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Scacchi S, Pavarino LF, Mazzanti A, Trancuccio A, Priori SG, Colli Franzone P. Transmural APD heterogeneity determines ventricular arrhythmogenesis in LQT8 syndrome: Insights from Bidomain computational modeling. PLoS One 2024; 19:e0305248. [PMID: 38968219 PMCID: PMC11226139 DOI: 10.1371/journal.pone.0305248] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2024] [Accepted: 05/27/2024] [Indexed: 07/07/2024] Open
Abstract
Long QT Syndrome type 8 (LQT8) is a cardiac arrhythmic disorder associated with Timothy Syndrome, stemming from mutations in the CACNA1C gene, particularly the G406R mutation. While prior studies hint at CACNA1C mutations' role in ventricular arrhythmia genesis, the mechanisms, especially in G406R presence, are not fully understood. This computational study explores how the G406R mutation, causing increased transmural dispersion of repolarization, induces and sustains reentrant ventricular arrhythmias. Using three-dimensional numerical simulations on an idealized left-ventricular model, integrating the Bidomain equations with the ten Tusscher-Panfilov ionic model, we observe that G406R mutation with 11% and 50% heterozygosis significantly increases transmural dispersion of repolarization. During S1-S4 stimulation protocols, these gradients facilitate conduction blocks, triggering reentrant ventricular tachycardia. Sustained reentry pathways occur only with G406R mutation at 50% heterozygosis, while neglecting transmural heterogeneities of action potential duration prevents stable reentry, regardless of G406R mutation presence.
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Affiliation(s)
- Simone Scacchi
- Dipartimento di Matematica, Università degli Studi di Milano, Milano, Italy
| | - Luca F. Pavarino
- Dipartimento di Matematica, Università degli Studi di Pavia, Pavia, Italy
| | - Andrea Mazzanti
- Molecular Cardiology, Centro Nacional de Investigaciones Cardiovasculares (CNIC), Madrid, Spain
- Molecular Cardiology, IRCCS Istituti Clinici Scientifici Maugeri, Pavia, Italy
- Department of Molecular Medicine, University of Pavia, Pavia, Italy
| | - Alessandro Trancuccio
- Molecular Cardiology, Centro Nacional de Investigaciones Cardiovasculares (CNIC), Madrid, Spain
- Molecular Cardiology, IRCCS Istituti Clinici Scientifici Maugeri, Pavia, Italy
- Department of Molecular Medicine, University of Pavia, Pavia, Italy
| | - Silvia G. Priori
- Molecular Cardiology, Centro Nacional de Investigaciones Cardiovasculares (CNIC), Madrid, Spain
- Molecular Cardiology, IRCCS Istituti Clinici Scientifici Maugeri, Pavia, Italy
- Department of Molecular Medicine, University of Pavia, Pavia, Italy
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2
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Trayanova NA, Lyon A, Shade J, Heijman J. Computational modeling of cardiac electrophysiology and arrhythmogenesis: toward clinical translation. Physiol Rev 2024; 104:1265-1333. [PMID: 38153307 DOI: 10.1152/physrev.00017.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Revised: 12/19/2023] [Accepted: 12/21/2023] [Indexed: 12/29/2023] Open
Abstract
The complexity of cardiac electrophysiology, involving dynamic changes in numerous components across multiple spatial (from ion channel to organ) and temporal (from milliseconds to days) scales, makes an intuitive or empirical analysis of cardiac arrhythmogenesis challenging. Multiscale mechanistic computational models of cardiac electrophysiology provide precise control over individual parameters, and their reproducibility enables a thorough assessment of arrhythmia mechanisms. This review provides a comprehensive analysis of models of cardiac electrophysiology and arrhythmias, from the single cell to the organ level, and how they can be leveraged to better understand rhythm disorders in cardiac disease and to improve heart patient care. Key issues related to model development based on experimental data are discussed, and major families of human cardiomyocyte models and their applications are highlighted. An overview of organ-level computational modeling of cardiac electrophysiology and its clinical applications in personalized arrhythmia risk assessment and patient-specific therapy of atrial and ventricular arrhythmias is provided. The advancements presented here highlight how patient-specific computational models of the heart reconstructed from patient data have achieved success in predicting risk of sudden cardiac death and guiding optimal treatments of heart rhythm disorders. Finally, an outlook toward potential future advances, including the combination of mechanistic modeling and machine learning/artificial intelligence, is provided. As the field of cardiology is embarking on a journey toward precision medicine, personalized modeling of the heart is expected to become a key technology to guide pharmaceutical therapy, deployment of devices, and surgical interventions.
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Affiliation(s)
- Natalia A Trayanova
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, United States
- Alliance for Cardiovascular Diagnostic and Treatment Innovation, Johns Hopkins University, Baltimore, Maryland, United States
| | - Aurore Lyon
- Department of Biomedical Engineering, CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, The Netherlands
- Division of Heart and Lungs, Department of Medical Physiology, University Medical Centre Utrecht, Utrecht, The Netherlands
| | - Julie Shade
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, United States
- Alliance for Cardiovascular Diagnostic and Treatment Innovation, Johns Hopkins University, Baltimore, Maryland, United States
| | - Jordi Heijman
- Department of Cardiology, CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, The Netherlands
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3
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Gerach T, Loewe A. Differential effects of mechano-electric feedback mechanisms on whole-heart activation, repolarization, and tension. J Physiol 2024. [PMID: 38185911 DOI: 10.1113/jp285022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2023] [Accepted: 12/11/2023] [Indexed: 01/09/2024] Open
Abstract
The human heart is subject to highly variable amounts of strain during day-to-day activities and needs to adapt to a wide range of physiological demands. This adaptation is driven by an autoregulatory loop that includes both electrical and the mechanical components. In particular, mechanical forces are known to feed back into the cardiac electrophysiology system, which can result in pro- and anti-arrhythmic effects. Despite the widespread use of computational modelling and simulation for cardiac electrophysiology research, the majority of in silico experiments ignore this mechano-electric feedback entirely due to the high computational cost associated with solving cardiac mechanics. In this study, we therefore use an electromechanically coupled whole-heart model to investigate the differential and combined effects of electromechanical feedback mechanisms with a focus on their physiological relevance during sinus rhythm. In particular, we consider troponin-bound calcium, the effect of deformation on the tissue diffusion tensor, and stretch-activated channels. We found that activation of the myocardium was only significantly affected when including deformation into the diffusion term of the monodomain equation. Repolarization, on the other hand, was influenced by both troponin-bound calcium and stretch-activated channels and resulted in steeper repolarization gradients in the atria. The latter also caused afterdepolarizations in the atria. Due to its central role for tension development, calcium bound to troponin affected stroke volume and pressure. In conclusion, we found that mechano-electric feedback changes activation and repolarization patterns throughout the heart during sinus rhythm and lead to a markedly more heterogeneous electrophysiological substrate. KEY POINTS: The electrophysiological and mechanical function of the heart are tightly interrelated by excitation-contraction coupling (ECC) in the forward direction and mechano-electric feedback (MEF) in the reverse direction. While ECC is considered in many state-of-the-art computational models of cardiac electromechanics, less is known about the effect of different MEF mechanisms. Accounting for calcium bound to troponin increases stroke volume and delays repolarization. Geometry-mediated MEF leads to more heterogeneous activation and repolarization with steeper gradients. Both effects combine in an additive way. Non-selective stretch-activated channels as an additional MEF mechanism lead to heterogeneous diastolic transmembrane voltage, higher developed tension and delayed repolarization or afterdepolarizations in highly stretched parts of the atria. The differential and combined effects of these three MEF mechanisms during sinus rhythm activation in a human four-chamber heart model may have implications for arrhythmogenesis, both in terms of substrate (repolarization gradients) and triggers (ectopy).
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Affiliation(s)
- Tobias Gerach
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
| | - Axel Loewe
- Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
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4
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Unger LA, Azzolin L, Nothstein M, Sánchez J, Luik A, Seemann G, Yeshwant S, Oesterlein T, Dössel O, Schmitt C, Spector P, Loewe A. Cycle length statistics during human atrial fibrillation reveal refractory properties of the underlying substrate: a combined in silico and clinical test of concept study. Europace 2021; 23:i133-i142. [PMID: 33751084 DOI: 10.1093/europace/euaa404] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2020] [Accepted: 12/04/2020] [Indexed: 11/12/2022] Open
Abstract
AIMS The treatment of atrial fibrillation beyond pulmonary vein isolation has remained an unsolved challenge. Targeting regions identified by different substrate mapping approaches for ablation resulted in ambiguous outcomes. With the effective refractory period being a fundamental prerequisite for the maintenance of fibrillatory conduction, this study aims at estimating the effective refractory period with clinically available measurements. METHODS AND RESULTS A set of 240 simulations in a spherical model of the left atrium with varying model initialization, combination of cellular refractory properties, and size of a region of lowered effective refractory period was implemented to analyse the capabilities and limitations of cycle length mapping. The minimum observed cycle length and the 25% quantile were compared to the underlying effective refractory period. The density of phase singularities was used as a measure for the complexity of the excitation pattern. Finally, we employed the method in a clinical test of concept including five patients. Areas of lowered effective refractory period could be distinguished from their surroundings in simulated scenarios with successfully induced multi-wavelet re-entry. Larger areas and higher gradients in effective refractory period as well as complex activation patterns favour the method. The 25% quantile of cycle lengths in patients with persistent atrial fibrillation was found to range from 85 to 190 ms. CONCLUSION Cycle length mapping is capable of highlighting regions of pathologic refractory properties. In combination with complementary substrate mapping approaches, the method fosters confidence to enhance the treatment of atrial fibrillation beyond pulmonary vein isolation particularly in patients with complex activation patterns.
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Affiliation(s)
- Laura A Unger
- Department of Electrical Engineering and Information Technology, Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Kaiserstr. 12, 76131 Karlsruhe, Germany
| | - Luca Azzolin
- Department of Electrical Engineering and Information Technology, Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Kaiserstr. 12, 76131 Karlsruhe, Germany
| | - Mark Nothstein
- Department of Electrical Engineering and Information Technology, Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Kaiserstr. 12, 76131 Karlsruhe, Germany
| | - Jorge Sánchez
- Department of Electrical Engineering and Information Technology, Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Kaiserstr. 12, 76131 Karlsruhe, Germany
| | - Armin Luik
- Medizinische Klinik IV, Städtisches Klinikum Karlsruhe, Karlsruhe 76133, Germany
| | - Gunnar Seemann
- Institute for Experimental Cardiovascular Medicine, University Heart Center Freiburg Bad Krozingen, Medical Center, University of Freiburg, Freiburg 79110, Germany.,Faculty of Medicine, University of Freiburg, Freiburg 79110, Germany
| | - Srinath Yeshwant
- Division of Cardiovascular Medicine, College of Medicine, University of Vermont, Burlington, Colchester, VT 05446, USA
| | - Tobias Oesterlein
- Department of Electrical Engineering and Information Technology, Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Kaiserstr. 12, 76131 Karlsruhe, Germany
| | - Olaf Dössel
- Department of Electrical Engineering and Information Technology, Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Kaiserstr. 12, 76131 Karlsruhe, Germany
| | - Claus Schmitt
- Medizinische Klinik IV, Städtisches Klinikum Karlsruhe, Karlsruhe 76133, Germany
| | - Peter Spector
- Division of Cardiovascular Medicine, College of Medicine, University of Vermont, Burlington, Colchester, VT 05446, USA
| | - Axel Loewe
- Department of Electrical Engineering and Information Technology, Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Kaiserstr. 12, 76131 Karlsruhe, Germany
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5
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Zhang XD, Thai PN, Lieu DK, Chiamvimonvat N. Model Systems for Addressing Mechanism of Arrhythmogenesis in Cardiac Repair. Curr Cardiol Rep 2021; 23:72. [PMID: 34050853 PMCID: PMC8164614 DOI: 10.1007/s11886-021-01498-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 03/09/2021] [Indexed: 11/09/2022]
Abstract
PURPOSE OF REVIEW Cardiac cell-based therapy represents a promising approach for cardiac repair. However, one of the main challenges is cardiac arrhythmias associated with stem cell transplantation. The current review summarizes the recent progress in model systems for addressing mechanisms of arrhythmogenesis in cardiac repair. RECENT FINDINGS Animal models have been extensively developed for mechanistic studies of cardiac arrhythmogenesis. Advances in human induced pluripotent stem cells (hiPSCs), patient-specific disease models, tissue engineering, and gene editing have greatly enhanced our ability to probe the mechanistic bases of cardiac arrhythmias. Additionally, recent development in multiscale computational studies and machine learning provides yet another powerful tool to quantitatively decipher the mechanisms of cardiac arrhythmias. Advancing efforts towards the integrations of experimental and computational studies are critical to gain insights into novel mitigation strategies for cardiac arrhythmias in cell-based therapy.
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Affiliation(s)
- Xiao-Dong Zhang
- Division of Cardiovascular Medicine, Department of Internal Medicine, School of Medicine, University of California, Davis, Davis, CA 95616 USA
- Department of Veterans Affairs, Veterans Affairs Northern California Health Care System, Mather, CA 95655 USA
| | - Phung N. Thai
- Division of Cardiovascular Medicine, Department of Internal Medicine, School of Medicine, University of California, Davis, Davis, CA 95616 USA
- Department of Veterans Affairs, Veterans Affairs Northern California Health Care System, Mather, CA 95655 USA
| | - Deborah K. Lieu
- Division of Cardiovascular Medicine, Department of Internal Medicine, School of Medicine, University of California, Davis, Davis, CA 95616 USA
| | - Nipavan Chiamvimonvat
- Division of Cardiovascular Medicine, Department of Internal Medicine, School of Medicine, University of California, Davis, Davis, CA 95616 USA
- Department of Veterans Affairs, Veterans Affairs Northern California Health Care System, Mather, CA 95655 USA
- Department of Pharmacology, School of Medicine, University of California, Davis, Davis, CA 95616 USA
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6
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Eleutheroside B, a selective late sodium current inhibitor, suppresses atrial fibrillation induced by sea anemone toxin II in rabbit hearts. Acta Pharmacol Sin 2021; 42:209-217. [PMID: 32612277 DOI: 10.1038/s41401-020-0453-z] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2020] [Accepted: 06/01/2020] [Indexed: 11/09/2022] Open
Abstract
Eleutheroside B (EB) is the main active constituent derived from the Chinese herb Acanthopanax senticosus (AS) that has been reported to possess cardioprotective effects. In this study we investigated the effects of EB on cardiac electrophysiology and its suppression on atrial fibrillation (AF). Whole-cell recording was conducted in isolated rabbit atrial myocytes. The intracellular calcium ([Ca2+]i) concentration was measured using calcium indicator Fura-2/AM fluorescence. Monophasic action potential (MAP) and electrocardiogram (ECG) synchronous recordings were conducted in Langendorff-perfused rabbit hearts using ECG signal sampling and analysis system. We showed that EB dose-dependently inhibited late sodium current (INaL), transient sodium current (INaT), and sea anemone toxin II (ATX II)-increased INaL with IC50 values of 167, 1582, and 181 μM, respectively. On the other hand, EB (800 μM) did not affect L-type calcium current (ICaL), inward rectifier potassium channel current (IK), and action potential duration (APD). Furthermore, EB (300 μM) markedly decreased ATX II-prolonged the APD at 90% repolarization (APD90) and eliminated ATX II-induced early afterdepolarizations (EADs), delayed afterdepolarizations (DADs), and triggered activities (TAs). Moreover, EB (200 μM) significantly suppressed ATX II-induced Na+-dependent [Ca2+]i overload in atrial myocytes. In the Langendorff-perfused rabbit hearts, application of EB (200 μM) or TTX (2 μM) substantially decreased ATX II-induced incidences of atrial fibrillation (AF), ventricular fibrillation (VF), and heart death. These results suggest that augmented INaL alone is sufficient to induce AF, and EB exerts anti-AF actions mainly via blocking INaL, which put forward the basis of pharmacology for new clinical application of EB.
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7
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Zhou X, Qu Y, Passini E, Bueno-Orovio A, Liu Y, Vargas HM, Rodriguez B. Blinded In Silico Drug Trial Reveals the Minimum Set of Ion Channels for Torsades de Pointes Risk Assessment. Front Pharmacol 2020; 10:1643. [PMID: 32082155 PMCID: PMC7003137 DOI: 10.3389/fphar.2019.01643] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2019] [Accepted: 12/16/2019] [Indexed: 12/11/2022] Open
Abstract
Torsades de Pointes (TdP) is a type of ventricular arrhythmia which could be observed as an unwanted drug-induced cardiac side effect, and it is associated with repolarization abnormalities in single cells. The pharmacological evaluations of TdP risk in previous years mainly focused on the hERG channel due to its vital role in the repolarization of cardiomyocytes. However, only considering drug effects on hERG led to false positive predictions since the drug action on other ion channels can also have crucial regulatory effects on repolarization. To address the limitation of only evaluating hERG, the Comprehensive in Vitro Proarrhythmia Assay initiative has proposed to systematically integrate drug effects on multiple ion channels into in silico drug trial to improve TdP risk assessment. It is not clear how many ion channels are sufficient for reliable TdP risk predictions, and whether differences in IC50 and Hill coefficient values from independent sources can lead to divergent in silico prediction outcomes. The rationale of this work is to investigate the above two questions using a computationally efficient population of human ventricular cells optimized to favor repolarization abnormality. Our blinded results based on two independent data sources confirm that simulations with the optimized population of human ventricular cell models enable efficient in silico drug screening, and also provide direct observation and mechanistic analysis of repolarization abnormality. Our results show that 1) the minimum set of ion channels required for reliable TdP risk predictions are Nav1.5 (peak), Cav1.2, and hERG; 2) for drugs with multiple ion channel blockage effects, moderate IC50 variations combined with variable Hill coefficients can affect the accuracy of in silico predictions.
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Affiliation(s)
- Xin Zhou
- Department of Computer Science, British Heart Foundation Centre of Research Excellence, University of Oxford, Oxford, United Kingdom
| | - Yusheng Qu
- SPARC, Amgen Research, Amgen Inc., Thousand Oaks, CA, United States
| | - Elisa Passini
- Department of Computer Science, British Heart Foundation Centre of Research Excellence, University of Oxford, Oxford, United Kingdom
| | - Alfonso Bueno-Orovio
- Department of Computer Science, British Heart Foundation Centre of Research Excellence, University of Oxford, Oxford, United Kingdom
| | - Yang Liu
- GAU, Amgen Research, Amgen Inc., South San Francisco, CA, United States
| | - Hugo M Vargas
- SPARC, Amgen Research, Amgen Inc., Thousand Oaks, CA, United States
| | - Blanca Rodriguez
- Department of Computer Science, British Heart Foundation Centre of Research Excellence, University of Oxford, Oxford, United Kingdom
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8
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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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9
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Trayanova NA, Doshi AN, Prakosa A. How personalized heart modeling can help treatment of lethal arrhythmias: A focus on ventricular tachycardia ablation strategies in post-infarction patients. WILEY INTERDISCIPLINARY REVIEWS-SYSTEMS BIOLOGY AND MEDICINE 2020; 12:e1477. [PMID: 31917524 DOI: 10.1002/wsbm.1477] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/12/2019] [Revised: 12/16/2019] [Accepted: 12/17/2019] [Indexed: 12/18/2022]
Abstract
Precision Cardiology is a targeted strategy for cardiovascular disease prevention and treatment that accounts for individual variability. Computational heart modeling is one of the novel approaches that have been developed under the umbrella of Precision Cardiology. Personalized computational modeling of patient hearts has made strides in the development of models that incorporate the individual geometry and structure of the heart as well as other patient-specific information. Of these developments, one of the potentially most impactful is the research aimed at noninvasively predicting the targets of ablation of lethal arrhythmia, ventricular tachycardia (VT), using patient-specific models. The approach has been successfully applied to patients with ischemic cardiomyopathy in proof-of-concept studies. The goal of this paper is to review the strategies for computational VT ablation guidance in ischemic cardiomyopathy patients, from model developments to the intricacies of the actual clinical application. To provide context in describing the road these computational modeling applications have undertaken, we first review the state of the art in VT ablation in the clinic, emphasizing the benefits that personalized computational prediction of ablation targets could bring to the clinical electrophysiology practice. This article is characterized under: Analytical and Computational Methods > Computational Methods Models of Systems Properties and Processes > Organ, Tissue, and Physiological Models Translational, Genomic, and Systems Medicine > Translational Medicine.
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Affiliation(s)
- Natalia A Trayanova
- Alliance for Cardiovascular Diagnostic and Treatment Innovation, Johns Hopkins University, Baltimore, Maryland.,Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland
| | - Ashish N Doshi
- Alliance for Cardiovascular Diagnostic and Treatment Innovation, Johns Hopkins University, Baltimore, Maryland
| | - Adityo Prakosa
- Alliance for Cardiovascular Diagnostic and Treatment Innovation, Johns Hopkins University, Baltimore, Maryland
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10
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Vandersickel N, Van Nieuwenhuyse E, Van Cleemput N, Goedgebeur J, El Haddad M, De Neve J, Demolder A, Strisciuglio T, Duytschaever M, Panfilov AV. Directed Networks as a Novel Way to Describe and Analyze Cardiac Excitation: Directed Graph Mapping. Front Physiol 2019; 10:1138. [PMID: 31551814 PMCID: PMC6746922 DOI: 10.3389/fphys.2019.01138] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2019] [Accepted: 08/19/2019] [Indexed: 12/31/2022] Open
Abstract
Networks provide a powerful methodology with applications in a variety of biological, technological and social systems such as analysis of brain data, social networks, internet search engine algorithms, etc. To date, directed networks have not yet been applied to characterize the excitation of the human heart. In clinical practice, cardiac excitation is recorded by multiple discrete electrodes. During (normal) sinus rhythm or during cardiac arrhythmias, successive excitation connects neighboring electrodes, resulting in their own unique directed network. This in theory makes it a perfect fit for directed network analysis. In this study, we applied directed networks to the heart in order to describe and characterize cardiac arrhythmias. Proof-of-principle was established using in-silico and clinical data. We demonstrated that tools used in network theory analysis allow determination of the mechanism and location of certain cardiac arrhythmias. We show that the robustness of this approach can potentially exceed the existing state-of-the art methodology used in clinics. Furthermore, implementation of these techniques in daily practice can improve the accuracy and speed of cardiac arrhythmia analysis. It may also provide novel insights in arrhythmias that are still incompletely understood.
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Affiliation(s)
- Nele Vandersickel
- Department of Physics and Astronomy, Ghent University, Ghent, Belgium
| | | | - Nico Van Cleemput
- Department of Applied Mathematics, Computer Science and Statistics, Ghent University, Ghent, Belgium
| | - Jan Goedgebeur
- Department of Applied Mathematics, Computer Science and Statistics, Ghent University, Ghent, Belgium
- Computer Science Department, University of Mons, Mons, Belgium
| | - Milad El Haddad
- Ghent University Hospital Heart Center, Ghent University, Ghent, Belgium
| | - Jan De Neve
- Department of Data Analysis, Ghent University, Ghent, Belgium
| | - Anthony Demolder
- Ghent University Hospital Heart Center, Ghent University, Ghent, Belgium
| | | | - Mattias Duytschaever
- Ghent University Hospital Heart Center, Ghent University, Ghent, Belgium
- Cardiology Department, AZ Sint-Jan, Bruges, Belgium
| | - Alexander V. Panfilov
- Department of Physics and Astronomy, Ghent University, Ghent, Belgium
- Laboratory of Computational Biology and Medicine, Ural Federal University, Ekaterinburg, Russia
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11
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Abstract
Excitable biological cells, such as cardiac muscle cells, can exhibit complex patterns of oscillations such as spiking and bursting. Moreover, it is well known that an enhancement in calcium currents may yield certain kind of cardiac arrhythmia, so-called early afterdepolarisations (EADs). The presence of EADs strongly correlates with the onset of dangerous cardiac arrhythmia. In this paper we study mathematically and numerically the dynamics of a cardiac muscle cell with respect to the calcium current by investigating a simplistic system of differential equations. For the study of this phenomena, we use bifurcation theory, numerical bifurcation analysis, geometric singular perturbation theory and computational methods to investigate a nonlinear multiple time scales system. It will turn out that EADs related to an enhanced calcium current are canard–induced and that we have to combine these theories to derive a better understanding of the dynamics behind EADs. Moreover, a suitable time scale separation argument determines the important and sensitive system parameters which are related to the occurrence of EADs.
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12
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Bifurcation Analysis of a Certain Hodgkin-Huxley Model Depending on Multiple Bifurcation Parameters. MATHEMATICS 2018. [DOI: 10.3390/math6060103] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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