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Front Physiol. 2016 Oct 25;7:474. eCollection 2016.

Slow Conduction in the Border Zones of Patchy Fibrosis Stabilizes the Drivers for Atrial Fibrillation: Insights from Multi-Scale Human Atrial Modeling.

Author information

1
Division of Imaging Sciences and Biomedical Engineering, Department of Biomedical Engineering, King's College London London, UK.
2
School of Biomedical Sciences, University of Leeds Leeds, UK.
3
Institute for Experimental Cardiovascular Medicine, University Heart Center - Bad Krozingen, Medical Center - University of Freiburg Freiburg, Germany.

Abstract

Introduction: The genesis of atrial fibrillation (AF) and success of AF ablation therapy have been strongly linked with atrial fibrosis. Increasing evidence suggests that patient-specific distributions of fibrosis may determine the locations of electrical drivers (rotors) sustaining AF, but the underlying mechanisms are incompletely understood. This study aims to elucidate a missing mechanistic link between patient-specific fibrosis distributions and AF drivers. Methods: 3D atrial models integrated human atrial geometry, rule-based fiber orientation, region-specific electrophysiology, and AF-induced ionic remodeling. A novel detailed model for an atrial fibroblast was developed, and effects of myocyte-fibroblast (M-F) coupling were explored at single-cell, 1D tissue and 3D atria levels. Left atrial LGE MRI datasets from 3 chronic AF patients were segmented to provide the patient-specific distributions of fibrosis. The data was non-linearly registered and mapped to the 3D atria model. Six distinctive fibrosis levels (0-healthy tissue, 5-dense fibrosis) were identified based on LGE MRI intensity and modeled as progressively increasing M-F coupling and decreasing atrial tissue coupling. Uniform 3D atrial model with diffuse (level 2) fibrosis was considered for comparison. Results: In single cells and tissue, the largest effect of atrial M-F coupling was on the myocyte resting membrane potential, leading to partial inactivation of sodium current and reduction of conduction velocity (CV). In the 3D atria, further to the M-F coupling, effects of fibrosis on tissue coupling greatly reduce atrial CV. AF was initiated by fast pacing in each 3D model with either uniform or patient-specific fibrosis. High variation in fibrosis distributions between the models resulted in varying complexity of AF, with several drivers emerging. In the diffuse fibrosis models, waves randomly meandered through the atria, whereas in each the patient-specific models, rotors stabilized in fibrotic regions. The rotors propagated slowly around the border zones of patchy fibrosis (levels 3-4), failing to spread into inner areas of dense fibrosis. Conclusion: Rotors stabilize in the border zones of patchy fibrosis in 3D atria, where slow conduction enable the development of circuits within relatively small regions. Our results can provide a mechanistic explanation for the clinical efficacy of ablation around fibrotic regions.

KEYWORDS:

MR imaging; arrhythmia mechanisms; atrial fibrillation; fibrosis; modeling and simulation

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