12 lead surface ECGs as a surrogate of atrial electrical remodeling - a deep learning based approach.

Journal: Journal of electrocardiology
PMID: 39742814

Abstract

BACKGROUND AND PURPOSE: Atrial fibrillation (AF), a common arrhythmia, is linked with atrial electrical and structural changes, notably low voltage areas (LVAs) which are associated with poor ablation outcomes and increased thromboembolic risk. This study aims to evaluate the efficacy of a deep learning model applied to 12‑lead ECGs for non-invasively predicting the presence of LVAs, potentially guiding pre-ablation strategies and improving patient outcomes.

Authors

  • Ishan Vatsaraj
    Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA; Alliance for Cardiovascular Diagnostic and Treatment Innovation, Johns Hopkins University, Baltimore, MD, USA. Electronic address: ivatsar1@jhu.edu.
  • Yazan Mohsen
    Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA; Alliance for Cardiovascular Diagnostic and Treatment Innovation, Johns Hopkins University, Baltimore, MD, USA; Department of Cardiology, Faculty of Health, School of Medicine, University Witten/Herdecke, Witten, Germany; Krankenhaus Porz am Rhein, Department of Cardiology, Electrophysiology and Rhythmology, Cologne, Germany.
  • Lukas Grüne
    Krankenhaus Porz am Rhein, Department of Cardiology, Electrophysiology and Rhythmology, Cologne, Germany.
  • Lucas Steffens
    Krankenhaus Porz am Rhein, Department of Cardiology, Electrophysiology and Rhythmology, Cologne, Germany.
  • Shane Loeffler
    Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA; Alliance for Cardiovascular Diagnostic and Treatment Innovation, Johns Hopkins University, Baltimore, MD, USA.
  • Marc Horlitz
    Department of Cardiology, Faculty of Health, School of Medicine, University Witten/Herdecke, Witten, Germany; Krankenhaus Porz am Rhein, Department of Cardiology, Electrophysiology and Rhythmology, Cologne, Germany.
  • Florian Stöckigt
    Krankenhaus Porz am Rhein, Department of Cardiology, Electrophysiology and Rhythmology, Cologne, Germany; Department of Cardiology, University Hospital Bonn, Bonn, Germany.
  • Natalia Trayanova
    Department of Biomedical Engineering (A.P., N.T.).

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