1
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Colman MA, Varela M, MacLeod RS, Hancox JC, Aslanidi OV. Interactions between calcium-induced arrhythmia triggers and the electrophysiological-anatomical substrate underlying the induction of atrial fibrillation. J Physiol 2024; 602:835-853. [PMID: 38372694 DOI: 10.1113/jp285740] [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: 09/28/2023] [Accepted: 01/17/2024] [Indexed: 02/20/2024] Open
Abstract
Atrial fibrillation (AF) is the most common cardiac arrhythmia and is sustained by spontaneous focal excitations and re-entry. Spontaneous electrical firing in the pulmonary vein (PV) sleeves is implicated in AF generation. The aim of this simulation study was to identify the mechanisms determining the localisation of AF triggers in the PVs and their contribution to the genesis of AF. A novel biophysical model of the canine atria was used that integrates stochastic, spontaneous subcellular Ca2+ release events (SCRE) with regional electrophysiological heterogeneity in ionic properties and a detailed three-dimensional model of atrial anatomy, microarchitecture and patchy fibrosis. Simulations highlighted the importance of the smaller inward rectifier potassium current (IK1 ) in PV cells compared to the surrounding atria, which enabled SCRE more readily to result in delayed-afterdepolarisations that induced triggered activity. There was a leftward shift in the dependence of the probability of triggered activity on sarcoplasmic reticulum Ca2+ load. This feature was accentuated in 3D tissue compared to single cells (Δ half-maximal [Ca2+ ]SR = 58 μM vs. 22 μM). In 3D atria incorporating electrical heterogeneity, excitations preferentially emerged from the PV region. These triggered focal excitations resulted in transient re-entry in the left atrium. Addition of fibrotic patches promoted localised emergence of focal excitations and wavebreaks that had a more substantial impact on generating AF-like patterns than the PVs. Thus, a reduced IK1 , less negative resting membrane potential, and fibrosis-induced changes of the electrotonic load all contribute to the emergence of complex excitation patterns from spontaneous focal triggers. KEY POINTS: Focal excitations in the atria are most commonly associated with the pulmonary veins, but the mechanisms for this localisation are yet to be elucidated. We applied a multi-scale computational modelling approach to elucidate the mechanisms underlying such localisations. Myocytes in the pulmonary vein region of the atria have a less negative resting membrane potential and reduced time-independent potassium current; we demonstrate that both of these factors promote triggered activity in single cells and tissues. The less negative resting membrane potential also contributes to heterogeneous inactivation of the fast sodium current, which can enable re-entrant-like excitation patterns to emerge without traditional conduction block.
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Affiliation(s)
- Michael A Colman
- School of Biomedical Sciences, Faculty of Biological Sciences, University of Leeds, Leeds, UK
| | - Marta Varela
- National Heart & Lung Institute, Faculty of Medicine, Imperial College London, London, UK
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | - Rob S MacLeod
- The Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT, USA
| | - Jules C Hancox
- School of Physiology, Pharmacology & Neuroscience, Faculty of Life Sciences, University of Bristol, Bristol, UK
| | - Oleg V Aslanidi
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
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2
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Kervadec A, Kezos J, Ni H, Yu M, Marchant J, Spiering S, Kannan S, Kwon C, Andersen P, Bodmer R, Grandi E, Ocorr K, Colas AR. Multiplatform modeling of atrial fibrillation identifies phospholamban as a central regulator of cardiac rhythm. Dis Model Mech 2023; 16:dmm049962. [PMID: 37293707 PMCID: PMC10387351 DOI: 10.1242/dmm.049962] [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: 10/25/2022] [Accepted: 05/26/2023] [Indexed: 06/10/2023] Open
Abstract
Atrial fibrillation (AF) is a common and genetically inheritable form of cardiac arrhythmia; however, it is currently not known how these genetic predispositions contribute to the initiation and/or maintenance of AF-associated phenotypes. One major barrier to progress is the lack of experimental systems to investigate the effects of gene function on rhythm parameters in models with human atrial and whole-organ relevance. Here, we assembled a multi-model platform enabling high-throughput characterization of the effects of gene function on action potential duration and rhythm parameters using human induced pluripotent stem cell-derived atrial-like cardiomyocytes and a Drosophila heart model, and validation of the findings using computational models of human adult atrial myocytes and tissue. As proof of concept, we screened 20 AF-associated genes and identified phospholamban loss of function as a top conserved hit that shortens action potential duration and increases the incidence of arrhythmia phenotypes upon stress. Mechanistically, our study reveals that phospholamban regulates rhythm homeostasis by functionally interacting with L-type Ca2+ channels and NCX. In summary, our study illustrates how a multi-model system approach paves the way for the discovery and molecular delineation of gene regulatory networks controlling atrial rhythm with application to AF.
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Affiliation(s)
- Anaïs Kervadec
- Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA 92037, USA
| | - James Kezos
- Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA 92037, USA
| | - Haibo Ni
- Department of Pharmacology, UC Davis, Davis, CA 95616, USA
| | - Michael Yu
- Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA 92037, USA
| | - James Marchant
- Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA 92037, USA
| | - Sean Spiering
- Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA 92037, USA
| | - Suraj Kannan
- Johns Hopkins University, Baltimore, MD 21205, USA
| | - Chulan Kwon
- Johns Hopkins University, Baltimore, MD 21205, USA
| | | | - Rolf Bodmer
- Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA 92037, USA
| | | | - Karen Ocorr
- Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA 92037, USA
| | - Alexandre R. Colas
- Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA 92037, USA
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3
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He J, Pertsov AM, Cherry EM, Fenton FH, Roney CH, Niederer SA, Zang Z, Mangharam R. Fiber Organization has Little Effect on Electrical Activation Patterns during Focal Arrhythmias in the Left Atrium. ARXIV 2023:arXiv:2210.16497v3. [PMID: 36776816 PMCID: PMC9915751] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Figures] [Subscribe] [Scholar Register] [Indexed: 04/21/2023]
Abstract
Over the past two decades there has been a steady trend towards the development of realistic models of cardiac conduction with increasing levels of detail. However, making models more realistic complicates their personalization and use in clinical practice due to limited availability of tissue and cellular scale data. One such limitation is obtaining information about myocardial fiber organization in the clinical setting. In this study, we investigated a chimeric model of the left atrium utilizing clinically derived patient-specific atrial geometry and a realistic, yet foreign for a given patient fiber organization. We discovered that even significant variability of fiber organization had a relatively small effect on the spatio-temporal activation pattern during regular pacing. For a given pacing site, the activation maps were very similar across all fiber organizations tested.
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Affiliation(s)
- Jiyue He
- Department of Electrical and Systems Engineering, University of Pennsylvania, USA
| | | | - Elizabeth M Cherry
- School of Computational Science and Engineering, Georgia Institute of Technology, USA
| | | | - Caroline H Roney
- School of Engineering and Materials Science, Queen Mary University of London, UK
| | - Steven A Niederer
- School of Biomedical Engineering and Imaging Sciences, King's College London, UK
| | - Zirui Zang
- Department of Electrical and Systems Engineering, University of Pennsylvania, USA
| | - Rahul Mangharam
- Department of Electrical and Systems Engineering, University of Pennsylvania, USA
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4
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Yang F, Wei X, Chen B, Li C, Li D, Zhang S, Lu W, Zhang L. Cardiac biophysical detailed synergetic modality rendering and visible correlation. Front Physiol 2023; 14:1086154. [PMID: 37089421 PMCID: PMC10119415 DOI: 10.3389/fphys.2023.1086154] [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: 11/01/2022] [Accepted: 03/27/2023] [Indexed: 04/25/2023] Open
Abstract
The heart is a vital organ in the human body. Research and treatment for the heart have made remarkable progress, and the functional mechanisms of the heart have been simulated and rendered through the construction of relevant models. The current methods for rendering cardiac functional mechanisms only consider one type of modality, which means they cannot show how different types of modality, such as physical and physiological, work together. To realistically represent the three-dimensional synergetic biological modality of the heart, this paper proposes a WebGL-based cardiac synergetic modality rendering framework to visualize the cardiac physical volume data and present synergetic correspondence rendering of the cardiac electrophysiological modality. By constructing the biological detailed interactive histogram, users can implement local details rendering for the heart, which could reveal the cardiac biology details more clearly. We also present cardiac physical-physiological correlation visualization to explore cardiac biological association characteristics. Experimental results show that the proposed framework can provide favorable cardiac biological detailed synergetic modality rendering results in terms of both effectiveness and efficiency. Compared with existing methods, the framework can facilitate the study of the internal mechanism of the heart and subsequently deduce the process of initiation, development, and transformation from a healthy heart to an ill one, and thereby improve the diagnosis and treatment of cardiac disorders.
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Affiliation(s)
- Fei Yang
- School of Mechanical, Electrical and Information Engineering, Shandong University, Weihai, China
- School of Computer Science and Technology, Shandong University, Qingdao, China
| | - Xiaoxi Wei
- School of Mechanical, Electrical and Information Engineering, Shandong University, Weihai, China
| | - Bo Chen
- School of Mechanical, Electrical and Information Engineering, Shandong University, Weihai, China
| | - Chenxi Li
- Pizhou Power Supply Branch of State Grid Jiangsu Electric Power Co., Ltd., Pizhou, China
| | - Dong Li
- School of Mechanical, Electrical and Information Engineering, Shandong University, Weihai, China
| | - Shugang Zhang
- College of Computer Science and Technology, Ocean University of China, Qingdao, China
| | - Weigang Lu
- Department of Educational Technology, Ocean University of China, Qingdao, China
- *Correspondence: Weigang Lu,
| | - Lei Zhang
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA, United States
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5
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Cellular heterogeneity and repolarisation across the atria: an in silico study. Med Biol Eng Comput 2022; 60:3153-3168. [PMID: 36104609 PMCID: PMC9537222 DOI: 10.1007/s11517-022-02640-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2022] [Accepted: 07/28/2022] [Indexed: 11/08/2022]
Abstract
Mechanisms of atrial fibrillation and the susceptibility to reentries can be impacted by the repolarization across the atria. Studies into atrial fibrillation ignore cell-to-cell heterogeneity due to electrotonic coupling. Recent studies show that cellular variability may have a larger impact on electrophysiological behaviour than assumed. This paper aims to determine the impact of cellular heterogeneity on the repolarization phase across the AF remodelled atria. Using a population of models approach, 10 anatomically identical atrial models were created to include cellular heterogeneity. Atrial models were compared with an equivalent homogenous model. Activation, APD90, and repolarization maps were used to compare models. The impact of electrotonic coupling in the tissue was determined through a comparison of RMP, APD20, APD50, APD90, and triangulation between regional atrial tissue and the single cell populations. After calibration, cellular heterogeneity does not impact atrial depolarization. Repolarization patterns were significantly impacted by cellular heterogeneity, with the APD90 across the LA increasing due to heterogeneity and the reverse occurring in the RA. Electrotonic coupling caused a reduction in variability across all biomarkers but did not fully remove variability. Electrotonic coupling resulted in an increase in APD20 and APD50, and reduced triangulation compared to isolated cell populations. Heterogeneity also caused a reduction in triangulation compared with regionally homogeneous atria.
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6
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Bai J, Lu Y, Wang H, Zhao J. How synergy between mechanistic and statistical models is impacting research in atrial fibrillation. Front Physiol 2022; 13:957604. [PMID: 36111152 PMCID: PMC9468674 DOI: 10.3389/fphys.2022.957604] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Accepted: 08/08/2022] [Indexed: 11/13/2022] Open
Abstract
Atrial fibrillation (AF) with multiple complications, high morbidity and mortality, and low cure rates, has become a global public health problem. Although significant progress has been made in the treatment methods represented by anti-AF drugs and radiofrequency ablation, the therapeutic effect is not as good as expected. The reason is mainly because of our lack of understanding of AF mechanisms. This field has benefited from mechanistic and (or) statistical methodologies. Recent renewed interest in digital twin techniques by synergizing between mechanistic and statistical models has opened new frontiers in AF analysis. In the review, we briefly present findings that gave rise to the AF pathophysiology and current therapeutic modalities. We then summarize the achievements of digital twin technologies in three aspects: understanding AF mechanisms, screening anti-AF drugs and optimizing ablation strategies. Finally, we discuss the challenges that hinder the clinical application of the digital twin heart. With the rapid progress in data reuse and sharing, we expect their application to realize the transition from AF description to response prediction.
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Affiliation(s)
- Jieyun Bai
- Guangdong Provincial Key Laboratory of Traditional Chinese Medicine Information Technology, Jinan University, Guangzhou, China
- College of Information Science and Technology, Jinan University, Guangzhou, China
- *Correspondence: Jieyun Bai, ; Jichao Zhao,
| | - Yaosheng Lu
- Guangdong Provincial Key Laboratory of Traditional Chinese Medicine Information Technology, Jinan University, Guangzhou, China
- College of Information Science and Technology, Jinan University, Guangzhou, China
| | - Huijin Wang
- College of Information Science and Technology, Jinan University, Guangzhou, China
| | - Jichao Zhao
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
- *Correspondence: Jieyun Bai, ; Jichao Zhao,
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7
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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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8
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Jæger KH, Edwards AG, Giles WR, Tveito A. Arrhythmogenic influence of mutations in a myocyte-based computational model of the pulmonary vein sleeve. Sci Rep 2022; 12:7040. [PMID: 35487957 PMCID: PMC9054808 DOI: 10.1038/s41598-022-11110-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Accepted: 04/12/2022] [Indexed: 11/09/2022] Open
Abstract
In the heart, electrophysiological dysregulation arises from defects at many biological levels (from point mutations in ion channel proteins to gross structural abnormalities). These defects disrupt the normal pattern of electrical activation, producing ectopic activity and reentrant arrhythmia. To interrogate mechanisms that link these primary biological defects to macroscopic electrophysiologic dysregulation most prior computational studies have utilized either (i) detailed models of myocyte ion channel dynamics at limited spatial scales, or (ii) homogenized models of action potential conduction that reproduce arrhythmic activity at tissue and organ levels. Here we apply our recent model (EMI), which integrates electrical activation and propagation across these scales, to study human atrial arrhythmias originating in the pulmonary vein (PV) sleeves. These small structures initiate most supraventricular arrhythmias and include pronounced myocyte-to-myocyte heterogeneities in ion channel expression and intercellular coupling. To test EMI's cell-based architecture in this physiological context we asked whether ion channel mutations known to underlie atrial fibrillation are capable of initiating arrhythmogenic behavior via increased excitability or reentry in a schematic PV sleeve geometry. Our results illustrate that EMI's improved spatial resolution can directly interrogate how electrophysiological changes at the individual myocyte level manifest in tissue and as arrhythmia in the PV sleeve.
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Affiliation(s)
| | | | - Wayne R Giles
- Simula Research Laboratory, Oslo, Norway.,Department of Physiology and Pharmacology, Cumming School of Medicine, University of Calgary, Calgary, Canada
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9
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A Review on Atrial Fibrillation (Computer Simulation and Clinical Perspectives). HEARTS 2022. [DOI: 10.3390/hearts3010005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
Atrial fibrillation (AF), a heart condition, has been a well-researched topic for the past few decades. This multidisciplinary field of study deals with signal processing, finite element analysis, mathematical modeling, optimization, and clinical procedure. This article is focused on a comprehensive review of journal articles published in the field of AF. Topics from the age-old fundamental concepts to specialized modern techniques involved in today’s AF research are discussed. It was found that a lot of research articles have already been published in modeling and simulation of AF. In comparison to that, the diagnosis and post-operative procedures for AF patients have not yet been totally understood or explored by the researchers. The simulation and modeling of AF have been investigated by many researchers in this field. Cellular model, tissue model, and geometric model among others have been used to simulate AF. Due to a very complex nature, the causes of AF have not been fully perceived to date, but the simulated results are validated with real-life patient data. Many algorithms have been proposed to detect the source of AF in human atria. There are many ablation strategies for AF patients, but the search for more efficient ablation strategies is still going on. AF management for patients with different stages of AF has been discussed in the literature as well but is somehow limited mostly to the patients with persistent AF. The authors hope that this study helps to find existing research gaps in the analysis and the diagnosis of AF.
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10
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Cumberland MJ, Riebel LL, Roy A, O’Shea C, Holmes AP, Denning C, Kirchhof P, Rodriguez B, Gehmlich K. Basic Research Approaches to Evaluate Cardiac Arrhythmia in Heart Failure and Beyond. Front Physiol 2022; 13:806366. [PMID: 35197863 PMCID: PMC8859441 DOI: 10.3389/fphys.2022.806366] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2021] [Accepted: 01/10/2022] [Indexed: 12/20/2022] Open
Abstract
Patients with heart failure often develop cardiac arrhythmias. The mechanisms and interrelations linking heart failure and arrhythmias are not fully understood. Historically, research into arrhythmias has been performed on affected individuals or in vivo (animal) models. The latter however is constrained by interspecies variation, demands to reduce animal experiments and cost. Recent developments in in vitro induced pluripotent stem cell technology and in silico modelling have expanded the number of models available for the evaluation of heart failure and arrhythmia. An agnostic approach, combining the modalities discussed here, has the potential to improve our understanding for appraising the pathology and interactions between heart failure and arrhythmia and can provide robust and validated outcomes in a variety of research settings. This review discusses the state of the art models, methodologies and techniques used in the evaluation of heart failure and arrhythmia and will highlight the benefits of using them in combination. Special consideration is paid to assessing the pivotal role calcium handling has in the development of heart failure and arrhythmia.
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Affiliation(s)
- Max J. Cumberland
- Institute of Cardiovascular Sciences, College of Medical and Dental Sciences, University of Birmingham, Birmingham, United Kingdom
| | - Leto L. Riebel
- Department of Computer Science, University of Oxford, Oxford, United Kingdom
| | - Ashwin Roy
- Institute of Cardiovascular Sciences, College of Medical and Dental Sciences, University of Birmingham, Birmingham, United Kingdom
| | - Christopher O’Shea
- Institute of Cardiovascular Sciences, College of Medical and Dental Sciences, University of Birmingham, Birmingham, United Kingdom
| | - Andrew P. Holmes
- Institute of Cardiovascular Sciences, College of Medical and Dental Sciences, University of Birmingham, Birmingham, United Kingdom
- Institute of Clinical Sciences, College of Medical and Dental Sciences, University of Birmingham, Birmingham, United Kingdom
| | - Chris Denning
- Stem Cell Biology Unit, Biodiscovery Institute, British Heart Foundation Centre for Regenerative Medicine, University of Nottingham, Nottingham, United Kingdom
| | - Paulus Kirchhof
- Institute of Cardiovascular Sciences, College of Medical and Dental Sciences, University of Birmingham, Birmingham, United Kingdom
- University Heart and Vascular Center, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Blanca Rodriguez
- Department of Computer Science, University of Oxford, Oxford, United Kingdom
| | - Katja Gehmlich
- Institute of Cardiovascular Sciences, College of Medical and Dental Sciences, University of Birmingham, Birmingham, United Kingdom
- Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford and British Heart Foundation Centre of Research Excellence Oxford, Oxford, United Kingdom
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11
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Kwon OS, Hwang I, Pak HN. Computational modeling of atrial fibrillation. INTERNATIONAL JOURNAL OF ARRHYTHMIA 2021. [DOI: 10.1186/s42444-021-00051-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
AbstractWith the aging society, the prevalence of atrial fibrillation (AF) continues to increase. Nevertheless, there are still limitations in antiarrhythmic drugs (AAD) or catheter interventions for AF. If it is possible to predict the outcome of AF management according to various AADs or ablation lesion sets through computational modeling, it will be of great clinical help. AF computational modeling has been utilized for in-silico arrhythmia research and enabled high-density entire chamber mapping, reproducible condition control, virtual intervention, not possible clinically or experimentally, in-depth mechanistic research. With the recent development of computer science and technology, more sophisticated and faster computational modeling has become available for clinical application. In particular, it can be applied to determine the extra-PV target of persistent AF catheter ablation or to select the AAD with the best effect. AF computational modeling combined with artificial intelligence is expected to contribute to precision medicine for more diverse uses in the future. Therefore, in this review, we will deal with the history, development, and various applications of computation modeling.
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12
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Berman JP, Kaboudian A, Uzelac I, Iravanian S, Iles T, Iaizzo PA, Lim H, Smolka S, Glimm J, Cherry EM, Fenton FH. Interactive 3D Human Heart Simulations on Segmented Human MRI Hearts. COMPUTING IN CARDIOLOGY 2021; 48:10.23919/cinc53138.2021.9662948. [PMID: 35754523 PMCID: PMC9228622 DOI: 10.23919/cinc53138.2021.9662948] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Understanding cardiac arrhythmic mechanisms and developing new strategies to control and terminate them using computer simulations requires realistic physiological cell models with anatomically accurate heart structures. Furthermore, numerical simulations must be fast enough to study and validate model and structure parameters. Here, we present an interactive parallel approach for solving detailed cell dynamics in high-resolution human heart structures with a local PC's GPU. In vitro human heart MRI scans were manually segmented to produce 3D structures with anatomically realistic electrophysiology. The Abubu.js library was used to create an interactive code to solve the OVVR human ventricular cell model and the FDA extension of the model in the human MRI heart structures, allowing the simulation of reentrant waves and investigation of their dynamics in real time. Interactive simulations of a physiological cell model in a detailed anatomical human heart reveals propagation of waves through the fine structures of the trabeculae and pectinate muscle that can perpetuate arrhythmias, thereby giving new insights into effects that may need to be considered when planning ablation and other defibrillation methods.
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Affiliation(s)
- John P Berman
- School of Physics, Georgia Institute of Technology, Atlanta, GA, USA
| | - Abouzar Kaboudian
- School of Physics, Georgia Institute of Technology, Atlanta, GA, USA
| | - Ilija Uzelac
- School of Physics, Georgia Institute of Technology, Atlanta, GA, USA
| | | | - Tinen Iles
- Medical School, University of Minnesota, Minneapolis, MN, USA
| | - Paul A Iaizzo
- Medical School, University of Minnesota, Minneapolis, MN, USA
| | | | | | | | - Elizabeth M Cherry
- School of Computational Science and Engineering, Georgia Institute of Technology, Atlanta, GA, USA
| | - Flavio H Fenton
- School of Physics, Georgia Institute of Technology, Atlanta, GA, USA
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13
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Bai J, Lu Y, Zhu Y, Wang H, Yin D, Zhang H, Franco D, Zhao J. Understanding PITX2-Dependent Atrial Fibrillation Mechanisms through Computational Models. Int J Mol Sci 2021; 22:7681. [PMID: 34299303 PMCID: PMC8307824 DOI: 10.3390/ijms22147681] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2021] [Revised: 07/14/2021] [Accepted: 07/16/2021] [Indexed: 01/11/2023] Open
Abstract
Atrial fibrillation (AF) is a common arrhythmia. Better prevention and treatment of AF are needed to reduce AF-associated morbidity and mortality. Several major mechanisms cause AF in patients, including genetic predispositions to AF development. Genome-wide association studies have identified a number of genetic variants in association with AF populations, with the strongest hits clustering on chromosome 4q25, close to the gene for the homeobox transcription PITX2. Because of the inherent complexity of the human heart, experimental and basic research is insufficient for understanding the functional impacts of PITX2 variants on AF. Linking PITX2 properties to ion channels, cells, tissues, atriums and the whole heart, computational models provide a supplementary tool for achieving a quantitative understanding of the functional role of PITX2 in remodelling atrial structure and function to predispose to AF. It is hoped that computational approaches incorporating all we know about PITX2-related structural and electrical remodelling would provide better understanding into its proarrhythmic effects leading to development of improved anti-AF therapies. In the present review, we discuss advances in atrial modelling and focus on the mechanistic links between PITX2 and AF. Challenges in applying models for improving patient health are described, as well as a summary of future perspectives.
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Affiliation(s)
- Jieyun Bai
- College of Information Science and Technology, Jinan University, Guangzhou 510632, China; (Y.L.); (Y.Z.)
- Auckland Bioengineering Institute, University of Auckland, Auckland 1010, New Zealand
| | - Yaosheng Lu
- College of Information Science and Technology, Jinan University, Guangzhou 510632, China; (Y.L.); (Y.Z.)
| | - Yijie Zhu
- College of Information Science and Technology, Jinan University, Guangzhou 510632, China; (Y.L.); (Y.Z.)
| | - Huijin Wang
- College of Information Science and Technology, Jinan University, Guangzhou 510632, China; (Y.L.); (Y.Z.)
| | - Dechun Yin
- Department of Cardiology, First Affiliated Hospital of Harbin Medical University, Harbin 150000, China;
| | - Henggui Zhang
- Biological Physics Group, School of Physics & Astronomy, The University of Manchester, Manchester M13 9PL, UK;
| | - Diego Franco
- Department of Experimental Biology, University of Jaen, 23071 Jaen, Spain;
| | - Jichao Zhao
- Auckland Bioengineering Institute, University of Auckland, Auckland 1010, New Zealand
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14
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A Comparison of Regional Classification Strategies Implemented for the Population Based Approach to Modelling Atrial Fibrillation. MATHEMATICS 2021. [DOI: 10.3390/math9141686] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
(1) Background: in silico models are increasingly relied upon to study the mechanisms of atrial fibrillation. Due to the complexity associated with atrial models, cellular variability is often ignored. Recent studies have shown that cellular variability may have a larger impact on electrophysiological behaviour than previously expected. This paper compares two methods for AF remodelling using regional populations. (2) Methods: using 200,000 action potentials, experimental data was used to calibrate healthy atrial regional populations with two cellular models. AF remodelling was applied by directly adjusting maximum channel conductances. AF remodelling was also applied through adjusting biomarkers. The methods were compared upon replication of experimental data. (3) Results: compared to the percentage method, the biomarker approach resulted in smaller changes. RMP, APD20, APD50, and APD90 were changed in the percentage method by up to 11%, 500%, 50%, and 60%, respectively. In the biomarker approach, RMP, APD20, APD50, and APD90 were changed by up to 4.5%, 132%, 50%, and 35%, respectively. (4) Conclusion: applying AF remodelling through biomarker-based clustering resulted in channel conductance changes that were consistent with experimental data, while maintaining the highly non-linear relationships between channel conductances and biomarkers. Directly changing conductances in the healthy regional populations impacted the non-linear relationships and resulted in non-physiological APD20 and APD50 values.
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15
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van Schie MS, Starreveld R, Roos-Serote MC, Taverne YJHJ, van Schaagen FRN, Bogers AJJC, de Groot NMS. Classification of sinus rhythm single potential morphology in patients with mitral valve disease. Europace 2021; 22:1509-1519. [PMID: 33033830 PMCID: PMC7544534 DOI: 10.1093/europace/euaa130] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2020] [Revised: 03/24/2020] [Accepted: 04/28/2020] [Indexed: 12/31/2022] Open
Abstract
Aims The morphology of unipolar single potentials (SPs) contains information on intra-atrial conduction disorders and possibly the substrate underlying atrial fibrillation (AF). This study examined the impact of AF episodes on features of SP morphology during sinus rhythm (SR) in patients with mitral valve disease. Methods and results Intraoperative epicardial mapping (interelectrode distance 2 mm) of the right and left atrium (RA, LA), Bachmann’s bundle (BB), and pulmonary vein area (PVA) was performed in 67 patients (27 male, 67 ± 11 years) with or without a history of paroxysmal AF (PAF). Unipolar SPs were classified according to their differences in relative R- and S-wave amplitude ratios. A clear predominance of S-waves was observed at BB and the RA in both the no AF and PAF groups (BB 88.8% vs. 85.9%, RA 92.1% vs. 85.1%, respectively). Potential voltages at the RA, BB, and PVA were significantly lower in the PAF group (P < 0.001 for each) and were mainly determined by the size of the S-waves amplitudes. The largest difference in S-wave amplitudes was found at BB; the S-wave amplitude was lower in the PAF group [4.08 (2.45–6.13) mV vs. 2.94 (1.40–4.75) mV; P < 0.001]. In addition, conduction velocity (CV) at BB was lower as well [0.97 (0.70–1.21) m/s vs. 0.89 (0.62–1.16) m/s, P < 0.001]. Conclusion Though excitation of the atria during SR is heterogeneously disrupted, a history of AF is characterized by decreased SP amplitudes at BB due to loss of S-wave amplitudes and decreased CV. This suggests that SP morphology could provide additional information on wavefront propagation.
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Affiliation(s)
- Mathijs S van Schie
- Department of Cardiology, Unit Translational Electrophysiology, Erasmus Medical Centre, Dr Molewaterplein 40, 3015GD Rotterdam, the Netherlands
| | - Roeliene Starreveld
- Department of Cardiology, Unit Translational Electrophysiology, Erasmus Medical Centre, Dr Molewaterplein 40, 3015GD Rotterdam, the Netherlands
| | - Maarten C Roos-Serote
- Department of Cardiology, Unit Translational Electrophysiology, Erasmus Medical Centre, Dr Molewaterplein 40, 3015GD Rotterdam, the Netherlands
| | - Yannick J H J Taverne
- Department of Cardiothoracic Surgery, Erasmus Medical Centre, Rotterdam, the Netherlands
| | - Frank R N van Schaagen
- Department of Cardiothoracic Surgery, Erasmus Medical Centre, Rotterdam, the Netherlands
| | - Ad J J C Bogers
- Department of Cardiothoracic Surgery, Erasmus Medical Centre, Rotterdam, the Netherlands
| | - Natasja M S de Groot
- Department of Cardiology, Unit Translational Electrophysiology, Erasmus Medical Centre, Dr Molewaterplein 40, 3015GD Rotterdam, the Netherlands
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16
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Roy A, Varela M, Chubb H, MacLeod R, Hancox JC, Schaeffter T, Aslanidi O. Identifying locations of re-entrant drivers from patient-specific distribution of fibrosis in the left atrium. PLoS Comput Biol 2020; 16:e1008086. [PMID: 32966275 PMCID: PMC7535127 DOI: 10.1371/journal.pcbi.1008086] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2020] [Revised: 10/05/2020] [Accepted: 06/22/2020] [Indexed: 11/18/2022] Open
Abstract
Clinical evidence suggests a link between fibrosis in the left atrium (LA) and atrial fibrillation (AF), the most common sustained arrhythmia. Image-derived fibrosis is increasingly used for patient stratification and therapy guidance. However, locations of re-entrant drivers (RDs) sustaining AF are unknown and therapy success rates remain suboptimal. This study used image-derived LA models to explore the dynamics of RD stabilization in fibrotic regions and generate maps of RD locations. LA models with patient-specific geometry and fibrosis distribution were derived from late gadolinium enhanced magnetic resonance imaging of 6 AF patients. In each model, RDs were initiated at multiple locations, and their trajectories were tracked and overlaid on the LA fibrosis distributions to identify the most likely regions where the RDs stabilized. The simulations showed that the RD dynamics were strongly influenced by the amount and spatial distribution of fibrosis. In patients with fibrosis burden greater than 25%, RDs anchored to specific locations near large fibrotic patches. In patients with fibrosis burden below 25%, RDs either moved near small fibrotic patches or anchored to anatomical features. The patient-specific maps of RD locations showed that areas that harboured the RDs were much smaller than the entire fibrotic areas, indicating potential targets for ablation therapy. Ablating the predicted locations and connecting them to the existing pulmonary vein ablation lesions was the most effective in-silico ablation strategy.
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Affiliation(s)
- Aditi Roy
- Department of Biomedical Engineering, School of Biomedical Engineering & Imaging Sciences, King’s College London, St Thomas’ Hospital, London, United Kingdom
| | - Marta Varela
- Department of Biomedical Engineering, School of Biomedical Engineering & Imaging Sciences, King’s College London, St Thomas’ Hospital, London, United Kingdom
- National Heart and Lung Institute, Imperial College London, London, United Kingdom
| | - Henry Chubb
- Cardiothoracic Surgery, Stanford University, United States of America
| | - Robert MacLeod
- Bioengineering Department, University of Utah, Salt Lake City, Utah, United States of America
| | - Jules C. Hancox
- School of Physiology and Pharmacology, Cardiovascular Research Laboratories, University of Bristol, Bristol, United Kingdom
| | | | - Oleg Aslanidi
- Department of Biomedical Engineering, School of Biomedical Engineering & Imaging Sciences, King’s College London, St Thomas’ Hospital, London, United Kingdom
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17
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Lim B, Park JW, Hwang M, Ryu AJ, Kim IS, Yu HT, Joung B, Shim EB, Pak HN. Electrophysiological significance of the interatrial conduction including cavo-tricuspid isthmus during atrial fibrillation. J Physiol 2020; 598:3597-3612. [PMID: 32495943 DOI: 10.1113/jp279660] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2020] [Accepted: 05/29/2020] [Indexed: 11/08/2022] Open
Abstract
KEY POINTS The interatrial conduction, including Bachmann's bundle, the posterior septal conduction, the anterior septal conduction, and the cavo-tricuspid isthmus, contributes to the maintenance mechanisms of atrial fibrillation in a 3D biatrial model. The interatrial conduction ablation including a cavo-tricuspid isthmus ablation significantly affects the wave dynamics of atrial fibrillation (AF) and facilitates the AF termination or atrial tachycardia conversion of the AF after the circumferential pulmonary vein isolation. Additional cavo-tricuspid isthmus ablation after the circumferential pulmonary vein isolation improves long-term rhythm outcome after clinical AF catheter ablation. ABSTRACT Although it is known that atrial fibrillation (AF) is mainly a left atrial (LA) disease, the role of the right atrium (RA) and interatrial conduction (IAC), including the cavo-tricuspid isthmus (CTI), has not been clearly defined. We tested AF wave dynamics with or without IAC in computational modelling and the rhythm outcome of AF catheter ablation (AFCA) including CTI ablation in clinical cohort data. We evaluated the dominant frequency (DF) in 3D biatrial AF simulations integrated with 3D-computed tomograms obtained from 10 patients. The IAC was implemented at Bachmann's bundle, posterior septum and the CTI. After virtual circumferential PV isolation (CPVI), we disconnected IACs one by one, and observed the wave dynamics. We compared the long-term rhythm outcome after CPVI alone and additional CTI ablation in 846 patients with AFCA. LA-DF was higher than RA-DF in AF (P < 0.001). After CPVI, the DF decreased significantly by additional IAC ablation (P = 0.003), especially in the LA (P = 0.016). The amount of DF reduction (P = 0.020) and rates of AF termination (P < 0.001) or AT conversion (P = 0.021) were significantly higher after IAC ablations including CTI than those without. In clinical AFCA, the AF recurrence rate was significantly lower in patients with additional CTI ablation than CPVI alone during 25 ± 20 months' follow-up (hazard ratio 0.60 [0.46-0.79], P < 0.001, Log rank P < 0.001). IAC contributes to the maintenance mechanism of AF, and IAC including CTI ablation affects AF wave dynamics, facilitating AF termination in 3D biatrial modelling. Additional CTI ablation after CPVI improves the long-term rhythm outcome in clinical AFCA, potentially in a paroxysmal type with accompanying atrial flutter, or atrial dimension close to normal.
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Affiliation(s)
- Byounghyun Lim
- Yonsei University Health System, Seoul, Republic of Korea
| | - Je-Wook Park
- Yonsei University Health System, Seoul, Republic of Korea
| | | | - Ah-Jin Ryu
- Silicon Sapiens, Seoul, Republic of Korea
| | - In Soo Kim
- Yonsei University Health System, Seoul, Republic of Korea
| | - Hee Tae Yu
- Yonsei University Health System, Seoul, Republic of Korea
| | - Boyoung Joung
- Yonsei University Health System, Seoul, Republic of Korea
| | | | - Hui-Nam Pak
- Yonsei University Health System, Seoul, Republic of Korea
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18
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Gharaviri A, Bidar E, Potse M, Zeemering S, Verheule S, Pezzuto S, Krause R, Maessen JG, Auricchio A, Schotten U. Epicardial Fibrosis Explains Increased Endo-Epicardial Dissociation and Epicardial Breakthroughs in Human Atrial Fibrillation. Front Physiol 2020; 11:68. [PMID: 32153419 PMCID: PMC7047215 DOI: 10.3389/fphys.2020.00068] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2019] [Accepted: 01/21/2020] [Indexed: 01/22/2023] Open
Abstract
Background Atrial fibrillation (AF) is accompanied by progressive epicardial fibrosis, dissociation of electrical activity between the epicardial layer and the endocardial bundle network, and transmural conduction (breakthroughs). However, causal relationships between these phenomena have not been demonstrated yet. Our goal was to test the hypothesis that epicardial fibrosis suffices to increase endo–epicardial dissociation (EED) and breakthroughs (BT) during AF. Methods We simulated the effect of fibrosis in the epicardial layer on EED and BT in a detailed, high-resolution, three-dimensional model of the human atria with realistic electrophysiology. The model results were compared with simultaneous endo–epicardial mapping in human atria. The model geometry, specifically built for this study, was based on MR images and histo-anatomical studies. Clinical data were obtained in four patients with longstanding persistent AF (persAF) and three patients without a history of AF. Results The AF cycle length (AFCL), conduction velocity (CV), and EED were comparable in the mapping studies and the simulations. EED increased from 24.1 ± 3.4 to 56.58 ± 6.2% (p < 0.05), and number of BTs per cycle from 0.89 ± 0.55 to 6.74 ± 2.11% (p < 0.05), in different degrees of fibrosis in the epicardial layer. In both mapping data and simulations, EED correlated with prevalence of BTs. Fibrosis also increased the number of fibrillation waves per cycle in the model. Conclusion A realistic 3D computer model of AF in which epicardial fibrosis was increased, in the absence of other pathological changes, showed increases in EED and epicardial BT comparable to those in longstanding persAF. Thus, epicardial fibrosis can explain both phenomena.
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Affiliation(s)
- Ali Gharaviri
- Department of Physiology, Maastricht University, Maastricht, Netherlands.,Center for Computational Medicine in Cardiology, Institute of Computational Science, Università della Svizzera Italiana, Lugano, Switzerland
| | - Elham Bidar
- Maastricht University Medical Centre, Maastricht, Netherlands
| | - Mark Potse
- Inria Bordeaux - Sud-Ouest Research Centre, Talence, France.,IMB, UMR 5251, Université de Bordeaux, Talence, France.,IHU Liryc, Electrophysiology and Heart Modeling Institute, Foundation Bordeaux Université, Bordeaux, France
| | - Stef Zeemering
- Department of Physiology, Maastricht University, Maastricht, Netherlands
| | - Sander Verheule
- Department of Physiology, Maastricht University, Maastricht, Netherlands
| | - Simone Pezzuto
- Center for Computational Medicine in Cardiology, Institute of Computational Science, Università della Svizzera Italiana, Lugano, Switzerland
| | - Rolf Krause
- Center for Computational Medicine in Cardiology, Institute of Computational Science, Università della Svizzera Italiana, Lugano, Switzerland
| | - Jos G Maessen
- Maastricht University Medical Centre, Maastricht, Netherlands
| | - Angelo Auricchio
- Center for Computational Medicine in Cardiology, Institute of Computational Science, Università della Svizzera Italiana, Lugano, Switzerland.,Fondazione Cardiocentro Ticino, Lugano, Switzerland
| | - Ulrich Schotten
- Department of Physiology, Maastricht University, Maastricht, Netherlands
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19
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Bai J, Lo A, Gladding PA, Stiles MK, Fedorov VV, Zhao J. In silico investigation of the mechanisms underlying atrial fibrillation due to impaired Pitx2. PLoS Comput Biol 2020; 16:e1007678. [PMID: 32097431 PMCID: PMC7059955 DOI: 10.1371/journal.pcbi.1007678] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2019] [Revised: 03/06/2020] [Accepted: 01/22/2020] [Indexed: 01/04/2023] Open
Abstract
Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia and is a major cause of stroke and morbidity. Recent genome-wide association studies have shown that paired-like homeodomain transcription factor 2 (Pitx2) to be strongly associated with AF. However, the mechanisms underlying Pitx2 modulated arrhythmogenesis and variable effectiveness of antiarrhythmic drugs (AADs) in patients in the presence or absence of impaired Pitx2 expression remain unclear. We have developed multi-scale computer models, ranging from a single cell to tissue level, to mimic control and Pitx2-knockout atria by incorporating recent experimental data on Pitx2-induced electrical and structural remodeling in humans, as well as the effects of AADs. The key findings of this study are twofold. We have demonstrated that shortened action potential duration, slow conduction and triggered activity occur due to electrical and structural remodelling under Pitx2 deficiency conditions. Notably, the elevated function of calcium transport ATPase increases sarcoplasmic reticulum Ca2+ concentration, thereby enhancing susceptibility to triggered activity. Furthermore, heterogeneity is further elevated due to Pitx2 deficiency: 1) Electrical heterogeneity between left and right atria increases; and 2) Increased fibrosis and decreased cell-cell coupling due to structural remodelling slow electrical propagation and provide obstacles to attract re-entry, facilitating the initiation of re-entrant circuits. Secondly, our study suggests that flecainide has antiarrhythmic effects on AF due to impaired Pitx2 by preventing spontaneous calcium release and increasing wavelength. Furthermore, our study suggests that Na+ channel effects alone are insufficient to explain the efficacy of flecainide. Our study may provide the mechanisms underlying Pitx2-induced AF and possible explanation behind the AAD effects of flecainide in patients with Pitx2 deficiency.
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Affiliation(s)
- Jieyun Bai
- Department of Electronic Engineering, College of Information Science and Technology, Jinan University, Guangzhou, China
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
| | - Andy Lo
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
| | - Patrick A. Gladding
- Department of Cardiology, Waitemata District Health Board, Auckland, New Zealand
| | - Martin K. Stiles
- Waikato Clinical School, Faculty of Medical and Health Sciences, University of Auckland, New Zealand
| | - Vadim V. Fedorov
- Department of Physiology & Cell Biology and Bob and Corrine Frick Center for Heart Failure and Arrhythmia, The Ohio State University Wexner Medical Center, Columbus, Ohio, United States of America
| | - Jichao Zhao
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
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20
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Abstract
The treatment of individual patients in cardiology practice increasingly relies on advanced imaging, genetic screening and devices. As the amount of imaging and other diagnostic data increases, paralleled by the greater capacity to personalize treatment, the difficulty of using the full array of measurements of a patient to determine an optimal treatment seems also to be paradoxically increasing. Computational models are progressively addressing this issue by providing a common framework for integrating multiple data sets from individual patients. These models, which are based on physiology and physics rather than on population statistics, enable computational simulations to reveal diagnostic information that would have otherwise remained concealed and to predict treatment outcomes for individual patients. The inherent need for patient-specific models in cardiology is clear and is driving the rapid development of tools and techniques for creating personalized methods to guide pharmaceutical therapy, deployment of devices and surgical interventions.
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21
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Filos D, Tachmatzidis D, Maglaveras N, Vassilikos V, Chouvarda I. Understanding the Beat-to-Beat Variations of P-Waves Morphologies in AF Patients During Sinus Rhythm: A Scoping Review of the Atrial Simulation Studies. Front Physiol 2019; 10:742. [PMID: 31275161 PMCID: PMC6591370 DOI: 10.3389/fphys.2019.00742] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2018] [Accepted: 05/28/2019] [Indexed: 11/13/2022] Open
Abstract
The remarkable advances in high-performance computing and the resulting increase of the computational power have the potential to leverage computational cardiology toward improving our understanding of the pathophysiological mechanisms of arrhythmias, such as Atrial Fibrillation (AF). In AF, a complex interaction between various triggers and the atrial substrate is considered to be the leading cause of AF initiation and perpetuation. In electrocardiography (ECG), P-wave is supposed to reflect atrial depolarization. It has been found that even during sinus rhythm (SR), multiple P-wave morphologies are present in AF patients with a history of AF, suggesting a higher dispersion of the conduction route in this population. In this scoping review, we focused on the mechanisms which modify the electrical substrate of the atria in AF patients, while investigating the existence of computational models that simulate the propagation of the electrical signal through different routes. The adopted review methodology is based on a structured analytical framework which includes the extraction of the keywords based on an initial limited bibliographic search, the extensive literature search and finally the identification of relevant articles based on the reference list of the studies. The leading mechanisms identified were classified according to their scale, spanning from mechanisms in the cell, tissue or organ level, and the produced outputs. The computational modeling approaches for each of the factors that influence the initiation and the perpetuation of AF are presented here to provide a clear overview of the existing literature. Several levels of categorization were adopted while the studies which aim to translate their findings to ECG phenotyping are highlighted. The results denote the availability of multiple models, which are appropriate under specific conditions. However, the consideration of complex scenarios taking into account multiple spatiotemporal scales, personalization of electrophysiological and anatomical models and the reproducibility in terms of ECG phenotyping has only partially been tackled so far.
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Affiliation(s)
- Dimitrios Filos
- Lab of Computing, Medical Informatics and Biomedical Imaging Technologies, School of Medicine, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | | | - Nicos Maglaveras
- Lab of Computing, Medical Informatics and Biomedical Imaging Technologies, School of Medicine, Aristotle University of Thessaloniki, Thessaloniki, Greece
- Department of Industrial Engineering and Management Sciences, Northwestern University, Evanston, IL, United States
| | - Vassilios Vassilikos
- 3rd Cardiology Department, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Ioanna Chouvarda
- Lab of Computing, Medical Informatics and Biomedical Imaging Technologies, School of Medicine, Aristotle University of Thessaloniki, Thessaloniki, Greece
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22
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Tissue-Specific Optical Mapping Models of Swine Atria Informed by Optical Coherence Tomography. Biophys J 2019; 114:1477-1489. [PMID: 29590604 PMCID: PMC5883619 DOI: 10.1016/j.bpj.2018.01.035] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2017] [Revised: 01/12/2018] [Accepted: 01/30/2018] [Indexed: 11/21/2022] Open
Abstract
Computational models and experimental optical mapping of cardiac electrophysiology serve as powerful tools to investigate the underlying mechanisms of arrhythmias. Modeling can also aid the interpretation of optical mapping signals, which may have different characteristics with respect to the underlying electrophysiological signals they represent. However, despite the prevalence of atrial arrhythmias such as atrial fibrillation, models of optical electrical mapping incorporating realistic structure of the atria are lacking. Therefore, we developed image-based models of atrial tissue using structural information extracted from optical coherence tomography (OCT), which can provide volumetric tissue characteristics in high resolution. OCT volumetric data of four swine atrial tissue samples were used to develop models incorporating tissue geometry, tissue-specific myofiber orientation, and ablation lesion regions. We demonstrated the use of these models through electrophysiology and photon scattering simulations. Changes in transmural electrical conduction were observed with the inclusion of OCT-derived, depth-resolved fiber orientation. Additionally, the amplitude of optical mapping signals were not found to correspond with lesion transmurality because of lesion geometry and electrical propagation occurring beyond excitation light penetration. This work established a framework for the development of tissue-specific models of atrial tissue derived from OCT imaging data, which can be useful in future investigations of electrophysiology and optical mapping signals with respect to realistic atrial tissue structure.
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23
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Computational modeling: What does it tell us about atrial fibrillation therapy? Int J Cardiol 2019; 287:155-161. [PMID: 30803891 DOI: 10.1016/j.ijcard.2019.01.077] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/19/2018] [Revised: 12/09/2018] [Accepted: 01/22/2019] [Indexed: 12/19/2022]
Abstract
Atrial fibrillation (AF) is a complex cardiac arrhythmia with diverse etiology that negatively affects morbidity and mortality of millions of patients. Technological and experimental advances have provided a wealth of information on the pathogenesis of AF, highlighting a multitude of mechanisms involved in arrhythmia initiation and maintenance, and disease progression. However, it remains challenging to identify the predominant mechanisms for specific subgroups of AF patients, which, together with an incomplete understanding of the pleiotropic effects of antiarrhythmic therapies, likely contributes to the suboptimal efficacy of current antiarrhythmic approaches. Computer modeling of cardiac electrophysiology has advanced in parallel to experimental research and provides an integrative framework to attempt to overcome some of these challenges. Multi-scale cardiac modeling and simulation integrate structural and functional data from experimental and clinical work with knowledge of atrial electrophysiological mechanisms and dynamics, thereby improving our understanding of AF mechanisms and therapy. In this review, we describe recent advances in our quantitative understanding of AF through mathematical models. We discuss computational modeling of AF mechanisms and therapy using detailed, mechanistic cell/tissue-level models, including approaches to incorporate variability in patient populations. We also highlight efforts using whole-atria models to improve catheter ablation therapies. Finally, we describe recent efforts and suggest future extensions to model clinical concepts of AF using patient-level models.
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24
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Roney CH, Whitaker J, Sim I, O'Neill L, Mukherjee RK, Razeghi O, Vigmond EJ, Wright M, O'Neill MD, Williams SE, Niederer SA. A technique for measuring anisotropy in atrial conduction to estimate conduction velocity and atrial fibre direction. Comput Biol Med 2019; 104:278-290. [PMID: 30415767 PMCID: PMC6506689 DOI: 10.1016/j.compbiomed.2018.10.019] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2018] [Revised: 10/17/2018] [Accepted: 10/17/2018] [Indexed: 01/04/2023]
Abstract
BACKGROUND Cardiac conduction properties exhibit large variability, and affect patient-specific arrhythmia mechanisms. However, it is challenging to clinically measure conduction velocity (CV), anisotropy and fibre direction. Our aim is to develop a technique to estimate conduction anisotropy and fibre direction from clinically available electrical recordings. METHODS We developed and validated automated algorithms for estimating cardiac CV anisotropy, from any distribution of recording locations on the atrial surface. The first algorithm is for elliptical wavefront fitting to a single activation map (method 1), which works well close to the pacing location, but decreases in accuracy further from the pacing location (due to spatial heterogeneity in the conductivity and fibre fields). As such, we developed a second methodology for measuring local conduction anisotropy, using data from two or three activation maps (method 2: ellipse fitting to wavefront propagation velocity vectors from multiple activation maps). RESULTS Ellipse fitting to CV vectors from two activation maps (method 2) leads to an improved estimation of longitudinal and transverse CV compared to method 1, but fibre direction estimation is still relatively poor. Using three activation maps with method 2 provides accurate estimation, with approximately 70% of atrial fibres estimated within 20∘. We applied the technique to clinical activation maps to demonstrate the presence of heterogeneous conduction anisotropy, and then tested the effects of this conduction anisotropy on predicted arrhythmia dynamics using computational simulation. CONCLUSIONS We have developed novel algorithms for calculating CV and measuring the direction dependency of atrial activation to estimate atrial fibre direction, without the need for specialised pacing protocols, using clinically available electrical recordings.
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Affiliation(s)
- Caroline H Roney
- School of Imaging Sciences and Biomedical Engineering, King's College London, London, United Kingdom.
| | - John Whitaker
- School of Imaging Sciences and Biomedical Engineering, King's College London, London, United Kingdom
| | - Iain Sim
- School of Imaging Sciences and Biomedical Engineering, King's College London, London, United Kingdom
| | - Louisa O'Neill
- School of Imaging Sciences and Biomedical Engineering, King's College London, London, United Kingdom
| | - Rahul K Mukherjee
- School of Imaging Sciences and Biomedical Engineering, King's College London, London, United Kingdom
| | - Orod Razeghi
- School of Imaging Sciences and Biomedical Engineering, King's College London, London, United Kingdom
| | - Edward J Vigmond
- LIRYC Electrophysiology and Heart Modeling Institute, Campus Xavier Arnozan, Avenue du Haut Lévêque, 33600, Pessac, France; Univ. Bordeaux, IMB, UMR 5251, F-33400, Talence, France
| | - Matthew Wright
- School of Imaging Sciences and Biomedical Engineering, King's College London, London, United Kingdom
| | - Mark D O'Neill
- School of Imaging Sciences and Biomedical Engineering, King's College London, London, United Kingdom
| | - Steven E Williams
- School of Imaging Sciences and Biomedical Engineering, King's College London, London, United Kingdom
| | - Steven A Niederer
- School of Imaging Sciences and Biomedical Engineering, King's College London, London, United Kingdom
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25
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De Coster T, Claus P, Seemann G, Willems R, Sipido KR, Panfilov AV. Myocyte Remodeling Due to Fibro-Fatty Infiltrations Influences Arrhythmogenicity. Front Physiol 2018; 9:1381. [PMID: 30344493 PMCID: PMC6182296 DOI: 10.3389/fphys.2018.01381] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2018] [Accepted: 09/11/2018] [Indexed: 12/19/2022] Open
Abstract
The onset of cardiac arrhythmias depends on the electrophysiological and structural properties of cardiac tissue. Electrophysiological remodeling of myocytes due to the presence of adipocytes constitutes a possibly important pathway in the pathogenesis of atrial fibrillation. In this paper we perform an in-silico study of the effect of such myocyte remodeling on the onset of atrial arrhythmias and study the dynamics of arrhythmia sources—spiral waves. We use the Courtemanche model for atrial myocytes and modify their electrophysiological properties based on published cellular electrophysiological measurements in myocytes co-cultered with adipocytes (a 69–87 % increase in APD90 and an increase of the RMP by 2.5–5.5 mV). In a generic 2D setup we show that adipose tissue remodeling substantially affects the spiral wave dynamics resulting in complex arrhythmia and such arrhythmia can be initiated under high frequency pacing if the size of the remodeled tissue is sufficiently large. These results are confirmed in simulations with an anatomically accurate model of the human atria.
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Affiliation(s)
- Tim De Coster
- Department of Physics and Astronomy, Ghent University, Ghent, Belgium.,Department of Cardiovascular Sciences, KU Leuven, Leuven, Belgium
| | - Piet Claus
- Department of Cardiovascular Sciences, KU Leuven, Leuven, Belgium
| | - Gunnar Seemann
- Institute for Experimental Cardiovascular Medicine, University Heart Centre Freiburg • Bad Krozingen, Medical Center - University of Freiburg, and Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Rik Willems
- Department of Cardiovascular Sciences, KU Leuven, Leuven, Belgium
| | - Karin R Sipido
- Department of Cardiovascular Sciences, KU Leuven, Leuven, Belgium
| | - Alexander V Panfilov
- Department of Physics and Astronomy, Ghent University, Ghent, Belgium.,Laboratory of Experimental Cardiology, Department of Cardiology, Heart Lung Centre Leiden, Leiden University Medical Center, Leiden, Netherlands.,Laboratory of Computational Biology and Medicine, Ural Federal University, Ekaterinburg, Russia
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Roy A, Varela M, Aslanidi O. Image-Based Computational Evaluation of the Effects of Atrial Wall Thickness and Fibrosis on Re-entrant Drivers for Atrial Fibrillation. Front Physiol 2018; 9:1352. [PMID: 30349483 PMCID: PMC6187302 DOI: 10.3389/fphys.2018.01352] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2018] [Accepted: 09/06/2018] [Indexed: 12/19/2022] Open
Abstract
Introduction: Catheter ablation (CA) is a common treatment for atrial fibrillation (AF), but the knowledge of optimal ablation sites, and hence clinical outcomes, are suboptimal. Increasing evidence suggest that ablation strategies based on patient-specific substrates information, such as distributions of fibrosis and atrial wall thickness (AWT), may be used to improve therapy. We hypothesized that competing influences of large AWT gradients and fibrotic patches on conductive properties of atrial tissue can determine locations of re-entrant drivers (RDs) sustaining AF. Methods: Two sets of models were used: (1) a simple model of 3D atrial tissue slab with a step change in AWT and a synthetic fibrosis patch, and (2) 3D models based on patient-specific right atrial (RA) and left atrial (LA) geometries. The latter were obtained from four healthy volunteers and two AF patients, respectively, using magnetic resonance imaging (MRI). A synthetic fibrotic patch was added in the RA and fibrosis distributions in the LA were obtained from gadolinium-enhanced MRI of the same patients. In all models, 3D geometry was combined with the Fenton-Karma atrial cell model to simulate RDs. Results: In the slab, RDs drifted toward, and then along the AWT step. However, with additional fibrosis, the RDs were localized in regions between the step and fibrosis. In the RA, RDs drifted toward and anchored to a large AWT gradient between the crista terminalis (CT) region and the surrounding atrial wall. Without such a gradient, RDs drifted toward the superior vena cava (SVC) or the tricuspid valve (TSV). With additional fibrosis, RDs initiated away from the CT anchored to the fibrotic patch, whereas RDs initiated close to the CT region remained localized between the two structures. In the LA, AWT was more uniform and RDs drifted toward the pulmonary veins (PVs). However, with additional fibrotic patches, RDs either anchored to them or multiplied. Conclusion: In the RA, RD locations are determined by both fibrosis and AWT gradients at the CT region. In the LA, they are determined by fibrosis due to the absence of large AWT gradients. These results elucidate mechanisms behind the stabilization of RDs sustaining AF and can help guide ablation therapy.
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Affiliation(s)
| | | | - Oleg Aslanidi
- Department of Biomedical Engineering, School of Biomedical Engineering & Imaging Sciences, King’s College London, King’s Health Partners, St Thomas’ Hospital, London, United Kingdom
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Saha M, Roney CH, Bayer JD, Meo M, Cochet H, Dubois R, Vigmond EJ. Wavelength and Fibrosis Affect Phase Singularity Locations During Atrial Fibrillation. Front Physiol 2018; 9:1207. [PMID: 30246796 PMCID: PMC6139329 DOI: 10.3389/fphys.2018.01207] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2018] [Accepted: 08/10/2018] [Indexed: 01/06/2023] Open
Abstract
The mechanisms underlying atrial fibrillation (AF), the most common sustained cardiac rhythm disturbance, remain elusive. Atrial fibrosis plays an important role in the development of AF and rotor dynamics. Both electrical wavelength (WL) and the degree of atrial fibrosis change as AF progresses. However, their combined effect on rotor core location remains unknown. The aim of this study was to analyze the effects of WL change on rotor core location in both fibrotic and non-fibrotic atria. Three patient specific fibrosis distributions (total fibrosis content: 16.6, 22.8, and 19.2%) obtained from clinical imaging data of persistent AF patients were incorporated in a bilayer atrial computational model. Fibrotic effects were modeled as myocyte-fibroblast coupling + conductivity remodeling; structural remodeling; ionic current changes + conductivity remodeling; and combinations of these methods. To change WL, action potential duration (APD) was varied from 120 to 240ms, representing the range of clinically observed AF cycle length, by modifying the inward rectifier potassium current (IK1) conductance between 80 and 140% of the original value. Phase singularities (PSs) were computed to identify rotor core locations. Our results show that IK1 conductance variation resulted in a decrease of APD and WL across the atria. For large WL in the absence of fibrosis, PSs anchored to regions with high APD gradient at the center of the left atrium (LA) anterior wall and near the junctions of the inferior pulmonary veins (PVs) with the LA. Decreasing the WL induced more PSs, whose distribution became less clustered. With fibrosis, PS locations depended on the fibrosis distribution and the fibrosis implementation method. The proportion of PSs in fibrotic areas and along the borders varied with both WL and fibrosis modeling method: for patient one, this was 4.2-14.9% as IK1 varied for the structural remodeling representation, but 12.3-88.4% using the combination of structural remodeling with myocyte-fibroblast coupling. The degree and distribution of fibrosis and the choice of implementation technique had a larger effect on PS locations than the WL variation. Thus, distinguishing the fibrotic mechanisms present in a patient is important for interpreting clinical fibrosis maps to create personalized models.
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Affiliation(s)
- Mirabeau Saha
- IMB, UMR 5251, University of Bordeaux, Pessac, France
- IHU Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux University, Pessac, France
| | - Caroline H. Roney
- Department of Biomedical Engineering, King's College London, London, United Kingdom
| | - Jason D. Bayer
- IMB, UMR 5251, University of Bordeaux, Pessac, France
- IHU Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux University, Pessac, France
| | - Marianna Meo
- IMB, UMR 5251, University of Bordeaux, Pessac, France
- IHU Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux University, Pessac, France
| | - Hubert Cochet
- IMB, UMR 5251, University of Bordeaux, Pessac, France
- IHU Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux University, Pessac, France
| | - Remi Dubois
- IMB, UMR 5251, University of Bordeaux, Pessac, France
- IHU Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux University, Pessac, France
| | - Edward J. Vigmond
- IMB, UMR 5251, University of Bordeaux, Pessac, France
- IHU Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux University, Pessac, France
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28
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Vidmar D, Alhusseini MI, Narayan SM, Rappel WJ. Characterizing Electrogram Signal Fidelity and the Effects of Signal Contamination on Mapping Human Persistent Atrial Fibrillation. Front Physiol 2018; 9:1232. [PMID: 30237766 PMCID: PMC6135945 DOI: 10.3389/fphys.2018.01232] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2018] [Accepted: 08/15/2018] [Indexed: 11/30/2022] Open
Abstract
Objective: Determining accurate intracardiac maps of atrial fibrillation (AF) in humans can be difficult, owing primarily to various sources of contamination in electrogram signals. The goal of this study is to develop a measure for signal fidelity and to develop methods to quantify robustness of observed rotational activity in phase maps subject to signal contamination. Methods: We identified rotational activity in phase maps of human persistent AF using the Hilbert transform of sinusoidally recomposed signals, where localized ablation at rotational sites terminated fibrillation. A novel measure of signal fidelity was developed to quantify signal quality. Contamination is then introduced to the underlying electrograms by removing signals at random, adding noise to computations of cycle length, and adding realistic far-field signals. Mean tip number N and tip density δ, defined as the proportion of time a region contains a tip, at the termination site are computed to compare the effects of contamination. Results: Domains of low signal fidelity correspond to the location of rotational cores. Removing signals and altering cycle length accounted for minor changes in tip density, while targeted removal of low fidelity electrograms can result in a significant increase in tip density and stability. Far-field contamination was found to obscure rotation at the termination site. Conclusion: Rotational activity in clinical AF can produce domains of low fidelity electrogram recordings at rotational cores. Observed rotational patterns in phase maps appear most sensitive to far-field activation. These results may inform novel methods to map AF in humans which can be tested directly in patients at electrophysiological study and ablation.
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Affiliation(s)
- David Vidmar
- Department of Physics, University of California, San Diego, San Diego, CA, United States
| | - Mahmood I. Alhusseini
- Division of Cardiology, Department of Medicine, Stanford University, Stanford, CA, United States
| | - Sanjiv M. Narayan
- Division of Cardiology, Department of Medicine, Stanford University, Stanford, CA, United States
| | - Wouter-Jan Rappel
- Department of Physics, University of California, San Diego, San Diego, CA, United States
- *Correspondence: Wouter-Jan Rappel
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29
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Vagos M, van Herck IGM, Sundnes J, Arevalo HJ, Edwards AG, Koivumäki JT. Computational Modeling of Electrophysiology and Pharmacotherapy of Atrial Fibrillation: Recent Advances and Future Challenges. Front Physiol 2018; 9:1221. [PMID: 30233399 PMCID: PMC6131668 DOI: 10.3389/fphys.2018.01221] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2018] [Accepted: 08/13/2018] [Indexed: 12/19/2022] Open
Abstract
The pathophysiology of atrial fibrillation (AF) is broad, with components related to the unique and diverse cellular electrophysiology of atrial myocytes, structural complexity, and heterogeneity of atrial tissue, and pronounced disease-associated remodeling of both cells and tissue. A major challenge for rational design of AF therapy, particularly pharmacotherapy, is integrating these multiscale characteristics to identify approaches that are both efficacious and independent of ventricular contraindications. Computational modeling has long been touted as a basis for achieving such integration in a rapid, economical, and scalable manner. However, computational pipelines for AF-specific drug screening are in their infancy, and while the field is progressing quite rapidly, major challenges remain before computational approaches can fill the role of workhorse in rational design of AF pharmacotherapies. In this review, we briefly detail the unique aspects of AF pathophysiology that determine requirements for compounds targeting AF rhythm control, with emphasis on delimiting mechanisms that promote AF triggers from those providing substrate or supporting reentry. We then describe modeling approaches that have been used to assess the outcomes of drugs acting on established AF targets, as well as on novel promising targets including the ultra-rapidly activating delayed rectifier potassium current, the acetylcholine-activated potassium current and the small conductance calcium-activated potassium channel. Finally, we describe how heterogeneity and variability are being incorporated into AF-specific models, and how these approaches are yielding novel insights into the basic physiology of disease, as well as aiding identification of the important molecular players in the complex AF etiology.
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Affiliation(s)
- Márcia Vagos
- Computational Physiology Department, Simula Research Laboratory, Lysaker, Norway
- Department of Informatics, University of Oslo, Oslo, Norway
| | - Ilsbeth G. M. van Herck
- Computational Physiology Department, Simula Research Laboratory, Lysaker, Norway
- Department of Informatics, University of Oslo, Oslo, Norway
| | - Joakim Sundnes
- Computational Physiology Department, Simula Research Laboratory, Lysaker, Norway
- Center for Cardiological Innovation, Oslo, Norway
| | - Hermenegild J. Arevalo
- Computational Physiology Department, Simula Research Laboratory, Lysaker, Norway
- Center for Cardiological Innovation, Oslo, Norway
| | - Andrew G. Edwards
- Computational Physiology Department, Simula Research Laboratory, Lysaker, Norway
- Center for Cardiological Innovation, Oslo, Norway
| | - Jussi T. Koivumäki
- BioMediTech Institute and Faculty of Biomedical Sciences and Engineering, Tampere University of Technology, Tampere, Finland
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
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30
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Gharaviri A, Verheule S, Eckstein J, Potse M, Kuklik P, Kuijpers NHL, Schotten U. How disruption of endo-epicardial electrical connections enhances endo-epicardial conduction during atrial fibrillation. Europace 2018; 19:308-318. [PMID: 28175261 DOI: 10.1093/europace/euv445] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2015] [Accepted: 08/11/2015] [Indexed: 11/12/2022] Open
Abstract
Aims Loss of side-to-side electrical connections between atrial muscle bundles is thought to underlie conduction disturbances predisposing to atrial fibrillation (AF). Putatively, disruption of electrical connections occurs not only within the epicardial layer but also between the epicardial layer and the endocardial bundle network, thus impeding transmural conductions (‘breakthroughs’). However, both clinical and experimental studies have shown an enhancement of breakthroughs during later stages of AF. We tested the hypothesis that endo-epicardial uncoupling enhances endo-epicardial electrical dyssynchrony, breakthrough rate (BTR), and AF stability. Methods and Results In a novel dual-layer computer model of the human atria, 100% connectivity between the two layers served as healthy control. Atrial structural remodelling was simulated by reducing the number of connections between the layers from 96 to 6 randomly chosen locations. With progressive elimination of connections, AF stability increased. Reduction in the number of connections from 96 to 24 resulted in an increase in endo-epicardial dyssynchrony from 6.6 ± 1.9 to 24.6 ± 1.3%, with a concomitant increase in BTR. A further reduction to 12 and 6 resulted in more pronounced endo-epicardial dyssynchrony of 34.4 ± 1.15 and 40.2 ± 0.52% but with BTR reduction. This biphasic relationship between endo-epicardial coupling and BTR was found independently from whether AF was maintained by re-entry or by ectopic focal discharges. Conclusion Loss of endo-epicardial coupling increases AF stability. There is a biphasic relation between endo-epicardial coupling and BTR. While at high degrees of endo-epicardial connectivity, the BTR is limited by the endo-epicardial synchronicity, at low degrees of connectivity, it is limited by the number of endo-epicardial connections.
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Affiliation(s)
- Ali Gharaviri
- Department of Physiology and Maastricht Centre of Systems Biology, Maastricht University, PO Box 616, Maastricht 6200 MD, The Netherlands
| | - Sander Verheule
- Department of Physiology and Maastricht Centre of Systems Biology, Maastricht University, PO Box 616, Maastricht 6200 MD, The Netherlands
| | - Jens Eckstein
- Department of Physiology and Maastricht Centre of Systems Biology, Maastricht University, PO Box 616, Maastricht 6200 MD, The Netherlands.,Department of Internal Medicine, University Hospital Basel, Basel, Switzerland
| | - Mark Potse
- Department of Biomedical Engineering, Maastricht University, Maastricht, The Netherlands.,Institute of Computational Science, Faculty of Informatics, Università della Svizzera italiana, Lugano, Switzerland
| | - Pawel Kuklik
- Department of Physiology and Maastricht Centre of Systems Biology, Maastricht University, PO Box 616, Maastricht 6200 MD, The Netherlands
| | - Nico H L Kuijpers
- Department of Biomedical Engineering, Maastricht University, Maastricht, The Netherlands
| | - Ulrich Schotten
- Department of Physiology and Maastricht Centre of Systems Biology, Maastricht University, PO Box 616, Maastricht 6200 MD, The Netherlands
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31
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Corrado C, Williams S, Karim R, Plank G, O'Neill M, Niederer S. A work flow to build and validate patient specific left atrium electrophysiology models from catheter measurements. Med Image Anal 2018; 47:153-163. [PMID: 29753180 PMCID: PMC5998385 DOI: 10.1016/j.media.2018.04.005] [Citation(s) in RCA: 33] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2017] [Revised: 02/16/2018] [Accepted: 04/19/2018] [Indexed: 11/19/2022]
Abstract
Biophysical models of the atrium provide a physically constrained framework for describing the current state of an atrium and allow predictions of how that atrium will respond to therapy. We propose a work flow to simulate patient specific electrophysiological heterogeneity from clinical data and validate the resulting biophysical models. In 7 patients, we recorded the atrial anatomy with an electroanatomical mapping system (St Jude Velocity); we then applied an S1-S2 electrical stimulation protocol from the coronary sinus (CS) and the high right atrium (HRA) whilst recording the activation patterns using a PentaRay catheter with 10 bipolar electrodes at 12 ± 2 sites across the atrium. Using only the activation times measured with a PentaRay catheter and caused by a stimulus applied in the CS with a remote catheter we fitted the four parameters for a modified Mitchell-Schaeffer model and the tissue conductivity to the recorded local conduction velocity restitution curve and estimated local effective refractory period. Model parameters were then interpolated across each atrium. The fitted model recapitulated the S1-S2 activation times for CS pacing giving a correlation ranging between 0.81 and 0.98. The model was validated by comparing simulated activations times with the independently recorded HRA pacing S1-S2 activation times, giving a correlation ranging between 0.65 and 0.96. The resulting work flow provides the first validated cohort of models that capture clinically measured patient specific electrophysiological heterogeneity.
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Affiliation(s)
- Cesare Corrado
- Division of Imaging Sciences & Biomedical Engineering, King's College London, London SE17EH, United Kingdom.
| | - Steven Williams
- Division of Imaging Sciences & Biomedical Engineering, King's College London, London SE17EH, United Kingdom
| | - Rashed Karim
- Division of Imaging Sciences & Biomedical Engineering, King's College London, London SE17EH, United Kingdom
| | - Gernot Plank
- Department of Biophysics, Medical University of Graz, Neue Stiftingtalstraße 6/IV, 8010 Graz, Austria
| | - Mark O'Neill
- Division of Imaging Sciences & Biomedical Engineering, King's College London, London SE17EH, United Kingdom
| | - Steven Niederer
- Division of Imaging Sciences & Biomedical Engineering, King's College London, London SE17EH, United Kingdom
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32
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Aronis KN, Berger RD, Calkins H, Chrispin J, Marine JE, Spragg DD, Tao S, Tandri H, Ashikaga H. Is human atrial fibrillation stochastic or deterministic?-Insights from missing ordinal patterns and causal entropy-complexity plane analysis. CHAOS (WOODBURY, N.Y.) 2018; 28:063130. [PMID: 29960392 PMCID: PMC6026026 DOI: 10.1063/1.5023588] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/25/2018] [Accepted: 06/11/2018] [Indexed: 06/08/2023]
Abstract
The mechanism of atrial fibrillation (AF) maintenance in humans is yet to be determined. It remains controversial whether cardiac fibrillatory dynamics are the result of a deterministic or a stochastic process. Traditional methods to differentiate deterministic from stochastic processes have several limitations and are not reliably applied to short and noisy data obtained during clinical studies. The appearance of missing ordinal patterns (MOPs) using the Bandt-Pompe (BP) symbolization is indicative of deterministic dynamics and is robust to brief time series and experimental noise. Our aim was to evaluate whether human AF dynamics is the result of a stochastic or a deterministic process. We used 38 intracardiac atrial electrograms during AF from the coronary sinus of 10 patients undergoing catheter ablation of AF. We extracted the intervals between consecutive atrial depolarizations (AA interval) and converted the AA interval time series to their BP symbolic representation (embedding dimension 5, time delay 1). We generated 40 iterative amplitude-adjusted, Fourier-transform (IAAFT) surrogate data for each of the AA time series. IAAFT surrogates have the same frequency spectrum, autocorrelation, and probability distribution with the original time series. Using the BP symbolization, we compared the number of MOPs and the rate of MOP decay in the first 1000 timepoints of the original time series with that of the surrogate data. We calculated permutation entropy and permutation statistical complexity and represented each time series on the causal entropy-complexity plane. We demonstrated that (a) the number of MOPs in human AF is significantly higher compared to the surrogate data (2.7 ± 1.18 vs. 0.39 ± 0.28, p < 0.001); (b) the median rate of MOP decay in human AF was significantly lower compared with the surrogate data (6.58 × 10-3 vs. 7.79 × 10-3, p < 0.001); and (c) 81.6% of the individual recordings had a rate of decay lower than the 95% confidence intervals of their corresponding surrogates. On the causal entropy-complexity plane, human AF lay on the deterministic part of the plane that was located above the trajectory of fractional Brownian motion with different Hurst exponents on the plane. This analysis demonstrates that human AF dynamics does not arise from a rescaled linear stochastic process or a fractional noise, but either a deterministic or a nonlinear stochastic process. Our results justify the development and application of mathematical analysis and modeling tools to enable predictive control of human AF.
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Affiliation(s)
- Konstantinos N. Aronis
- Cardiac Arrhythmia Service, Johns Hopkins University School of Medicine, Baltimore, Maryland 21287, USA
| | - Ronald D. Berger
- Cardiac Arrhythmia Service, Johns Hopkins University School of Medicine, Baltimore, Maryland 21287, USA
| | - Hugh Calkins
- Cardiac Arrhythmia Service, Johns Hopkins University School of Medicine, Baltimore, Maryland 21287, USA
| | - Jonathan Chrispin
- Cardiac Arrhythmia Service, Johns Hopkins University School of Medicine, Baltimore, Maryland 21287, USA
| | - Joseph E. Marine
- Cardiac Arrhythmia Service, Johns Hopkins University School of Medicine, Baltimore, Maryland 21287, USA
| | - David D. Spragg
- Cardiac Arrhythmia Service, Johns Hopkins University School of Medicine, Baltimore, Maryland 21287, USA
| | - Susumu Tao
- Cardiac Arrhythmia Service, Johns Hopkins University School of Medicine, Baltimore, Maryland 21287, USA
| | - Harikrishna Tandri
- Cardiac Arrhythmia Service, Johns Hopkins University School of Medicine, Baltimore, Maryland 21287, USA
| | - Hiroshi Ashikaga
- Author to whom correspondence should be addressed: . Telephone: 410-955-7534. Fax: 443-873-5019
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33
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Lyon A, Mincholé A, Martínez JP, Laguna P, Rodriguez B. Computational techniques for ECG analysis and interpretation in light of their contribution to medical advances. J R Soc Interface 2018; 15:20170821. [PMID: 29321268 PMCID: PMC5805987 DOI: 10.1098/rsif.2017.0821] [Citation(s) in RCA: 74] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2017] [Accepted: 12/08/2017] [Indexed: 01/09/2023] Open
Abstract
Widely developed for clinical screening, electrocardiogram (ECG) recordings capture the cardiac electrical activity from the body surface. ECG analysis can therefore be a crucial first step to help diagnose, understand and predict cardiovascular disorders responsible for 30% of deaths worldwide. Computational techniques, and more specifically machine learning techniques and computational modelling are powerful tools for classification, clustering and simulation, and they have recently been applied to address the analysis of medical data, especially ECG data. This review describes the computational methods in use for ECG analysis, with a focus on machine learning and 3D computer simulations, as well as their accuracy, clinical implications and contributions to medical advances. The first section focuses on heartbeat classification and the techniques developed to extract and classify abnormal from regular beats. The second section focuses on patient diagnosis from whole recordings, applied to different diseases. The third section presents real-time diagnosis and applications to wearable devices. The fourth section highlights the recent field of personalized ECG computer simulations and their interpretation. Finally, the discussion section outlines the challenges of ECG analysis and provides a critical assessment of the methods presented. The computational methods reported in this review are a strong asset for medical discoveries and their translation to the clinical world may lead to promising advances.
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Affiliation(s)
- Aurore Lyon
- Department of Computer Science, British Heart Foundation, Oxford, UK
| | - Ana Mincholé
- Department of Computer Science, British Heart Foundation, Oxford, UK
| | - Juan Pablo Martínez
- Biomedical Signal Interpretation and Computational Simulation (BSICoS) Group, University of Zaragoza, CIBER-BBN, Zaragoza, Spain
| | - Pablo Laguna
- Biomedical Signal Interpretation and Computational Simulation (BSICoS) Group, University of Zaragoza, CIBER-BBN, Zaragoza, Spain
| | - Blanca Rodriguez
- Department of Computer Science, British Heart Foundation, Oxford, UK
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34
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Ni H, Whittaker DG, Wang W, Giles WR, Narayan SM, Zhang H. Synergistic Anti-arrhythmic Effects in Human Atria with Combined Use of Sodium Blockers and Acacetin. Front Physiol 2017; 8:946. [PMID: 29218016 PMCID: PMC5703742 DOI: 10.3389/fphys.2017.00946] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2017] [Accepted: 11/08/2017] [Indexed: 12/19/2022] Open
Abstract
Atrial fibrillation (AF) is the most common cardiac arrhythmia. Developing effective and safe anti-AF drugs remains an unmet challenge. Simultaneous block of both atrial-specific ultra-rapid delayed rectifier potassium (K+) current (IKur) and the Na+ current (INa) has been hypothesized to be anti-AF, without inducing significant QT prolongation and ventricular side effects. However, the antiarrhythmic advantage of simultaneously blocking these two channels vs. individual block in the setting of AF-induced electrical remodeling remains to be documented. Furthermore, many IKur blockers such as acacetin and AVE0118, partially inhibit other K+ currents in the atria. Whether this multi-K+-block produces greater anti-AF effects compared with selective IKur-block has not been fully understood. The aim of this study was to use computer models to (i) assess the impact of multi-K+-block as exhibited by many IKur blokers, and (ii) evaluate the antiarrhythmic effect of blocking IKur and INa, either alone or in combination, on atrial and ventricular electrical excitation and recovery in the setting of AF-induced electrical-remodeling. Contemporary mathematical models of human atrial and ventricular cells were modified to incorporate dose-dependent actions of acacetin (a multichannel blocker primarily inhibiting IKur while less potently blocking Ito, IKr, and IKs). Rate- and atrial-selective inhibition of INa was also incorporated into the models. These single myocyte models were then incorporated into multicellular two-dimensional (2D) and three-dimensional (3D) anatomical models of the human atria. As expected, application of IKur blocker produced pronounced action potential duration (APD) prolongation in atrial myocytes. Furthermore, combined multiple K+-channel block that mimicked the effects of acacetin exhibited synergistic APD prolongations. Synergistically anti-AF effects following inhibition of INa and combined IKur/K+-channels were also observed. The attainable maximal AF-selectivity of INa inhibition was greatly augmented by blocking IKur or multiple K+-currents in the atrial myocytes. This enhanced anti-arrhythmic effects of combined block of Na+- and K+-channels were also seen in 2D and 3D simulations; specially, there was an enhanced efficacy in terminating re-entrant excitation waves, exerting improved antiarrhythmic effects in the human atria as compared to a single-channel block. However, in the human ventricular myocytes and tissue, cellular repolarization and computed QT intervals were modestly affected in the presence of actions of acacetin and INa blockers (either alone or in combination). In conclusion, this study demonstrates synergistic antiarrhythmic benefits of combined block of IKur and INa, as well as those of INa and combined multi K+-current block of acacetin, without significant alterations of ventricular repolarization and QT intervals. This approach may be a valuable strategy for the treatment of AF.
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Affiliation(s)
- Haibo Ni
- Biological Physics Group, University of Manchester, Manchester, United Kingdom.,Space Institute of Southern China, Shenzhen, China.,Key Laboratory of Medical Electrophysiology, Ministry of Education, Collaborative Innovation Center for Prevention and Treatment of Cardiovascular Disease/Institute of Cardiovascular Research, Southwest Medical University, Luzhou, China
| | - Dominic G Whittaker
- Biological Physics Group, University of Manchester, Manchester, United Kingdom
| | - Wei Wang
- Biological Physics Group, University of Manchester, Manchester, United Kingdom
| | - Wayne R Giles
- Faculties of Kinesiology and Medicine, University of Calgary, Calgary, AB, Canada
| | - Sanjiv M Narayan
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, United States
| | - Henggui Zhang
- Biological Physics Group, University of Manchester, Manchester, United Kingdom.,Space Institute of Southern China, Shenzhen, China.,Key Laboratory of Medical Electrophysiology, Ministry of Education, Collaborative Innovation Center for Prevention and Treatment of Cardiovascular Disease/Institute of Cardiovascular Research, Southwest Medical University, Luzhou, China.,School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China
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35
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Campana C, Akar FG. Commentary: Atrial Fibrillation Dynamics and Ionic Block Effects in Six Heterogeneous Human 3D Virtual Atria with Distinct Repolarization Dynamics. Front Bioeng Biotechnol 2017; 5:59. [PMID: 29057224 PMCID: PMC5635327 DOI: 10.3389/fbioe.2017.00059] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2017] [Accepted: 09/20/2017] [Indexed: 11/26/2022] Open
Affiliation(s)
- Chiara Campana
- Icahn School of Medicine at Mount Sinai, The Cardiovascular Institute, New York, NY, United States
| | - Fadi G Akar
- Icahn School of Medicine at Mount Sinai, The Cardiovascular Institute, New York, NY, United States
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36
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In-silico investigations of the functional impact of KCNA5 mutations on atrial mechanical dynamics. J Mol Cell Cardiol 2017; 111:86-95. [DOI: 10.1016/j.yjmcc.2017.08.005] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/07/2017] [Revised: 07/19/2017] [Accepted: 08/04/2017] [Indexed: 12/20/2022]
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37
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Stephenson RS, Atkinson A, Kottas P, Perde F, Jafarzadeh F, Bateman M, Iaizzo PA, Zhao J, Zhang H, Anderson RH, Jarvis JC, Dobrzynski H. High resolution 3-Dimensional imaging of the human cardiac conduction system from microanatomy to mathematical modeling. Sci Rep 2017; 7:7188. [PMID: 28775383 PMCID: PMC5543124 DOI: 10.1038/s41598-017-07694-8] [Citation(s) in RCA: 67] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2017] [Accepted: 07/03/2017] [Indexed: 12/23/2022] Open
Abstract
Cardiac arrhythmias and conduction disturbances are accompanied by structural remodelling of the specialised cardiomyocytes known collectively as the cardiac conduction system. Here, using contrast enhanced micro-computed tomography, we present, in attitudinally appropriate fashion, the first 3-dimensional representations of the cardiac conduction system within the intact human heart. We show that cardiomyocyte orientation can be extracted from these datasets at spatial resolutions approaching the single cell. These data show that commonly accepted anatomical representations are oversimplified. We have incorporated the high-resolution anatomical data into mathematical simulations of cardiac electrical depolarisation. The data presented should have multidisciplinary impact. Since the rate of depolarisation is dictated by cardiac microstructure, and the precise orientation of the cardiomyocytes, our data should improve the fidelity of mathematical models. By showing the precise 3-dimensional relationships between the cardiac conduction system and surrounding structures, we provide new insights relevant to valvar replacement surgery and ablation therapies. We also offer a practical method for investigation of remodelling in disease, and thus, virtual pathology and archiving. Such data presented as 3D images or 3D printed models, will inform discussions between medical teams and their patients, and aid the education of medical and surgical trainees.
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Affiliation(s)
- Robert S Stephenson
- Comparative Medicine Lab, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
- School of Sport and Exercise Sciences, Liverpool John Moores University, Liverpool, UK
| | - Andrew Atkinson
- Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | - Petros Kottas
- School of Physics and Astronomy, University of Manchester, Manchester, UK
| | - Filip Perde
- National Institute of Legal Medicine, Bucharest, Romania
| | - Fatemeh Jafarzadeh
- Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | - Mike Bateman
- The Visible Heart Laboratory, University of Minnesota, Minneapolis, USA
| | - Paul A Iaizzo
- The Visible Heart Laboratory, University of Minnesota, Minneapolis, USA
| | - Jichao Zhao
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
| | - Henggui Zhang
- School of Physics and Astronomy, University of Manchester, Manchester, UK
| | - Robert H Anderson
- Institute of Genetic Medicine, University of Newcastle, Newcastle, UK
| | - Jonathan C Jarvis
- School of Sport and Exercise Sciences, Liverpool John Moores University, Liverpool, UK.
| | - Halina Dobrzynski
- Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK.
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38
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Soor N, Morgan R, Varela M, Aslanidi OV. Towards patient-specific modelling of lesion formation during radiofrequency catheter ablation for atrial fibrillation. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2017; 2016:489-492. [PMID: 28261003 DOI: 10.1109/embc.2016.7590746] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
Radiofrequency catheter ablation procedures are a first-line method of clinical treatment for atrial fibrillation. However, they suffer from suboptimal success rates and are also prone to potentially serious adverse effects. These limitations can be at least partially attributed to the inter- and intra- patient variations in atrial wall thickness, and could be mitigated by patient-specific approaches to the procedure. In this study, a modelling approach to optimising ablation procedures in subject-specific 3D atrial geometries was applied. The approach enabled the evaluation of optimal ablation times to create lesions for a given wall thickness measured from MRI. A nonliner relationship was revealed between the thickness and catheter contact time required for fully transmural lesions. Hence, our approach based on MRI reconstruction of the atrial wall combined with subject-specific modelling of ablation can provide useful information for improving clinical procedures.
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Affiliation(s)
- Navjeevan Soor
- Department of Biomedical Engineering, King's College London, St Thomas' Hospital, London, United Kingdom ( ; ; ; ; phone: +44 (0) 20 7188 7188)
| | - Ross Morgan
- Department of Biomedical Engineering, King's College London, St Thomas' Hospital, London, United Kingdom ( ; ; ; ; phone: +44 (0) 20 7188 7188)
| | - Marta Varela
- Department of Biomedical Engineering, King's College London, St Thomas' Hospital, London, United Kingdom ( ; ; ; ; phone: +44 (0) 20 7188 7188)
| | - Oleg V Aslanidi
- Department of Biomedical Engineering, King's College London, St Thomas' Hospital, London, United Kingdom ( ; ; ; ; phone: +44 (0) 20 7188 7188)
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39
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Ferrer-Albero A, Godoy EJ, Lozano M, Martínez-Mateu L, Atienza F, Saiz J, Sebastian R. Non-invasive localization of atrial ectopic beats by using simulated body surface P-wave integral maps. PLoS One 2017; 12:e0181263. [PMID: 28704537 PMCID: PMC5509320 DOI: 10.1371/journal.pone.0181263] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2017] [Accepted: 06/28/2017] [Indexed: 01/22/2023] Open
Abstract
Non-invasive localization of continuous atrial ectopic beats remains a cornerstone for the treatment of atrial arrhythmias. The lack of accurate tools to guide electrophysiologists leads to an increase in the recurrence rate of ablation procedures. Existing approaches are based on the analysis of the P-waves main characteristics and the forward body surface potential maps (BSPMs) or on the inverse estimation of the electric activity of the heart from those BSPMs. These methods have not provided an efficient and systematic tool to localize ectopic triggers. In this work, we propose the use of machine learning techniques to spatially cluster and classify ectopic atrial foci into clearly differentiated atrial regions by using the body surface P-wave integral map (BSPiM) as a biomarker. Our simulated results show that ectopic foci with similar BSPiM naturally cluster into differentiated non-intersected atrial regions and that new patterns could be correctly classified with an accuracy of 97% when considering 2 clusters and 96% for 4 clusters. Our results also suggest that an increase in the number of clusters is feasible at the cost of decreasing accuracy.
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Affiliation(s)
- Ana Ferrer-Albero
- Centro de Investigación e Innovación en Bioingeniería (Ci2B), Universitat Politècnica de València, Valencia, Spain
- * E-mail:
| | - Eduardo J. Godoy
- Computational Multiscale Physiology Lab (CoMMLab), Department of Computer Science, Universitat de Valencia, Valencia, Spain
| | - Miguel Lozano
- Computational Multiscale Physiology Lab (CoMMLab), Department of Computer Science, Universitat de Valencia, Valencia, Spain
| | - Laura Martínez-Mateu
- Centro de Investigación e Innovación en Bioingeniería (Ci2B), Universitat Politècnica de València, Valencia, Spain
| | | | - Javier Saiz
- Centro de Investigación e Innovación en Bioingeniería (Ci2B), Universitat Politècnica de València, Valencia, Spain
| | - Rafael Sebastian
- Computational Multiscale Physiology Lab (CoMMLab), Department of Computer Science, Universitat de Valencia, Valencia, Spain
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40
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Colman MA, Ni H, Liang B, Schmitt N, Zhang H. In silico assessment of genetic variation in KCNA5 reveals multiple mechanisms of human atrial arrhythmogenesis. PLoS Comput Biol 2017. [PMID: 28622331 PMCID: PMC5493429 DOI: 10.1371/journal.pcbi.1005587] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022] Open
Abstract
A recent experimental study investigating patients with lone atrial fibrillation identified six novel mutations in the KCNA5 gene. The mutants exhibited both gain- and loss-of-function of the atrial specific ultra-rapid delayed rectifier K+ current, IKur. The aim of this study is to elucidate and quantify the functional impact of these KCNA5 mutations on atrial electrical activity. A multi-scale model of the human atria was updated to incorporate detailed experimental data on IKur from both wild-type and mutants. The effects of the mutations on human atrial action potential and rate dependence were investigated at the cellular level. In tissue, we assessed the effects of the mutations on the vulnerability to unidirectional conduction patterns and dynamics of re-entrant excitation waves. Gain-of-function mutations shortened the action potential duration in single cells, and stabilised and accelerated re-entrant excitation in tissue. Loss-of-function mutations had heterogeneous effects on action potential duration and promoted early-after-depolarisations following beta-adrenergic stimulation. In the tissue model, loss-of-function mutations facilitated breakdown of excitation waves at more physiological excitation rates than the wild-type, and the generation of early-after-depolarisations promoted unidirectional patterns of excitation. Gain- and loss-of-function IKur mutations produced multiple mechanisms of atrial arrhythmogenesis, with significant differences between the two groups of mutations. This study provides new insights into understanding the mechanisms by which mutant IKur contributes to atrial arrhythmias. In addition, as IKur is an atrial-specific channel and a number of IKur-selective blockers have been developed as anti-AF agents, this study also helps to understand some contradictory results on both pro- and anti-arrhythmic effects of blocking IKur. In a recent study, six mutations resulting in either gain-of-function or loss-of-function in the ultra-rapid delayed rectifier potassium current IKur, were identified to be associated with atrial fibrillation (AF). However, the causative link between the mutant IKur (either gain- or loss-of-function) and AF genesis, especially the difference and similarity between the two mutant groups, has not been elucidated. In our study, we used multiscale computational models to investigate the mechanism of arrhythmogenesis mediated by the two groups of mutations. The results suggest that the gain-of-function mutations shortened atrial action potential duration, stabilised and accelerated re-entrant excitation waves in tissue; the loss-of-function mutation promoted early-after-depolarisations following beta-adrenergic stimulation and thus wave breaks in tissue. We show these two groups of mutants carrying IKur produced multiple mechanisms of atrial arrhythmogenesis, with significant differences between the two groups. Our study provides new insights into understanding the mechanisms by which mutant IKur contributes to atrial arrhythmias. In addition, as IKur is an atrial-specific channel and a number of IKur-selective blockers have been developed as anti-AF agents, this study also helps to understand some contradictory results on both pro- and anti-arrhythmic effects of blocking IKur.
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Affiliation(s)
- Michael A. Colman
- Biological Physics Group, School of Physics and Astronomy, University of Manchester, Manchester, United Kingdom
- School of Biomedical Sciences, Faculty of Biological Sciences, University of Leeds, Leeds, United Kingdom
| | - Haibo Ni
- Biological Physics Group, School of Physics and Astronomy, University of Manchester, Manchester, United Kingdom
| | - Bo Liang
- Department of Biomedical Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Nicole Schmitt
- Department of Biomedical Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Henggui Zhang
- Biological Physics Group, School of Physics and Astronomy, University of Manchester, Manchester, United Kingdom
- School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China
- * E-mail:
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41
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Atrial arrhythmogenicity of KCNJ2 mutations in short QT syndrome: Insights from virtual human atria. PLoS Comput Biol 2017; 13:e1005593. [PMID: 28609477 PMCID: PMC5487071 DOI: 10.1371/journal.pcbi.1005593] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2017] [Revised: 06/27/2017] [Accepted: 05/25/2017] [Indexed: 12/17/2022] Open
Abstract
Gain-of-function mutations in KCNJ2-encoded Kir2.1 channels underlie variant 3 (SQT3) of the short QT syndrome, which is associated with atrial fibrillation (AF). Using biophysically-detailed human atria computer models, this study investigated the mechanistic link between SQT3 mutations and atrial arrhythmogenesis, and potential ion channel targets for treatment of SQT3. A contemporary model of the human atrial action potential (AP) was modified to recapitulate functional changes in IK1 due to heterozygous and homozygous forms of the D172N and E299V Kir2.1 mutations. Wild-type (WT) and mutant formulations were incorporated into multi-scale homogeneous and heterogeneous tissue models. Effects of mutations on AP duration (APD), conduction velocity (CV), effective refractory period (ERP), tissue excitation threshold and their rate-dependence, as well as the wavelength of re-entry (WL) were quantified. The D172N and E299V Kir2.1 mutations produced distinct effects on IK1 and APD shortening. Both mutations decreased WL for re-entry through a reduction in ERP and CV. Stability of re-entrant excitation waves in 2D and 3D tissue models was mediated by changes to tissue excitability and dispersion of APD in mutation conditions. Combined block of IK1 and IKr was effective in terminating re-entry associated with heterozygous D172N conditions, whereas IKr block alone may be a safer alternative for the E299V mutation. Combined inhibition of IKr and IKur produced a synergistic anti-arrhythmic effect in both forms of SQT3. In conclusion, this study provides mechanistic insights into atrial proarrhythmia with SQT3 Kir2.1 mutations and highlights possible pharmacological strategies for management of SQT3-linked AF. Atrial fibrillation (AF) is the most common cardiac arrhythmia, and is characterised by complex and irregular electrical activation of the upper chambers of the heart. One rare, genetic condition associated with increased risk of AF is the short QT syndrome (SQTS), which is caused by mutations in genes involved in normal electrical function of the heart. Underlying mechanisms by which SQTS-related gene mutations facilitate development of arrhythmias in the human atria are not well understood. In this study, sophisticated computer models representing ‘virtual’ human atria, incorporating detailed electrophysiological data at the ‘ion channel’ protein level into both idealised and realistic multi-scale tissue geometries, were used to dissect mechanisms by which two mutations in the KCNJ2 gene responsible for SQTS variant 3 (SQT3) promote initiation and sustenance of arrhythmias. It was found that the D172N and E299V mutations to KCNJ2 accelerated the repolarisation process at the cellular level through distinct mechanisms. This, along with the way the mutations affected heterogeneity in electrical behaviour at the organ level, mediated stability of arrhythmias and response to simulated ion channel block. This study improves understanding of mechanisms underlying increased AF risk associated with D172N and E299V KCNJ2 mutations, and outlines potential therapeutic strategies.
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42
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Brocklehurst P, Ni H, Zhang H, Ye J. Electro-mechanical dynamics of spiral waves in a discrete 2D model of human atrial tissue. PLoS One 2017; 12:e0176607. [PMID: 28510575 PMCID: PMC5433700 DOI: 10.1371/journal.pone.0176607] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2016] [Accepted: 04/13/2017] [Indexed: 11/19/2022] Open
Abstract
We investigate the effect of mechano-electrical feedback and atrial fibrillation induced electrical remodelling (AFER) of cellular ion channel properties on the dynamics of spiral waves in a discrete 2D model of human atrial tissue. The tissue electro-mechanics are modelled using the discrete element method (DEM). Millions of bonded DEM particles form a network of coupled atrial cells representing 2D cardiac tissue, allowing simulations of the dynamic behaviour of electrical excitation waves and mechanical contraction in the tissue. In the tissue model, each cell is modelled by nine particles, accounting for the features of individual cellular geometry; and discrete inter-cellular spatial arrangement of cells is also considered. The electro-mechanical model of a human atrial single-cell was constructed by strongly coupling the electrophysiological model of Colman et al. to the mechanical myofilament model of Rice et al., with parameters modified based on experimental data. A stretch-activated channel was incorporated into the model to simulate the mechano-electrical feedback. In order to investigate the effect of mechano-electrical feedback on the dynamics of spiral waves, simulations of spiral waves were conducted in both the electromechanical model and the electrical-only model in normal and AFER conditions, to allow direct comparison of the results between the models. Dynamics of spiral waves were characterized by tracing their tip trajectories, stability, excitation frequencies and meandering range of tip trajectories. It was shown that the developed DEM method provides a stable and efficient model of human atrial tissue with considerations of the intrinsically discrete and anisotropic properties of the atrial tissue, which are challenges to handle in traditional continuum mechanics models. This study provides mechanistic insights into the complex behaviours of spiral waves and the genesis of atrial fibrillation by showing an important role of the mechano-electrical feedback in facilitating and promoting atrial fibrillation.
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Affiliation(s)
- Paul Brocklehurst
- Engineering Department, Lancaster University, Lancaster, United Kingdom
| | - Haibo Ni
- Biological Physics Group, School of Physics and Astronomy, University of Manchester, Manchester, United Kingdom
| | - Henggui Zhang
- Biological Physics Group, School of Physics and Astronomy, University of Manchester, Manchester, United Kingdom
- * E-mail: (HZ); (JY)
| | - Jianqiao Ye
- Engineering Department, Lancaster University, Lancaster, United Kingdom
- * E-mail: (HZ); (JY)
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43
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Alday EAP, Colman MA, Langley P, Zhang H. Novel non-invasive algorithm to identify the origins of re-entry and ectopic foci in the atria from 64-lead ECGs: A computational study. PLoS Comput Biol 2017; 13:e1005270. [PMID: 28253254 PMCID: PMC5333795 DOI: 10.1371/journal.pcbi.1005270] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2015] [Accepted: 11/28/2016] [Indexed: 02/02/2023] Open
Abstract
Atrial tachy-arrhytmias, such as atrial fibrillation (AF), are characterised by irregular electrical activity in the atria, generally associated with erratic excitation underlain by re-entrant scroll waves, fibrillatory conduction of multiple wavelets or rapid focal activity. Epidemiological studies have shown an increase in AF prevalence in the developed world associated with an ageing society, highlighting the need for effective treatment options. Catheter ablation therapy, commonly used in the treatment of AF, requires spatial information on atrial electrical excitation. The standard 12-lead electrocardiogram (ECG) provides a method for non-invasive identification of the presence of arrhythmia, due to irregularity in the ECG signal associated with atrial activation compared to sinus rhythm, but has limitations in providing specific spatial information. There is therefore a pressing need to develop novel methods to identify and locate the origin of arrhythmic excitation. Invasive methods provide direct information on atrial activity, but may induce clinical complications. Non-invasive methods avoid such complications, but their development presents a greater challenge due to the non-direct nature of monitoring. Algorithms based on the ECG signals in multiple leads (e.g. a 64-lead vest) may provide a viable approach. In this study, we used a biophysically detailed model of the human atria and torso to investigate the correlation between the morphology of the ECG signals from a 64-lead vest and the location of the origin of rapid atrial excitation arising from rapid focal activity and/or re-entrant scroll waves. A focus-location algorithm was then constructed from this correlation. The algorithm had success rates of 93% and 76% for correctly identifying the origin of focal and re-entrant excitation with a spatial resolution of 40 mm, respectively. The general approach allows its application to any multi-lead ECG system. This represents a significant extension to our previously developed algorithms to predict the AF origins in association with focal activities. Atrial tachy-arrhythmias are associated with irregular excitation waves arising from re-entrant excitation, multiple wavelets or rapid focal activity. Identifying the origin of the irregular activity may be vital for diagnosis and treatment of the disorder. Where invasive and non-invasive methods provide approaches for such identification, both have associated disadvantages. In this study, we used a biophysically detailed model of the human atria and torso to develop an algorithm based on the correlation between the electrocardiogram (ECG) signal from a 64-lead vest and the location of rapid focal and re-entrant excitation. Using the properties of the atrial activation and the ECG signals, we developed a focus-location algorithm which is able to distinguish rapid focal activity from re-entrant scroll waves centred in the same location. Based on simulated data, the algorithm had success rates of 93% and 76% for correctly identifying the origin of focal and re-entrant excitation, respectively, and 88% for distinguish focal and re-entrant excitation, with no false positives. Inherited from our previous algorithm, it is also easily generalizable to any multi-lead ECG system.
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Affiliation(s)
- Erick A. Perez Alday
- Biological Physics Group, Department of Physics and Astronomy, University of Manchester, Manchester, United Kingdom
| | - Michael A. Colman
- Theoretical Physics Division, Department of Physics and Astronomy, University of Manchester, Manchester, United Kingdom
- School of Biomedical Sciences, Faculty of Biological Sciences, University of Leeds, United Kingdom
| | - Philip Langley
- School of Engineering, University of Hull, Hull, United Kingdom
| | - Henggui Zhang
- Biological Physics Group, Department of Physics and Astronomy, University of Manchester, Manchester, United Kingdom
- * E-mail:
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44
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Varela M, Bisbal F, Zacur E, Berruezo A, Aslanidi OV, Mont L, Lamata P. Novel Computational Analysis of Left Atrial Anatomy Improves Prediction of Atrial Fibrillation Recurrence after Ablation. Front Physiol 2017; 8:68. [PMID: 28261103 PMCID: PMC5306209 DOI: 10.3389/fphys.2017.00068] [Citation(s) in RCA: 39] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2016] [Accepted: 01/25/2017] [Indexed: 11/16/2022] Open
Abstract
The left atrium (LA) can change in size and shape due to atrial fibrillation (AF)-induced remodeling. These alterations can be linked to poorer outcomes of AF ablation. In this study, we propose a novel comprehensive computational analysis of LA anatomy to identify what features of LA shape can optimally predict post-ablation AF recurrence. To this end, we construct smooth 3D geometrical models from the segmentation of the LA blood pool captured in pre-procedural MR images. We first apply this methodology to characterize the LA anatomy of 144 AF patients and build a statistical shape model that includes the most salient variations in shape across this cohort. We then perform a discriminant analysis to optimally distinguish between recurrent and non-recurrent patients. From this analysis, we propose a new shape metric called vertical asymmetry, which measures the imbalance of size along the anterior to posterior direction between the superior and inferior left atrial hemispheres. Vertical asymmetry was found, in combination with LA sphericity, to be the best predictor of post-ablation recurrence at both 12 and 24 months (area under the ROC curve: 0.71 and 0.68, respectively) outperforming other shape markers and any of their combinations. We also found that model-derived shape metrics, such as the anterior-posterior radius, were better predictors than equivalent metrics taken directly from MRI or echocardiography, suggesting that the proposed approach leads to a reduction of the impact of data artifacts and noise. This novel methodology contributes to an improved characterization of LA organ remodeling and the reported findings have the potential to improve patient selection and risk stratification for catheter ablations in AF.
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Affiliation(s)
- Marta Varela
- Department of Biomedical Engineering, Division of Imaging Sciences and Biomedical Engineering, King's College London London, UK
| | - Felipe Bisbal
- Arrhythmia Unit-Heart Institute (iCor), Hospital Universitari Germans Trias i Pujol Badalona, Spain
| | - Ernesto Zacur
- Department of Biomedical Engineering, Division of Imaging Sciences and Biomedical Engineering, King's College LondonLondon, UK; Department of Engineering Science, University of OxfordOxford, UK
| | - Antonio Berruezo
- Unitat de Fibrillació Auricular, Hospital Clínic, Universitat de Barcelona Barcelona, Spain
| | - Oleg V Aslanidi
- Department of Biomedical Engineering, Division of Imaging Sciences and Biomedical Engineering, King's College London London, UK
| | - Lluis Mont
- Unitat de Fibrillació Auricular, Hospital Clínic, Universitat de Barcelona Barcelona, Spain
| | - Pablo Lamata
- Department of Biomedical Engineering, Division of Imaging Sciences and Biomedical Engineering, King's College London London, UK
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45
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Varela M, Colman MA, Hancox JC, Aslanidi OV. Atrial Heterogeneity Generates Re-entrant Substrate during Atrial Fibrillation and Anti-arrhythmic Drug Action: Mechanistic Insights from Canine Atrial Models. PLoS Comput Biol 2016; 12:e1005245. [PMID: 27984585 PMCID: PMC5161306 DOI: 10.1371/journal.pcbi.1005245] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2016] [Accepted: 11/12/2016] [Indexed: 12/31/2022] Open
Abstract
Anti-arrhythmic drug therapy is a frontline treatment for atrial fibrillation (AF), but its success rates are highly variable. This is due to incomplete understanding of the mechanisms of action of specific drugs on the atrial substrate at different stages of AF progression. We aimed to elucidate the role of cellular, tissue and organ level atrial heterogeneities in the generation of a re-entrant substrate during AF progression, and their modulation by the acute action of selected anti-arrhythmic drugs. To explore the complex cell-to-organ mechanisms, a detailed biophysical models of the entire 3D canine atria was developed. The model incorporated atrial geometry and fibre orientation from high-resolution micro-computed tomography, region-specific atrial cell electrophysiology and the effects of progressive AF-induced remodelling. The actions of multi-channel class III anti-arrhythmic agents vernakalant and amiodarone were introduced in the model by inhibiting appropriate ionic channel currents according to experimentally reported concentration-response relationships. AF was initiated by applied ectopic pacing in the pulmonary veins, which led to the generation of localized sustained re-entrant waves (rotors), followed by progressive wave breakdown and rotor multiplication in both atria. The simulated AF scenarios were in agreement with observations in canine models and patients. The 3D atrial simulations revealed that a re-entrant substrate was typically provided by tissue regions of high heterogeneity of action potential duration (APD). Amiodarone increased atrial APD and reduced APD heterogeneity and was more effective in terminating AF than vernakalant, which increased both APD and APD dispersion. In summary, the initiation and sustenance of rotors in AF is linked to atrial APD heterogeneity and APD reduction due to progressive remodelling. Our results suggest that anti-arrhythmic strategies that increase atrial APD without increasing its dispersion are effective in terminating AF. The mechanisms behind the most common arrhythmia, atrial fibrillation (AF), remain unclear and anti-arrhythmic drug therapy is often ineffective. In this paper, we develop and apply a novel comprehensive 3D model of canine atria to investigate the role of atrial heterogeneity in the mechanisms of AF and anti-arrhythmic drug action. We find that regions of high heterogeneity of action potential duration (APD) throughout the atria typically provide substrate for arrhythmogenic re-entrant waves during both AF initiation and progression. These mechanistic insights are directly linked with the efficacy of two clinically used class III anti-arrhythmic drugs: amiodarone is more effective at terminating AF than vernakalant, because it leads to an increase in atrial APD without increasing its dispersion. Our computational results are consistent with clinical observations and can help explain the superior efficacy of amiodarone in the clinical treatment of AF at late stages. This framework can easily be extended to investigate the action of other anti-arrhythmic drugs and translated to the human atria. By incorporating patient-specific anatomical and electrophysiological information, and after undergoing careful validation, the proposed in silico approach can become a useful tool to evaluate and potentially guide anti-arrhythmic therapy in the clinic.
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Affiliation(s)
- Marta Varela
- Department of Biomedical Engineering, Division of Imaging Sciences and Biomedical Engineering, King’s College London, London, United Kingdom
| | - Michael A. Colman
- School of Biomedical Sciences, Faculty of Biological Sciences, University of Leeds, Leeds, United Kingdom
| | - Jules C. Hancox
- School of Physiology, Pharmacology and Neuroscience, Biomedical Sciences Building, University of Bristol, Bristol, United Kingdom
| | - Oleg V. Aslanidi
- Department of Biomedical Engineering, Division of Imaging Sciences and Biomedical Engineering, King’s College London, London, United Kingdom
- * E-mail:
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46
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Yang F, Zhang L, Lu W, Liu L, Zhang Y, Zuo W, Wang K, Zhang H. Depth Attenuation Degree Based Visualization for Cardiac Ischemic Electrophysiological Feature Exploration. BIOMED RESEARCH INTERNATIONAL 2016; 2016:2979081. [PMID: 28004002 PMCID: PMC5150122 DOI: 10.1155/2016/2979081] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/03/2016] [Revised: 09/21/2016] [Accepted: 10/11/2016] [Indexed: 01/23/2023]
Abstract
Although heart researches and acquirement of clinical and experimental data are progressively open to public use, cardiac biophysical functions are still not well understood. Due to the complex and fine structures of the heart, cardiac electrophysiological features of interest may be occluded when there is a necessity to demonstrate cardiac electrophysiological behaviors. To investigate cardiac abnormal electrophysiological features under the pathological condition, in this paper, we implement a human cardiac ischemic model and acquire the electrophysiological data of excitation propagation. A visualization framework is then proposed which integrates a novel depth weighted optic attenuation model into the pathological electrophysiological model. The hidden feature of interest in pathological tissue can be revealed from sophisticated overlapping biophysical information. Experiment results verify the effectiveness of the proposed method for intuitively exploring and inspecting cardiac electrophysiological activities, which is fundamental in analyzing and explaining biophysical mechanisms of cardiac functions for doctors and medical staff.
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Affiliation(s)
- Fei Yang
- School of Mechanical, Electrical & Information Engineering, Shandong University, Weihai 264200, China
| | - Lei Zhang
- School of Art and Design, Harbin University, Harbin 150086, China
| | - Weigang Lu
- Department of Educational Technology, Ocean University of China, Qingdao 266100, China
| | - Lei Liu
- Institute of Acoustics, Chinese Academy of Sciences, Beijing 100190, China
| | - Yue Zhang
- School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China
| | - Wangmeng Zuo
- School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China
| | - Kuanquan Wang
- School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China
| | - Henggui Zhang
- School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China
- School of Physics and Astronomy, University of Manchester, Manchester M139PL, UK
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47
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Morgan R, Colman MA, Chubb H, Seemann G, Aslanidi OV. Slow Conduction in the Border Zones of Patchy Fibrosis Stabilizes the Drivers for Atrial Fibrillation: Insights from Multi-Scale Human Atrial Modeling. Front Physiol 2016; 7:474. [PMID: 27826248 PMCID: PMC5079097 DOI: 10.3389/fphys.2016.00474] [Citation(s) in RCA: 55] [Impact Index Per Article: 6.9] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2016] [Accepted: 10/03/2016] [Indexed: 01/12/2023] Open
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.
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Affiliation(s)
- Ross Morgan
- Division of Imaging Sciences and Biomedical Engineering, Department of Biomedical Engineering, King's College LondonLondon, UK
| | | | - Henry Chubb
- Division of Imaging Sciences and Biomedical Engineering, Department of Biomedical Engineering, King's College LondonLondon, UK
| | - Gunnar Seemann
- Institute for Experimental Cardiovascular Medicine, University Heart Center - Bad Krozingen, Medical Center - University of FreiburgFreiburg, Germany
| | - Oleg V. Aslanidi
- Division of Imaging Sciences and Biomedical Engineering, Department of Biomedical Engineering, King's College LondonLondon, UK
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48
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Grandi E, Maleckar MM. Anti-arrhythmic strategies for atrial fibrillation: The role of computational modeling in discovery, development, and optimization. Pharmacol Ther 2016; 168:126-142. [PMID: 27612549 DOI: 10.1016/j.pharmthera.2016.09.012] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
Atrial fibrillation (AF), the most common cardiac arrhythmia, is associated with increased risk of cerebrovascular stroke, and with several other pathologies, including heart failure. Current therapies for AF are targeted at reducing risk of stroke (anticoagulation) and tachycardia-induced cardiomyopathy (rate or rhythm control). Rate control, typically achieved by atrioventricular nodal blocking drugs, is often insufficient to alleviate symptoms. Rhythm control approaches include antiarrhythmic drugs, electrical cardioversion, and ablation strategies. Here, we offer several examples of how computational modeling can provide a quantitative framework for integrating multiscale data to: (a) gain insight into multiscale mechanisms of AF; (b) identify and test pharmacological and electrical therapy and interventions; and (c) support clinical decisions. We review how modeling approaches have evolved and contributed to the research pipeline and preclinical development and discuss future directions and challenges in the field.
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Affiliation(s)
- Eleonora Grandi
- Department of Pharmacology, University of California Davis, Davis, USA.
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49
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Chang ETY, Lin YT, Galla T, Clayton RH, Eatock J. A Stochastic Individual-Based Model of the Progression of Atrial Fibrillation in Individuals and Populations. PLoS One 2016; 11:e0152349. [PMID: 27070920 PMCID: PMC4829251 DOI: 10.1371/journal.pone.0152349] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2015] [Accepted: 03/11/2016] [Indexed: 12/19/2022] Open
Abstract
Models that represent the mechanisms that initiate and sustain atrial fibrillation (AF) in the heart are computationally expensive to simulate and therefore only capture short time scales of a few heart beats. It is therefore difficult to embed biophysical mechanisms into both policy-level disease models, which consider populations of patients over multiple decades, and guidelines that recommend treatment strategies for patients. The aim of this study is to link these modelling paradigms using a stylised population-level model that both represents AF progression over a long time-scale and retains a description of biophysical mechanisms. We develop a non-Markovian binary switching model incorporating three different aspects of AF progression: genetic disposition, disease/age related remodelling, and AF-related remodelling. This approach allows us to simulate individual AF episodes as well as the natural progression of AF in patients over a period of decades. Model parameters are derived, where possible, from the literature, and the model development has highlighted a need for quantitative data that describe the progression of AF in population of patients. The model produces time series data of AF episodes over the lifetimes of simulated patients. These are analysed to quantitatively describe progression of AF in terms of several underlying parameters. Overall, the model has potential to link mechanisms of AF to progression, and to be used as a tool to study clinical markers of AF or as training data for AF classification algorithms.
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Affiliation(s)
- Eugene T. Y. Chang
- Insigneo Institute for in-silico Medicine and Department of Computer Science, The University of Sheffield, Sheffield S1 4DP, United Kingdom
| | - Yen Ting Lin
- School of Physics and Astronomy, The University of Manchester, Manchester M13 9PL, United Kingdom
| | - Tobias Galla
- School of Physics and Astronomy, The University of Manchester, Manchester M13 9PL, United Kingdom
| | - Richard H. Clayton
- Insigneo Institute for in-silico Medicine and Department of Computer Science, The University of Sheffield, Sheffield S1 4DP, United Kingdom
| | - Julie Eatock
- Department of Computer Science, Brunel University London, Uxbridge UB8 3PH, Middlesex, United Kingdom
- * E-mail:
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50
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Bayer JD, Roney CH, Pashaei A, Jaïs P, Vigmond EJ. Novel Radiofrequency Ablation Strategies for Terminating Atrial Fibrillation in the Left Atrium: A Simulation Study. Front Physiol 2016; 7:108. [PMID: 27148061 PMCID: PMC4828663 DOI: 10.3389/fphys.2016.00108] [Citation(s) in RCA: 46] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2015] [Accepted: 03/07/2016] [Indexed: 12/19/2022] Open
Abstract
Pulmonary vein isolation (PVI) with radiofrequency ablation (RFA) is the cornerstone of atrial fibrillation (AF) therapy, but few strategies exist for when it fails. To guide RFA, phase singularity (PS) mapping locates reentrant electrical waves (rotors) that perpetuate AF. The goal of this study was to test existing and develop new RFA strategies for terminating rotors identified with PS mapping. It is unsafe to test experimental RFA strategies in patients, so they were evaluated in silico using a bilayer computer model of the human atria with persistent AF (pAF) electrical (ionic) and structural (fibrosis) remodeling. pAF was initiated by rapidly pacing the right (RSPV) and left (LSPV) superior pulmonary veins during sinus rhythm, and rotor dynamics quantified by PS analysis. Three RFA strategies were studied: (i) PVI, roof, and mitral lines; (ii) circles, perforated circles, lines, and crosses 0.5-1.5 cm in diameter/length administered near rotor locations/pathways identified by PS mapping; and (iii) 4-8 lines streamlining the sequence of electrical activation during sinus rhythm. As in pAF patients, 2 ± 1 rotors with cycle length 185 ± 4 ms and short PS duration 452 ± 401 ms perpetuated simulated pAF. Spatially, PS density had weak to moderate positive correlations with fibrosis density (RSPV: r = 0.38, p = 0.35, LSPV: r = 0.77, p = 0.02). RFA PVI, mitral, and roof lines failed to terminate pAF, but RFA perforated circles and lines 1.5 cm in diameter/length terminated meandering rotors from RSPV pacing when placed at locations with high PS density. Similarly, RFA circles, perforated circles, and crosses 1.5 cm in diameter/length terminated stationary rotors from LSPV pacing. The most effective strategy for terminating pAF was to streamline the sequence of activation during sinus rhythm with >4 RFA lines. These results demonstrate that co-localizing 1.5 cm RFA lesions with locations of high PS density is a promising strategy for terminating pAF rotors. For patients immune to PVI, roof, mitral, and PS guided RFA strategies, streamlining patient-specific activation sequences during sinus rhythm is a robust but challenging alternative.
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Affiliation(s)
- Jason D Bayer
- Electrophysiology and Heart Modeling Institute (LIRYC), Bordeaux University FoundationPessac, France; Cardiothoracic Research Center of Bordeaux (Inserm U 1045), University of BordeauxBordeaux, France
| | - Caroline H Roney
- Electrophysiology and Heart Modeling Institute (LIRYC), Bordeaux University FoundationPessac, France; Institute of Mathematics of Bordeaux (IMB), University of BordeauxTalence, France
| | - Ali Pashaei
- Electrophysiology and Heart Modeling Institute (LIRYC), Bordeaux University FoundationPessac, France; Institute of Mathematics of Bordeaux (IMB), University of BordeauxTalence, France
| | - Pierre Jaïs
- Electrophysiology and Heart Modeling Institute (LIRYC), Bordeaux University FoundationPessac, France; Cardiothoracic Research Center of Bordeaux (Inserm U 1045), University of BordeauxBordeaux, France; Haut-Lévêque Cardiology Hospital, University Hospital Center (CHU) of BordeauxPessac, France
| | - Edward J Vigmond
- Electrophysiology and Heart Modeling Institute (LIRYC), Bordeaux University FoundationPessac, France; Institute of Mathematics of Bordeaux (IMB), University of BordeauxTalence, France
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