Functional Reentry Research Articles

The importance of scar border zone size in VT presentation and recurrence in post MI patients

Abstract Introduction Available mapping data in post-myocardial infarction patients describe ventricular tachycardia (VT) re-entry circuit characteristics of slow VT, that are typically related to transmural scars. Fast VTs with cycle lengths close to the refractory period may be related to functional re-entry in the scar border zone. Functional re-entry related border zone VTs may be difficult to control by ablation. Purpose The aims of this study are (1) to describe electroanatomical voltage map (EAVM) characteristics in post myocardial infarction (MI) patients with spontaneous and inducible fast VTs and (2) to assess the relation between scar border zone size and ablation outcomes. Methods Consecutive post-MI patients undergoing VT ablation at a tertiary referral center from January 2012 to November 2018 were included. Fast VT was defined as a VT cycle length (VTCL) = ventricular refractory period + max. 30ms. Areas of scar border zone (using 0.5 – 2.1mV/3.0mV cut-offs (according to LV remodeling stage; LVEF<47% and LV end-systolic volume index of >50 ml/m2)) were measured on the EAVM and correlated with clinical outcomes. Results In total, 138 patients were included (86% male; left ventricular ejection fraction 35±10%; 86% remodeled LV). Twenty-three patients (17%) had ≥1 fast VT (mean VTCL 275±52ms) at presentation, mean VTCL of the remaining patients 397±88ms). The median scar border zone size was 27% [IQR 20-38] of the left ventricular endocardial surface. Patients who presented with a spontaneous fast VT had a larger border zone than patients with slower VT (32% [IQR 28 – 41] vs. 25% [IQR 16 – 36], p=0.01). After ablation, 79 (57%) patients remained inducible for any VT, including 59/79 (75%) for a fast VT (median VTCL fast VT 260ms [IQR 236 -280]). Patients who remained inducible for fast VTs had a larger border zone than patients who remained inducible for slower VTs (35% [IQR 27 – 44] vs. 26% [IQR 20 – 36], p<0.001). During a median follow-up of 26 months [IQR 8 – 47], 45 patients (33%) had a VT recurrence (mean VTCL 357±98ms). Patients with a below median (27%) scar border zone area had a lower VT recurrence rate compared to patients with an above median scar border zone area (recurrence rate: 16/66 (24%) vs. 29/72 (40%), p=0.03). Kaplan-Meier survival analysis showed better free VT survival in the below median border zone patients (Log-rank: p<0.05) (Figure 1). Conclusion Patients who present with spontaneous fast VTs or who remain inducible for fast VTs after ablation have larger scar border zones during EAVM compared to patients with presenting or remaining slower VTs. A larger border zone appeared to be associated with higher VT-recurrence rates. The scar border zone may play an important role as VT substrate for (fast) VTs and may not be easily targeted by current ablation techniques.VT-free survival stratified by median BZ

NADPH Oxidases and Oxidative Stress in the Pathogenesis of Atrial Fibrillation.

Atrial fibrillation (AF) is the most common type of cardiac arrhythmia and its prevalence increases with age. The irregular and rapid contraction of the atria can lead to ineffective blood pumping, local blood stasis, blood clots, ischemic stroke, and heart failure. NADPH oxidases (NOX) and mitochondria are the main sources of reactive oxygen species in the heart, and dysregulated activation of NOX and mitochondrial dysfunction are associated with AF pathogenesis. NOX- and mitochondria-derived oxidative stress contribute to the onset of paroxysmal AF by inducing electrophysiological changes in atrial myocytes and structural remodeling in the atria. Because high atrial activity causes cardiac myocytes to expend extremely high energy to maintain excitation-contraction coupling during persistent AF, mitochondria, the primary energy source, undergo metabolic stress, affecting their morphology, Ca2+ handling, and ATP generation. In this review, we discuss the role of oxidative stress in activating AF-triggered activities, regulating intracellular Ca2+ handling, and functional and anatomical reentry mechanisms, all of which are associated with AF initiation, perpetuation, and progression. Changes in the extracellular matrix, inflammation, ion channel expression and function, myofibril structure, and mitochondrial function occur during the early transitional stages of AF, opening a window of opportunity to target NOX and mitochondria-derived oxidative stress using isoform-specific NOX inhibitors and mitochondrial ROS scavengers, as well as drugs that improve mitochondrial dynamics and metabolism to treat persistent AF and its transition to permanent AF.

Explainable Machine Learning to Predict Anchored Reentry Substrate Created by Persistent Atrial Fibrillation Ablation in Computational Models.

Background Postablation arrhythmia recurrence occurs in ~40% of patients with persistent atrial fibrillation. Fibrotic remodeling exacerbates arrhythmic activity in persistent atrial fibrillation and can play a key role in reentrant arrhythmia, but emergent interaction between nonconductive ablation-induced scar and native fibrosis (ie, residual fibrosis) is poorly understood. Methods and Results We conducted computational simulations in pre- and postablation left atrial models reconstructed from late gadolinium enhanced magnetic resonance imaging scans to test the hypothesis that ablation in patients with persistent atrial fibrillation creates new substrate conducive to recurrent arrhythmia mediated by anchored reentry. We trained a random forest machine learning classifier to accurately pinpoint specific nonconductive tissue regions (ie, areas of ablation-delivered scar or vein/valve boundaries) with the capacity to serve as substrate for anchored reentry-driven recurrent arrhythmia (area under the curve: 0.91±0.03). Our analysis suggests there is a distinctive nonconductive tissue pattern prone to serving as arrhythmogenic substrate in postablation models, defined by a specific size and proximity to residual fibrosis. Conclusions Overall, this suggests persistent atrial fibrillation ablation transforms substrate that favors functional reentry (ie, rotors meandering in excitable tissue) into an arrhythmogenic milieu more conducive to anchored reentry. Our work also indicates that explainable machine learning and computational simulations can be combined to effectively probe mechanisms of recurrent arrhythmia.

Cardiac Alternans: From Bedside to Bench and Back

Cardiac alternans arises from dynamical instabilities in the electrical and calcium cycling systems of the heart, and often precedes ventricular arrhythmias and sudden cardiac death. In this review, we integrate clinical observations with theory and experiment to paint a holistic portrait of cardiac alternans: the underlying mechanisms, arrhythmic manifestations and electrocardiographic signatures. We first summarize the cellular and tissue mechanisms of alternans that have been demonstrated both theoretically and experimentally, including 3 voltage-driven and 2 calcium-driven alternans mechanisms. Based on experimental and simulation results, we describe their relevance to mechanisms of arrhythmogenesis under different disease conditions, and their link to electrocardiographic characteristics of alternans observed in patients. Our major conclusion is that alternans is not only a predictor, but also a causal mechanism of potentially lethal ventricular and atrial arrhythmias across the full spectrum of arrhythmia mechanisms that culminate in functional reentry, although less important for anatomic reentry and focal arrhythmias.

Quantifying the impact of shape uncertainty on predicted arrhythmias

Background.Personalised computer models are increasingly used to diagnose cardiac arrhythmias and tailor treatment. Patient-specific models of the left atrium are often derived from pre-procedural imaging of anatomy and fibrosis. These images contain noise that can affect simulation predictions. There are few computationally tractable methods for propagating uncertainties from images to clinical predictions. Method.We describe the left atrium anatomy using our Bayesian shape model that captures anatomical uncertainty in medical images and has been validated on 63 independent clinical images. This algorithm describes the left atrium anatomy using Nmodes=15 principal components, capturing 95% of the shape variance and calculated from 70 clinical cardiac magnetic resonance (CMR) images. Latent variables encode shape uncertainty: we evaluate their posterior distribution for each new anatomy. We assume a normally distributed prior. We use the unscented transform to sample from the posterior shape distribution. For each sample, we assign the local material properties of the tissue using the projection of late gadolinium enhancement CMR (LGE-CMR) onto the anatomy to estimate local fibrosis. To test which activation patterns an atrium can sustain, we perform an arrhythmia simulation for each sample. We consider 34 possible outcomes (31 macro-re-entries, functional re-entry, atrial fibrillation, and non-sustained arrhythmia). For each sample, we determine the outcome by comparing pre- and post-ablation activation patterns following a cross-field stimulus. Results.We create patient-specific atrial electrophysiology models of ten patients. We validate the mean and standard deviation maps from the unscented transform with the same statistics obtained with 12,000 Monte Carlo (ground truth) samples. We found discrepancies <3% and <2% for the mean and standard deviation for fibrosis burden and activation time, respectively. For each patient case, we then compare the predicted outcome from a model built on the clinical data (deterministic approach) with the probability distribution obtained from the simulated samples. We found that the deterministic approach did not predict the most likely outcome in 80% of the cases. Finally, we estimate the influence of each source of uncertainty independently. Fixing the anatomy to the posterior mean and maintaining uncertainty in fibrosis reduced the prediction of self-terminating arrhythmias from ≃14% to ≃7%. Keeping the fibrosis fixed to the sample mean while retaining uncertainty in shape decreased the prediction of substrate-driven arrhythmias from ≃33% to ≃18% and increased the prediction of macro-re-entries from ≃54% to ≃68%. Conclusions.We presented a novel method for propagating shape uncertainty in atrial models through to uncertainty in numerical simulations. The algorithm takes advantage of the unscented transform to compute the output distribution of the outcomes. We validated the unscented transform as a viable sampling strategy to deal with anatomy uncertainty. We then showed that the prediction computed with a deterministic model does not always coincide with the most likely outcome. Finally, we found that shape uncertainty affects the predictions of macro-re-entries, while fibrosis uncertainty affects the predictions of functional re-entries.

Adenosine and Adenosine Receptors: Advances in Atrial Fibrillation.

Atrial fibrillation (AF) is the most common arrhythmia in the world. Because the key to developing innovative therapies that limit the onset and the progression of AF is to fully understand the underlying molecular mechanisms of AF, the aim of the present narrative review is to report the most recent advances in the potential role of the adenosinergic system in the pathophysiology of AF. After a comprehensive approach describing adenosinergic system signaling and the mechanisms of the initiation and maintenance of AF, we address the interactions of the adenosinergic system's signaling with AF. Indeed, adenosine release can activate four G-coupled membrane receptors, named A1, A2A, A2B and A3. Activation of the A2A receptors can promote the occurrence of delayed depolarization, while activation of the A1 receptors can shorten the action potential's duration and induce the resting membrane's potential hyperpolarization, which promote pulmonary vein firing, stabilize the AF rotors and allow for functional reentry. Moreover, the A2B receptors have been associated with atrial fibrosis homeostasis. Finally, the adenosinergic system can modulate the autonomous nervous system and is associated with AF risk factors. A question remains regarding adenosine release and the adenosine receptors' activation and whether this would be a cause or consequence of AF.

Direct observation of a stable spiral wave reentry in ventricles of a whole human heart using optical mapping for voltage and calcium.

From the studies of Gordon Moe in the 1960s, functional reentry has been investigated as a mechanism for tachycardia and fibrillation; however, it was not until 1990 that optical mapping (OM) experiments using sheep hearts verified the existence of reentrant spiral waves.1 Eventually, it was shown that electromechanical 3-dimensional vortex filaments drive cardiac fibrillation.2 To date, only multiple complex and short-lived reentrant waves have been recorded using OM on human ventricles.3 The presence of single spiral waves in human ventricles has only been demonstrated using low-resolution intracardiac electrocardiograms (ECGs).

Thermal ablation effects on rotors that characterize functional re-entry cardiac arrhythmia.

Thermal ablation is a well-established successful treatment for cardiac arrhythmia, but it still presents limitations that require further studies and developments. In the rotor-driven functional re-entry arrhythmia, tissue heterogeneity results on the generation of spiral/scroll waves and wave break dynamics that may cause dangerous sustainable fibrillation. The selection of the target region to perform thermal ablation to mitigate this type of arrhythmia is challenging, since it considerably affects the local electrophysiology dynamics. This work deals with the numerical simulation of the thermal ablation of a cardiac muscle tissue and its effects on the dynamics of rotor-driven functional re-entry arrhythmia. A non-homogeneous two-dimensional rectangular region is used in the present numerical analysis, where radiofrequency ablation is performed. The electrophysiology problem for the propagation of the action potential in the cardiac tissue is simulated with the Fenton-Karma model. Thermal damage caused to the tissue by the radiofrequency heating is modeled by the Arrhenius equation. The effects of size and position of a heterogeneous region in the original muscle tissue were first analyzed, in order to verify the possible existence of the functional re-entry arrhythmia during the time period considered in the simulations. For each case that exhibited re-entry arrhythmia, six different ablation procedures were analyzed, depending on the position of the radiofrequency electrode and heating time. The obtained results revealed the effects of different model parameters on the existence and possible mitigation of the functional re-entry arrhythmia.

Graph-based homogenisation for modelling cardiac fibrosis

Fibrosis, the excess of extracellular matrix, can affect, and even block, propagation of action potential in cardiac tissue. This can result in deleterious effects on heart function, but the nature and severity of these effects depend strongly on the localisation of fibrosis and its by-products in cardiac tissue, such as collagen scar formation. Computer simulation is an important means of understanding the complex effects of fibrosis on activation patterns in the heart, but concerns of computational cost place restrictions on the spatial resolution of these simulations. In this work, we present a novel numerical homogenisation technique that uses both Eikonal and graph approaches to allow fine-scale heterogeneities in conductivity to be incorporated into a coarser mesh. Homogenisation achieves this by deriving effective conductivity tensors so that a coarser mesh can then be used for numerical simulation. By taking a graph-based approach, our homogenisation technique functions naturally on irregular grids and does not rely upon any assumptions of periodicity, even implicitly. We present results of action potential propagation through fibrotic tissue in two dimensions that show the graph-based homogenisation technique is an accurate and effective way to capture fine-scale domain information on coarser meshes in the context of sharp-fronted travelling waves of activation. As test problems, we consider excitation propagation in tissue with diffuse fibrosis and through a tunnel-like structure designed to test homogenisation, interaction of an excitation wave with a scar region, and functional re-entry.

Characterization of the Electrophysiologic Remodeling of Patients With Ischemic Cardiomyopathy by Clinical Measurements and Computer Simulations Coupled With Machine Learning.

RationalePatients with ischemic cardiomyopathy (ICMP) are at high risk for malignant arrhythmias, largely due to electrophysiological remodeling of the non-infarcted myocardium. The electrophysiological properties of the non-infarcted myocardium of patients with ICMP remain largely unknown.ObjectivesTo assess the pro-arrhythmic behavior of non-infarcted myocardium in ICMP patients and couple computational simulations with machine learning to establish a methodology for the development of disease-specific action potential models based on clinically measured action potential duration restitution (APDR) data.Methods and ResultsWe enrolled 22 patients undergoing left-sided ablation (10 ICMP) and compared APDRs between ICMP and structurally normal left ventricles (SNLVs). APDRs were clinically assessed with a decremental pacing protocol. Using genetic algorithms (GAs), we constructed populations of action potential models that incorporate the cohort-specific APDRs. The variability in the populations of ICMP and SNLV models was captured by clustering models based on their similarity using unsupervised machine learning. The pro-arrhythmic potential of ICMP and SNLV models was assessed in cell- and tissue-level simulations. Clinical measurements established that ICMP patients have a steeper APDR slope compared to SNLV (by 38%, p < 0.01). In cell-level simulations, APD alternans were induced in ICMP models at a longer cycle length compared to SNLV models (385–400 vs 355 ms). In tissue-level simulations, ICMP models were more susceptible for sustained functional re-entry compared to SNLV models.ConclusionMyocardial remodeling in ICMP patients is manifested as a steeper APDR compared to SNLV, which underlies the greater arrhythmogenic propensity in these patients, as demonstrated by cell- and tissue-level simulations using action potential models developed by GAs from clinical measurements. The methodology presented here captures the uncertainty inherent to GAs model development and provides a blueprint for use in future studies aimed at evaluating electrophysiological remodeling resulting from other cardiac diseases.

Dynamic spatial dispersion of repolarization is present in regions critical for ischemic ventricular tachycardia ablation.

BackgroundThe presence of dynamic substrate changes may facilitate functional block and reentry in ventricular tachycardia (VT).ObjectiveWe aimed to study dynamic ventricular repolarization changes in critical regions of the VT circuit during sensed single extrastimulus pacing known as the Sense Protocol (SP).MethodsTwenty patients (aged 67 ± 9 years, 17 male) underwent VT ablation. A bipolar voltage map was obtained during sinus rhythm (SR) and right ventricular SP pacing at 20 ms above ventricular effective refractory period. Ventricular repolarization maps were constructed. Ventricular repolarization time (RT) was calculated from unipolar electrogram T waves, using the Wyatt method, as the dV/dtmax of the unipolar T wave. Entrainment or pace mapping confirmed critical sites for ablation.ResultsThe median global repolarization range (max-min RT per patient) was 166 ms (interquartile range [IQR] 143–181 ms) during SR mapping vs 208 ms (IQR 182–234) during SP mapping (P = .0003 vs intrinsic rhythm). Regions of late potentials (LP) had a longer RT during SP mapping compared to regions without LP (mean 394 ± 40 ms vs 342 ± 25 ms, P < .001). In paired regions of normal myocardium there was no significant spatial dispersion of repolarization (SDR)/10 mm2 during SP mapping vs SR mapping (SDR 11 ± 6 ms vs 10 ± 6 ms, P = .54). SDR/10 mm2 was greater in critical areas of the VT circuit during SP mapping 63 ± 29 ms vs SR mapping 16 ± 9 ms (P < .001).ConclusionVentricular repolarization is prolonged in regions of LP and increases dynamically, resulting in dynamic SDR in critical areas of the VT circuit. These dynamic substrate changes may be an important factor that facilitates VT circuits.

Challenges Associated with Interpreting Mechanisms of AF.

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.

Characterizing Conduction Channels in Postinfarction Patients Using a Personalized Virtual Heart

Patients with myocardial infarction have an abundance of conduction channels (CC); however, only a small subset of these CCs sustain ventricular tachycardia (VT). Identifying these critical CCs (CCCs) in the clinic so that they can be targeted by ablation remains a significant challenge. The objective of this study is to use a personalized virtual-heart approach to conduct a three-dimensional (3D) assessment of CCCs sustaining VTs of different morphologies in these patients, to investigate their 3D structural features, and to determine the optimal ablation strategy for each VT. To achieve these goals, ventricular models were constructed from contrast enhanced magnetic resonance imagings of six postinfarction patients. Rapid pacing induced VTs in each model. CCCs that sustained different VT morphologies were identified. CCCs’ 3D structure and type and the resulting rotational electrical activity were examined. Ablation was performed at the optimal part of each CCC, aiming to terminate each VT with a minimal lesion size. Predicted ablation locations were compared to clinical. Analyzing the simulation results, we found that the observed VTs in each patient model were sustained by a limited number (2.7 ± 1.2) of CCCs. Further, we identified three types of CCCs sustaining VTs: I-type and T-type channels, with all channel branches bounded by scar, and functional reentry channels, which were fully or partially bounded by conduction block surfaces. The different types of CCCs accounted for 43.8, 18.8, and 37.4% of all CCCs, respectively. The mean narrowest width of CCCs or a branch of CCC was 9.7 ± 3.6 mm. Ablation of the narrowest part of each CCC was sufficient to terminate VT. Our results demonstrate that a personalized virtual-heart approach can determine the possible VT morphologies in each patient and identify the CCCs that sustain reentry. The approach can aid clinicians in identifying accurately the optimal VT ablation targets in postinfarction patients.

Dynamics of Pivoting Electrical Waves in a Cardiac Tissue Model.

Through a detailed mathematical analysis we seek to advance our understanding of how cardiac tissue conductances govern pivoting (spiral, scroll, rotor, functional reentry) wave dynamics. This is an important problem in cardiology since pivoting waves likely underlie most reentrant tachycardias. The problem is complex, and to advance our methods of analysis we introduce two new tools: a ray tracing method and a moving-interface model. When used in combination with an ionic model, they permit us to elucidate the role played by tissue conductances on pivoting wave dynamics. Specifically we simulate traveling electrical waves with an ionic model that can reproduce the characteristics of plane and pivoting waves in small patches of cardiac tissue. Then ray tracing is applied to the simulated pivoting waves in a manner to expose their real displacement. In this exercise we find loci with special characteristics, as well as zones where a part of a pivoting wave quickly transitions from a regenerative to a non-regenerative propagation mode. The loci themselves and the monitoring of the ionic model state variables in this zone permit to elucidate several aspects of pivoting wave dynamics. We then formulate the moving-interface model based on the information gathered with the above-mentioned analysis. Equipped with a velocity profile v(s), s: distance along of the pivoting wave contour and the steady- state action potential duration (APD) of a plane wave during entrainment, APDss(T), at period T, this simple model can predict: shape, orbit of revolution, rotation period, whether a pivoting wave will break up or not, and whether the tissue will admit pivoting waves or not. Because v(s) and APDss(T) are linked to the ionic model, dynamical analysis with the moving-interface model conveys information on the role played by tissue conductances on pivoting wave dynamics. The analysis conducted here enables us to better understand previous results on the termination of pivoting waves. We surmise the method put forth here could become a means to discover how to alter tissue conductances in a manner to terminate pivoting waves at the origin of reentrant tachycardias.

Far-field contributions in multi-electrodes atrial recordings blur distinction between anatomical and functional reentries and may cause imaginary phase singularities – A computational study

BackgroundAtrial fibrillation (AF) is the most common cardiac arrhythmia and the most important cause of embolic stroke, requiring new technologies for its better understanding and therapies. Recent approaches to map the electrical activity during AF with multi-electrode systems aim at localizing patient-specific ablation targets of reentrant patterns. However, there is a critical need to determine the accuracy of those mapping systems. We performed computer simulations as a numerical approach of systematically evaluating the influence of far-field sources on the electrical recordings and detection of rotors. MethodsWe constructed 2 computer models of atrial tissue: (i) a 2D sheet model with varying non-active cells area in its center, and (ii) a whole realistic 3D atrial model. Phase maps were built based on the Hilbert transform of the unipolar electrograms recorded by virtual 2D and 3D multi-electrode systems and rotors were tracked through phase singularities detections. ResultsAnalysis of electrograms recorded away from the 2D atrial model shows that the larger the distance between an electrode and the tissue model, the stronger the far-field sources contribution to the electrogram is. Importantly, even if an electrode is positioned in contact with the tissue, the electrogram contains significant contributions from distal sources that blur the distinction between anatomical and functional reentries. Moreover, when mapping the 3D atrial model, remote activity generated false phase singularities at locations without local reentrant excitation patterns. ConclusionsFar-field contributions to electrograms during AF reduce the accuracy of detecting and interpreting reentrant activity.

Entropy Mapping Approach for Functional Reentry Detection in Atrial Fibrillation: An In-Silico Study.

Catheter ablation of critical electrical propagation sites is a promising tool for reducing the recurrence of atrial fibrillation (AF). The spatial identification of the arrhythmogenic mechanisms sustaining AF requires the evaluation of electrograms (EGMs) recorded over the atrial surface. This work aims to characterize functional reentries using measures of entropy to track and detect a reentry core. To this end, different AF episodes are simulated using a 2D model of atrial tissue. Modified Courtemanche human action potential and Fenton–Karma models are implemented. Action potential propagation is modeled by a fractional diffusion equation, and virtual unipolar EGM are calculated. Episodes with stable and meandering rotors, figure-of-eight reentry, and disorganized propagation with multiple reentries are generated. Shannon entropy (), approximate entropy (), and sample entropy () are computed from the virtual EGM, and entropy maps are built. Phase singularity maps are implemented as references. The results show that and maps are able to detect and track the reentry core of rotors and figure-of-eight reentry, while the results are not satisfactory. Moreover, and consistently highlight a reentry core by high entropy values for all of the studied cases, while the ability of to characterize the reentry core depends on the propagation dynamics. Such features make the and maps attractive tools for the study of AF reentries that persist for a period of time that is similar to the length of the observation window, and reentries could be interpreted as AF-sustaining mechanisms. Further research is needed to determine and fully understand the relation of these entropy measures with fibrillation mechanisms other than reentries.

Dynamical anchoring of distant arrhythmia sources by fibrotic regions via restructuring of the activation pattern.

Rotors are functional reentry sources identified in clinically relevant cardiac arrhythmias, such as ventricular and atrial fibrillation. Ablation targeting rotor sites has resulted in arrhythmia termination. Recent clinical, experimental and modelling studies demonstrate that rotors are often anchored around fibrotic scars or regions with increased fibrosis. However, the mechanisms leading to abundance of rotors at these locations are not clear. The current study explores the hypothesis whether fibrotic scars just serve as anchoring sites for the rotors or whether there are other active processes which drive the rotors to these fibrotic regions. Rotors were induced at different distances from fibrotic scars of various sizes and degree of fibrosis. Simulations were performed in a 2D model of human ventricular tissue and in a patient-specific model of the left ventricle of a patient with remote myocardial infarction. In both the 2D and the patient-specific model we found that without fibrotic scars, the rotors were stable at the site of their initiation. However, in the presence of a scar, rotors were eventually dynamically anchored from large distances by the fibrotic scar via a process of dynamical reorganization of the excitation pattern. This process coalesces with a change from polymorphic to monomorphic ventricular tachycardia.

Slow Recovery of Excitability Increases Ventricular Fibrillation Risk as Identified by Emulation.

Purpose: Rotor stability and meandering are key mechanisms determining and sustaining cardiac fibrillation, with important implications for anti-arrhythmic drug development. However, little is yet known on how rotor dynamics are modulated by variability in cellular electrophysiology, particularly on kinetic properties of ion channel recovery.Methods: We propose a novel emulation approach, based on Gaussian process regression augmented with machine learning, for data enrichment, automatic detection, classification, and analysis of re-entrant biomarkers in cardiac tissue. More than 5,000 monodomain simulations of long-lasting arrhythmic episodes with Fenton-Karma ionic dynamics, further enriched by emulation to 80 million electrophysiological scenarios, were conducted to investigate the role of variability in ion channel densities and kinetics in modulating rotor-driven arrhythmic behavior.Results: Our methods predicted the class of excitation behavior with classification accuracy up to 96%, and emulation effectively predicted frequency, stability, and spatial biomarkers of functional re-entry. We demonstrate that the excitation wavelength interpretation of re-entrant behavior hides critical information about rotor persistence and devolution into fibrillation. In particular, whereas action potential duration directly modulates rotor frequency and meandering, critical windows of excitability are identified as the main determinants of breakup. Further novel electrophysiological insights of particular relevance for ventricular arrhythmias arise from our multivariate analysis, including the role of incomplete activation of slow inward currents in mediating tissue rate-dependence and dispersion of repolarization, and the emergence of slow recovery of excitability as a significant promoter of this mechanism of dispersion and increased arrhythmic risk.Conclusions: Our results mechanistically explain pro-arrhythmic effects of class Ic anti-arrhythmics in the ventricles despite their established role in the pharmacological management of atrial fibrillation. This is mediated by their slow recovery of excitability mode of action, promoting incomplete activation of slow inward currents and therefore increased dispersion of repolarization, given the larger influence of these currents in modulating the action potential in the ventricles compared to the atria. These results exemplify the potential of emulation techniques in elucidating novel mechanisms of arrhythmia and further application to cardiac electrophysiology.

Characterisation of re-entrant circuit (or rotational activity) in vitro using the HL1-6 myocyte cell line

Fibrillation is the most common arrhythmia observed in clinical practice. Understanding of the mechanisms underlying its initiation and maintenance remains incomplete. Functional re-entries are potential drivers of the arrhythmia. Two main concepts are still debated, the “leading circle” and the “spiral wave or rotor” theories. The homogeneous subclone of the HL1 atrial-derived cardiomyocyte cell line, HL1-6, spontaneously exhibits re-entry on a microscopic scale due to its slow conduction velocity and the presence of triggers, making it possible to examine re-entry at the cellular level.We therefore investigated the re-entry cores in cell monolayers through the use of fluorescence optical mapping at high spatiotemporal resolution in order to obtain insights into the mechanisms of re-entry.Re-entries in HL1-6 myocytes required at least two triggers and a minimum colony area to initiate (3.5 to 6.4 mm2). After electrical activity was completely stopped and re-started by varying the extracellular K+ concentration, re-entries never returned to the same location while 35% of triggers re-appeared at the same position. A conduction delay algorithm also allows visualisation of the core of the re-entries. This work has revealed that the core of re-entries is conduction blocks constituted by lines and/or groups of cells rather than the round area assumed by the other concepts of functional re-entry. This highlights the importance of experimentation at the microscopic level in the study of re-entry mechanisms.

Complex restitution behavior and reentry in a cardiac tissue model for neonatal mice.

Spatiotemporal dynamics in cardiac tissue emerging from the coupling of individual cardiomyocytes underlie the heart's normal rhythm as well as undesired and possibly life‐threatening arrhythmias. While single cells and their transmembrane currents have been studied extensively, systematically investigating spatiotemporal dynamics is complicated by the nontrivial relationship between single‐cell and emergent tissue properties. Mathematical models have been employed to bridge this gap and contribute to a deepened understanding of the onset, development, and termination of arrhythmias. However, no such tissue‐level model currently exists for neonatal mice. Here, we build on a recent single‐cell model of neonatal mouse cardiomyocytes by Wang and Sobie (Am. J. Physiol. Heart Circ. Physiol. 294:H2565) to predict properties that are commonly used to gauge arrhythmogenicity of cardiac substrates. We modify the model to yield well‐defined behavior for common experimental protocols and construct a spatially extended version to study emergent tissue dynamics. We find a complex action potential duration (APD) restitution behavior characterized by a nonmonotonic dependence on pacing frequency. Electrotonic coupling in tissue leads not only to changes in action potential morphology but can also induce spatially concordant and discordant alternans not observed in the single‐cell model. In two‐dimensional tissue, our results show that the model supports stable functional reentry, whose frequency is in good agreement with that observed in adult mice. Our results can be used to further constrain and validate the mathematical model of neonatal mouse cardiomyocytes with future experiments.