1
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Schmidt S, Li W, Schubert M, Binnewerg B, Prönnecke C, Zitzmann FD, Bulst M, Wegner S, Meier M, Guan K, Jahnke HG. Novel high-dense microelectrode array based multimodal bioelectronic monitoring system for cardiac arrhythmia re-entry analysis. Biosens Bioelectron 2024; 252:116120. [PMID: 38394704 DOI: 10.1016/j.bios.2024.116120] [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: 10/31/2023] [Revised: 01/26/2024] [Accepted: 02/07/2024] [Indexed: 02/25/2024]
Abstract
In recent decades, significant progress has been made in the treatment of heart diseases, particularly in the field of personalized medicine. Despite the development of genetic tests, phenotyping and risk stratification are performed based on clinical findings and invasive in vivo techniques, such as stimulation conduction mapping techniques and programmed ventricular pacing. Consequently, label-free non-invasive in vitro functional analysis systems are urgently needed for more accurate and effective in vitro risk stratification, model-based therapy planning, and clinical safety profile evaluation of drugs. To overcome these limitations, a novel multilayer high-density microelectrode array (HD-MEA), with an optimized configuration of 512 sensing and 4 pacing electrodes on a sensor area of 100 mm2, was developed for the bioelectronic detection of re-entry arrhythmia patterns. Together with a co-developed front-end, we monitored label-free and in parallel cardiac electrophysiology based on field potential monitoring and mechanical contraction using impedance spectroscopy at the same microelectrode. In proof of principle experiments, human induced pluripotent stem cell (hiPS)-derived cardiomyocytes were cultured on HD-MEAs and used to demonstrate the sensitive quantification of contraction strength modulation by cardioactive drugs such as blebbistatin (IC50 = 4.2 μM), omecamtiv and levosimendan. Strikingly, arrhythmia-typical rotor patterns (re-entry) can be induced by optimized electrical stimulation sequences and detected with high spatial resolution. Therefore, we provide a novel cardiac re-entry analysis system as a promising reference point for diagnostic approaches based on in vitro assays using patient-specific hiPS-derived cardiomyocytes.
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Affiliation(s)
- Sabine Schmidt
- Centre for Biotechnology and Biomedicine, Biochemical Cell Technology, Leipzig University, Deutscher Platz 5, D-04103, Leipzig, Germany
| | - Wener Li
- Institute of Pharmacology and Toxicology, Carl Gustav Carus Medical Faculty, Technical University Dresden, Fetscherstraße 74, D-01307, Dresden, Germany
| | - Mario Schubert
- Institute of Pharmacology and Toxicology, Carl Gustav Carus Medical Faculty, Technical University Dresden, Fetscherstraße 74, D-01307, Dresden, Germany
| | - Björn Binnewerg
- Institute of Pharmacology and Toxicology, Carl Gustav Carus Medical Faculty, Technical University Dresden, Fetscherstraße 74, D-01307, Dresden, Germany
| | - Christoph Prönnecke
- Centre for Biotechnology and Biomedicine, Biochemical Cell Technology, Leipzig University, Deutscher Platz 5, D-04103, Leipzig, Germany
| | - Franziska D Zitzmann
- Centre for Biotechnology and Biomedicine, Biochemical Cell Technology, Leipzig University, Deutscher Platz 5, D-04103, Leipzig, Germany
| | - Martin Bulst
- Sciospec Scientific Instruments GmbH, Leipziger Str. 43b, D-04828, Bennewitz, Germany
| | - Sebastian Wegner
- Sciospec Scientific Instruments GmbH, Leipziger Str. 43b, D-04828, Bennewitz, Germany
| | - Matthias Meier
- Centre for Biotechnology and Biomedicine, Biochemical Cell Technology, Leipzig University, Deutscher Platz 5, D-04103, Leipzig, Germany; Helmholtz Pioneer Campus, Helmholtz Zentrum Munich, Neuherberg, Germany
| | - Kaomei Guan
- Institute of Pharmacology and Toxicology, Carl Gustav Carus Medical Faculty, Technical University Dresden, Fetscherstraße 74, D-01307, Dresden, Germany
| | - Heinz-Georg Jahnke
- Centre for Biotechnology and Biomedicine, Biochemical Cell Technology, Leipzig University, Deutscher Platz 5, D-04103, Leipzig, Germany.
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2
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Lootens S, Janssens I, Van Den Abeele R, Wülfers EM, Bezerra AS, Verstraeten B, Hendrickx S, Okenov A, Nezlobinsky T, Panfilov AV, Vandersickel N. Directed Graph Mapping exceeds Phase Mapping for the detection of simulated 2D meandering rotors in fibrotic tissue with added noise. Comput Biol Med 2024; 171:108138. [PMID: 38401451 DOI: 10.1016/j.compbiomed.2024.108138] [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: 10/27/2023] [Revised: 02/09/2024] [Accepted: 02/12/2024] [Indexed: 02/26/2024]
Abstract
Cardiac arrhythmias such as atrial fibrillation (AF) are recognised to be associated with re-entry or rotors. A rotor is a wave of excitation in the cardiac tissue that wraps around its refractory tail, causing faster-than-normal periodic excitation. The detection of rotor centres is of crucial importance in guiding ablation strategies for the treatment of arrhythmia. The most popular technique for detecting rotor centres is Phase Mapping (PM), which detects phase singularities derived from the phase of a signal. This method has been proven to be prone to errors, especially in regimes of fibrotic tissue and temporal noise. Recently, a novel technique called Directed Graph Mapping (DGM) was developed to detect rotational activity such as rotors by creating a network of excitation. This research aims to compare the performance of advanced PM techniques versus DGM for the detection of rotors using 64 simulated 2D meandering rotors in the presence of various levels of fibrotic tissue and temporal noise. Four strategies were employed to compare the performances of PM and DGM. These included a visual analysis, a comparison of F2-scores and distance distributions, and calculating p-values using the mid-p McNemar test. Results indicate that in the case of low meandering, fibrosis and noise, PM and DGM yield excellent results and are comparable. However, in the case of high meandering, fibrosis and noise, PM is undeniably prone to errors, mainly in the form of an excess of false positives, resulting in low precision. In contrast, DGM is more robust against these factors as F2-scores remain high, yielding F2≥0.931 as opposed to the best PM F2≥0.635 across all 64 simulations.
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Affiliation(s)
| | - Iris Janssens
- Department of Physics and Astronomy, Ghent University, Ghent, Belgium
| | | | - Eike M Wülfers
- Department of Physics and Astronomy, Ghent University, Ghent, Belgium
| | | | - Bjorn Verstraeten
- Department of Physics and Astronomy, Ghent University, Ghent, Belgium
| | - Sander Hendrickx
- Department of Physics and Astronomy, Ghent University, Ghent, Belgium
| | - Arstanbek Okenov
- Department of Physics and Astronomy, Ghent University, Ghent, Belgium
| | - Timur Nezlobinsky
- Department of Physics and Astronomy, Ghent University, Ghent, Belgium
| | - Alexander V Panfilov
- Department of Physics and Astronomy, Ghent University, Ghent, Belgium; World-Class Research Center "Digital Biodesign and personalised healthcare", Sechenov University, Moscow 119991, Russia; Laboratory of Computational Biology and Medicine, Ural Federal University, Ekaterinburg 620002, Russia
| | - Nele Vandersickel
- Department of Physics and Astronomy, Ghent University, Ghent, Belgium
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3
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Galappaththige S, Pathmanathan P, Gray RA. A computational modeling framework for pre-clinical evaluation of cardiac mapping systems. Front Physiol 2023; 14:1074527. [PMID: 37485068 PMCID: PMC10358980 DOI: 10.3389/fphys.2023.1074527] [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: 10/19/2022] [Accepted: 05/31/2023] [Indexed: 07/25/2023] Open
Abstract
There are a variety of difficulties in evaluating clinical cardiac mapping systems, most notably the inability to record the transmembrane potential throughout the entire heart during patient procedures which prevents the comparison to a relevant "gold standard". Cardiac mapping systems are comprised of hardware and software elements including sophisticated mathematical algorithms, both of which continue to undergo rapid innovation. The purpose of this study is to develop a computational modeling framework to evaluate the performance of cardiac mapping systems. The framework enables rigorous evaluation of a mapping system's ability to localize and characterize (i.e., focal or reentrant) arrhythmogenic sources in the heart. The main component of our tool is a library of computer simulations of various dynamic patterns throughout the entire heart in which the type and location of the arrhythmogenic sources are known. Our framework allows for performance evaluation for various electrode configurations, heart geometries, arrhythmias, and electrogram noise levels and involves blind comparison of mapping systems against a "silver standard" comprised of computer simulations in which the precise transmembrane potential patterns throughout the heart are known. A feasibility study was performed using simulations of patterns in the human left atria and three hypothetical virtual catheter electrode arrays. Activation times (AcT) and patterns (AcP) were computed for three virtual electrode arrays: two basket arrays with good and poor contact and one high-resolution grid with uniform spacing. The average root mean squared difference of AcTs of electrograms and those of the nearest endocardial action potential was less than 1 ms and therefore appears to be a poor performance metric. In an effort to standardize performance evaluation of mapping systems a novel performance metric is introduced based on the number of AcPs identified correctly and those considered spurious as well as misclassifications of arrhythmia type; spatial and temporal localization accuracy of correctly identified patterns was also quantified. This approach provides a rigorous quantitative analysis of cardiac mapping system performance. Proof of concept of this computational evaluation framework suggests that it could help safeguard that mapping systems perform as expected as well as provide estimates of system accuracy.
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4
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Jenkins EV, Dharmaprani D, Schopp M, Quah JX, Tiver K, Mitchell L, Nash MP, Clayton RH, Pope K, Ganesan AN. Markov modeling of phase singularity interaction effects in human atrial and ventricular fibrillation. CHAOS (WOODBURY, N.Y.) 2023; 33:2895977. [PMID: 37307158 DOI: 10.1063/5.0141890] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/09/2023] [Accepted: 05/12/2023] [Indexed: 06/14/2023]
Abstract
Atrial and ventricular fibrillation (AF/VF) are characterized by the repetitive regeneration of topological defects known as phase singularities (PSs). The effect of PS interactions has not been previously studied in human AF and VF. We hypothesized that PS population size would influence the rate of PS formation and destruction in human AF and VF, due to increased inter-defect interaction. PS population statistics were studied in computational simulations (Aliev-Panfilov), human AF and human VF. The influence of inter-PS interactions was evaluated by comparison between directly modeled discrete-time Markov chain (DTMC) transition matrices of the PS population changes, and M/M/∞ birth-death transition matrices of PS dynamics, which assumes that PS formations and destructions are effectively statistically independent events. Across all systems examined, PS population changes differed from those expected with M/M/∞. In human AF and VF, the formation rates decreased slightly with PS population when modeled with the DTMC, compared with the static formation rate expected through M/M/∞, suggesting new formations were being inhibited. In human AF and VF, the destruction rates increased with PS population for both models, with the DTMC rate increase exceeding the M/M/∞ estimates, indicating that PS were being destroyed faster as the PS population grew. In human AF and VF, the change in PS formation and destruction rates as the population increased differed between the two models. This indicates that the presence of additional PS influenced the likelihood of new PS formation and destruction, consistent with the notion of self-inhibitory inter-PS interactions.
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Affiliation(s)
- Evan V Jenkins
- College of Medicine and Public Health, Flinders University, Adelaide 5042, Australia
| | - Dhani Dharmaprani
- College of Medicine and Public Health, Flinders University, Adelaide 5042, Australia
- College of Science and Engineering, Flinders University, Adelaide 5042, Australia
| | - Madeline Schopp
- College of Science and Engineering, Flinders University, Adelaide 5042, Australia
| | - Jing Xian Quah
- College of Medicine and Public Health, Flinders University, Adelaide 5042, Australia
- Department of Cardiovascular Medicine, Flinders Medical Centre, Adelaide 5042, Australia
| | - Kathryn Tiver
- Department of Cardiovascular Medicine, Flinders Medical Centre, Adelaide 5042, Australia
| | - Lewis Mitchell
- School of Mathematical Sciences, University of Adelaide, Adelaide 5005, Australia
| | - Martyn P Nash
- Auckland Bioengineering Institute, University of Auckland, Auckland 1010, New Zealand
| | - Richard H Clayton
- Insigneo Institute for In Silico Medicine and Department of Computer Science, University of Sheffield, Sheffield, S1 4DP, United Kingdom
| | - Kenneth Pope
- College of Science and Engineering, Flinders University, Adelaide 5042, Australia
| | - Anand N Ganesan
- College of Medicine and Public Health, Flinders University, Adelaide 5042, Australia
- Department of Cardiovascular Medicine, Flinders Medical Centre, Adelaide 5042, Australia
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5
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Atrial conduction velocity mapping: clinical tools, algorithms and approaches for understanding the arrhythmogenic substrate. Med Biol Eng Comput 2022; 60:2463-2478. [PMID: 35867323 PMCID: PMC9365755 DOI: 10.1007/s11517-022-02621-0] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2022] [Accepted: 06/07/2022] [Indexed: 11/02/2022]
Abstract
Characterizing patient-specific atrial conduction properties is important for understanding arrhythmia drivers, for predicting potential arrhythmia pathways, and for personalising treatment approaches. One metric that characterizes the health of the myocardial substrate is atrial conduction velocity, which describes the speed and direction of propagation of the electrical wavefront through the myocardium. Atrial conduction velocity mapping algorithms are under continuous development in research laboratories and in industry. In this review article, we give a broad overview of different categories of currently published methods for calculating CV, and give insight into their different advantages and disadvantages overall. We classify techniques into local, global, and inverse methods, and discuss these techniques with respect to their faithfulness to the biophysics, incorporation of uncertainty quantification, and their ability to take account of the atrial manifold.
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6
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DG-Mapping: a novel software package for the analysis of any type of reentry and focal activation of simulated, experimental or clinical data of cardiac arrhythmia. Med Biol Eng Comput 2022; 60:1929-1945. [DOI: 10.1007/s11517-022-02550-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2021] [Accepted: 02/13/2022] [Indexed: 01/24/2023]
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7
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Jenkins EV, Dharmaprani D, Schopp M, Quah JX, Tiver K, Mitchell L, Pope K, Ganesan AN. Understanding the origins of the basic equations of statistical fibrillatory dynamics. CHAOS (WOODBURY, N.Y.) 2022; 32:032101. [PMID: 35364849 DOI: 10.1063/5.0062095] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/02/2021] [Accepted: 02/07/2022] [Indexed: 06/14/2023]
Abstract
The mechanisms governing cardiac fibrillation remain unclear; however, it most likely represents a form of spatiotemporal chaos with conservative system dynamics. Renewal theory has recently been suggested as a statistical formulation with governing equations to quantify the formation and destruction of wavelets and rotors in fibrillatory dynamics. In this perspective Review, we aim to explain the origin of the renewal theory paradigm in spatiotemporal chaos. The ergodic nature of pattern formation in spatiotemporal chaos is demonstrated through the use of three chaotic systems: two classical systems and a simulation of cardiac fibrillation. The logistic map and the baker's transformation are used to demonstrate how the apparently random appearance of patterns in classical chaotic systems has macroscopic parameters that are predictable in a statistical sense. We demonstrate that the renewal theory approach developed for cardiac fibrillation statistically predicts pattern formation in these classical chaotic systems. Renewal theory provides governing equations to describe the apparently random formation and destruction of wavelets and rotors in atrial fibrillation (AF) and ventricular fibrillation (VF). This statistical framework for fibrillatory dynamics provides a holistic understanding of observed rotor and wavelet dynamics and is of conceptual significance in informing the clinical and mechanistic research of the rotor and multiple-wavelet mechanisms of AF and VF.
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Affiliation(s)
- Evan V Jenkins
- College of Medicine and Public Health, Flinders University, Adelaide 5042, Australia
| | - Dhani Dharmaprani
- College of Medicine and Public Health, Flinders University, Adelaide 5042, Australia
| | - Madeline Schopp
- College of Science and Engineering, Flinders University, Adelaide 5042, Australia
| | - Jing Xian Quah
- College of Medicine and Public Health, Flinders University, Adelaide 5042, Australia
| | - Kathryn Tiver
- Department of Cardiovascular Medicine, Flinders Medical Centre, Adelaide 5042, Australia
| | - Lewis Mitchell
- School of Mathematical Sciences, University of Adelaide, Adelaide 5005, Australia
| | - Kenneth Pope
- College of Science and Engineering, Flinders University, Adelaide 5042, Australia
| | - Anand N Ganesan
- College of Medicine and Public Health, Flinders University, Adelaide 5042, Australia
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8
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Nonlinear interdependence of electrograms as a tool to characterize propagation patterns in atrial fibrillation. Biomed Signal Process Control 2022. [DOI: 10.1016/j.bspc.2021.103282] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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9
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Bartolucci C, Fabbri C, Tomasi C, Sabbatani P, Severi S, Corsi C. Computational Analysis of Mapping Catheter Geometry and Contact Quality Effects on Rotor Detection in Atrial Fibrillation. Front Physiol 2021; 12:732161. [PMID: 34955872 PMCID: PMC8696082 DOI: 10.3389/fphys.2021.732161] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2021] [Accepted: 11/18/2021] [Indexed: 11/30/2022] Open
Abstract
Atrial fibrillation (AF) is the most common cardiac arrhythmia and catheter mapping has been proved to be an effective approach for detecting AF drivers to be targeted by ablation. Among drivers, the so-called rotors have gained the most attention: their identification and spatial location could help to understand which patient-specific mechanisms are acting, and thus to guide the ablation execution. Since rotor detection by multi-electrode catheters may be influenced by several structural parameters including inter-electrode spacing, catheter coverage, and endocardium-catheter distance, in this study we proposed a tool for testing the ability of different catheter shapes to detect rotors in different conditions. An approach based on the solution of the monodomain equations coupled with a modified Courtemanche ionic atrial model, that considers an electrical remodeling, was applied to simulate spiral wave dynamics on a 2D model for 7.75 s. The developed framework allowed the acquisition of unipolar signals at 2 KHz. Two high-density multipolar catheters were simulated (Advisor™ HD Grid and PentaRay®) and placed in a 2D region in which the simulated spiral wave persists longer. The configuration of the catheters was then modified by changing the number of electrodes, inter-electrodes distance, position, and atrial-wall distance for assessing how they would affect the rotor detection. In contact with the wall and at 1 mm distance from it, all the configurations detected the rotor correctly, irrespective of geometry, coverage, and inter-electrode distance. In the HDGrid-like geometry, the increase of the inter-electrode distance from 3 to 6 mm caused rotor detection failure at 2 mm distance from the LA wall. In the PentaRay-like configuration, regardless of inter-electrode distance, rotor detection failed at 3 mm endocardium-catheter distance. The asymmetry of this catheter resulted in rotation-dependent rotor detection. To conclude, the computational framework we developed is based on realistic catheter shapes designed with parameter configurations which resemble clinical settings. Results showed it is well suited to investigate how mapping catheter geometry and location affect AF driver detection, therefore it is a reliable tool to design and test new mapping catheters.
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Affiliation(s)
- Chiara Bartolucci
- Computational Physiopathology Unit, Department of Electrical, Electronic and Information Engineering "Guglielmo Marconi", University of Bologna, Bologna, Italy
| | - Claudio Fabbri
- Computational Physiopathology Unit, Department of Electrical, Electronic and Information Engineering "Guglielmo Marconi", University of Bologna, Bologna, Italy
| | - Corrado Tomasi
- Electrophysiology Laboratory, Cardiology Unit, Ravenna and Cesena Hospitals, Azienda Unità Sanitaria Locale della Romagna, Ravenna, Italy
| | - Paolo Sabbatani
- Electrophysiology Laboratory, Cardiology Unit, Ravenna and Cesena Hospitals, Azienda Unità Sanitaria Locale della Romagna, Ravenna, Italy
| | - Stefano Severi
- Computational Physiopathology Unit, Department of Electrical, Electronic and Information Engineering "Guglielmo Marconi", University of Bologna, Bologna, Italy
| | - Cristiana Corsi
- Computational Physiopathology Unit, Department of Electrical, Electronic and Information Engineering "Guglielmo Marconi", University of Bologna, Bologna, Italy
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10
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Masè M, Cristoforetti A, Del Greco M, Ravelli F. A Divergence-Based Approach for the Identification of Atrial Fibrillation Focal Drivers From Multipolar Mapping: A Computational Study. Front Physiol 2021; 12:749430. [PMID: 35002755 PMCID: PMC8740027 DOI: 10.3389/fphys.2021.749430] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Accepted: 11/30/2021] [Indexed: 11/13/2022] Open
Abstract
The expanding role of catheter ablation of atrial fibrillation (AF) has stimulated the development of novel mapping strategies to guide the procedure. We introduce a novel approach to characterize wave propagation and identify AF focal drivers from multipolar mapping data. The method reconstructs continuous activation patterns in the mapping area by a radial basis function (RBF) interpolation of multisite activation time series. Velocity vector fields are analytically determined, and the vector field divergence is used as a marker of focal drivers. The method was validated in a tissue patch cellular automaton model and in an anatomically realistic left atrial (LA) model with Courtemanche-Ramirez-Nattel ionic dynamics. Divergence analysis was effective in identifying focal drivers in a complex simulated AF pattern. Localization was reliable even with consistent reduction (47%) in the number of mapping points and in the presence of activation time misdetections (noise <10% of the cycle length). Proof-of-concept application of the method to human AF mapping data showed that divergence analysis consistently detected focal activation in the pulmonary veins and LA appendage area. These results suggest the potential of divergence analysis in combination with multipolar mapping to identify AF critical sites. Further studies on large clinical datasets may help to assess the clinical feasibility and benefit of divergence analysis for the optimization of ablation treatment.
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Affiliation(s)
- Michela Masè
- Laboratory of Biophysics and Translational Cardiology, Department of Cellular, Computational and Integrative Biology – CIBIO, University of Trento, Trento, Italy
- Institute of Mountain Emergency Medicine, EURAC Research, Bolzano, Italy
| | - Alessandro Cristoforetti
- Laboratory of Biophysics and Translational Cardiology, Department of Cellular, Computational and Integrative Biology – CIBIO, University of Trento, Trento, Italy
| | - Maurizio Del Greco
- Division of Cardiology, Santa Maria del Carmine Hospital, Rovereto, Italy
| | - Flavia Ravelli
- Laboratory of Biophysics and Translational Cardiology, Department of Cellular, Computational and Integrative Biology – CIBIO, University of Trento, Trento, Italy
- CISMed – Centre for Medical Sciences, University of Trento, Trento, Italy
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11
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de Groot NMS, Shah D, Boyle PM, Anter E, Clifford GD, Deisenhofer I, Deneke T, van Dessel P, Doessel O, Dilaveris P, Heinzel FR, Kapa S, Lambiase PD, Lumens J, Platonov PG, Ngarmukos T, Martinez JP, Sanchez AO, Takahashi Y, Valdigem BP, van der Veen AJ, Vernooy K, Casado-Arroyo Co-Chair R. Critical appraisal of technologies to assess electrical activity during atrial fibrillation: a position paper from the European Heart Rhythm Association and European Society of Cardiology Working Group on eCardiology in collaboration with the Heart Rhythm Society, Asia Pacific Heart Rhythm Society, Latin American Heart Rhythm Society and Computing in Cardiology. Europace 2021; 24:313-330. [PMID: 34878119 DOI: 10.1093/europace/euab254] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2021] [Accepted: 09/21/2021] [Indexed: 11/13/2022] Open
Abstract
We aim to provide a critical appraisal of basic concepts underlying signal recording and processing technologies applied for (i) atrial fibrillation (AF) mapping to unravel AF mechanisms and/or identifying target sites for AF therapy and (ii) AF detection, to optimize usage of technologies, stimulate research aimed at closing knowledge gaps, and developing ideal AF recording and processing technologies. Recording and processing techniques for assessment of electrical activity during AF essential for diagnosis and guiding ablative therapy including body surface electrocardiograms (ECG) and endo- or epicardial electrograms (EGM) are evaluated. Discussion of (i) differences in uni-, bi-, and multi-polar (omnipolar/Laplacian) recording modes, (ii) impact of recording technologies on EGM morphology, (iii) global or local mapping using various types of EGM involving signal processing techniques including isochronal-, voltage- fractionation-, dipole density-, and rotor mapping, enabling derivation of parameters like atrial rate, entropy, conduction velocity/direction, (iv) value of epicardial and optical mapping, (v) AF detection by cardiac implantable electronic devices containing various detection algorithms applicable to stored EGMs, (vi) contribution of machine learning (ML) to further improvement of signals processing technologies. Recording and processing of EGM (or ECG) are the cornerstones of (body surface) mapping of AF. Currently available AF recording and processing technologies are mainly restricted to specific applications or have technological limitations. Improvements in AF mapping by obtaining highest fidelity source signals (e.g. catheter-electrode combinations) for signal processing (e.g. filtering, digitization, and noise elimination) is of utmost importance. Novel acquisition instruments (multi-polar catheters combined with improved physical modelling and ML techniques) will enable enhanced and automated interpretation of EGM recordings in the near future.
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Affiliation(s)
- Natasja M S de Groot
- Department of Cardiology, Erasmus University Medical Centre, Rotterdam, Delft University of Technology, Delft the Netherlands
| | - Dipen Shah
- Cardiology Service, University Hospitals Geneva, Geneva, Switzerland
| | - Patrick M Boyle
- Department of Bioengineering, University of Washington, Seattle, Washington, USA
| | - Elad Anter
- Cardiac Electrophysiology Section, Department of Cardiovascular Medicine, Cleveland Clinic, Cleveland, Ohio, USA
| | - Gari D Clifford
- Department of Biomedical Informatics, Emory University, Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, USA
| | - Isabel Deisenhofer
- Department of Electrophysiology, German Heart Center Munich and Technical University of Munich, Munich, Germany
| | - Thomas Deneke
- Department of Cardiology, Rhon-klinikum Campus Bad Neustadt, Germany
| | - Pascal van Dessel
- Department of Cardiology, Medisch Spectrum Twente, Twente, the Netherlands
| | - Olaf Doessel
- Karlsruher Institut für Technologie (KIT), Karlsruhe, Germany
| | - Polychronis Dilaveris
- 1st University Department of Cardiology, National & Kapodistrian University of Athens School of Medicine, Hippokration Hospital, Athens, Greece
| | - Frank R Heinzel
- Department of Internal Medicine and Cardiology, Charité-Universitätsmedizin Berlin, Campus Virchow-Klinikum and DZHK (German Centre for Cardiovascular Research), Berlin, Germany
| | - Suraj Kapa
- Department of Cardiology, Mayo Clinic, Rochester, USA
| | | | - Joost Lumens
- Cardiovascular Research Institute Maastricht (CARIM) Maastricht University, Maastricht, the Netherlands
| | - Pyotr G Platonov
- Department of Cardiology, Clinical Sciences, Lund University, Lund, Sweden
| | - Tachapong Ngarmukos
- Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand
| | - Juan Pablo Martinez
- Aragon Institute of Engineering Research/IIS-Aragon and University of Zaragoza, Zaragoza, Spain, CIBER Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Zaragoza, Spain
| | - Alejandro Olaya Sanchez
- Department of Cardiology, Hospital San José, Fundacion Universitaia de Ciencas de la Salud, Bogota, Colombia
| | - Yoshihide Takahashi
- Department of Cardiovascular Medicine, Tokyo Medical and Dental University, Tokyo, Japan
| | - Bruno P Valdigem
- Department of Cardiology, Hospital Rede D'or São Luiz, hospital Albert einstein and Dante pazzanese heart institute, São Paulo, Brasil
| | - Alle-Jan van der Veen
- Department Circuits and Systems, Delft University of Technology, Delft, the Netherlands
| | - Kevin Vernooy
- Department of Cardiology, Cardiovascular Research Institute Maastricht (CARIM), Maastricht University Medical Centre, Maastricht, the Netherlands
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12
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Roney CH, Child N, Porter B, Sim I, Whitaker J, Clayton RH, Laughner JI, Shuros A, Neuzil P, Williams SE, Razavi RS, O'Neill M, Rinaldi CA, Taggart P, Wright M, Gill JS, Niederer SA. Time-Averaged Wavefront Analysis Demonstrates Preferential Pathways of Atrial Fibrillation, Predicting Pulmonary Vein Isolation Acute Response. Front Physiol 2021; 12:707189. [PMID: 34646149 PMCID: PMC8503618 DOI: 10.3389/fphys.2021.707189] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2021] [Accepted: 08/24/2021] [Indexed: 11/13/2022] Open
Abstract
Electrical activation during atrial fibrillation (AF) appears chaotic and disorganised, which impedes characterisation of the underlying substrate and treatment planning. While globally chaotic, there may be local preferential activation pathways that represent potential ablation targets. This study aimed to identify preferential activation pathways during AF and predict the acute ablation response when these are targeted by pulmonary vein isolation (PVI). In patients with persistent AF (n = 14), simultaneous biatrial contact mapping with basket catheters was performed pre-ablation and following each ablation strategy (PVI, roof, and mitral lines). Unipolar wavefront activation directions were averaged over 10 s to identify preferential activation pathways. Clinical cases were classified as responders or non-responders to PVI during the procedure. Clinical data were augmented with a virtual cohort of 100 models. In AF pre-ablation, pathways originated from the pulmonary vein (PV) antra in PVI responders (7/7) but not in PVI non-responders (6/6). We proposed a novel index that measured activation waves from the PV antra into the atrial body. This index was significantly higher in PVI responders than non-responders (clinical: 16.3 vs. 3.7%, p = 0.04; simulated: 21.1 vs. 14.1%, p = 0.02). Overall, this novel technique and proof of concept study demonstrated that preferential activation pathways exist during AF. Targeting patient-specific activation pathways that flowed from the PV antra to the left atrial body using PVI resulted in AF termination during the procedure. These PV activation flow pathways may correspond to the presence of drivers in the PV regions.
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Affiliation(s)
- Caroline H. Roney
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Nicholas Child
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Bradley Porter
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Iain Sim
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - John Whitaker
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Richard H. Clayton
- INSIGNEO Institute for In Silico Medicine and Department of Computer Science, University of Sheffield, Sheffield, United Kingdom
| | | | - Allan Shuros
- Boston Scientific Corp, St. Paul, MN, United States
| | - Petr Neuzil
- Department of Cardiology, Na Holmolce Hospital, Prague, Czechia
| | - Steven E. Williams
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Reza S. Razavi
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Mark O'Neill
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | | | - Peter Taggart
- Institute of Cardiovascular Science, University College London, London, United Kingdom
| | - Matt Wright
- Department of Cardiology, Guy's and St Thomas' Hospital, London, United Kingdom
| | - Jaswinder S. Gill
- Department of Cardiology, Guy's and St Thomas' Hospital, London, United Kingdom
| | - Steven A. Niederer
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
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13
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Heijman J, Sutanto H, Crijns HJGM, Nattel S, Trayanova NA. Computational models of atrial fibrillation: achievements, challenges, and perspectives for improving clinical care. Cardiovasc Res 2021; 117:1682-1699. [PMID: 33890620 PMCID: PMC8208751 DOI: 10.1093/cvr/cvab138] [Citation(s) in RCA: 38] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/31/2020] [Indexed: 12/11/2022] Open
Abstract
Despite significant advances in its detection, understanding and management, atrial fibrillation (AF) remains a highly prevalent cardiac arrhythmia with a major impact on morbidity and mortality of millions of patients. AF results from complex, dynamic interactions between risk factors and comorbidities that induce diverse atrial remodelling processes. Atrial remodelling increases AF vulnerability and persistence, while promoting disease progression. The variability in presentation and wide range of mechanisms involved in initiation, maintenance and progression of AF, as well as its associated adverse outcomes, make the early identification of causal factors modifiable with therapeutic interventions challenging, likely contributing to suboptimal efficacy of current AF management. Computational modelling facilitates the multilevel integration of multiple datasets and offers new opportunities for mechanistic understanding, risk prediction and personalized therapy. Mathematical simulations of cardiac electrophysiology have been around for 60 years and are being increasingly used to improve our understanding of AF mechanisms and guide AF therapy. This narrative review focuses on the emerging and future applications of computational modelling in AF management. We summarize clinical challenges that may benefit from computational modelling, provide an overview of the different in silico approaches that are available together with their notable achievements, and discuss the major limitations that hinder the routine clinical application of these approaches. Finally, future perspectives are addressed. With the rapid progress in electronic technologies including computing, clinical applications of computational modelling are advancing rapidly. We expect that their application will progressively increase in prominence, especially if their added value can be demonstrated in clinical trials.
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Affiliation(s)
- Jordi Heijman
- Department of Cardiology, Cardiovascular Research Institute Maastricht, Faculty of Health, Medicine, and Life Sciences, Maastricht University, PO Box 616, 6200 MD Maastricht, The Netherlands
| | - Henry Sutanto
- Department of Cardiology, Cardiovascular Research Institute Maastricht, Faculty of Health, Medicine, and Life Sciences, Maastricht University, PO Box 616, 6200 MD Maastricht, The Netherlands
| | - Harry J G M Crijns
- Department of Cardiology, Cardiovascular Research Institute Maastricht, Faculty of Health, Medicine, and Life Sciences, Maastricht University, PO Box 616, 6200 MD Maastricht, The Netherlands
| | - Stanley Nattel
- Department of Medicine, Montreal Heart Institute and Université de Montréal, Montreal, Canada
- Department of Pharmacology and Therapeutics, McGill University, Montreal, Canada
- Institute of Pharmacology, West German Heart and Vascular Center, Faculty of Medicine, University Duisburg-Essen, Duisburg, Germany
- IHU Liryc and Fondation Bordeaux Université, Bordeaux, France
| | - Natalia A Trayanova
- Alliance for Cardiovascular Diagnostic and Treatment Innovation, and Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
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14
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Handa BS, Li X, Aras KK, Qureshi NA, Mann I, Chowdhury RA, Whinnett ZI, Linton NW, Lim PB, Kanagaratnam P, Efimov IR, Peters NS, Ng FS. Granger Causality-Based Analysis for Classification of Fibrillation Mechanisms and Localization of Rotational Drivers. Circ Arrhythm Electrophysiol 2020; 13:e008237. [PMID: 32064900 PMCID: PMC7069398 DOI: 10.1161/circep.119.008237] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/24/2019] [Accepted: 02/04/2020] [Indexed: 11/16/2022]
Abstract
BACKGROUND The mechanisms sustaining myocardial fibrillation remain disputed, partly due to a lack of mapping tools that can accurately identify the mechanism with low spatial resolution clinical recordings. Granger causality (GC) analysis, an econometric tool for quantifying causal relationships between complex time-series, was developed as a novel fibrillation mapping tool and adapted to low spatial resolution sequentially acquired data. METHODS Ventricular fibrillation (VF) optical mapping was performed in Langendorff-perfused Sprague-Dawley rat hearts (n=18), where novel algorithms were developed using GC-based analysis to (1) quantify causal dependence of neighboring signals and plot GC vectors, (2) quantify global organization with the causality pairing index, a measure of neighboring causal signal pairs, and (3) localize rotational drivers (RDs) by quantifying the circular interdependence of neighboring signals with the circular interdependence value. GC-based mapping tools were optimized for low spatial resolution from downsampled optical mapping data, validated against high-resolution phase analysis and further tested in previous VF optical mapping recordings of coronary perfused donor heart left ventricular wedge preparations (n=12), and adapted for sequentially acquired intracardiac electrograms during human persistent atrial fibrillation mapping (n=16). RESULTS Global VF organization quantified by causality pairing index showed a negative correlation at progressively lower resolutions (50% resolution: P=0.006, R2=0.38, 12.5% resolution, P=0.004, R2=0.41) with a phase analysis derived measure of disorganization, locations occupied by phase singularities. In organized VF with high causality pairing index values, GC vector mapping characterized dominant propagating patterns and localized stable RDs, with the circular interdependence value showing a significant difference in driver versus nondriver regions (0.91±0.05 versus 0.35±0.06, P=0.0002). These findings were further confirmed in human VF. In persistent atrial fibrillation, a positive correlation was found between the causality pairing index and presence of stable RDs (P=0.0005,R2=0.56). Fifty percent of patients had RDs, with a low incidence of 0.9±0.3 RDs per patient. CONCLUSIONS GC-based fibrillation analysis can measure global fibrillation organization, characterize dominant propagating patterns, and map RDs using low spatial resolution sequentially acquired data.
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Affiliation(s)
- Balvinder S. Handa
- National Heart & Lung Institute, Imperial College London, United Kingdom (B.S.H., X.L., N.A.Q., I.M., R.A.C., Z.I.W., N.W.F.L., P.B.L., P.K., N.S.P., F.S.N.)
| | - Xinyang Li
- National Heart & Lung Institute, Imperial College London, United Kingdom (B.S.H., X.L., N.A.Q., I.M., R.A.C., Z.I.W., N.W.F.L., P.B.L., P.K., N.S.P., F.S.N.)
| | - Kedar K. Aras
- Department of Biomedical Engineering, George Washington University, Washington, DC (K.K.A., I.R.E.)
| | - Norman A. Qureshi
- National Heart & Lung Institute, Imperial College London, United Kingdom (B.S.H., X.L., N.A.Q., I.M., R.A.C., Z.I.W., N.W.F.L., P.B.L., P.K., N.S.P., F.S.N.)
| | - Ian Mann
- National Heart & Lung Institute, Imperial College London, United Kingdom (B.S.H., X.L., N.A.Q., I.M., R.A.C., Z.I.W., N.W.F.L., P.B.L., P.K., N.S.P., F.S.N.)
| | - Rasheda A. Chowdhury
- National Heart & Lung Institute, Imperial College London, United Kingdom (B.S.H., X.L., N.A.Q., I.M., R.A.C., Z.I.W., N.W.F.L., P.B.L., P.K., N.S.P., F.S.N.)
| | - Zachary I. Whinnett
- National Heart & Lung Institute, Imperial College London, United Kingdom (B.S.H., X.L., N.A.Q., I.M., R.A.C., Z.I.W., N.W.F.L., P.B.L., P.K., N.S.P., F.S.N.)
| | - Nick W.F. Linton
- National Heart & Lung Institute, Imperial College London, United Kingdom (B.S.H., X.L., N.A.Q., I.M., R.A.C., Z.I.W., N.W.F.L., P.B.L., P.K., N.S.P., F.S.N.)
| | - Phang Boon Lim
- National Heart & Lung Institute, Imperial College London, United Kingdom (B.S.H., X.L., N.A.Q., I.M., R.A.C., Z.I.W., N.W.F.L., P.B.L., P.K., N.S.P., F.S.N.)
| | - Prapa Kanagaratnam
- National Heart & Lung Institute, Imperial College London, United Kingdom (B.S.H., X.L., N.A.Q., I.M., R.A.C., Z.I.W., N.W.F.L., P.B.L., P.K., N.S.P., F.S.N.)
| | - Igor R. Efimov
- Department of Biomedical Engineering, George Washington University, Washington, DC (K.K.A., I.R.E.)
| | - Nicholas S. Peters
- National Heart & Lung Institute, Imperial College London, United Kingdom (B.S.H., X.L., N.A.Q., I.M., R.A.C., Z.I.W., N.W.F.L., P.B.L., P.K., N.S.P., F.S.N.)
- Department of Biomedical Engineering, George Washington University, Washington, DC (K.K.A., I.R.E.)
| | - Fu Siong Ng
- National Heart & Lung Institute, Imperial College London, United Kingdom (B.S.H., X.L., N.A.Q., I.M., R.A.C., Z.I.W., N.W.F.L., P.B.L., P.K., N.S.P., F.S.N.)
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15
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Gagné S, Jacquemet V. Time resolution for wavefront and phase singularity tracking using activation maps in cardiac propagation models. CHAOS (WOODBURY, N.Y.) 2020; 30:033132. [PMID: 32237790 DOI: 10.1063/1.5133077] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/22/2019] [Accepted: 03/02/2020] [Indexed: 06/11/2023]
Abstract
The dynamics of cardiac fibrillation can be described by the number, the trajectory, the stability, and the lifespan of phase singularities (PSs). Accurate PS tracking is straightforward in simple uniform tissues but becomes more challenging as fibrosis, structural heterogeneity, and strong anisotropy are combined. In this paper, we derive a mathematical formulation for PS tracking in two-dimensional reaction-diffusion models. The method simultaneously tracks wavefronts and PS based on activation maps at full spatiotemporal resolution. PS tracking is formulated as a linear assignment problem solved by the Hungarian algorithm. The cost matrix incorporates information about distances between PS, chirality, and wavefronts. A graph of PS trajectories is generated to represent the creations and annihilations of PS pairs. Structure-preserving graph transformations are applied to provide a simplified description at longer observation time scales. The approach is validated in 180 simulations of fibrillation in four different types of substrates featuring, respectively, wavebreaks, ionic heterogeneities, fibrosis, and breakthrough patterns. The time step of PS tracking is studied in the range from 0.1 to 10 ms. The results show the benefits of improving time resolution from 1 to 0.1 ms. The tracking error rate decreases by an order of magnitude because the occurrence of simultaneous events becomes less likely. As observed on PS survival curves, the graph-based analysis facilitates the identification of macroscopically stable rotors despite wavefront fragmentation by fibrosis.
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Affiliation(s)
- Samuel Gagné
- Institut de Génie Biomédical, Département de Pharmacologie et Physiologie, Université de Montréal, C.P. 6128, succursale Centre-ville, Montréal, Quebec H3C 3J7, Canada
| | - Vincent Jacquemet
- Institut de Génie Biomédical, Département de Pharmacologie et Physiologie, Université de Montréal, C.P. 6128, succursale Centre-ville, Montréal, Quebec H3C 3J7, Canada
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16
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Abstract
Determining optimal treatment strategies for complex arrhythmogenesis in AF is confounded by the lack of consensus regarding the mechanisms causing AF. Studies report different mechanisms for AF, ranging from hierarchical drivers to anarchical multiple activation wavelets. Differences in the assessment of AF mechanisms are likely due to AF being recorded across diverse models using different investigational tools, spatial scales and clinical populations. The authors review different AF mechanisms, including anatomical and functional re-entry, hierarchical drivers and anarchical multiple wavelets. They then describe different cardiac mapping techniques and analysis tools, including activation mapping, phase mapping and fibrosis identification. They explain and review different data challenges, including differences between recording devices in spatial and temporal resolutions, spatial coverage and recording surface, and report clinical outcomes using different data modalities. They suggest future research directions for investigating the mechanisms underlying human AF.
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Affiliation(s)
- Caroline H Roney
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.,Imperial Centre for Cardiac Engineering, Imperial College London, London, UK
| | - Andrew L Wit
- Imperial Centre for Cardiac Engineering, Imperial College London, London, UK.,Department of Pharmacology, Columbia University College of Physicians and Surgeons, New York, NY, US
| | - Nicholas S Peters
- Imperial Centre for Cardiac Engineering, Imperial College London, London, UK.,National Heart and Lung Institute, Imperial College London, London, UK
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17
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Li X, Roney CH, Handa BS, Chowdhury RA, Niederer SA, Peters NS, Ng FS. Standardised Framework for Quantitative Analysis of Fibrillation Dynamics. Sci Rep 2019; 9:16671. [PMID: 31723154 PMCID: PMC6853901 DOI: 10.1038/s41598-019-52976-y] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2019] [Accepted: 10/23/2019] [Indexed: 12/21/2022] Open
Abstract
The analysis of complex mechanisms underlying ventricular fibrillation (VF) and atrial fibrillation (AF) requires sophisticated tools for studying spatio-temporal action potential (AP) propagation dynamics. However, fibrillation analysis tools are often custom-made or proprietary, and vary between research groups. With no optimal standardised framework for analysis, results from different studies have led to disparate findings. Given the technical gap, here we present a comprehensive framework and set of principles for quantifying properties of wavefront dynamics in phase-processed data recorded during myocardial fibrillation with potentiometric dyes. Phase transformation of the fibrillatory data is particularly useful for identifying self-perpetuating spiral waves or rotational drivers (RDs) rotating around a phase singularity (PS). RDs have been implicated in sustaining fibrillation, and thus accurate localisation and quantification of RDs is crucial for understanding specific fibrillatory mechanisms. In this work, we assess how variation of analysis parameters and thresholds in the tracking of PSs and quantification of RDs could result in different interpretations of the underlying fibrillation mechanism. These techniques have been described and applied to experimental AF and VF data, and AF simulations, and examples are provided from each of these data sets to demonstrate the range of fibrillatory behaviours and adaptability of these tools. The presented methodologies are available as an open source software and offer an off-the-shelf research toolkit for quantifying and analysing fibrillatory mechanisms.
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Affiliation(s)
- Xinyang Li
- National Heart and Lung Institute, Hammersmith Campus, Imperial College London, 72 Du Cane Rd, London, W120UQ, UK
| | - Caroline H Roney
- School of Biomedical Engineering & Imaging Sciences, King's College London, St. Thomas' Hospital, Westminster Bridge Road, London, UK
| | - Balvinder S Handa
- National Heart and Lung Institute, Hammersmith Campus, Imperial College London, 72 Du Cane Rd, London, W120UQ, UK
| | - Rasheda A Chowdhury
- National Heart and Lung Institute, Hammersmith Campus, Imperial College London, 72 Du Cane Rd, London, W120UQ, UK
| | - Steven A Niederer
- School of Biomedical Engineering & Imaging Sciences, King's College London, St. Thomas' Hospital, Westminster Bridge Road, London, UK
| | - Nicholas S Peters
- National Heart and Lung Institute, Hammersmith Campus, Imperial College London, 72 Du Cane Rd, London, W120UQ, UK
| | - Fu Siong Ng
- National Heart and Lung Institute, Hammersmith Campus, Imperial College London, 72 Du Cane Rd, London, W120UQ, UK.
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18
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Podziemski P, Zeemering S, Kuklik P, van Hunnik A, Maesen B, Maessen J, Crijns HJ, Verheule S, Schotten U. Rotors Detected by Phase Analysis of Filtered, Epicardial Atrial Fibrillation Electrograms Colocalize With Regions of Conduction Block. Circ Arrhythm Electrophysiol 2019; 11:e005858. [PMID: 30354409 PMCID: PMC6553551 DOI: 10.1161/circep.117.005858] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND Several recent studies suggest rotors detected by phase mapping may act as main drivers of persistent atrial fibrillation. However, the electrophysiological nature of detected rotors remains unclear. We performed a direct, 1:1 comparison between phase and activation time mapping in high-density, epicardial, direct-contact mapping files of human atrial fibrillation. METHODS Thirty-eight unipolar electrogram files of 10 s duration were recorded in patients with atrial fibrillation (n=20 patients) using a 16×16 electrode array placed on the epicardial surface of the left atrial posterior wall or the right atrial free wall. Phase maps and isochrone wave maps were constructed for all recordings. For each detected phase singularity (PS) with a lifespan of >1 cycle length, the corresponding conduction pattern was investigated in the isochrone wave maps. RESULTS When using sinusoidal recomposition and Hilbert Transform, 138 PSs were detected. One hundred and four out of 138 PSs were detected within 1 electrode distance (1.5 mm) from a line of conduction block between nonrotating wavefronts detected by activation mapping. Far fewer rotating wavefronts were detected when rotating activity was identified based on wave mapping (18 out of 8219 detected waves). Fourteen out of these 18 cases were detected as PSs in phase mapping. Phase analysis of filtered electrograms produced by simulated wavefronts separated by conduction block also identified PSs on the line of conduction block. CONCLUSIONS PSs identified by phase analysis of filtered epicardial electrograms colocalize with conduction block lines identified by activation mapping. Detection of PSs using phase analysis has a low specificity for identifying rotating wavefronts during human atrial fibrillation using activation mapping.
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Affiliation(s)
- Piotr Podziemski
- Department of Physiology, Maastricht University, the Netherlands (P.P., S.Z., A.v.H., S.V.).,Cardiovascular Research Institute Maastricht (CARIM), the Netherlands (P.P., S.Z., A.v.H., B.M., J.M., H.J.C., S.V., U.S.)
| | - Stef Zeemering
- Department of Physiology, Maastricht University, the Netherlands (P.P., S.Z., A.v.H., S.V.).,Cardiovascular Research Institute Maastricht (CARIM), the Netherlands (P.P., S.Z., A.v.H., B.M., J.M., H.J.C., S.V., U.S.)
| | - Pawel Kuklik
- Department of Cardiology, Electrophysiology, University Medical Center Hamburg-Eppendorf, Germany (P.K.)
| | - Arne van Hunnik
- Department of Physiology, Maastricht University, the Netherlands (P.P., S.Z., A.v.H., S.V.).,Cardiovascular Research Institute Maastricht (CARIM), the Netherlands (P.P., S.Z., A.v.H., B.M., J.M., H.J.C., S.V., U.S.)
| | - Bart Maesen
- Cardiovascular Research Institute Maastricht (CARIM), the Netherlands (P.P., S.Z., A.v.H., B.M., J.M., H.J.C., S.V., U.S.).,Department of Cardiothoracic Surgery, Maastricht University Medical Center, the Netherlands (B.M., J.M.)
| | - Jos Maessen
- Cardiovascular Research Institute Maastricht (CARIM), the Netherlands (P.P., S.Z., A.v.H., B.M., J.M., H.J.C., S.V., U.S.).,Department of Cardiothoracic Surgery, Maastricht University Medical Center, the Netherlands (B.M., J.M.)
| | - Harry J Crijns
- Cardiovascular Research Institute Maastricht (CARIM), the Netherlands (P.P., S.Z., A.v.H., B.M., J.M., H.J.C., S.V., U.S.).,Department of Cardiology, Maastricht University Medical Center, the Netherlands (H.J.C.)
| | - Sander Verheule
- Department of Physiology, Maastricht University, the Netherlands (P.P., S.Z., A.v.H., S.V.).,Cardiovascular Research Institute Maastricht (CARIM), the Netherlands (P.P., S.Z., A.v.H., B.M., J.M., H.J.C., S.V., U.S.)
| | - Ulrich Schotten
- Department of Physiology, Maastricht University, the Netherlands (P.P., S.Z., A.v.H., S.V.).,Cardiovascular Research Institute Maastricht (CARIM), the Netherlands (P.P., S.Z., A.v.H., B.M., J.M., H.J.C., S.V., U.S.)
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19
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Ciaccio EJ, Wan EY, Saluja DS, Acharya UR, Peters NS, Garan H. Addressing challenges of quantitative methodologies and event interpretation in the study of atrial fibrillation. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2019; 178:113-122. [PMID: 31416540 PMCID: PMC6748794 DOI: 10.1016/j.cmpb.2019.06.017] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/24/2019] [Revised: 05/21/2019] [Accepted: 06/14/2019] [Indexed: 05/06/2023]
Abstract
Atrial fibrillation (AF) is the commonest arrhythmia, yet the mechanisms of its onset and persistence are incompletely known. Although techniques for quantitative assessment have been investigated, there have been few attempts to integrate this information to advance disease treatment protocols. In this review, key quantitative methods for AF analysis are described, and suggestions are provided for the coordination of the available information, and to develop foci and directions for future research efforts. Quantitative biologists may have an interest in this topic in order to develop machine learning and tools for arrhythmia characterization, but they may perhaps have a minimal background in the clinical methodology and in the types of observed events and mechanistic hypotheses that have thus far been developed. We attempt to address these issues via exploration of the published literature. Although no new data is presented in this review, examples are shown of current lines of investigation, and in particular, how electrogram analysis and whole-chamber quantitative modeling of the left atrium may be useful to characterize fibrillatory patterns of activity, so as to propose avenues for more efficacious acquisition and interpretation of AF data.
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Affiliation(s)
- Edward J Ciaccio
- Department of Medicine - Division of Cardiology, Columbia University Medical Center, New York, NY, USA; ElectroCardioMaths Programme, Imperial Centre for Cardiac Engineering, Imperial College London, London, UK.
| | - Elaine Y Wan
- Department of Medicine - Division of Cardiology, Columbia University Medical Center, New York, NY, USA
| | - Deepak S Saluja
- Department of Medicine - Division of Cardiology, Columbia University Medical Center, New York, NY, USA
| | - U Rajendra Acharya
- Department of Electronics and Computer Engineering, Ngee Ann Polytechnic, Singapore
| | - Nicholas S Peters
- ElectroCardioMaths Programme, Imperial Centre for Cardiac Engineering, Imperial College London, London, UK
| | - Hasan Garan
- Department of Medicine - Division of Cardiology, Columbia University Medical Center, New York, NY, USA
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20
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Child N, Clayton RH, Roney CH, Laughner JI, Shuros A, Neuzil P, Petru J, Jackson T, Porter B, Bostock J, Niederer SA, Razavi RS, Rinaldi CA, Taggart P, Wright MJ, Gill J. Unraveling the Underlying Arrhythmia Mechanism in Persistent Atrial Fibrillation: Results From the STARLIGHT Study. Circ Arrhythm Electrophysiol 2019; 11:e005897. [PMID: 29858382 DOI: 10.1161/circep.117.005897] [Citation(s) in RCA: 31] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/22/2017] [Accepted: 03/20/2018] [Indexed: 11/16/2022]
Abstract
BACKGROUND The mechanisms that initiate and sustain persistent atrial fibrillation are not well characterized. Ablation results remain significantly worse than in paroxysmal atrial fibrillation in which the mechanism is better understood and subsequent targeted therapy has been developed. The aim of this study was to characterize and quantify patterns of activation during atrial fibrillation using contact mapping. METHODS Patients with persistent atrial fibrillation (n=14; mean age, 61±8 years; ejection fraction, 59±10%) underwent simultaneous biatrial contact mapping with 64 electrode catheters. The atrial electrograms were transformed into phase, and subsequent spatiotemporal mapping was performed to identify phase singularities (PSs). RESULTS PSs were located in both atria, but we observed more PSs in the left atrium compared with the right atrium (779±302, 552±235; P=0.015). Although some PSs of duration sufficient to complete >1 rotation were detected, the maximum PS duration was only 1150 ms, and the vast majority (97%) of PSs persisted for too short a period to complete a full rotation. Although in selected patients there was evidence of PS local clustering, overall, PSs were distributed globally throughout both chambers with no clear anatomic predisposition. In a subset of patients (n=7), analysis was repeated using an alternative established atrial PS mapping technique, which confirmed our initial findings. CONCLUSIONS No sustained rotors or localized drivers were detected, and instead, the mechanism of arrhythmia maintenance was consistent with the multiple wavelet hypothesis, with passive activation of short-lived rotational activity. CLINICAL TRIAL REGISTRATION URL: https://www.clinicaltrials.gov. Unique identifier: NCT01765075.
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Affiliation(s)
- Nicholas Child
- Department of Imaging Sciences and Biomedical Engineering, King's College London, United Kingdom (N.C., C.R.R., T.J., B.P., S.A.N., R.S.R.).
| | - Richard H Clayton
- INSIGNEO Institute for In Silico Medicine, University of Sheffield, United Kingdom (R.H.C.)
| | - Caroline H Roney
- Department of Imaging Sciences and Biomedical Engineering, King's College London, United Kingdom (N.C., C.R.R., T.J., B.P., S.A.N., R.S.R.)
| | | | - Allan Shuros
- Boston Scientific Corp, St. Paul, MN (J.I.L., A.S.)
| | - Petr Neuzil
- Department of Cardiology, Na Holmolce Hospital, Prague, Czech Republic (P.N., J.P.)
| | - Jan Petru
- Department of Cardiology, Na Holmolce Hospital, Prague, Czech Republic (P.N., J.P.)
| | - Tom Jackson
- Department of Imaging Sciences and Biomedical Engineering, King's College London, United Kingdom (N.C., C.R.R., T.J., B.P., S.A.N., R.S.R.)
| | - Bradley Porter
- Department of Imaging Sciences and Biomedical Engineering, King's College London, United Kingdom (N.C., C.R.R., T.J., B.P., S.A.N., R.S.R.)
| | - Julian Bostock
- Department of Cardiology, Guy's and St Thomas' Hospital, London, United Kingdom (J.B., C.A.R., M.J.W., J.G.)
| | - Steven A Niederer
- Department of Imaging Sciences and Biomedical Engineering, King's College London, United Kingdom (N.C., C.R.R., T.J., B.P., S.A.N., R.S.R.)
| | - Reza S Razavi
- Department of Imaging Sciences and Biomedical Engineering, King's College London, United Kingdom (N.C., C.R.R., T.J., B.P., S.A.N., R.S.R.)
| | - Christopher A Rinaldi
- Department of Cardiology, Guy's and St Thomas' Hospital, London, United Kingdom (J.B., C.A.R., M.J.W., J.G.)
| | | | - Matthew J Wright
- Department of Cardiology, Guy's and St Thomas' Hospital, London, United Kingdom (J.B., C.A.R., M.J.W., J.G.)
| | - Jaswinder Gill
- Department of Cardiology, Guy's and St Thomas' Hospital, London, United Kingdom (J.B., C.A.R., M.J.W., J.G.)
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21
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Ganesan P, Cherry EM, Huang DT, Pertsov AM, Ghoraani B. Locating Atrial Fibrillation Rotor and Focal Sources Using Iterative Navigation of Multipole Diagnostic Catheters. Cardiovasc Eng Technol 2019; 10:354-366. [PMID: 30989616 PMCID: PMC6527788 DOI: 10.1007/s13239-019-00414-5] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/03/2018] [Accepted: 04/08/2019] [Indexed: 01/14/2023]
Abstract
Purpose Multi-polar diagnostic catheters are used to construct the 3D electro-anatomic mapping of the atrium during atrial fibrillation (AF) ablation procedures; however, it remains unclear how to use the electrograms recorded by these catheters to locate AF-driving sites known as focal and rotor source types. The purpose of this study is to present the first algorithm to iteratively navigate a circular multi-polar catheter to locate AF focal and rotor sources without the need to map the entire atria. Methods Starting from an initial location, the algorithm, which was blinded to the location and type of the AF source, iteratively advanced a Lasso catheter based on its electrogram characteristics. The algorithm stopped the catheter when it located of an AF source and identified the type. The efficiency of the algorithm is validated using a set of simulated focal and rotor-driven arrhythmias in fibrotic human 2D and 3D atrial tissue. Results Our study shows the feasibility of locating AF sources with a success rate of greater than 95.25% within average 7.56 ± 2.28 placements independently of the initial position of the catheter and the source type. Conclusions The algorithm could play a critical role in clinical electrophysiology laboratories for mapping patient-specific ablation of AF sources located outside the pulmonary veins and improving the procedure success. Electronic supplementary material The online version of this article (10.1007/s13239-019-00414-5) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Prasanth Ganesan
- Department of Computer and Electrical Engineering, Florida Atlantic University, Boca Raton, FL, USA
| | - Elizabeth M Cherry
- School of Mathematical Sciences, Rochester Institute of Technology, Rochester, NY, USA
| | - David T Huang
- Department of Cardiology, University of Rochester Medical Center, Rochester, NY, USA
| | - Arkady M Pertsov
- Department of Pharmacology, SUNY Upstate Medical Center, Syracuse, NY, USA
| | - Behnaz Ghoraani
- Department of Computer and Electrical Engineering, Florida Atlantic University, Boca Raton, FL, USA. .,, 777 Glades Road, EE (Bldg. 96) Room 319, Boca Raton, FL, 33431, USA.
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22
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Vicera JJB, Lo LW, Shinya Y, Chou YH, Lin YJ, Lo MT, Lin WL, Liu SH, Cheng WH, Tsai TY, Chen SA. Ultra-rapid high-density mapping system with the phase singularity technique is feasible in identifying rotors and focal sources and predicting AF termination. J Cardiovasc Electrophysiol 2019; 30:952-963. [PMID: 30983063 DOI: 10.1111/jce.13952] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/31/2018] [Revised: 03/12/2019] [Accepted: 03/13/2019] [Indexed: 11/29/2022]
Abstract
INTRODUCTION Phase singularity (PS) mapping provides additional insight into the AF mechanism and is accurate in identifying rotors. The study aimed to evaluate the feasibility of PS mapping in identifying AF rotors using data obtained from an automatic ultra-rapid high-resolution mapping system with a high-density mini-basket catheter. METHODS Twenty-three pigs underwent rapid right atrial (RA) pacing (RAP 480 bpm) for 5 weeks before the experiment. During AF, RA endocardial automatic continuous mappings with a mini-basket catheter were generated using an automatic ultra-rapid mapping system. Both fractionation mapping and waveform similarity measurements using a PS mapping algorithm were applied on the same recording signals to localize substrates maintaining AF. RESULTS Seventeen (74%) pigs developed sustained AF after RAP. Three were excluded because of periprocedural ventricular arrhythmia and corrupted digital data. RA fractionation maps were acquired with 6.17 ± 4.29 minutes mean acquisition time, 13768 ± 12698 acquisition points mapped during AF from 581 ± 387 beats. Fractionation mapping identified extensively distributed (66.7%) RA complex fractionated atrial electrogram (CFAE), whereas the nonlinear analysis identified high similarity index (SI > 0.7) parts in limited areas (23.7%). There was an average of 1.67 ± 0.87 SI sites with 0.43 ± 0.76 rotor/focal source/chamber. AF termination occurred in 11/16 (68.75%) AF events in 14 pigs during ablation targeting max CFAE. There was a higher incidence of rotor/focal source at AF termination sites compared with non-AF termination sites (54.5% vs 0%, P = 0.011). CONCLUSIONS The data obtained from ultra-rapid high-density automatic mapping is feasible and effective in identifying AF rotors/focal sources using PS technique, and those critical substrates were closely related to AF procedural termination.
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Affiliation(s)
- Jennifer Jeanne B Vicera
- Heart Rhythm Center and Division of Cardiology, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Li-Wei Lo
- Heart Rhythm Center and Division of Cardiology, Taipei Veterans General Hospital, Taipei, Taiwan.,Institute of Clinical Medicine and Cardiovascular Research Institute, National Yang-Ming University, Taipei, Taiwan
| | - Yamada Shinya
- Department of Cardiovascular Medicine, Fukushima Medical University, Fukushima, Japan
| | - Yu-Hui Chou
- Heart Rhythm Center and Division of Cardiology, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Yenn-Jiang Lin
- Heart Rhythm Center and Division of Cardiology, Taipei Veterans General Hospital, Taipei, Taiwan.,Institute of Clinical Medicine and Cardiovascular Research Institute, National Yang-Ming University, Taipei, Taiwan
| | - Men-Tzung Lo
- Department of Biomedical Sciences and Engineering National Central University, Taoyuan, Taiwan
| | - Wei-Lun Lin
- Heart Rhythm Center and Division of Cardiology, Taipei Veterans General Hospital, Taipei, Taiwan.,Institute of Clinical Medicine and Cardiovascular Research Institute, National Yang-Ming University, Taipei, Taiwan
| | - Shin-Huei Liu
- Heart Rhythm Center and Division of Cardiology, Taipei Veterans General Hospital, Taipei, Taiwan.,Institute of Clinical Medicine and Cardiovascular Research Institute, National Yang-Ming University, Taipei, Taiwan
| | - Wen-Han Cheng
- Heart Rhythm Center and Division of Cardiology, Taipei Veterans General Hospital, Taipei, Taiwan.,Institute of Clinical Medicine and Cardiovascular Research Institute, National Yang-Ming University, Taipei, Taiwan
| | - Tsung-Ying Tsai
- Heart Rhythm Center and Division of Cardiology, Taipei Veterans General Hospital, Taipei, Taiwan.,Institute of Clinical Medicine and Cardiovascular Research Institute, National Yang-Ming University, Taipei, Taiwan
| | - Shih-Ann Chen
- Heart Rhythm Center and Division of Cardiology, Taipei Veterans General Hospital, Taipei, Taiwan.,Institute of Clinical Medicine and Cardiovascular Research Institute, National Yang-Ming University, Taipei, Taiwan
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23
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Ganesan P, Salmin A, Cherry EM, Huang DT, Pertsov AM, Ghoraani B. Iterative navigation of multipole diagnostic catheters to locate repeating-pattern atrial fibrillation drivers. J Cardiovasc Electrophysiol 2019; 30:758-768. [PMID: 30725499 PMCID: PMC6554033 DOI: 10.1111/jce.13872] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/12/2018] [Revised: 01/16/2019] [Accepted: 01/31/2019] [Indexed: 01/01/2023]
Abstract
Introduction Targeting repeating‐pattern atrial fibrillation (AF) sources (reentry or focal drivers) can help in patient‐specific ablation therapy for AF; however, the development of reliable and accurate tools for locating such sources remains a major challenge. We describe iterative catheter navigation (ICAN) algorithm to locate AF drivers using a conventional circular Lasso catheter. Methods and Results At each step, the algorithm analyzes 10 bipolar electrograms recoded at a given catheter location and the history of previous catheter movements to determine if the source is inside the catheter loop. If not, it calculates new coordinates and selects a new position for the catheter. The process continues until a source is located. The algorithm was evaluated in a computer model of atrial tissue with various degrees of fibrosis under a broad range of arrhythmia scenarios. The latter included slow and fast reentry, macroreentry, figure‐of‐eight reentry, and fibrillatory conduction. Depending on the initial distance of the catheter from the source and scenario, it took about 3 to 16 steps to localize an AF source. In 94% of cases, the identified location was within 4 mm from the source, independently of the initial position of the catheter. The algorithm worked equally well in the presence of patchy fibrosis, low‐voltage areas, fragmented electrograms, and dominant‐frequency gradients. Conclusions AF repeating‐pattern sources can be localized using circular catheters without the need to map the entire tissue. The proposed algorithm has the potential to become a useful tool for patient‐specific ablation of AF sources located outside the pulmonary veins.
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Affiliation(s)
- Prasanth Ganesan
- Computer and Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, Florida
| | - Anthony Salmin
- School of Mathematical Sciences, Rochester Institute of Technology, Rochester, New York
| | - Elizabeth M Cherry
- School of Mathematical Sciences, Rochester Institute of Technology, Rochester, New York
| | - David T Huang
- Department of Cardiology, University of Rochester Medical Center, Rochester, New York
| | - Arkady M Pertsov
- Department of Pharmacology, SUNY Upstate Medical Center, Syracuse, New York
| | - Behnaz Ghoraani
- Computer and Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, Florida
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24
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O'Shea C, Holmes AP, Yu TY, Winter J, Wells SP, Correia J, Boukens BJ, De Groot JR, Chu GS, Li X, Ng GA, Kirchhof P, Fabritz L, Rajpoot K, Pavlovic D. ElectroMap: High-throughput open-source software for analysis and mapping of cardiac electrophysiology. Sci Rep 2019; 9:1389. [PMID: 30718782 PMCID: PMC6362081 DOI: 10.1038/s41598-018-38263-2] [Citation(s) in RCA: 54] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2018] [Accepted: 12/21/2018] [Indexed: 02/04/2023] Open
Abstract
The ability to record and analyse electrical behaviour across the heart using optical and electrode mapping has revolutionised cardiac research. However, wider uptake of these technologies is constrained by the lack of multi-functional and robustly characterised analysis and mapping software. We present ElectroMap, an adaptable, high-throughput, open-source software for processing, analysis and mapping of complex electrophysiology datasets from diverse experimental models and acquisition modalities. Key innovation is development of standalone module for quantification of conduction velocity, employing multiple methodologies, currently not widely available to researchers. ElectroMap has also been designed to support multiple methodologies for accurate calculation of activation, repolarisation, arrhythmia detection, calcium handling and beat-to-beat heterogeneity. ElectroMap implements automated signal segmentation, ensemble averaging and integrates optogenetic approaches. Here we employ ElectroMap for analysis, mapping and detection of pro-arrhythmic phenomena in silico, in cellulo, animal model and in vivo patient datasets. We anticipate that ElectroMap will accelerate innovative cardiac research and enhance the uptake, application and interpretation of mapping technologies leading to novel approaches for arrhythmia prevention.
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Affiliation(s)
- Christopher O'Shea
- Institute of Cardiovascular Sciences, University of Birmingham, Birmingham, UK
- EPSRC Centre for Doctoral Training in Physical Sciences for Health, School of Chemistry, University of Birmingham, Birmingham, UK
- School of Computer Science, University of Birmingham, Birmingham, UK
| | - Andrew P Holmes
- Institute of Cardiovascular Sciences, University of Birmingham, Birmingham, UK
- Institute of Clinical Sciences, University of Birmingham, Birmingham, UK
| | - Ting Y Yu
- Institute of Cardiovascular Sciences, University of Birmingham, Birmingham, UK
| | - James Winter
- Institute of Cardiovascular Sciences, University of Birmingham, Birmingham, UK
| | - Simon P Wells
- Institute of Cardiovascular Sciences, University of Birmingham, Birmingham, UK
- Department of Physiology, University of Melbourne, Melbourne, Australia
| | - Joao Correia
- Institute of Microbiology and Infection, School of Biosciences, University of Birmingham, Birmingham, UK
| | - Bastiaan J Boukens
- Amsterdam UMC, University of Amsterdam, Department of Anatomy and Physiology, Amsterdam, The Netherlands
| | - Joris R De Groot
- Amsterdam UMC, University of Amsterdam, Heart Center, Department of Cardiology, Amsterdam, The Netherlands
| | - Gavin S Chu
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, UK
| | - Xin Li
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
| | - G Andre Ng
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, UK
| | - Paulus Kirchhof
- Institute of Cardiovascular Sciences, University of Birmingham, Birmingham, UK
- Department of Cardiology, UHB NHS Trust, Birmingham, UK
| | - Larissa Fabritz
- Institute of Cardiovascular Sciences, University of Birmingham, Birmingham, UK
- Department of Cardiology, UHB NHS Trust, Birmingham, UK
| | - Kashif Rajpoot
- School of Computer Science, University of Birmingham, Birmingham, UK.
| | - Davor Pavlovic
- Institute of Cardiovascular Sciences, University of Birmingham, Birmingham, UK.
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25
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Orozco-Duque A, Tobón C, Ugarte JP, Morillo C, Bustamante J. Electroanatomical mapping based on discrimination of electrograms clusters for localization of critical sites in atrial fibrillation. PROGRESS IN BIOPHYSICS AND MOLECULAR BIOLOGY 2019; 141:37-46. [DOI: 10.1016/j.pbiomolbio.2018.07.003] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/22/2018] [Revised: 05/07/2018] [Accepted: 07/03/2018] [Indexed: 11/30/2022]
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26
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Jacquemet V. Phase singularity detection through phase map interpolation: Theory, advantages and limitations. Comput Biol Med 2018; 102:381-389. [DOI: 10.1016/j.compbiomed.2018.07.014] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2018] [Revised: 07/18/2018] [Accepted: 07/19/2018] [Indexed: 10/28/2022]
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27
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Handa BS, Roney CH, Houston C, Qureshi NA, Li X, Pitcher DS, Chowdhury RA, Lim PB, Dupont E, Niederer SA, Cantwell CD, Peters NS, Ng FS. Analytical approaches for myocardial fibrillation signals. Comput Biol Med 2018; 102:315-326. [PMID: 30025847 PMCID: PMC6215772 DOI: 10.1016/j.compbiomed.2018.07.008] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2018] [Revised: 07/11/2018] [Accepted: 07/11/2018] [Indexed: 12/11/2022]
Abstract
Atrial and ventricular fibrillation are complex arrhythmias, and their underlying mechanisms remain widely debated and incompletely understood. This is partly because the electrical signals recorded during myocardial fibrillation are themselves complex and difficult to interpret with simple analytical tools. There are currently a number of analytical approaches to handle fibrillation data. Some of these techniques focus on mapping putative drivers of myocardial fibrillation, such as dominant frequency, organizational index, Shannon entropy and phase mapping. Other techniques focus on mapping the underlying myocardial substrate sustaining fibrillation, such as voltage mapping and complex fractionated electrogram mapping. In this review, we discuss these techniques, their application and their limitations, with reference to our experimental and clinical data. We also describe novel tools including a new algorithm to map microreentrant circuits sustaining fibrillation.
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Affiliation(s)
- Balvinder S Handa
- ElectroCardioMaths, Imperial Centre for Cardiac Engineering, National Heart & Lung Institute, Imperial College London, United Kingdom
| | - Caroline H Roney
- Division of Imaging Sciences and Bioengineering, King's College London, United Kingdom
| | - Charles Houston
- ElectroCardioMaths, Imperial Centre for Cardiac Engineering, National Heart & Lung Institute, Imperial College London, United Kingdom
| | - Norman A Qureshi
- ElectroCardioMaths, Imperial Centre for Cardiac Engineering, National Heart & Lung Institute, Imperial College London, United Kingdom
| | - Xinyang Li
- ElectroCardioMaths, Imperial Centre for Cardiac Engineering, National Heart & Lung Institute, Imperial College London, United Kingdom
| | - David S Pitcher
- ElectroCardioMaths, Imperial Centre for Cardiac Engineering, National Heart & Lung Institute, Imperial College London, United Kingdom
| | - Rasheda A Chowdhury
- ElectroCardioMaths, Imperial Centre for Cardiac Engineering, National Heart & Lung Institute, Imperial College London, United Kingdom
| | - Phang Boon Lim
- ElectroCardioMaths, Imperial Centre for Cardiac Engineering, National Heart & Lung Institute, Imperial College London, United Kingdom
| | - Emmanuel Dupont
- ElectroCardioMaths, Imperial Centre for Cardiac Engineering, National Heart & Lung Institute, Imperial College London, United Kingdom
| | - Steven A Niederer
- Division of Imaging Sciences and Bioengineering, King's College London, United Kingdom
| | - Chris D Cantwell
- ElectroCardioMaths, Imperial Centre for Cardiac Engineering, National Heart & Lung Institute, Imperial College London, United Kingdom; Department of Aeronautics, Imperial College London, United Kingdom
| | - Nicholas S Peters
- ElectroCardioMaths, Imperial Centre for Cardiac Engineering, National Heart & Lung Institute, Imperial College London, United Kingdom
| | - Fu Siong Ng
- ElectroCardioMaths, Imperial Centre for Cardiac Engineering, National Heart & Lung Institute, Imperial College London, United Kingdom.
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28
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Sahli Costabal F, Zaman JAB, Kuhl E, Narayan SM. Interpreting Activation Mapping of Atrial Fibrillation: A Hybrid Computational/Physiological Study. Ann Biomed Eng 2018; 46:257-269. [PMID: 29214421 PMCID: PMC5880222 DOI: 10.1007/s10439-017-1969-3] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2017] [Accepted: 11/23/2017] [Indexed: 11/30/2022]
Abstract
Atrial fibrillation is the most common rhythm disorder of the heart associated with a rapid and irregular beating of the upper chambers. Activation mapping remains the gold standard to diagnose and interpret atrial fibrillation. However, fibrillatory activation maps are highly sensitive to far-field effects, and often disagree with other optical mapping modalities. Here we show that computational modeling can identify spurious non-local components of atrial fibrillation electrograms and improve activation mapping. We motivate our approach with a cohort of patients with potential drivers of persistent atrial fibrillation. In a computational study using a monodomain Maleckar model, we demonstrate that in organized rhythms, electrograms successfully track local activation, whereas in atrial fibrillation, electrograms are sensitive to spiral wave distance and number, spiral tip trajectories, and effects of fibrosis. In a clinical study, we analyzed n = 15 patients with persistent atrial fibrillation that was terminated by limited ablation. In five cases, traditional activation maps revealed a spiral wave at sites of termination; in ten cases, electrogram timings were ambiguous and activation maps showed incomplete reentry. By adjusting electrogram timing through computational modeling, we found rotational activation, which was undetectable with conventional methods. Our results demonstrate that computational modeling can identify non-local deflections to improve activation mapping and explain how and where ablation can terminate persistent atrial fibrillation. Our hybrid computational/physiological approach has the potential to optimize map-guided ablation and improve ablation therapy in atrial fibrillation.
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29
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Jacquemet V. A statistical model of false negative and false positive detection of phase singularities. CHAOS (WOODBURY, N.Y.) 2017; 27:103124. [PMID: 29092458 DOI: 10.1063/1.4999939] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
The complexity of cardiac fibrillation dynamics can be assessed by analyzing the distribution of phase singularities (PSs) observed using mapping systems. Interelectrode distance, however, limits the accuracy of PS detection. To investigate in a theoretical framework the PS false negative and false positive rates in relation to the characteristics of the mapping system and fibrillation dynamics, we propose a statistical model of phase maps with controllable number and locations of PSs. In this model, phase maps are generated from randomly distributed PSs with physiologically-plausible directions of rotation. Noise and distortion of the phase are added. PSs are detected using topological charge contour integrals on regular grids of varying resolutions. Over 100 × 106 realizations of the random field process are used to estimate average false negative and false positive rates using a Monte-Carlo approach. The false detection rates are shown to depend on the average distance between neighboring PSs expressed in units of interelectrode distance, following approximately a power law with exponents in the range of 1.14 to 2 for false negatives and around 2.8 for false positives. In the presence of noise or distortion of phase, false detection rates at high resolution tend to a non-zero noise-dependent lower bound. This model provides an easy-to-implement tool for benchmarking PS detection algorithms over a broad range of configurations with multiple PSs.
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Affiliation(s)
- Vincent Jacquemet
- Département de Pharmacologie et Physiologie, Institut de Génie Biomédical, Université de Montréal, Montréal, Québec H4J 1C5, Canada
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30
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Roney CH, Cantwell CD, Bayer JD, Qureshi NA, Lim PB, Tweedy JH, Kanagaratnam P, Peters NS, Vigmond EJ, Ng FS. Spatial Resolution Requirements for Accurate Identification of Drivers of Atrial Fibrillation. Circ Arrhythm Electrophysiol 2017; 10:e004899. [PMID: 28500175 PMCID: PMC5434962 DOI: 10.1161/circep.116.004899] [Citation(s) in RCA: 85] [Impact Index Per Article: 12.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/20/2016] [Accepted: 04/11/2017] [Indexed: 11/25/2022]
Abstract
Supplemental Digital Content is available in the text. Background— Recent studies have demonstrated conflicting mechanisms underlying atrial fibrillation (AF), with the spatial resolution of data often cited as a potential reason for the disagreement. The purpose of this study was to investigate whether the variation in spatial resolution of mapping may lead to misinterpretation of the underlying mechanism in persistent AF. Methods and Results— Simulations of rotors and focal sources were performed to estimate the minimum number of recording points required to correctly identify the underlying AF mechanism. The effects of different data types (action potentials and unipolar or bipolar electrograms) and rotor stability on resolution requirements were investigated. We also determined the ability of clinically used endocardial catheters to identify AF mechanisms using clinically recorded and simulated data. The spatial resolution required for correct identification of rotors and focal sources is a linear function of spatial wavelength (the distance between wavefronts) of the arrhythmia. Rotor localization errors are larger for electrogram data than for action potential data. Stationary rotors are more reliably identified compared with meandering trajectories, for any given spatial resolution. All clinical high-resolution multipolar catheters are of sufficient resolution to accurately detect and track rotors when placed over the rotor core although the low-resolution basket catheter is prone to false detections and may incorrectly identify rotors that are not present. Conclusions— The spatial resolution of AF data can significantly affect the interpretation of the underlying AF mechanism. Therefore, the interpretation of human AF data must be taken in the context of the spatial resolution of the recordings.
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Affiliation(s)
- Caroline H Roney
- From the ElectroCardioMaths Programme (C.H.R., C.D.C., N.A.Q., P.B.L., P.K., N.S.P., F.S.N.), and the Department of Bioengineering (J.H.T.), Imperial College London, United Kingdom; IHU Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Université, Pessac-Bordeaux, France (J.D.B., E.J.V.); and Université de Bordeaux, IMB, UMR 5251, Talence, France (J.D.B., E.J.V.)
| | - Chris D Cantwell
- From the ElectroCardioMaths Programme (C.H.R., C.D.C., N.A.Q., P.B.L., P.K., N.S.P., F.S.N.), and the Department of Bioengineering (J.H.T.), Imperial College London, United Kingdom; IHU Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Université, Pessac-Bordeaux, France (J.D.B., E.J.V.); and Université de Bordeaux, IMB, UMR 5251, Talence, France (J.D.B., E.J.V.)
| | - Jason D Bayer
- From the ElectroCardioMaths Programme (C.H.R., C.D.C., N.A.Q., P.B.L., P.K., N.S.P., F.S.N.), and the Department of Bioengineering (J.H.T.), Imperial College London, United Kingdom; IHU Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Université, Pessac-Bordeaux, France (J.D.B., E.J.V.); and Université de Bordeaux, IMB, UMR 5251, Talence, France (J.D.B., E.J.V.)
| | - Norman A Qureshi
- From the ElectroCardioMaths Programme (C.H.R., C.D.C., N.A.Q., P.B.L., P.K., N.S.P., F.S.N.), and the Department of Bioengineering (J.H.T.), Imperial College London, United Kingdom; IHU Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Université, Pessac-Bordeaux, France (J.D.B., E.J.V.); and Université de Bordeaux, IMB, UMR 5251, Talence, France (J.D.B., E.J.V.)
| | - Phang Boon Lim
- From the ElectroCardioMaths Programme (C.H.R., C.D.C., N.A.Q., P.B.L., P.K., N.S.P., F.S.N.), and the Department of Bioengineering (J.H.T.), Imperial College London, United Kingdom; IHU Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Université, Pessac-Bordeaux, France (J.D.B., E.J.V.); and Université de Bordeaux, IMB, UMR 5251, Talence, France (J.D.B., E.J.V.)
| | - Jennifer H Tweedy
- From the ElectroCardioMaths Programme (C.H.R., C.D.C., N.A.Q., P.B.L., P.K., N.S.P., F.S.N.), and the Department of Bioengineering (J.H.T.), Imperial College London, United Kingdom; IHU Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Université, Pessac-Bordeaux, France (J.D.B., E.J.V.); and Université de Bordeaux, IMB, UMR 5251, Talence, France (J.D.B., E.J.V.)
| | - Prapa Kanagaratnam
- From the ElectroCardioMaths Programme (C.H.R., C.D.C., N.A.Q., P.B.L., P.K., N.S.P., F.S.N.), and the Department of Bioengineering (J.H.T.), Imperial College London, United Kingdom; IHU Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Université, Pessac-Bordeaux, France (J.D.B., E.J.V.); and Université de Bordeaux, IMB, UMR 5251, Talence, France (J.D.B., E.J.V.)
| | - Nicholas S Peters
- From the ElectroCardioMaths Programme (C.H.R., C.D.C., N.A.Q., P.B.L., P.K., N.S.P., F.S.N.), and the Department of Bioengineering (J.H.T.), Imperial College London, United Kingdom; IHU Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Université, Pessac-Bordeaux, France (J.D.B., E.J.V.); and Université de Bordeaux, IMB, UMR 5251, Talence, France (J.D.B., E.J.V.).
| | - Edward J Vigmond
- From the ElectroCardioMaths Programme (C.H.R., C.D.C., N.A.Q., P.B.L., P.K., N.S.P., F.S.N.), and the Department of Bioengineering (J.H.T.), Imperial College London, United Kingdom; IHU Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Université, Pessac-Bordeaux, France (J.D.B., E.J.V.); and Université de Bordeaux, IMB, UMR 5251, Talence, France (J.D.B., E.J.V.)
| | - Fu Siong Ng
- From the ElectroCardioMaths Programme (C.H.R., C.D.C., N.A.Q., P.B.L., P.K., N.S.P., F.S.N.), and the Department of Bioengineering (J.H.T.), Imperial College London, United Kingdom; IHU Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Université, Pessac-Bordeaux, France (J.D.B., E.J.V.); and Université de Bordeaux, IMB, UMR 5251, Talence, France (J.D.B., E.J.V.)
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