Artificial Intelligence in Aortic Regurgitation
ConditionAortic Regurgitation Disease
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
This trial does not accept healthy volunteersQualifiers
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
Design model
Parallel
Treatments tested in this trial
AI-Assisted Group
Diagnostic testParticipants in this group will undergo aortic regurgitation assessment using an advanced artificial intelligence tool.
Manual measurement group
Other interventionParticipants in this group will receive a traditional diagnostic assessment for aortic regurgitation, performed by trained sonographers following standard protocols.
Treatment groups
540 Participants
are divided into 2 treatment groupsGroup A: AI-Assisted GroupActive comparator 1 intervention
Group B: Manual Measurement GroupOther 1 intervention
Trial outcomes
Primary outcomes
1
Study Outcomes
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.
Time frame
This will be recorded from baseline to study completion (20 months)Secondary outcomes
1
Comparing Accuracy in Differentiating AR Severity Levels
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.
Time frame
This will be recorded from baseline to study completion (20 months)2
Assessing deviations in Effective Regurgitant Orifice Area (EROA)
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.
Time frame
This will be recorded from baseline to study completion (20 months)3
Assessing deviations in Vena Contracta (VC)
The Vena Contracta (VC) is an important measurement in echocardiography used to evaluate how severe mitral regurgitation is and will be measured during echocardiography.
Time frame
This will be recorded from baseline to study completion (20 months)4
Assessing deviations in Proximal Isovelocity Surface Area (PISA)
Proximal Isovelocity Surface Area (PISA) is a method used in echocardiography to evaluate mitral regurgitation and will be measured during echocardiography.
Time frame
This will be recorded from baseline to study completion (20 months)Sponsors and contacts
Click on the lead sponsor to view all of their trials.
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
Source ClinicalTrials.gov