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Falkenberg M, Coleman JA, Dobson S, Hickey DJ, Terrill L, Ciacci A, Thomas B, Sau A, Ng FS, Zhao J, Peters NS, Christensen K. Identifying locations susceptible to micro-anatomical reentry using a spatial network representation of atrial fibre maps. PLoS One 2022; 17:e0267166. [PMID: 35737662 PMCID: PMC9223322 DOI: 10.1371/journal.pone.0267166] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2021] [Accepted: 04/03/2022] [Indexed: 11/18/2022] Open
Abstract
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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Affiliation(s)
- Max Falkenberg
- Centre for Complexity Science, Imperial College London, London, United Kingdom
- Department of Physics, Imperial College London, London, United Kingdom
- ElectroCardioMaths Programme, Imperial Centre for Cardiac Engineering, National Heart & Lung Institute, Imperial College London, London, United Kingdom
| | - James A. Coleman
- Department of Physics, Imperial College London, London, United Kingdom
| | - Sam Dobson
- Department of Physics, Imperial College London, London, United Kingdom
| | - David J. Hickey
- Department of Physics, Imperial College London, London, United Kingdom
| | - Louie Terrill
- Department of Physics, Imperial College London, London, United Kingdom
| | - Alberto Ciacci
- Centre for Complexity Science, Imperial College London, London, United Kingdom
- Department of Physics, Imperial College London, London, United Kingdom
- ElectroCardioMaths Programme, Imperial Centre for Cardiac Engineering, National Heart & Lung Institute, Imperial College London, London, United Kingdom
| | - Belvin Thomas
- Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand
| | - Arunashis Sau
- ElectroCardioMaths Programme, Imperial Centre for Cardiac Engineering, National Heart & Lung Institute, Imperial College London, London, United Kingdom
| | - Fu Siong Ng
- ElectroCardioMaths Programme, Imperial Centre for Cardiac Engineering, National Heart & Lung Institute, Imperial College London, London, United Kingdom
| | - Jichao Zhao
- Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand
| | - Nicholas S. Peters
- ElectroCardioMaths Programme, Imperial Centre for Cardiac Engineering, National Heart & Lung Institute, Imperial College London, London, United Kingdom
| | - Kim Christensen
- Centre for Complexity Science, Imperial College London, London, United Kingdom
- Department of Physics, Imperial College London, London, United Kingdom
- ElectroCardioMaths Programme, Imperial Centre for Cardiac Engineering, National Heart & Lung Institute, Imperial College London, London, United Kingdom
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Ciacci A, Falkenberg M, Manani KA, Evans TS, Peters NS, Christensen K. Understanding the transition from paroxysmal to persistent atrial fibrillation. PHYSICAL REVIEW RESEARCH 2020; 2:023311. [PMID: 32607500 PMCID: PMC7326608 DOI: 10.1103/physrevresearch.2.023311] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Atrial fibrillation (AF) is the most common cardiac arrhytmia, characterized by the chaotic motion of electrical wavefronts in the atria. In clinical practice, AF is classified under two primary categories: paroxysmal AF, short intermittent episodes separated by periods of normal electrical activity; and persistent AF, longer uninterrupted episodes of chaotic electrical activity. However, the precise reasons why AF in a given patient is paroxysmal or persistent is poorly understood. Recently, we have introduced the percolation-based Christensen-Manani-Peters (CMP) model of AF which naturally exhibits both paroxysmal and persistent AF, but precisely how these differences emerge in the model is unclear. In this paper, we dissect the CMP model to identify the cause of these different AF classifications. Starting from a mean-field model where we describe AF as a simple birth-death process, we add layers of complexity to the model and show that persistent AF arises from reentrant circuits which exhibit an asymmetry in their probability of activation relative to deactivation. As a result, different simulations generated at identical model parameters can exhibit fibrillatory episodes spanning several orders of magnitude from a few seconds to months. These findings demonstrate that diverse, complex fibrillatory dynamics can emerge from very simple dynamics in models of AF.
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Affiliation(s)
- Alberto Ciacci
- Blackett Laboratory, Imperial College London, London SW7 2BW, United Kingdom
- Center for Complexity Science, Imperial College London, London SW7 2AZ, United Kingdom
- ElectroCardioMaths Programme, Imperial Centre for Cardiac Engineering, Imperial College London, London W12 0NN, United Kingdom
| | - Max Falkenberg
- Blackett Laboratory, Imperial College London, London SW7 2BW, United Kingdom
- Center for Complexity Science, Imperial College London, London SW7 2AZ, United Kingdom
- ElectroCardioMaths Programme, Imperial Centre for Cardiac Engineering, Imperial College London, London W12 0NN, United Kingdom
| | - Kishan A. Manani
- Blackett Laboratory, Imperial College London, London SW7 2BW, United Kingdom
- Center for Complexity Science, Imperial College London, London SW7 2AZ, United Kingdom
- National Heart and Lung Institute, Imperial College London, London W12 0NN, United Kingdom
| | - Tim S. Evans
- Blackett Laboratory, Imperial College London, London SW7 2BW, United Kingdom
- Center for Complexity Science, Imperial College London, London SW7 2AZ, United Kingdom
| | - Nicholas S. Peters
- ElectroCardioMaths Programme, Imperial Centre for Cardiac Engineering, Imperial College London, London W12 0NN, United Kingdom
| | - Kim Christensen
- Blackett Laboratory, Imperial College London, London SW7 2BW, United Kingdom
- Center for Complexity Science, Imperial College London, London SW7 2AZ, United Kingdom
- ElectroCardioMaths Programme, Imperial Centre for Cardiac Engineering, Imperial College London, London W12 0NN, United Kingdom
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