Key result
Spatial network model reveals atrial micro-reentry clusters in thin, convex regions with low fibrosis.
Why the study?
Micro-anatomical reentry has been identified as a potential driver of AF, but computational methods are needed to identify which atrial regions are most susceptible to micro-reentry.
Answers are grounded in this paper and cite their sources.
A novel computational method demonstrates that the accumulation of interstitial fibrosis alters the spatial clustering of micro-reentrant substrates, potentially impacting the efficacy of localized ablation for atrial fibrillation.
Micro-anatomical reentry has been identified as a potential driver of atrial fibrillation (AF). In this paper, we introduce a novel computational method which aims to identify which atrial regions are most susceptible to micro-reentry. The approach, which considers the structural basis for micro-reentry only, is based on the premise that the accumulation of electrically insulating interstitial fibrosis can be modelled by simulating percolation-like phenomena on spatial networks. Our results suggest that at high coupling, where micro-reentry is rare, the micro-reentrant substrate is highly clustered in areas where the atrial walls are thin and have convex wall morphology, likely facilitating localised treatment via ablation. However, as transverse connections between fibres are removed, mimicking the accumulation of interstitial fibrosis, the substrate becomes less spatially clustered, and the bias to forming in thin, convex regions of the atria is reduced, possibly restricting the efficacy of localised ablation. Comparing our algorithm on image-based models with and without atrial fibre structure, we find that strong longitudinal fibre coupling can suppress the micro-reentrant substrate, whereas regions with disordered fibre orientations have an enhanced risk of micro-reentry. With further development, these methods may be useful for modelling the temporal development of the fibrotic substrate on an individualised basis.
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Falkenberg et al. (2022) studied Atrial fibrillation (n=3). Spatial network representation of atrial fibre maps (fibre model) vs. Fibre-less null model was evaluated on Identification of atrial regions susceptible to micro-reentry. A novel spatial network model demonstrated that micro-reentrant substrates are highly clustered in thin, convex atrial regions at low fibrosis densities, and are suppressed by strong longitudinal fibre coupling.
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