Artificial Intelligence in Aortic Regurgitation

Trial statusRecruiting
Trial phaseNot applicable
Trial typeInterventional
Biological sexAll
Age18+
SponsorChinese University of Hong Kong

About this trial

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 criteria

Qualifiers

Confirmed AR diagnosis via TTE and Doppler imaging per guidelines.

Age ≥ 18 years.

Adequate acoustic window for AR quantification.

Disqualifiers

Prior cardiac transplant or implanted cardiac devices.

Poor image quality.

Pregnancy or lactation.

Trial design

Treatments tested in this trial

  • AI-Assisted Group
  • Manual measurement group

Treatment groups

540 Participants
are divided into 2 treatment groups

Sponsors and collaborators

Chinese University of Hong Kong

Lead sponsor

Semmelweis University

Collaborator

The Prince Charles Hospital

Collaborator

Toho University

Collaborator

Us2.ai

Collaborator

The University of New South Wales

Collaborator