Wahab, A., Nadarajah, R., Tomoaia, R. et al. (10 more authors) (2025) Cardiac magnetic resonance imaging-derived atrial fibrosis in patients with pre-atrial fibrillation. Open Heart, 12 (2). e003747. ISSN: 2053-3624
Abstract
Introduction Atrial fibrosis identified on cardiac magnetic resonance (CMR) imaging has been proposed as a preprocedural imaging biomarker for patient selection for rhythm control interventions in patients with atrial fibrillation (AF). Whether atrial fibrosis is present in patients considered as ‘pre-AF’ is unknown.
Methods and results We prospectively recruited 12 participants with pre-AF as defined by the Future Innovations in Novel Detection for Atrial Fibrillation (FIND-AF machine learning algorithm, without AF diagnosed during AF screening, and compared them to 25 participants with confirmed AF. All participants underwent CMR using a 3T system with left atrial fibrosis quantification and ADAS-3D left atrial image postprocessing software. Participants with pre-AF had smaller left atrial end-systolic (33.6±9.8 vs 43.0±17.0, p=0.003) and end-diastolic (16.5±8.7 vs 28.2±14.4, p=0.007) volumes, and higher left atrial ejection fraction (59.6±14.6 vs 40.7±17.5, p=0.005) than participants with AF. The extent of atrial fibrosis was not different between those with pre-AF and AF (borderzone (%) 5.2±5.0 vs 2.9±6.9, p=0.772; borderzone fibrosis (cm) 6.2±5.8 vs 6.8±10.7, p=0.927).
Conclusion CMR identifies atrial fibrosis before manifest AF in patients with pre-AF as defined by a machine learning algorithm.
Metadata
| Item Type: | Article |
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| Authors/Creators: |
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| Copyright, Publisher and Additional Information: | © Author(s) (or their employer(s)) 2025. This is an open access article under the terms of the Creative Commons Attribution License (CC-BY 4.0), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited. |
| Dates: |
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| Institution: | The University of Leeds |
| Academic Units: | The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Medicine (Leeds) The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Medicine (Leeds) > Leeds Institute of Cardiovascular and Metabolic Medicine (LICAMM) > Biomedical Imaging Science Dept (Leeds) |
| Funding Information: | Funder Grant number British Heart Foundation Accounts Payable - Gloria Sankey PG/24/12123 Leeds Hospitals Charity A2002295 FL03 British Heart Foundation Accounts Payable - Gloria Sankey CC/22/250026 NIHR National Inst Health Research UBTB Bid No 035 22/23 |
| Date Deposited: | 15 Jan 2026 14:50 |
| Last Modified: | 15 Jan 2026 14:50 |
| Status: | Published |
| Publisher: | BMJ |
| Identification Number: | 10.1136/openhrt-2025-003747 |
| Related URLs: | |
| Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:236090 |

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