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| Name | Class |
|---|---|
| Semmelweis University | OTHER |
| The Prince Charles Hospital | OTHER_GOV |
| Toho University | OTHER |
| Us2.ai |
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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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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| AI-Assisted Group | Active Comparator | AR severity will be assessed using an AI tool that evaluates grading and key echocardiographic parameters (e.g., EROA, VC, PISA, jet width, and RegVol), along with the time required for assessments. |
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| Manual Measurement Group | Other | AR severity will be assessed manually by trained sonographers following standard protocols. Cardiologists (ASE level III or equivalent), blinded to patient history and group assignment, will review both AI-generated and manual outputs to make final diagnoses and treatment decisions based solely on the initial assessments. |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| AI-Assisted Group | Diagnostic Test | Participants in this group will undergo aortic regurgitation assessment using an advanced artificial intelligence tool. |
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| Measure | Description | Time Frame |
|---|---|---|
| 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. | This will be recorded from baseline to study completion (20 months) |
| Measure | Description | Time Frame |
|---|---|---|
| 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. | This will be recorded from baseline to study completion (20 months) |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Xueting Wang | Contact | (852) 3505 3840 | xueting@cuhk.edu.hk |
| Name | Affiliation | Role |
|---|---|---|
| Alex PW Lee, Professor | Chinese University of Hong Kong | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Division of Cardiology, Department of Medicine and Therapeutics Faculty of Medicine, The Chinese University of Hong Kong | Recruiting | Hong Kong | New Territories | Sha Tin | Hong Kong |
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| ID | Term |
|---|---|
| D001022 | Aortic Valve Insufficiency |
| ID | Term |
|---|---|
| D000082862 | Aortic Valve Disease |
| D006349 | Heart Valve Diseases |
| D006331 | Heart Diseases |
| D002318 | Cardiovascular Diseases |
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| UNKNOWN |
| The University of New South Wales | OTHER |
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| Manual measurement group | Other | Participants in this group will receive a traditional diagnostic assessment for aortic regurgitation, performed by trained sonographers following standard protocols. |
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| 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. |
| This will be recorded from baseline to study completion (20 months) |
| 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. | This will be recorded from baseline to study completion (20 months) |
| 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. | This will be recorded from baseline to study completion (20 months) |
| Assessing deviations in jet width | The jet width is a critical measurement used to assess the severity of aortic regurgitation and will be measured during echocardiography. | This will be recorded from baseline to study completion (20 months) |
| Assessing deviations in Regurgitant Volume (RegVol) | Regurgitant Volume assesses how much blood leaks back into the left atrium during mitral regurgitation and will be measured using Doppler echocardiography. | This will be recorded from baseline to study completion (20 months) |
| Comparing Assessment Completion Time | To compare the time taken by the AI group, the manual group, and the cardiologists to complete their assessments. | The time taken for each method to reach a diagnosis will be recorded from baseline to study completion (20 months) |
| Tracking 1-Year Outcomes | 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. | Participants will be followed up at 6 and 12 months to monitor outcomes, including 1-year all-cause mortality and HFH. |
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