AI Assessment of Low-Gradient Aortic Stenosis Severity Based on Echocardiography

NCT07144189 | Recruiting

• 1 other identifier: 4.35/VI/25
• Study Type: observational
• Target: 300
• Locations: 1 country
• Sites: 1

Brief Summary

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.

Conditions

Low-gradient Aortic Stenosis; Aortic Stenosis

Keywords

low-gradient aortic stenosis; Echocardiography; Artificial intelligence; Cardiac imaging; Machine learning

Outcome Measures

Primary Outcomes (1)

• Area Under the Receiver Operating Characteristic Curve (AUC) describing the sensitivity-specificity relationship of the AI model.

  AUC will be calculated to assess the ability of the AI model to differentiate between severe low-gradient and moderate aortic stenosis. The analysis will use physician assessment and guideline-based diagnostic criteria as the reference standard. AUC will be reported with 95% confidence intervals.

  At the time of the nearest Heart Team meeting following the echocardiographic examination (typically within 1 week).

Secondary Outcomes (1)

• Diagnostic performance of the AI model in clinically relevant subgroups.

  At the nearest Heart Team meeting following the echocardiographic examination (typically within 1 week).

Study Arms (1)

Patients with suspected significant low-gradient aortic stenosis.

Approximately 300 patients with suspected significant low-gradient aortic stenosis undergoing standard echocardiographic evaluation between 2025 and 2026. Echocardiographic images will be secondarily analyzed by the AI model to classify stenosis as severe or moderate. The AI results will be compared with physicians assessments. No intervention or modification of clinical care is involved.

Diagnostic Test: AI diagnostic test for severe low-gradient aortic stenosis

Interventions

AI diagnostic test for severe low-gradient aortic stenosis DIAGNOSTIC_TEST

All participants will undergo standard transthoracic echocardiography performed for clinical indications. Echocardiographic images will be analyzed both by experienced physicians and by the investigational AI model. Additional diagnostic tests (such as cardiac CT, low-dose dobutamine stress echocardiography or transesophageal echocardiography) may be performed if clinically indicated, according to current guideline recommendations. The AI-derived results will not influence clinical decision-making.

Patients with suspected significant low-gradient aortic stenosis.

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

The study population will include adult patients (≥18 years) diagnosed in the Echocardiography Laboratory of the National Institute of Cardiology in Warsaw, Department of Valvular Heart Disease. Eligible participants will be those referred for echocardiographic evaluation due to clinical suspicion of significant low-gradient aortic stenosis. Standard-of-care imaging performed for clinical indications will be analyzed. Approximately 300 patients are expected to be enrolled between 2025 and 2026. Patients with previous aortic valve intervention (surgical or transcatheter) or other exclusion criteria will not be included.

You may qualify if:

• Age ≥ 18 years
• Clinical suspicion of significant low-gradient aortic stenosis
• Echocardiographic examination performed for clinical indications
• Ability to provide informed consent

You may not qualify if:

• Previous aortic valve intervention (surgical or transcatheter)
• Inadequate image quality precluding echocardiographic analysis
• Concomitant severe valvular disease (severe mitral stenosis or mitral/aortic regurgitation) that could confound assessment
• Patients unwilling or unable to provide informed consent

Sponsors & Collaborators

• National Institute of Cardiology, Warsaw, Poland: lead
• The Institute of Bioorganic Chemistry, Polish Academy of Sciences: collaborator

Study Sites (1)

Department of Valvular Heart Disease, National Institute of Cardiology, Warsaw, Poland

Warsaw, Masovian Voivodeship, Poland

RECRUITING

Related Publications (1)

• Wrzosek M, Buchwald M, Czernik P, Kupinski S, Zatorska K, Jasinska A, Zakrzewski D, Pukacki J, Mazurek C, Pekal R, Hryniewiecki T. Diagnosing Severe Low-Gradient vs Moderate Aortic Stenosis with Artificial Intelligence Based on Echocardiography Images. J Imaging Inform Med. 2025 Apr 21. doi: 10.1007/s10278-025-01497-4. Online ahead of print.

  PMID: 40259202 RESULT

MeSH Terms

Conditions

Aortic Valve Stenosis

Condition Hierarchy (Ancestors)

Aortic Valve Disease; Heart Valve Diseases; Heart Diseases; Cardiovascular Diseases; Ventricular Outflow Obstruction

Study Officials

• Tomasz Hryniewiecki, Professor of Medicine

  Department of Valvular Heart Disease, National Institute of Cardiology, Warsaw, Poland

  STUDY CHAIR

• Michał Wrzosek, MD

  Department of Valvular Heart Disease, National Institute of Cardiology, Warsaw, Poland

  PRINCIPAL INVESTIGATOR

• Karina Zatorska, MD, PhD

  Department of Valvular Heart Disease, National Institute of Cardiology, Warsaw, Poland

  STUDY DIRECTOR

Central Study Contacts

Michał Wrzosek, MD

CONTACT

+48 22 3434189; mwrzosek@ikard.pl

Tomasz Hryniewiecki, Professor of Medicine

CONTACT

+48 223434180; thryniewiecki@ikard.pl

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: August 20, 2025
• First Posted: August 27, 2025
• Study Start: August 20, 2025
• Primary Completion (Estimated): August 20, 2026
• Study Completion (Estimated): August 20, 2026
• Last Updated: December 2, 2025

Record last verified: 2025-08

Data Sharing

• IPD Sharing: Will not share

Locations

PL (1)