortic regurgitation and will be measured during echocardiography.

  6. Assessing deviations in Regurgitant Volume (RegVol)

    Time frame: This will be recorded from baseline to study completion (20 months)

    Regurgitant Volume assesses how much blood leaks back into the left atrium during mitral regurgitation and will be measured using Doppler echocardiography.

  7. Comparing Assessment Completion Time

    Time frame: The time taken for each method to reach a diagnosis will be recorded from baseline to study completion (20 months)

    To compare the time taken by the AI group, the manual group, and the cardiologists to complete their assessments.

  8. Tracking 1-Year Outcomes

    Time frame: Participants will be followed up at 6 and 12 months to monitor outcomes, including 1-year all-cause mortality and HFH.

    To track 1-year all-cause mortality and heart failure hospitalizations (HFH), comparing outcomes for patients with severe aortic regurgitation identified by the AI and manual groups, separately.

Study contacts

Contact information is provided by the study sponsor or research team.

Xueting Wang

CONTACT

[email protected]

(852) 3505 3840

Sponsors and collaborators

Lead sponsor

Chinese University of Hong Kong

Other

Collaborators

  • Semmelweis University
  • The Prince Charles Hospital
  • The University of New South Wales
  • Toho University
  • Us2.ai

Registry information

Official study title

Artificial Intelligence in Aortic Regurgitation: A Multicenter Randomised Controlled Trial

Important dates

Study start
2025
Primary completion
2028
Study completion
2028
First posted
Mar 20, 2026
Registry last updated
Mar 20, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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