ArticleIEEE transactions on bio-medical engineering2013
Electroanatomical characterization of atrial microfibrosis in a histologically detailed computer model.
Article in IEEE transactions on bio-medical engineering, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed.
- Generating patient-specific computational models with point cloud data from human atrial electrophysiology studies.PloS one · 2026Article
- Late gadolinium enhancement in areas with electrically fractionated potentials during sinus rhythm in patients with atrial fibrillation.Heart and vessels · 2025Article
- Ablation of persistent atrial fibrillation based on atrial electrogram duration map: methodology and clinical outcomes from the AEDUM pilot study.Journal of interventional cardiac electrophysiology : an international journal of arrhythmias and pacing · 2024Article
- A case report of successful treatment of longstanding persistent atrial fibrillation with ablation for fractionated potential with conduction delay during rapid pacing.HeartRhythm case reports · 2024Article
- Atrial fibrosis identification with unipolar electrogram eigenvalue distribution analysis in multi-electrode arrays.Medical & biological engineering & computing · 2022Article
- Graph-based homogenisation for modelling cardiac fibrosis.Journal of computational physics · 2022Article
- A Review of Healthy and Fibrotic Myocardium Microstructure Modeling and Corresponding Intracardiac Electrograms.Frontiers in physiology · 2022Review
- Article
- Etiology-Specific Remodeling in Ventricular Tissue of Heart Failure Patients and Its Implications for Computational Modeling of Electrical Conduction.Frontiers in physiology · 2021Article
- Using Machine Learning to Characterize Atrial Fibrotic Substrate From Intracardiac Signals With a HybridFrontiers in physiology · 2021Article
- An Inverse Eikonal Method for Identifying Ventricular Activation Sequences from Epicardial Activation Maps.Journal of computational physics · 2020Article
- Characterizing the clinical implementation of a novel activation-repolarization metric to identify targets for catheter ablation of ventricular tachycardias using computational models.Computers in biology and medicine · 2019Article
- Ectopic beats arise from micro-reentries near infarct regions in simulations of a patient-specific heart model.Scientific reports · 2018Article
- Microheterogeneity-induced conduction slowing and wavefront collisions govern macroscopic conduction behavior: A computational and experimental study.PLoS computational biology · 2018Article
- Rabbit-specific computational modelling of ventricular cell electrophysiology: Using populations of models to explore variability in the response to ischemia.Progress in biophysics and molecular biology · 2016Article
- Lessons from computer simulations of ablation of atrial fibrillation.The Journal of physiology · 2016Review
- Article
- Automated Texture Analysis and Determination of Fibre Orientation of Heart Tissue: A Morphometric Study.PloS one · 2016Article
- Simulation of Ectopic Pacemakers in the Heart: Multiple Ectopic Beats Generated by Reentry inside Fibrotic Regions.BioMed research international · 2015Article
- Computational Approaches to Understanding the Role of Fibroblast-Myocyte Interactions in Cardiac Arrhythmogenesis.BioMed research international · 2015Review
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8 authors.
Funding
Abstract
Fibrosis is thought to play an important role in the formation and maintenance of atrial fibrillation (AF). The propensity of fibrosis to increase AF vulnerability depends not only on its amount, its texture plays a crucial role as well. While the detection of fibrotic tissue patches in the atria with extracellular recordings is feasible based on the analysis of electrogram fractionation, as used in clinical practice to identify ablation targets, the classification of fibrotic texture is a more challenging problem. This study seeks to establish a method for the electroanatomical characterization of the fibrotic textures based on the analysis of electrogram fractionation. The proposed method exploits the dependence of fractionation patterns on the incidence direction of wavefronts which differs significantly as a function of texture. A histologically detailed computer model of the right atrial isthmus was developed for testing the method. A stimulation protocol was conceived which generated various incidence directions for any given recording site where electrograms were computed. A classification method is derived then for discriminating three types of fibrosis, no fibrosis (control), diffuse, and patchy fibrosis. Simulation results showed that electrogram fractionation and amplitudes and their dependence upon incidence direction allow a robust discrimination between different classes of fibrosis. Finally, to minimize the technical effort, sensitivity analysis was performed to identify a minimum number of incidence directions required for robust classification.
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