City Research Online

Identifying locations susceptible to micro-anatomical reentry using a spatial network representation of atrial fibre maps

Falkenberg, M., Coleman, J. A., Dobson, S. , Hickey, D. J., Terrill, L., Ciacci, A., Thomas, B., Sau, A., Ng, F. S., Zhao, J., Peters, N. S. & Christensen, K. (2022). Identifying locations susceptible to micro-anatomical reentry using a spatial network representation of atrial fibre maps. PLoS ONE, 17(6), article number e0267166. doi: 10.1371/journal.pone.0267166


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.

Publication Type: Article
Additional Information: © 2022 Falkenberg et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Subjects: Q Science > QA Mathematics
Departments: School of Science & Technology > Mathematics
[thumbnail of journal.pone.0267166.pdf]
Text - Published Version
Available under License Creative Commons Attribution.

Download (3MB) | Preview


Add to AnyAdd to TwitterAdd to FacebookAdd to LinkedinAdd to PinterestAdd to Email


Downloads per month over past year

View more statistics

Actions (login required)

Admin Login Admin Login