Aortic Regurgitation Disease
Conditions
Keywords
Aortic Regurgitation, Artificial Intelligence, Echocardiography, Automated Diagnosis, Clinical Efficacy
Brief summary
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.
Interventions
DIAGNOSTIC_TESTAI-Assisted Group
Participants in this group will undergo aortic regurgitation assessment using an advanced artificial intelligence tool.
OTHERManual measurement group
Participants in this group will receive a traditional diagnostic assessment for aortic regurgitation, performed by trained sonographers following standard protocols.
Sponsors
Chinese University of Hong Kong
Semmelweis University
The Prince Charles Hospital
Toho University
Us2.ai
The University of New South Wales
Study design
Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
DIAGNOSTIC
Masking
DOUBLE (Subject, Investigator)
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No
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.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Study Outcomes | 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
| Measure | Time frame | Description |
|---|---|---|
| Comparing Accuracy in Differentiating AR Severity Levels | 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. |
| Assessing deviations in Effective Regurgitant Orifice Area (EROA) | 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. |
| Assessing deviations in Vena Contracta (VC) | 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. |
| Assessing deviations in Proximal Isovelocity Surface Area (PISA) | 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. |
| Assessing deviations in jet width | 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. |
| Assessing deviations in Regurgitant Volume (RegVol) | 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. |
| Comparing Assessment Completion Time | 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. |
| Tracking 1-Year Outcomes | 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. |
Countries
Hong Kong
Contacts
CONTACTXueting Wang
PRINCIPAL_INVESTIGATORAlex PW Lee, Professor
Chinese University of Hong Kong
Outcome results
None listed