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Clayton RH, Sridhar S. Re-entry in models of cardiac ventricular tissue with scar represented as a Gaussian random field. Front Physiol 2024; 15:1403545. [PMID: 39005500 PMCID: PMC11239552 DOI: 10.3389/fphys.2024.1403545] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2024] [Accepted: 06/10/2024] [Indexed: 07/16/2024] Open
Abstract
Introduction: Fibrotic scar in the heart is known to act as a substrate for arrhythmias. Regions of fibrotic scar are associated with slowed or blocked conduction of the action potential, but the detailed mechanisms of arrhythmia formation are not well characterised and this can limit the effective diagnosis and treatment of scar in patients. The aim of this computational study was to evaluate different representations of fibrotic scar in models of 2D 10 × 10 cm ventricular tissue, where the region of scar was defined by sampling a Gaussian random field with an adjustable length scale of between 1.25 and 10.0 mm. Methods: Cellular electrophysiology was represented by the Ten Tusscher 2006 model for human ventricular cells. Fibrotic scar was represented as a spatially varying diffusion, with different models of the boundary between normal and fibrotic tissue. Dispersion of activation time and action potential duration (APD) dispersion was assessed in each sample by pacing at an S1 cycle length of 400 ms followed by a premature S2 beat with a coupling interval of 323 ms. Vulnerability to reentry was assessed with an aggressive pacing protocol. In all models, simulated fibrosis acted to delay activation, to increase the dispersion of APD, and to generate re-entry. Results: A higher incidence of re-entry was observed in models with simulated fibrotic scar at shorter length scale, but the type of model used to represent fibrotic scar had a much bigger influence on the incidence of reentry. Discussion: This study shows that in computational models of fibrotic scar the effects that lead to either block or propagation of the action potential are strongly influenced by the way that fibrotic scar is represented in the model, and so the results of computational studies involving fibrotic scar should be interpreted carefully.
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Affiliation(s)
- Richard H Clayton
- Insigneo Institute for in-silico Medicine and Department of Computer Science, University of Sheffield, Sheffield, United Kingdom
| | - S Sridhar
- Insigneo Institute for in-silico Medicine and Department of Computer Science, University of Sheffield, Sheffield, United Kingdom
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Sridhar S, Clayton RH. Fibroblast mediated dynamics in diffusively uncoupled myocytes: a simulation study using 2-cell motifs. Sci Rep 2024; 14:4493. [PMID: 38396245 PMCID: PMC10891142 DOI: 10.1038/s41598-024-54564-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2023] [Accepted: 02/14/2024] [Indexed: 02/25/2024] Open
Abstract
In healthy hearts myocytes are typically coupled to nearest neighbours through gap junctions. Under pathological conditions such as fibrosis, or in scar tissue, or across ablation lines myocytes can uncouple from their neighbours. Electrical conduction may still occur via fibroblasts that not only couple proximal myocytes but can also couple otherwise unconnected regions. We hypothesise that such coupling can alter conduction between myocytes via introduction of delays or by initiation of premature stimuli that can potentially result in reentry or conduction blocks. To test this hypothesis we have developed several 2-cell motifs and investigated the effect of fibroblast mediated electrical coupling between uncoupled myocytes. We have identified various regimes of myocyte behaviour that depend on the strength of gap-junctional conductance, connection topology, and parameters of the myocyte and fibroblast models. These motifs are useful in developing a mechanistic understanding of long-distance coupling on myocyte dynamics and enable the characterisation of interaction between different features such as myocyte and fibroblast properties, coupling strengths and pacing period. They are computationally inexpensive and allow for incorporation of spatial effects such as conduction velocity. They provide a framework for constructing scar tissue boundaries and enable linking of cellular level interactions with scar induced arrhythmia.
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Affiliation(s)
- S Sridhar
- Department of Computer Science, University of Sheffield, Sheffield, UK.
| | - Richard H Clayton
- Department of Computer Science, University of Sheffield, Sheffield, UK
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Lawson BA, dos Santos RW, Turner IW, Bueno-Orovio A, Burrage P, Burrage K. Homogenisation for the monodomain model in the presence of microscopic fibrotic structures. COMMUNICATIONS IN NONLINEAR SCIENCE & NUMERICAL SIMULATION 2023; 116:None. [PMID: 37113591 PMCID: PMC10124103 DOI: 10.1016/j.cnsns.2022.106794] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/06/2021] [Revised: 05/06/2022] [Accepted: 08/04/2022] [Indexed: 06/08/2023]
Abstract
Computational models in cardiac electrophysiology are notorious for long runtimes, restricting the numbers of nodes and mesh elements in the numerical discretisations used for their solution. This makes it particularly challenging to incorporate structural heterogeneities on small spatial scales, preventing a full understanding of the critical arrhythmogenic effects of conditions such as cardiac fibrosis. In this work, we explore the technique of homogenisation by volume averaging for the inclusion of non-conductive micro-structures into larger-scale cardiac meshes with minor computational overhead. Importantly, our approach is not restricted to periodic patterns, enabling homogenised models to represent, for example, the intricate patterns of collagen deposition present in different types of fibrosis. We first highlight the importance of appropriate boundary condition choice for the closure problems that define the parameters of homogenised models. Then, we demonstrate the technique's ability to correctly upscale the effects of fibrotic patterns with a spatial resolution of 10 µm into much larger numerical mesh sizes of 100- 250 µm . The homogenised models using these coarser meshes correctly predict critical pro-arrhythmic effects of fibrosis, including slowed conduction, source/sink mismatch, and stabilisation of re-entrant activation patterns. As such, this approach to homogenisation represents a significant step towards whole organ simulations that unravel the effects of microscopic cardiac tissue heterogeneities.
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Affiliation(s)
- Brodie A.J. Lawson
- Centre for Data Science, Queensland University of Technology, 2 George Street, Brisbane, 4000, Queensland, Australia
- ARC Centre of Excellence for Mathematical and Statistical Frontiers, Queensland University of Technology, 2 George Street, Brisbane, 4000, Queensland, Australia
- School of Mathematical Sciences, Queensland University of Technology, 2 George Street, Brisbane, 4000, Queensland, Australia
| | - Rodrigo Weber dos Santos
- Graduate Program on Computational Modelling, Universidade de Federal de Juiz de Fora, Rua Jose Lourenco Kelmer s/n, Juiz de Fora, 36036-900, Minas Gerais, Brazil
| | - Ian W. Turner
- ARC Centre of Excellence for Mathematical and Statistical Frontiers, Queensland University of Technology, 2 George Street, Brisbane, 4000, Queensland, Australia
- School of Mathematical Sciences, Queensland University of Technology, 2 George Street, Brisbane, 4000, Queensland, Australia
| | - Alfonso Bueno-Orovio
- Department of Computer Science, University of Oxford, Parks Rd, Oxford, OX1 3QD, Oxfordshire, United Kingdom
| | - Pamela Burrage
- ARC Centre of Excellence for Mathematical and Statistical Frontiers, Queensland University of Technology, 2 George Street, Brisbane, 4000, Queensland, Australia
- School of Mathematical Sciences, Queensland University of Technology, 2 George Street, Brisbane, 4000, Queensland, Australia
| | - Kevin Burrage
- ARC Centre of Excellence for Mathematical and Statistical Frontiers, Queensland University of Technology, 2 George Street, Brisbane, 4000, Queensland, Australia
- School of Mathematical Sciences, Queensland University of Technology, 2 George Street, Brisbane, 4000, Queensland, Australia
- Department of Computer Science, University of Oxford, Parks Rd, Oxford, OX1 3QD, Oxfordshire, United Kingdom
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