AI Assessment of Low-Gradient Aortic Stenosis Severity Based on Echocardiography
Key facts
- Where
- Warsaw, PolandSee the site
Where in Poland
- Department of Valvular Heart Disease, National Institute of Cardiology, Warsaw, PolandWarsaw, PolandContact: Michał Wrzosek, MDTaking people
Questions to ask the study team
- How often do I need to come in, and for how long each time?
- Are travel costs paid?
- Can I keep my own doctor?
- What happens if I want to stop?
Contact the study team: see the registry record → Contacts and Locations
Print a page for my doctorTrial details
- Who runs it
- National Institute of Cardiology, Warsaw, Poland
- Trial code
- NCT07144189
- Record updated
- 2 December 2025
- Original description
The purpose of this study is to evaluate the effectiveness of an artificial intelligence (AI) model developed by the investigators for identifying severe low-gradient aortic valve stenosis. Accurate assessment of stenosis severity is crucial for proper qualification for surgical treatment. It is expected that the use of AI will improve diagnostic accuracy and thereby support better clinical outcomes.Read full original descriptionShow less
Artificial Intelligence-Based Assessment of Low-Gradient Aortic Stenosis Severity Using Echocardiographic Images
The purpose of this study is to evaluate the effectiveness of an artificial intelligence (AI) model developed by the investigators for identifying severe low-gradient aortic valve stenosis. Accurate assessment of stenosis severity is crucial for proper qualification for surgical treatment. It is expected that the use of AI will improve diagnostic accuracy and thereby support better clinical outcomes.
Patients with suspected significant low-gradient aortic stenosis will be enrolled. The study is observational and involves no additional risk for participants. Standard imaging studies performed for clinical indications will be additionally analyzed by the AI model, which will classify aortic stenosis as severe or moderate. The model's results will not influence the clinical management of participants but will be compared with physicians' assessments to validate its diagnostic performance.
The study will be conducted in 2025-2026. The findings will provide insights into the usefulness of AI in the diagnosis of severe aortic stenosis and may contribute to the development of advanced clinical decision-support tools.
Inclusion: Age ≥ 18 years; Clinical suspicion of significant low-gradient aortic stenosis; Echocardiographic examination performed for clinical indications; Ability to provide informed consent.
Exclusion: Previous aortic valve intervention (surgical or transcatheter); Concomitant severe valvular disease (severe mitral stenosis or mitral/aortic regurgitation) that could confound assessment; Inadequate image quality precluding echocardiographic analysis; Patients unwilling or unable to provide informed consent.