Manifold analysis of the P-wave changes induced by pulmonary vein isolation during cryoballoon procedure.

BACKGROUND/AIM: In atrial fibrillation (AF) ablation procedures, it is desirable to know whether a proper disconnection of the pulmonary veins (PVs) was achieved. We hypothesize that information about their isolation could be provided by analyzing changes in P-wave after ablation. Thus, we present a method to detect PV disconnection using P-wave signal analysis. METHODS: Conventional P-wave feature extraction was compared to an automatic feature extraction procedure based on creating low-dimensional latent spaces for cardiac signals with the Uniform Manifold Approximation and Projection (UMAP) method. A database of patients (19 controls and 16 AF individuals who underwent a PV ablation procedure) was collected. Standard 12-lead ECG was recorded, and P-waves were segmented and averaged to extract conventional features (duration, amplitude, and area) and their manifold representations provided by UMAP on a 3-dimensional latent space. A virtual patient was used to validate these results further and study the spatial distribution of the extracted characteristics over the whole torso surface. RESULTS: Both methods showed differences between P-wave before and after ablation. Conventional methods were more prone to noise, P-wave delineation errors, and inter-patient variability. P-wave differences were observed in the standard leads recordings. However, higher differences appeared in the torso region over the precordial leads. Recordings near the left scapula also yielded noticeable differences. CONCLUSIONS: P-wave analysis based on UMAP parameters detects PV disconnection after ablation in AF patients and is more robust than heuristic parameterization. Moreover, additional leads different from the standard 12-lead ECG should be used to detect PV isolation and possible future reconnections better.

Atrial fibrosis identification with unipolar electrogram eigenvalue distribution analysis in multi-electrode arrays.

Atrial fibrosis plays a key role in the initiation and progression of atrial fibrillation (AF). Atrial fibrosis is typically identified by a peak-to-peak amplitude of bipolar electrograms (b-EGMs) lower than 0.5 mV, which may be considered as ablation targets. Nevertheless, this approach disregards signal spatiotemporal information and b-EGM sensitivity to catheter orientation. To overcome these limitations, we propose the dominant-to-remaining eigenvalue dominance ratio (EIGDR) of unipolar electrograms (u-EGMs) within neighbor electrode cliques as a waveform dispersion measure, hypothesizing that it is correlated with the presence of fibrosis. A simulated 2D tissue with a fibrosis patch was used for validation. We computed EIGDR maps from both original and time-aligned u-EGMs, denoted as [Formula: see text] and [Formula: see text], respectively, also mapping the gain in eigenvalue concentration obtained by the alignment, [Formula: see text]. The performance of each map in detecting fibrosis was evaluated in scenarios including noise and variable electrode-tissue distance. Best results were achieved by [Formula: see text], reaching 94% detection accuracy, versus the 86% of b-EGMs voltage maps. The proposed strategy was also tested in real u-EGMs from fibrotic and non-fibrotic areas over 3D electroanatomical maps, supporting the ability of the EIGDRs as fibrosis markers, encouraging further studies to confirm their translation to clinical settings. Upper panels: map of [Formula: see text] from 3×3 cliques for Ψ= 0∘ and bipolar voltage map Vb-m, performed assuming a variable electrode-to-tissue distance and noisy u-EGMs (noise level σv = 46.4 µV ). Lower panels: detected fibrotic areas (brown), using the thresholds that maximize detection accuracy of each map.

Rotors Drift Toward and Stabilize in Low Power Regions in Heterogeneous Models of Atrial Fibrillation.

Atrial fibrillation (AF) afflicts more than 33 million people worldwide. Success of therapy strategies remains poor and better understanding of the arrhythmia and how to device more effective therapies are needed. The aim of this work is to study the role of electric power distributions in rotors and AF dynamics. For this purpose, single cell and tissue simulations were performed to study the effect of ionic currents gradients and fibrosis in rotor's drifting. The root mean square of the ionic (Pion), capacitance (Pc) and electrotonic (Pele) power was computed over action potentials. Single cell simulations were performed for different values of IK1 and ICaL and number of coupled myofibroblasts. Tissue simulations were performed in presence of IK1 and ICaL gradients and diffused fibrosis. Single cell simulations showed that Pion and Pc increased with IK1, while decreased by increasing ICaL. Increasing the number of coupled myofibroblasts reduced Pion and Pc, whereas Pele increased. Finally, in tissue simulations rotors drifted to regions with low power and anchored in regions with higher density of blunted ionic induced power gradients.

Atrial low voltage areas: A comparison between atrial fibrillation and sinus rhythm.

BACKGROUND: Atrial fibrosis can promote atrial fibrillation (AF). Electroanatomic mapping (EAM) can provide information regarding local voltage abnormalities that may be used as a surrogate marker for fibrosis. Specific voltage cut-off values have been reproduced accurately to identify fibrosis in the ventricles, but these values are not well defined in atrial tissue. METHODS: This study is a prospective single-center study. Patients with persistent AF referred for ablation were included. EAM was performed before ablation. We recorded bipolar signals, first in AF and later in sinus rhythm (SR). Two thresholds delimited low-voltage areas (LVA), 0.5 and 0.3 mV. We compared LVA extension between maps in SR and AF in each patient. RESULTS: A total of 23 patients were included in the study. The percentage of points with voltage lower than 0.5 mV and 0.3 mV was significantly higher in maps in AF compared with maps in SR: 38.2% of points < 0.5 mV in AF vs. 22.9% in SR (p < 0.001); 22.3% of points < 0.3 mV in AF vs. 14% in SR (p < 0.001). Areas with reduced voltage were significantly larger in maps in AF (0.5 mV threshold, mean area in AF 41.3 ± 42.5 cm2 vs. 11.7 ± 17.9 cm2 in SR, p < 0.001; 0.3 mV threshold, mean area in AF 15.6 ± 22.1 cm2 vs. 6.2 ± 11.5 cm2 in SR, p < 0.001). CONCLUSIONS: Using the same voltage thresholds, LVA extension in AF is greater than in SR in patients with persistent AF. These findings provide arguments for defining a different atrial fibrosis threshold based on EAM rhythm.

Macrophage-Dependent Interleukin-6-Production and Inhibition of IK Contributes to Acquired QT Prolongation in Lipotoxic Guinea Pig Heart.

In the heart, the delayed rectifier K current, IK, composed of the rapid (IKr) and slow (IKs) components contributes prominently to normal cardiac repolarization. In lipotoxicity, chronic elevation of pro-inflammatory cytokines may remodel IK, elevating the risk for ventricular arrythmias and sudden cardiac death. We investigated whether and how the pro-inflammatory interleukin-6 altered IK in the heart, using electrophysiology to evaluate changes in IK in adult guinea pig ventricular myocytes. We found that palmitic acid (a potent inducer of lipotoxicity), induced a rapid (~24 h) and significant increase in IL-6 in RAW264.7 cells. PA-diet fed guinea pigs displayed a severely prolonged QT interval when compared to low-fat diet fed controls. Exposure to isoproterenol induced torsade de pointes, and ventricular fibrillation in lipotoxic guinea pigs. Pre-exposure to IL-6 with the soluble IL-6 receptor produced a profound depression of IKr and IKs densities, prolonged action potential duration, and impaired mitochondrial ATP production. Only with the inhibition of IKr did a proarrhythmic phenotype of IKs depression emerge, manifested as a further prolongation of action potential duration and QT interval. Our data offer unique mechanistic insights with implications for pathological QT interval in patients and vulnerability to fatal arrhythmias.

Characterization of Atrial Propagation Patterns and Fibrotic Substrate With a Modified Omnipolar Electrogram Strategy in Multi-Electrode Arrays.

Introduction: The omnipolar electrogram method was recently proposed to try to generate orientation-independent electrograms. It estimates the electric field from the bipolar electrograms of a clique, under the assumption of locally plane and homogeneous propagation. The local electric field evolution over time describes a loop trajectory from which omnipolar signals in the propagation direction, substrate and propagation features, are derived. In this work, we propose substrate and conduction velocity mapping modalities based on a modified version of the omnipolar electrogram method, which aims to reduce orientation-dependent residual components in the standard approach. Methods: A simulated electrical propagation in 2D, with a tissue including a circular patch of diffuse fibrosis, was used for validation. Unipolar electrograms were calculated in a multi-electrode array, also deriving bipolar electrograms along the two main directions of the grid. Simulated bipolar electrograms were also contaminated with real noise, to assess the robustness of the mapping strategies against noise. The performance of the maps in identifying fibrosis and in reproducing unipolar reference voltage maps was evaluated. Bipolar voltage maps were also considered for performance comparison. Results: Results show that the modified omnipolar mapping strategies are more accurate and robust against noise than bipolar and standard omnipolar maps in fibrosis detection (accuracies higher than 85 vs. 80% and 70%, respectively). They present better correlation with unipolar reference voltage maps than bipolar and original omnipolar maps (Pearson's correlations higher than 0.75 vs. 0.60 and 0.70, respectively). Conclusion: The modified omnipolar method improves fibrosis detection, characterization of substrate and propagation, also reducing the residual sensitivity to directionality over the standard approach and improving robustness against noise. Nevertheless, studies with real electrograms will elucidate its impact in catheter ablation interventions.

Arrhythmogenic Effects of Genetic Mutations Affecting Potassium Channels in Human Atrial Fibrillation: A Simulation Study.

Genetic mutations in genes encoding for potassium channel protein structures have been recently associated with episodes of atrial fibrillation in asymptomatic patients. The aim of this study is to investigate the potential arrhythmogenicity of three gain-of-function mutations related to atrial fibrillation-namely, KCNH2 T895M, KCNH2 T436M, and KCNE3-V17M-using modeling and simulation of the electrophysiological activity of the heart. A genetic algorithm was used to tune the parameters' value of the original ionic currents to reproduce the alterations experimentally observed caused by the mutations. The effects on action potentials, ionic currents, and restitution properties were analyzed using versions of the Courtemanche human atrial myocyte model in different tissues: pulmonary vein, right, and left atrium. Atrial susceptibility of the tissues to spiral wave generation was also investigated studying the temporal vulnerability. The presence of the three mutations resulted in an overall more arrhythmogenic substrate. Higher current density, action potential duration shortening, and flattening of the restitution curves were the major effects of the three mutations at the single-cell level. The genetic mutations at the tissue level induced a higher temporal vulnerability to the rotor's initiation and progression, by sustaining spiral waves that perpetuate until the end of the simulation. The mutation with the highest pro-arrhythmic effects, exhibiting the widest sustained VW and the smallest meandering rotor's tip areas, was KCNE3-V17M. Moreover, the increased susceptibility to arrhythmias and rotor's stability was tissue-dependent. Pulmonary vein tissues were more prone to rotor's initiation, while in left atrium tissues rotors were more easily sustained. Re-entries were also progressively more stable in pulmonary vein tissue, followed by the left atrium, and finally the right atrium. The presence of the genetic mutations increased the susceptibility to arrhythmias by promoting the rotor's initiation and maintenance. The study provides useful insights into the mechanisms underlying fibrillatory events caused by KCNH2 T895M, KCNH2 T436M, and KCNE3-V17M and might aid the planning of patient-specific targeted therapies.

Directed graph mapping exceeds phase mapping in discriminating true and false rotors detected with a basket catheter in a complex in-silico excitation pattern.

Atrial fibrillation (AF) is the most frequently encountered arrhythmia in clinical practise. One of the major problems in the management of AF is the difficulty in identifying the arrhythmia sources from clinical recordings. That difficulty occurs because it is currently impossible to verify algorithms which determine these sources in clinical data, as high resolution true excitation patterns cannot be recorded in patients. Therefore, alternative approaches, like computer modelling are of great interest. In a recent published study such an approach was applied for the verification of one of the most commonly used algorithms, phase mapping (PM). A meandering rotor was simulated in the right atrium and a basket catheter was placed at 3 different locations: at the Superior Vena Cava (SVC), the Crista Terminalis (CT) and at the Coronary Sinus (CS). It was shown that although PM can identify the true source, it also finds several false sources due to the far-field effects and interpolation errors in all three positions. In addition, the detection efficiency strongly depended on the basket location. Recently, a novel tool was developed to analyse any arrhythmia called Directed Graph Mapping (DGM). DGM is based on network theory and creates a directed graph of the excitation pattern, from which the location and the source of the arrhythmia can be detected. Therefore, the objective of the current study was to compare the efficiency of DGM with PM on the basket dataset of this meandering rotor. The DGM-tool was applied for a wide variety of conduction velocities (minimal and maximal), which are input parameters of DGM. Overall we found that DGM was able to distinguish between the true rotor and false rotors for both the SVC and CT basket positions. For example, for the SVC position with a CVmin=0.01cmms, DGM detected the true core with a prevalence of 82% versus 94% for PM. Three false rotors where detected for 39.16% (DGM) versus 100% (PM); 22.64% (DGM) versus 100% (PM); and 0% (DGM) versus 57% (PM). Increasing CVmin to 0.02cmms had a stronger effect on the false rotors than on the true rotor. This led to a detection rate of 56.6% for the true rotor, while all the other false rotors disappeared. A similar trend was observed for the CT position. For the CS position, DGM already had a low performance for the true rotor for CVmin=0.01cmms (14.7%). For CVmin=0.02cmms the false and the true rotors could therefore not be distinguished. We can conclude that DGM can overcome some of the limitations of PM by varying one of its input parameters (CVmin). The true rotor is less dependent on this parameter than the false rotors, which disappear at a CVmin=0.02cmms. In order to increase to detection rate of the true rotor, one can decrease CVmin and discard the new rotors which also appear at lower values of CVmin.

Differential Modulation of IK and ICa,L Channels in High-Fat Diet-Induced Obese Guinea Pig Atria.

Obesity mechanisms that make atrial tissue vulnerable to arrhythmia are poorly understood. Voltage-dependent potassium (IK , IKur , and IK1 ) and L-type calcium currents (ICa,L ) are electrically relevant and represent key substrates for modulation in obesity. We investigated whether electrical remodeling produced by high-fat diet (HFD) alone or in concert with acute atrial stimulation were different. Electrophysiology was used to assess atrial electrical function after short-term HFD-feeding in guinea pigs. HFD atria displayed spontaneous beats, increased IK (IKr + IKs ) and decreased ICa,L densities. Only with pacing did a reduction in IKur and increased IK1 phenotype emerge, leading to a further shortening of action potential duration. Computer modeling studies further indicate that the measured changes in potassium and calcium current densities contribute prominently to shortened atrial action potential duration in human heart. Our data are the first to show that multiple mechanisms (shortened action potential duration, early afterdepolarizations and increased incidence of spontaneous beats) may underlie initiation of supraventricular arrhythmias in obese guinea pig hearts. These results offer different mechanistic insights with implications for obese patients harboring supraventricular arrhythmias.

Heterogeneous Effects of Fibroblast-Myocyte Coupling in Different Regions of the Human Atria Under Conditions of Atrial Fibrillation.

Background: Atrial fibrillation (AF), the most common cardiac arrhythmia, is characterized by alteration of the action potential (AP) propagation. Under persistent AF, myocytes undergo electrophysiological and structural remodeling, which involves fibroblast proliferation and differentiation, modifying the substrate for AP propagation. The aim of this study was to analyze the effects on the AP of fibroblast-myocyte coupling during AF and its propagation in different regions of the atria. Methods: Isolated myocytes were coupled to different numbers of fibroblasts using the established AP models and tissue simulations were performed by randomly distributing fibroblasts. Fibroblast formulations were updated to match recent experimental data. Major ion current conductances of the myocyte model were modified to simulate AP heterogeneity in four different atrial regions (right atrium posterior wall, crista terminalis, left atrium posterior wall, and pulmonary vein) according to experimental and computational studies. Results: The results of the coupled myocyte-fibroblast simulations suggest that a more depolarized membrane potential and higher fibroblast membrane capacitance have a greater impact on AP duration and myocyte maximum depolarization velocity. The number of coupled fibroblasts and the stimulation frequency are determining factors in altering myocyte AP. Strand simulations show that conduction velocity tends to homogenize in all regions, while the left atrium is more likely to be affected by fibroblast and AP propagation block is more likely to occur. The pulmonary vein is the most affected region, even at low fibroblast densities. In 2D sheets with randomly placed fibroblasts, wavebreaks are observed in the low density (10%) central fibrotic zone and when fibroblast density increases (40%) propagation in the fibrotic region is practically blocked. At densities of 10 and 20% the width of the vulnerable window increases with respect to control but is decreased at 40%. Conclusion: Myocyte-fibroblast coupling characteristics heterogeneously affect AP propagation and features in the different atrial zones, and myocytes from the left atria are more sensitive to fibroblast coupling.

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

BACKGROUND: Atrial 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. METHODS: We 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. RESULTS: Analysis 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. CONCLUSIONS: Far-field contributions to electrograms during AF reduce the accuracy of detecting and interpreting reentrant activity.

Factors affecting basket catheter detection of real and phantom rotors in the atria: A computational study.

Anatomically based procedures to ablate atrial fibrillation (AF) are often successful in terminating paroxysmal AF. However, the ability to terminate persistent AF remains disappointing. New mechanistic approaches use multiple-electrode basket catheter mapping to localize and target AF drivers in the form of rotors but significant concerns remain about their accuracy. We aimed to evaluate how electrode-endocardium distance, far-field sources and inter-electrode distance affect the accuracy of localizing rotors. Sustained rotor activation of the atria was simulated numerically and mapped using a virtual basket catheter with varying electrode densities placed at different positions within the atrial cavity. Unipolar electrograms were calculated on the entire endocardial surface and at each of the electrodes. Rotors were tracked on the interpolated basket phase maps and compared with the respective atrial voltage and endocardial phase maps, which served as references. Rotor detection by the basket maps varied between 35-94% of the simulation time, depending on the basket's position and the electrode-to-endocardial wall distance. However, two different types of phantom rotors appeared also on the basket maps. The first type was due to the far-field sources and the second type was due to interpolation between the electrodes; increasing electrode density decreased the incidence of the second but not the first type of phantom rotors. In the simulations study, basket catheter-based phase mapping detected rotors even when the basket was not in full contact with the endocardial wall, but always generated a number of phantom rotors in the presence of only a single real rotor, which would be the desired ablation target. Phantom rotors may mislead and contribute to failure in AF ablation procedures.

Non-invasive localization of atrial ectopic beats by using simulated body surface P-wave integral maps.

Non-invasive localization of continuous atrial ectopic beats remains a cornerstone for the treatment of atrial arrhythmias. The lack of accurate tools to guide electrophysiologists leads to an increase in the recurrence rate of ablation procedures. Existing approaches are based on the analysis of the P-waves main characteristics and the forward body surface potential maps (BSPMs) or on the inverse estimation of the electric activity of the heart from those BSPMs. These methods have not provided an efficient and systematic tool to localize ectopic triggers. In this work, we propose the use of machine learning techniques to spatially cluster and classify ectopic atrial foci into clearly differentiated atrial regions by using the body surface P-wave integral map (BSPiM) as a biomarker. Our simulated results show that ectopic foci with similar BSPiM naturally cluster into differentiated non-intersected atrial regions and that new patterns could be correctly classified with an accuracy of 97% when considering 2 clusters and 96% for 4 clusters. Our results also suggest that an increase in the number of clusters is feasible at the cost of decreasing accuracy.