Diagnosing Severe Low-Gradient vs Moderate Aortic Stenosis with Artificial Intelligence Based on Echocardiography Images

Diagnosis of aortic valve stenosis (AS) is performed manually by a physician experienced in echocardiography imaging. A specific subtype of AS, a severe low-gradient AS, is the most challenging one in terms of differentiating it from the moderate AS. In this study, an artificial intelligence (AI)-based model was used to diagnose the severe low-gradient AS in a fully automatic manner. Data from 158 consecutive patients undergoing echocardiography examination to assess AS severity were used. The obtained performance of our fully automatic approach was AUC = 0.719, 95% confidence interval, 0.640-0.798. It is an important step towards a comprehensive and automatic, image-only-based clinical decision support system for determining the presence of AS and its severity, especially in AS subtypes, such as low-gradient AS.

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Publication Details

Journal
Journal of Imaging Informatics in Medicine
Published
2025-04-21
DOI
https://doi.org/10.1007/s10278-025-01497-4
Citations
1
Primary Topic
Cardiac Valve Diseases and Treatments
Type
article
Field-Weighted Citation Impact
1.39
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article

Diagnosing Severe Low-Gradient vs Moderate Aortic Stenosis with Artificial Intelligence Based on Echocardiography Images

Juliusz Pukacki, Tomasz Hryniewiecki, Michał Wrzosek, Dariusz Zakrzewski et al.
1 citations
Journal of Imaging Informatics in Medicine
Cardiac Valve Diseases and Treatments
1.39
article

Diagnosing Severe Low-Gradient vs Moderate Aortic Stenosis with Artificial Intelligence Based on Echocardiography Images

Juliusz Pukacki, Tomasz Hryniewiecki, Michał Wrzosek, Dariusz Zakrzewski, R. Pekal, Cezary Mazurek, Karina Zatorska, Anna Jasińska, Mikołaj Buchwald, Szymon Kupiński, Piotr J. Czernik
article en
1 citations

Abstract

Diagnosis of aortic valve stenosis (AS) is performed manually by a physician experienced in echocardiography imaging. A specific subtype of AS, a severe low-gradient AS, is the most challenging one in terms of differentiating it from the moderate AS. In this study, an artificial intelligence (AI)-based model was used to diagnose the severe low-gradient AS in a fully automatic manner. Data from 158 consecutive patients undergoing echocardiography examination to assess AS severity were used. The obtained performance of our fully automatic approach was AUC = 0.719, 95% confidence interval, 0.640-0.798. It is an important step towards a comprehensive and automatic, image-only-based clinical decision support system for determining the presence of AS and its severity, especially in AS subtypes, such as low-gradient AS.

Journal of Imaging Informatics in MedicineVol. 39(1)
Poznan Supercomputing and Networking Center (PL), Institute of Cardiology (PL)
Peace, Justice and strong institutions
Openalex Percentile: Top 20%
Cardiac Valve Diseases and Treatments
1.39
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