Genetic risk factors for drug-induced long QT syndrome: findings from a large real-world case-control study.

Aim: Drug-induced long QT syndrome (diLQTS), an adverse effect of many drugs, can lead to sudden cardiac death. Candidate genetic variants in cardiac ion channels have been associated with diLQTS, but several limitations of previous studies hamper clinical utility. Materials & methods: Thus, the purpose of this study was to assess the associations of KCNE1-D85N, KCNE2-I57T and SCN5A-G615E with diLQTS in a large observational case-control study (6,083 self-reported white patients treated with 27 different high-risk QT-prolonging medications; 12.0% with diLQTS). Results: KCNE1-D85N significantly associated with diLQTS (adjusted odds ratio: 2.24 [95% CI: 1.35-3.58]; p = 0.001). Given low minor allele frequencies, the study had insufficient power to analyze KCNE2-I57T and SCN5A-G615E. Conclusion: KCNE1-D85N is a risk factor for diLQTS that should be considered in future clinical practice guidelines.

Some medications can lead to a condition called drug-induced long QT syndrome (diLQTS), which can be a serious abnormal heart rhythm in some patients. In our research, we explored three specific changes in DNA related to the electrical function of the heart (KCNE1-D85N, KCNE2-I57T, SCN5A-G615E) and their link to diLQTS. Our study revealed a connection between KCNE1-D85N and diLQTS. This study emphasized the importance of including KCNE1-D85N in the medical guidelines to help identify patients at risk of diLQTS. We were unable to identify the connection of KCNE2-I57T and SCN5A-G615E with diLQTS, due to a low number of carriers in the study.

ELUCIDATING THE ROLE OF THE HIS-PURKINJE SYSTEM DURING LONG QT MEDIATED ARRHYTHMIAS.

Mutation in the hERG gene leading to partial or complete blockade of the rapid delayed rectifier current causes Long QT Type 2 (LQT2) phenotype, the second most common form of Long QT Syndrome. However, the exact involvement of the His-Purkinje System (HPS) remains elusive. We utilized a finite element model of the rabbit ventricles integrated with a HPS to elucidate the role of HPS during LQT2-mediated arrhythmia. Following the induction of persistent reentry from an ectopic stimulus, we isolated the HPS at different time points. Moreover, we varied the coupling resistance and the number of myocytes at the Purkinje-Myocardial Junctions (PMJs) to ascertain how the junctional parameters altered reentry dynamics. Reentry was terminated with the earliest termination time for reentry coinciding with the earliest time the HPS was isolated. This observation provides evidence of direct involvement of the HPS during LQT2-mediated ventricular arrhythmia. Increasing the coupling resistance or the number of myocytes at the PMJs reduced the percentage of successful retrograde propagation during reentry. Thus, the HPS alters reentry dynamics. Our multi-scale computer modeling outcomes offer important new understandings of probable arrhythmia mechanisms under LQT2 circumstances.

Artificial intelligence analysis of the impact of fibrosis in arrhythmogenesis and drug response.

Background: Cardiac fibrosis has been identified as a major factor in conduction alterations leading to atrial arrhythmias and modification of drug treatment response. Objective: To perform an in silico proof-of-concept study of Artificial Intelligence (AI) ability to identify susceptibility for conduction blocks in simulations on a population of models with diffused fibrotic atrial tissue and anti-arrhythmic drugs. Methods: Activity in 2D cardiac tissue planes were simulated on a population of variable electrophysiological and anatomical profiles using the Koivumaki model for the atrial cardiomyocytes and the Maleckar model for the diffused fibroblasts (0%, 5% and 10% fibrosis area). Tissue sheets were of 2 cm side and the effect of amiodarone, dofetilide and sotalol was simulated to assess the conduction of the electrical impulse across the planes. Four different AI algorithms (Quadratic Support Vector Machine, QSVM, Cubic Support Vector Machine, CSVM, decision trees, DT, and K-Nearest Neighbors, KNN) were evaluated in predicting conduction of a stimulated electrical impulse. Results: Overall, fibrosis implementation lowered conduction velocity (CV) for the conducting profiles (0% fibrosis: 67.52 ± 7.3 cm/s; 5%: 58.81 ± 14.04 cm/s; 10%: 57.56 ± 14.78 cm/s; p < 0.001) in combination with a reduced 90% action potential duration (0% fibrosis: 187.77 ± 37.62 ms; 5%: 93.29 ± 82.69 ms; 10%: 106.37 ± 85.15 ms; p < 0.001) and peak membrane potential (0% fibrosis: 89.16 ± 16.01 mV; 5%: 70.06 ± 17.08 mV; 10%: 82.21 ± 19.90 mV; p < 0.001). When the antiarrhythmic drugs were present, a total block was observed in most of the profiles. In those profiles in which electrical conduction was preserved, a decrease in CV was observed when simulations were performed in the 0% fibrosis tissue patch (Amiodarone ΔCV: -3.59 ± 1.52 cm/s; Dofetilide ΔCV: -13.43 ± 4.07 cm/s; Sotalol ΔCV: -0.023 ± 0.24 cm/s). This effect was preserved for amiodarone in the 5% fibrosis patch (Amiodarone ΔCV: -4.96 ± 2.15 cm/s; Dofetilide ΔCV: 0.14 ± 1.87 cm/s; Sotalol ΔCV: 0.30 ± 4.69 cm/s). 10% fibrosis simulations showed that part of the profiles increased CV while others showed a decrease in this variable (Amiodarone ΔCV: 0.62 ± 9.56 cm/s; Dofetilide ΔCV: 0.05 ± 1.16 cm/s; Sotalol ΔCV: 0.22 ± 1.39 cm/s). Finally, when the AI algorithms were tested for predicting conduction on input of variables from the population of modelled, Cubic SVM showed the best performance with AUC = 0.95. Conclusion: In silico proof-of-concept study demonstrates that fibrosis can alter the expected behavior of antiarrhythmic drugs in a minority of atrial population models and AI can assist in revealing the profiles that will respond differently.

Distinct spectral dynamics of implanted cardiac defibrillator signals in spontaneous termination of polymorphic ventricular tachycardia and fibrillation in patients with electrical and structural diseases.

AIMS: To determine the spectral dynamics of early spontaneous polymorphic ventricular tachycardia and ventricular fibrillation (PVT/VF) in humans. METHODS AND RESULTS: Fifty-eight self-terminated and 173 shock-terminated episodes of spontaneously initiated PVT/VF recorded by Medtronic implanted cardiac defibrillators (ICDs) in 87 patients with various cardiac pathologies were analyzed by short fast Fourier transform of shifting segments to determine the dynamics of dominant frequency (DF) and regularity index (RI). The progression in the intensity of DF and RI accumulations further quantified the time course of spectral characteristics of the episodes. Episodes of self-terminated PVT/VF lasted 8.6 s [95% confidence interval (CI): 8.1-9.1] and shock-terminated lasted 13.9 s (13.6-14.3) (P < 0.001). Recordings from patients with primarily electrical pathologies displayed higher DF and RI values than those from patients with primarily structural pathologies (P < 0.05) independently of ventricular function or antiarrhythmic drug therapy. Regardless of the underlying pathology, the average DF and RI intensities were lower in self-terminated than shock-terminated episodes [DF: 3.67 (4.04-4.58) vs. 4.32 (3.46-3.93) Hz, P < 0.001; RI: 0.53 (0.48-0.56) vs. 0.63 (0.60-0.65), P < 0.001]. In a multivariate analysis controlled by the type of pathology and clinical variables, regularity remained an independent predictor of self-termination [hazard ratio: 0.954 (0.928-0.980)]. Receiver operating characteristic (ROC) curve analysis of DF and RI intensities demonstrated increased predictability for self-termination in time with 95% CI above the 0.5 cut-off limit at about t = 8.6 s and t = 6.95 s, respectively. CONCLUSION: Consistent with the notion that fast organized sources maintain PVT/VF in humans, reduction of frequency and regularity correlates with early self-termination. Our findings might help generate ICD methods aiming to reduce inappropriate shock deliveries.

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.

TIME- AND FREQUENCY-BASED INDEPENDENT EVALUATION OF QRST CANCELLATION TECHNIQUES FOR SINGLE-LEAD ELECTROCARDIOGRAMS DURING ATRIAL FIBRILLATION.

With the increased prevalence of atrial fibrillation (AF) - a rhythm disturbance in heart's top chambers - there is growing interest in accurate non-invasive diagnosis of atrial activity to improve its therapy. A key component in non-invasive analysis of atrial activity is a successful removal of the ventricular QRST complexes from electrocardiograms (ECGs). In this study, we have developed a new approach for an objective and physiologically-based evaluation of QRST cancellation methods based on comparisons with the power spectra of the AF. Three commonly used QRST cancellation methods were evaluated; namely, average beat subtraction, singular value cancellation, and principal component analysis. These methods were evaluated in time and frequency domains using a set of synthesized ECGs preserving the atrial-specific temporal and spectral properties. It was observed that the ABS method provided the best estimation when QRST morphological variability is low, while PCA produces an overall best estimate when a large QRST morphological variability is present.

Panoramic Endocardial Optical Mapping Demonstrates Serial Rotors Acceleration and Increasing Complexity of Activity During Onset of Cholinergic Atrial Fibrillation.

Background Activation during onset of atrial fibrillation is poorly understood. We aimed at developing a panoramic optical mapping system for the atria and test the hypothesis that sequential rotors underlie acceleration of atrial fibrillation during onset. Methods and Results Five sheep hearts were Langendorff perfused in the presence of 0.25 µmol/L carbachol. Novel optical system recorded activations simultaneously from the entire left and right atrial endocardial surfaces. Twenty sustained (>40 s) atrial fibrillation episodes were induced by a train and premature stimuli protocol. Movies obtained immediately (Initiation stage) and 30 s (Early Stabilization stage) after premature stimulus were analyzed. Serial rotor formation was observed in all sustained inductions and none in nonsustained inductions. In sustained episodes maximal dominant frequency increased from (mean±SD) 11.5±1.74 Hz during Initiation to 14.79±1.30 Hz at Early Stabilization (P<0.0001) and stabilized thereafter. At rotor sites, mean cycle length (CL) during 10 prerotor activations increased every cycle by 0.53% (P=0.0303) during Initiation and 0.34% (P=0.0003) during Early Stabilization. In contrast, CLs at rotor sites showed abrupt decreases after the rotors appearances by a mean of 9.65% (P<0.0001) during both stages. At Initiation, atria-wide accelerations and decelerations during rotors showed a net acceleration result whereby post-rotors atria-wide minimal CL (CLmin) were 95.5±6.8% of the prerotor CLmin (P=0.0042). In contrast, during Early Stabilization, there was no net acceleration in CLmin during accelerating rotors (prerotor=84.9±11.0% versus postrotor=85.8±10.8% of Initiation, P=0.4029). Levels of rotor drift distance and velocity correlated with atria-wide acceleration. Nonrotor phase singularity points did not accelerate atria-wide activation but multiplied during Initiation until Early Stabilization. Increasing number of singularity points, indicating increased complexity, correlated with atria-wide CLmin reduction (P<0.0001). Conclusions Novel panoramic optical mapping of the atria demonstrates shortening CL at rotor sites during cholinergic atrial fibrillation onset. Atrial fibrillation acceleration toward Early Stabilization correlates with the net result of atria-wide accelerations during drifting rotors activity.

Electrocardiographic Imaging for Atrial Fibrillation: A Perspective From Computer Models and Animal Experiments to Clinical Value.

Electrocardiographic imaging (ECGI) is a technique to reconstruct non-invasively the electrical activity on the heart surface from body-surface potential recordings and geometric information of the torso and the heart. ECGI has shown scientific and clinical value when used to characterize and treat both atrial and ventricular arrhythmias. Regarding atrial fibrillation (AF), the characterization of the electrical propagation and the underlying substrate favoring AF is inherently more challenging than for ventricular arrhythmias, due to the progressive and heterogeneous nature of the disease and its manifestation, the small volume and wall thickness of the atria, and the relatively large role of microstructural abnormalities in AF. At the same time, ECGI has the advantage over other mapping technologies of allowing a global characterization of atrial electrical activity at every atrial beat and non-invasively. However, since ECGI is time-consuming and costly and the use of electrical mapping to guide AF ablation is still not fully established, the clinical value of ECGI for AF is still under assessment. Nonetheless, AF is known to be the manifestation of a complex interaction between electrical and structural abnormalities and therefore, true electro-anatomical-structural imaging may elucidate important key factors of AF development, progression, and treatment. Therefore, it is paramount to identify which clinical questions could be successfully addressed by ECGI when it comes to AF characterization and treatment, and which questions may be beyond its technical limitations. In this manuscript we review the questions that researchers have tried to address on the use of ECGI for AF characterization and treatment guidance (for example, localization of AF triggers and sustaining mechanisms), and we discuss the technological requirements and validation. We address experimental and clinical results, limitations, and future challenges for fruitful application of ECGI for AF understanding and management. We pay attention to existing techniques and clinical application, to computer models and (animal or human) experiments, to challenges of methodological and clinical validation. The overall objective of the study is to provide a consensus on valuable directions that ECGI research may take to provide future improvements in AF characterization and treatment guidance.

Short-wave infrared light imaging measures tissue moisture and distinguishes superficial from deep burns.

Existing clinical approaches and tools to measure burn tissue destruction are limited resulting in misdiagnosis of injury depth in over 40% of cases. Thus, our objective in this study was to characterize the ability of short-wave infrared (SWIR) imaging to detect moisture levels as a surrogate for tissue viability with resolution to differentiate between burns of various depths. To accomplish our aim, we constructed an imaging system consisting of a broad-band Tungsten light source; 1,200-, 1,650-, 1,940-, and 2,250-nm wavelength filters; and a specialized SWIR camera. We initially used agar slabs to provide a baseline spectrum for SWIR light imaging and demonstrated the differential absorbance at the multiple wavelengths, with 1,940 nm being the highest absorbed wavelength. These spectral bands were then demonstrated to detect levels of moisture in inorganic and in vivo mice models. The multiwavelength SWIR imaging approach was used to diagnose depth of burns using an in vivo porcine burn model. Healthy and injured skin regions were imaged 72 hours after short (20 seconds) and long (60 seconds) burn application, and biopsies were extracted from those regions for histologic analysis. Burn depth analysis based on collagen coagulation histology confirmed the formation of superficial and deep burns. SWIR multispectral reflectance imaging showed enhanced intensity levels in long burned regions, which correlated with histology and distinguished between superficial and deep burns. This SWIR imaging method represents a novel, real-time method to objectively distinguishing superficial from deep burns.

Mechanisms by Which Ranolazine Terminates Paroxysmal but Not Persistent Atrial Fibrillation.

BACKGROUND: Ranolazine inhibits Na+ current (INa), but whether it can convert atrial fibrillation (AF) to sinus rhythm remains unclear. We investigated antiarrhythmic mechanisms of ranolazine in sheep models of paroxysmal (PxAF) and persistent AF (PsAF). METHODS: PxAF was maintained during acute stretch (N=8), and PsAF was induced by long-term atrial tachypacing (N=9). Isolated, Langendorff-perfused sheep hearts were optically mapped. RESULTS: In PxAF ranolazine (10 µmol/L) reduced dominant frequency from 8.3±0.4 to 6.2±0.5 Hz (P<0.01) before converting to sinus rhythm, decreased singularity point density from 0.070±0.007 to 0.039±0.005 cm-2 s-1 (P<0.001) in left atrial epicardium (LAepi), and prolonged AF cycle length (AFCL); rotor duration, tip trajectory, and variance of AFCL were unaltered. In PsAF, ranolazine reduced dominant frequency (8.3±0.5 to 6.5±0.4 Hz; P<0.01), prolonged AFCL, increased the variance of AFCL, had no effect on singularity point density (0.048±0.011 to 0.042±0.016 cm-2 s-1; P=ns) and failed to convert AF to sinus rhythm. Doubling the ranolazine concentration (20 µmol/L) or supplementing with dofetilide (1 µmol/L) failed to convert PsAF to sinus rhythm. In computer simulations of rotors, reducing INa decreased dominant frequency, increased tip meandering and produced vortex shedding on wave interaction with unexcitable regions. CONCLUSIONS: PxAF and PsAF respond differently to ranolazine. Cardioversion in the former can be attributed partly to decreased dominant frequency and singularity point density, and prolongation of AFCL. In the latter, increased dispersion of AFCL and likely vortex shedding contributes to rotor formation, compensating for any rotor loss, and may underlie the inefficacy of ranolazine to terminate PsAF.

Optical Mapping.

Optical mapping of electrical activity in the heart is based on voltage-sensitive and lipophilic fluorescence dyes. Optical signals recorded from cardiac cells correlate well with their transmembrane potentials. High spatiotemporal resolution, wide field mapping, and high sensitivity to transmembrane potential enable detailed characterization of action potential initiation and propagation. Optical mapping is used to study complex patterns of excitation propagation, including propagation across the sinoatrial and atrioventricular nodes and during atrial and ventricular arrhythmias.Optical mapping is used to study the role of reentrant activity in atrial and ventricular fibrillation.

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.

Bimodal classification algorithm for atrial fibrillation detection from m-health ECG recordings.

INTRODUCTION: Atrial Fibrillation (AF) is the most common cardiac arrhythmia, presenting a significant independent risk factor for stroke and thromboembolism. With the emergence of m-Health devices, the importance of automatic detection of AF in an off-clinic setting is growing. This study demonstrates the performance of a bimodal classifier for distinguishing AF from sinus rhythm (SR) that could be used for automated detection of AF episodes. METHODS: Surface recordings from a hand-held research device and standard electrocardiograms (ECG) were collected and analyzed from 68 subjects. An additional 48 subjects from the MIT-BIH Arrythmia Database were also analyzed. All ECGs were blindly reviewed by physicians independently of the bimodal algorithm analysis. The algorithm selects an artifact-free 6-s ECG segment out of a 20-s long recording and computes a spectral Frequency Dispersion Metric (FDM) and a temporal R-R interval variability (VRR) index. RESULTS: Scatter plots of the VRR and FDM indices revealed two distinct clusters. The bimodal scattering of the indices revealed a linear classification boundary that could be employed to differentiate the SR from AF waveforms. The selected classification boundary was able to correctly differentiate all the subjects from both datasets into either SR or AF groups, except for 3 SR subjects from the MIT-BIH dataset. CONCLUSION: Our bimodal classification algorithm was demonstrated to successfully acquire, analyze and interpret ECGs for the presence of AF indicating its potential to support m-Health diagnosis, monitoring, and management of therapy in AF patients.

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.

Causality analysis of leading singular value decomposition modes identifies rotor as the dominant driving normal mode in fibrillation.

Cardiac fibrillation is a major clinical and societal burden. Rotors may drive fibrillation in many cases, but their role and patterns are often masked by complex propagation. We used Singular Value Decomposition (SVD), which ranks patterns of activation hierarchically, together with Wiener-Granger causality analysis (WGCA), which analyses direction of information among observations, to investigate the role of rotors in cardiac fibrillation. We hypothesized that combining SVD analysis with WGCA should reveal whether rotor activity is the dominant driving force of fibrillation even in cases of high complexity. Optical mapping experiments were conducted in neonatal rat cardiomyocyte monolayers (diameter, 35 mm), which were genetically modified to overexpress the delayed rectifier K+ channel IKr only in one half of the monolayer. Such monolayers have been shown previously to sustain fast rotors confined to the IKr overexpressing half and driving fibrillatory-like activity in the other half. SVD analysis of the optical mapping movies revealed a hierarchical pattern in which the primary modes corresponded to rotor activity in the IKr overexpressing region and the secondary modes corresponded to fibrillatory activity elsewhere. We then applied WGCA to evaluate the directionality of influence between modes in the entire monolayer using clear and noisy movies of activity. We demonstrated that the rotor modes influence the secondary fibrillatory modes, but influence was detected also in the opposite direction. To more specifically delineate the role of the rotor in fibrillation, we decomposed separately the respective SVD modes of the rotor and fibrillatory domains. In this case, WGCA yielded more information from the rotor to the fibrillatory domains than in the opposite direction. In conclusion, SVD analysis reveals that rotors can be the dominant modes of an experimental model of fibrillation. Wiener-Granger causality on modes of the rotor domains confirms their preferential driving influence on fibrillatory modes.

Eplerenone Reduces Atrial Fibrillation Burden Without Preventing Atrial Electrical Remodeling.

BACKGROUND: The aldosterone inhibitor eplerenone (EPL) has been shown to reduce the incidence of atrial fibrillation (AF) in patients with systolic heart failure, but the mechanism is unknown. OBJECTIVES: This study hypothesized that by reducing atrial dilation and fibrosis in the absence of heart failure, EPL also reduces AF burden and prevents AF perpetuation. METHODS: The authors conducted a randomized controlled study in 34 sheep that were atrially tachypaced (13 ± 1 week). They compared daily oral EPL (n = 19) versus sugar pill (SP) treatment (n = 15) from the start of tachypacing. The endpoint was a continuous 7-day stretch of persistent AF (n = 29) or completion of 23 weeks tachypacing (n = 5). RESULTS: EPL significantly reduced the rate of left atrial dilation increase during AF progression. Atria from EPL-treated sheep had less smooth muscle actin protein, collagen-III expression, interstitial atrial fibrosis, and cell hypertrophy than SP-treated sheep atria did. However, EPL did not modify the AF-induced increase in the rate of dominant frequency and ion channel densities seen under SP treatment, but rather prolonged the time to persistent AF in 26% of animals. It also reduced the degree of fibrillatory conduction, AF inducibility, and AF burden. CONCLUSIONS: In the sheep model, EPL mitigates fibrosis and atrial dilation, modifies AF inducibility and AF complexity, and prolongs the transition to persistent AF in 26% of animals, but it does not prevent AF-induced electrical remodeling or AF persistence. The results highlight structural remodeling as a central upstream target to reduce AF burden, and the need to prevent electrical remodeling to avert AF perpetuation.

Technical Considerations on Phase Mapping for Identification of Atrial Reentrant Activity in Direct- and Inverse-Computed Electrograms.

BACKGROUND: Phase mapping has become a broadly used technique to identify atrial reentrant circuits for ablative therapy guidance. This work studies the phase mapping process and how the signal nature and its filtering affect the reentrant pattern characterization in electrogram (EGM), body surface potential mapping, and electrocardiographic imaging signals. METHODS AND RESULTS: EGM, body surface potential mapping, and electrocardiographic imaging phase maps were obtained from 17 simulations of atrial fibrillation, atrial flutter, and focal atrial tachycardia. Reentrant activity was identified by singularity point recognition in raw signals and in signals after narrow band-pass filtering at the highest dominant frequency (HDF). Reentrant activity was dominantly present in the EGM recordings only for atrial fibrillation and some atrial flutter propagations patterns, and HDF filtering allowed increasing the reentrant activity detection from 60% to 70% of time in atrial fibrillation in unipolar recordings and from 0% to 62% in bipolar. In body surface potential mapping maps, HDF filtering increased from 10% to 90% the sensitivity, although provoked a residual false reentrant activity ≈30% of time. In electrocardiographic imaging, HDF filtering allowed to increase ≤100% the time with detected rotors, although provoked the apparition of false rotors during 100% of time. Nevertheless, raw electrocardiographic imaging phase maps presented reentrant activity just in atrial fibrillation recordings accounting for ≈80% of time. CONCLUSIONS: Rotor identification is accurate and sensitive and does not require additional signal processing in measured or noninvasively computed unipolar EGMs. Bipolar EGMs and body surface potential mapping do require HDF filtering to detect rotors at the expense of a decreased specificity.