Artificial Intelligence–Based Feature Analysis of Pulmonary Vein Morphology on Computed Tomography Scans and Risk of Atrial Fibrillation Recurrence After Catheter Ablation: A Multi-Site Study

This largest multi-institutional study to date revealed associations between artificial intelligence-extracted morphological features of the primary PV branches with AF recurrence in 809 patients from 3 sites. Future work will focus on enhancing the predictive ability of the classifier by integrating clinical, structural, and morphological features, including left atrial appendage and left atrium-related characteristics.

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Institutions

Publication Details

Journal
Circulation Arrhythmia and Electrophysiology
Published
2024-12-01
DOI
https://doi.org/10.1161/circep.123.012679
Citations
6
Primary Topic
Atrial Fibrillation Management and Outcomes
Type
article
Field-Weighted Citation Impact
2.41

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article

Artificial Intelligence–Based Feature Analysis of Pulmonary Vein Morphology on Computed Tomography Scans and Risk of Atrial Fibrillation Recurrence After Catheter Ablation: A Multi-Site Study

Majd El‐Harasis, Kevin Park, Golnoush Asaeikheybari, ROD S. PASSMAN et al.
6 citations
Circulation Arrhythmia and Electrophysiology
Atrial Fibrillation Management and Outcomes
2.41
article

Artificial Intelligence–Based Feature Analysis of Pulmonary Vein Morphology on Computed Tomography Scans and Risk of Atrial Fibrillation Recurrence After Catheter Ablation: A Multi-Site Study

Majd El‐Harasis, Kevin Park, Golnoush Asaeikheybari, ROD S. PASSMAN, John Barnard, Anant Madabhushi, William H. Telfer, M. Benjamin Shoemaker, Amit Banwari Gupta, Bibin Varghese, Hyun Su Kim, Alison Jin, Abhishek Midya, Han Sun, Samuel Harwood, Sojin Y. Wass, David R. Van Wagoner, Joshua G. Hunter, Po‐Hao Chen, Taylor Schilling, Mina K. Chung, Animesh Tandon, Aleksandar Izda, Bruce F. Eldridge, Abel Abraham
article en
6 citations

Abstract

This largest multi-institutional study to date revealed associations between artificial intelligence-extracted morphological features of the primary PV branches with AF recurrence in 809 patients from 3 sites. Future work will focus on enhancing the predictive ability of the classifier by integrating clinical, structural, and morphological features, including left atrial appendage and left atrium-related characteristics.

Circulation Arrhythmia and ElectrophysiologyVol. 17(12)
Northwestern University (US), Cleveland Clinic (US), United States Department of Veterans Affairs (US), Cerner (United States) (US), Vanderbilt University (US), University Hospitals of Cleveland (US), The Wallace H. Coulter Department of Biomedical Engineering (US), Cleveland Clinic Lerner College of Medicine (US), Quantitative BioSciences (US), Northwestern University (PH), Norwegian Womens Public Health Association (NO), Imaging Center (US), Case Western Reserve University (US), Northeast Ohio Medical University (US)
U.S. Department of Defense, U.S. Department of Veterans Affairs, American Heart Association, Eli Lilly and Company, AstraZeneca, Cleveland Clinic, Case Western Reserve University, Frederick National Laboratory for Cancer Research, National Institutes of Health, National Heart, Lung, and Blood Institute, National Cancer Institute, National Center for Research Resources, DOD Prostate Cancer Research Program, DOD Peer Reviewed Cancer Research Program
Quality Education
Openalex Percentile: Top 9%
Atrial Fibrillation Management and Outcomes
2.41
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