Artificial intelligence-based characterization of multi-organ ultrasound congestion across the heart failure Spectrum

European Heart Journal - Imaging Methods and Practice 2026 Open access

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Authors: Lavinia Del Punta, Giacomo Aru, Alina Sîrbu, Nicolò De Biase, Stefano Taddei, Giuseppe Prencipe, Stefano Masi, Nicola Riccardo Pugliese
DOI: 10.1093/ehjimp/qyag036
Cited by: 0
References: 34

Abstract

Aims: To investigate, using artificial intelligence (AI), the relationships between ultrasound (US)-defined systemic congestion and demographic, echocardiographic, and biohumoral parameters across the heart failure (HF) spectrum. Methods and results: A total of 1588 subjects (651 Stage A-B, 376 HF with reduced left ventricular ejection fraction [HFrEF,

Fields of Study & Subjects

Ultrasound in Clinical Applications Heart Failure Treatment and Management Cardiovascular Function and Risk Factors

Publication details

Journal / source
European Heart Journal - Imaging Methods and Practice
Volume
4
Issue
1
Pages
qyag036–qyag036
Publication date
1 January 2026
Language
EN