ArticleCardiovascular research2019
Arrhythmogenic propensity of the fibrotic substrate after atrial fibrillation ablation: a longitudinal study using magnetic resonance imaging-based atrial models.
Article in Cardiovascular research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers.
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42 citing papers in PubMed, 58 citations in OpenAlex.
- The Hodgkin-Huxley-Katz Prize Lecture: Heart digital twins: A new paradigm in arrhythmia medicine.The Journal of physiology · 2026Article
- Late Gadolinium Enhancement Entropy as a Novel Imaging Biomarker of Myocardial Tissue Heterogeneity-A Comprehensive Review.Diagnostics (Basel, Switzerland) · 2026Review
- Transmural heterogeneity in 3D fibrosis distribution is associated with endo-epicardial electrical dyssynchrony in persistent atrial fibrillation.The Journal of physiology · 2026Article
- Influence of Anatomical Definition and Substrate Condition on Simulations of Atrial Arrhythmias.Annals of biomedical engineering · 2026Article
- Predicting arrhythmia recurrence post-ablation in atrial fibrillation using explainable machine learning.Communications medicine · 2025Article
- Digital Twin Models in Atrial Fibrillation: Charting the Future of Precision Therapy?Journal of personalized medicine · 2025Review
- A Talk with ChatGPT: The Role of Artificial Intelligence in Shaping the Future of Cardiology and Electrophysiology.Journal of personalized medicine · 2025Article
- Cardiovascular imaging techniques for electrophysiologists.Nature cardiovascular research · 2025Review
- Medical Digital Twin: A Review on Technical Principles and Clinical Applications.Journal of clinical medicine · 2025Review
- Mechanisms of stretch-induced electro-anatomical remodeling and atrial arrhythmogenesis.Journal of molecular and cellular cardiology · 2024Review
- Computational modeling of cardiac electrophysiology and arrhythmogenesis: toward clinical translation.Physiological reviews · 2024Review
- Assessing the arrhythmogenic propensity of fibrotic substrate using digital twins to inform a mechanisms-based atrial fibrillation ablation strategy.Nature cardiovascular research · 2024Article
- Digital twins in medicine.Nature computational science · 2024Review
- Computational Modeling and Simulation of the Fibrotic Human Atria.Methods in molecular biology (Clifton, N.J.) · 2024Article
- Up digital and personal: How heart digital twins can transform heart patient care.Heart rhythm · 2024Review
- Comparing Inducibility of Re-Entrant Arrhythmia in Patient-Specific Computational Models to Clinical Atrial Fibrillation Phenotypes.JACC. Clinical electrophysiology · 2023Article
- Artificial Intelligence in the Image-Guided Care of Atrial Fibrillation.Life (Basel, Switzerland) · 2023Review
- Explainable Machine Learning to Predict Anchored Reentry Substrate Created by Persistent Atrial Fibrillation Ablation in Computational Models.Journal of the American Heart Association · 2023Article
- Long-term changes in heart rate and electrical remodeling contribute to alternans formation in heart failure: a patient-specific in silico study.American journal of physiology. Heart and circulatory physiology · 2023Article
- Clinical and Structural Factors Affecting Ablation Outcomes in Atrial Fibrillation Patients - A Review.Current cardiology reviews · 2023Review
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Authors and funding
9 authors at 3 institutions in 1 country.
Funding
Abstract
aimsInadequate modification of the atrial fibrotic substrate necessary to sustain re-entrant drivers (RDs) may explain atrial fibrillation (AF) recurrence following failed pulmonary vein isolation (PVI). Personalized computational models of the fibrotic atrial substrate derived from late gadolinium enhanced (LGE)-magnetic resonance imaging (MRI) can be used to non-invasively determine the presence of RDs. The objective of this study is to assess the changes of the arrhythmogenic propensity of the fibrotic substrate after PVI. METHODS AND
resultsPre- and post-ablation individualized left atrial models were constructed from 12 AF patients who underwent pre- and post-PVI LGE-MRI, in six of whom PVI failed. Pre-ablation AF sustained by RDs was induced in 10 models. RDs in the post-ablation models were classified as either preserved or emergent. Pre-ablation models derived from patients for whom the procedure failed exhibited a higher number of RDs and larger areas defined as promoting RD formation when compared with atrial models from patients who had successful ablation, 2.6 ± 0.9 vs. 1.8 ± 0.2 and 18.9 ± 1.6% vs. 13.8 ± 1.5%, respectively. In cases of successful ablation, PVI eliminated completely the RDs sustaining AF. Preserved RDs unaffected by ablation were documented only in post-ablation models of patients who experienced recurrent AF (2/5 models); all of these models had also one or more emergent RDs at locations distinct from those of pre-ablation RDs. Emergent RDs occurred in regions that had the same characteristics of the fibrosis spatial distribution (entropy and density) as regions that harboured RDs in pre-ablation models.
conclusionRecurrent AF after PVI in the fibrotic atria may be attributable to both preserved RDs that sustain AF pre- and post-ablation, and the emergence of new RDs following ablation. The same levels of fibrosis entropy and density underlie the pro-RD propensity in both pre- and post-ablation substrates.
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