Journal: Circ Arrhythm Electrophysiol

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Abstract

Single-molecule Localization of Na1.5 Reveals Different Modes of Reorganization at Cardiomyocyte Membrane Domains.

Vermij SH, Rougier JS, Agulló-Pascual E, Rothenberg E, Delmar M, Abriel H

- Mutations in the gene encoding the sodium channel Na1.5 cause various cardiac arrhythmias. This variety may arise from different determinants of Na1.5 expression between cardiomyocyte domains. At the lateral membrane and T-tubules, Na1.5 localization and function remain insufficiently characterized.- We used novel single-molecule localization microscopy (SMLM) and computational modeling to define nanoscale features of Na1.5 localization and distribution at the lateral membrane (LM), the LM groove, and T-tubules (TT) in cardiomyocytes from wild-type ( = 3), dystrophin-deficient (;= 3) mice, and mice expressing C-terminally truncated Na1.5 (ΔSIV;= 3). We moreover assessed TT sodium current by recording whole-cell sodium currents in control ( = 5) and detubulated ( = 5) wild-type cardiomyocytes.- We show that Na1.5 organizes as distinct clusters in the groove and T-tubules which density, distribution, and organization partially depend on SIV and dystrophin. We found that overall reduction in Na1.5 expression inand ΔSIV cells results in a non-uniform re-distribution with Na1.5 being specifically reduced at the groove of ΔSIV and increased in T-tubules ofcardiomyocytes. A TT sodium current could however not be demonstrated.- Na1.5 mutations may site-specifically affect Na1.5 localization and distribution at the lateral membrane and T-tubules, depending on site-specific interacting proteins. Future research efforts should elucidate the functional consequences of this redistribution.



Circ Arrhythm Electrophysiol: 14 Jun 2020; epub ahead of print
Vermij SH, Rougier JS, Agulló-Pascual E, Rothenberg E, Delmar M, Abriel H
Circ Arrhythm Electrophysiol: 14 Jun 2020; epub ahead of print | PMID: 32536203
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Abstract

A Clinico-pathological \"Bird\'s-Eye\" View of Left Atrial Myocardial Fibrosis in 121 Patients with Persistent Atrial Fibrillation: Developing Architecture and Main Cellular Players.

Callegari S, Macchi E, Monaco R, Magnani L, ... Alfieri O, Corradi D

- Scientific research on atrial fibrosis in atrial fibrillation (AF) has mainly focused on quantitative and/or molecular features. The purpose of this study was to perform a clinico-architectural/structural investigation of fibrosis to provide one key to understanding the electrophysiological/clinical aspects of AF.- We characterized the fibrosis (amount, architecture, cellular components, and ultrastructure) in left atrial biopsies from 121 patients with persistent/long-lasting persistent AF () (59 males; 60±11 years; 91 mitral disease-related AF, 30 non-mitral disease-related AF) and from 39 patients in sinus rhythm with mitral-valve regurgitation (; 32 males; 59±12 years). Ten autopsy hearts served as controls.- Qualitatively, the fibrosis exhibited the same characteristics in all cases and displayed particular architectural scenarios (which we arbitrarily subdivided into four stages) ranging from isolated foci to confluent sclerotic areas. The percentage of fibrosis was larger and at a more advanced stage invs.and, within , in patients with rheumatic disease vs. non-rheumatic cases. In AF patients with mitral disease and no rheumatic disease, the percentage of fibrosis and the fibrosis stages correlated with both left atrial volume index and AF duration. The fibrotic areas mainly consisted of type I collagen with only a minor cellular component (especially fibroblasts/myofibroblasts; average value range 69-150 cells/mm, depending on the areas in AF biopsies). A few fibrocytes-circulating and bone marrow-derived mesenchymal cells-were also detectable. The fibrosis-entrapped cardiomyocytes showed sarcolemmal damage and connexin 43 redistribution/internalization.- Atrial fibrosis is an evolving and inhomogeneous histological/architectural change which progresses through different stages ranging from isolated foci to confluent sclerotic zones which - seemingly - constrain impulse conduction across restricted regions of electrotonically-coupled cardiomyocytes. The fibrotic areas mainly consist of type I collagen extracellular matrix and, only to a lesser extent, mesenchymal cells.



Circ Arrhythm Electrophysiol: 13 Jun 2020; epub ahead of print
Callegari S, Macchi E, Monaco R, Magnani L, ... Alfieri O, Corradi D
Circ Arrhythm Electrophysiol: 13 Jun 2020; epub ahead of print | PMID: 32538131
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Abstract

Machine Learning of 12-lead QRS Waveforms to Identify Cardiac Resynchronization Therapy Patients with Differential Outcomes.

Feeny AK, Rickard J, Trulock KM, Patel D, ... Madabhushi A, Chung MK

- Cardiac resynchronization therapy (CRT) improves heart failure outcomes but has significant non-response rates, highlighting limitations in ECG selection criteria: QRS duration (QRSd) ≥150 ms and subjective labeling of left bundle branch block (LBBB). We explored unsupervised machine learning of ECG waveforms to identify CRT subgroups that may differentiate outcomes beyond QRSd and LBBB.- We retrospectively analyzed 946 CRT patients with conduction delay. Principal components analysis (PCA) dimensionality reduction obtained a two-dimensional representation of pre-CRT 12-lead QRS waveforms. -means clustering of the two-dimensional PCA representation of 12-lead QRS waveforms identified two patient subgroups (QRS PCA groups). Vectorcardiographic QRS area was also calculated. We examined two primary outcomes: (1) composite endpoint of death, left ventricular assist device, or heart transplant, and (2) degree of echocardiographic left ventricular ejection fraction (LVEF) change after CRT.- Compared to QRS PCA Group 2 (=425), Group 1 (n=521) had lower risk for reaching the composite endpoint (HR 0.44, 95% CI, 0.38-0.53, p<0.001) and experienced greater mean LVEF improvement (11.1±11.7% vs. 4.8±9.7%, p<0.001), even among LBBB patients with QRSd ≥150 ms (HR 0.42, 95% CI, 0.30-0.57, p<0.001; mean LVEF change 12.5±11.8% vs. 7.3±8.1%, p=0.001). QRS area also stratified outcomes but had significant differences from QRS PCA groups. A stratification scheme combining QRS area and QRS PCA group identified LBBB patients with similar outcomes to non-LBBB patients (HR 1.32, 95% CI: 0.93-1.62; difference in mean LVEF change: 0.8%, 95% CI: -2.1%-3.7%). The stratification scheme also identified LBBB patients with QRSd <150 ms with comparable outcomes to LBBB patients with QRSd ≥150 ms (HR: 0.93, 95% CI: 0.67-1.29; difference in mean LVEF change: -0.2%, 95% CI: -2.7%-3.0%).- Unsupervised machine learning of ECG waveforms identified CRT subgroups with relevance beyond LBBB and QRSd. This method may assist in objective classification of bundle branch block morphology in CRT.



Circ Arrhythm Electrophysiol: 13 Jun 2020; epub ahead of print
Feeny AK, Rickard J, Trulock KM, Patel D, ... Madabhushi A, Chung MK
Circ Arrhythm Electrophysiol: 13 Jun 2020; epub ahead of print | PMID: 32538136
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Abstract

Pre-Procedure Application of Machine Learning and Mechanistic Simulations Predicts Likelihood of Paroxysmal Atrial Fibrillation Recurrence Following Pulmonary Vein Isolation.

Shade JK, Ali RL, Basile D, Popescu D, ... Calkins H, Trayanova NA

- Pulmonary vein isolation (PVI) is an effective treatment strategy for patients with atrial fibrillation (AF), but many experience AF recurrence and require repeat ablation procedures. The goal of this study was to develop and evaluate a methodology which combines machine learning (ML) and personalized computational modeling to predict, prior to PVI, which patients are most likely to experience AF recurrence after PVI.- This single-center retrospective proof-of-concept study included 32 patients with documented paroxysmal AF who underwent PVI and had pre-procedural late gadolinium enhanced magnetic resonance imaging (LGE-MRI). For each patient, a personalized computational model of the left atrium simulated AF induction via rapid pacing. Features were derived from pre-PVI LGE-MRI images and from results of simulations (SimAF). The most predictive features were used as input to a quadratic discriminant analysis ML classifier, which was trained, optimized, and evaluated with 10-fold nested cross validation to predict the probability of AF recurrence post-PVI.- In our cohort, the ML classifier predicted probability of AF recurrence with an average validation sensitivity and specificity of 82% and 89%, respectively, and a validation AUC of 0.82. Dissecting the relative contributions of SimAF and raw images to the predictive capability of the ML classifier, we found that when only features from SimAF were used to train the ML classifier, its performance remained similar (validation AUC=0.81). However, when only features extracted from raw images were used for training, the validation AUC significantly decreased (0.47).- ML and personalized computational modeling can be used together to accurately predict, using only pre-PVI LGE-MRI scans as input, whether a patient is likely to experience AF recurrence following PVI, even when the patient cohort is small.



Circ Arrhythm Electrophysiol: 13 Jun 2020; epub ahead of print
Shade JK, Ali RL, Basile D, Popescu D, ... Calkins H, Trayanova NA
Circ Arrhythm Electrophysiol: 13 Jun 2020; epub ahead of print | PMID: 32536204
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Abstract

Prospective Assessment of An Automated Intraprocedural 12-lead ECG-Based System for Localization of Early Left Ventricular Activation.

Zhou S, AbdelWahab A, Horáček BM, MacInnis PJ, ... Trayanova NA, Sapp JL

- To facilitate ablation of ventricular tachycardia (VT), an automated localization system to identify the site of origin of left ventricular (LV) activation in real time using the 12-lead ECG was developed. The objective of this study was to prospectively assess its accuracy.- The automated site of origin localization (SOLO) system consists of three steps: (1) localization of ventricular segment based on population templates, (2) population-based localization within a segment, and (3) patient-specific site localization. Localization error was assessed by the distance between the known reference site and the estimated site.- In 19 patients undergoing 21 catheter ablation procedures of scar-related VT, SOLO accuracy was estimated using 552 LV endocardial pacing sites pooled together, and 25 VT-exit sites identified by contact mapping. For the 25 VT-exit sites, localization error of the population-based localization steps was within 10 mm. Patient-specific site localization achieved accuracy of within 3.5 mm after including up to 11 pacing (training) sites. Using three remotes (67.8 ± 17.0 mm from the reference VT-exit site), and then 5 close pacing sites, resulted in localization error of 7.2 ± 4.1 mm for the 25 identified VT-exit sites. In two emulated clinical procedure with 2 induced VTs, the SOLO system achieved accuracy within 4 mm.- In this prospective validation study, the automated localization system achieved estimated accuracy within 10 mm and could thus provide clinical utility.



Circ Arrhythm Electrophysiol: 14 Jun 2020; epub ahead of print
Zhou S, AbdelWahab A, Horáček BM, MacInnis PJ, ... Trayanova NA, Sapp JL
Circ Arrhythm Electrophysiol: 14 Jun 2020; epub ahead of print | PMID: 32538133
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Abstract

Clinical Outcomes and Characteristics with Dofetilide in Atrial Fibrillation Patients Considered for Implantable Cardioverter-Defibrillator.

Koene RJ, Menon V, Cantillon DJ, Dresing TJ, ... Lindsay BD, Wazni OM

- Dofetilide is one of the only anti-arrhythmic agents approved for atrial fibrillation (AF) in patients with reduced left ventricular ejection fraction (LVEF). However, post-approval data and safety outcomes are limited. In this study, we assessed the incidence and predictors of LVEF improvement, safety, and outcomes in AF patients with LVEF ≤ 35% without prior implantable cardioverter defibrillator (ICD), cardiac resynchronization therapy (CRT), or AF ablation.- An analysis of 168 consecutive patients from 2007 to 2016 was performed. Incidences of adverse events, drug continuation, ICD and/or CRT implantation, LVEF improvement (>35%) and recovery (≥50%), AF recurrence, and AF ablation were determined. Multivariable regression analysis to identify predictors of LVEF improvement/recovery was performed.- The mean age was 64±12 years. Dofetilide was discontinued prior to hospital discharge in 46 (27%) because of QT prolongation (14%), torsades de pointe or polymorphic ventricular tachycardia/fibrillation (6% [sustained 3%, non-sustained 3%]), ineffectiveness (5%), or other causes (3%). At 1 year, 43% remained on dofetilide. Freedom from AF was 42% at 1 year, and 40% underwent future AF ablation. LVEF recovered (≥ 50%) in 45% and improved to >35% in 73%. Predictors of LVEF improvement included presence of AF during echocardiogram (odds ratio [OR] 4.22, 95% CI, 1.71 - 10.4, p=0.002), coronary artery disease (OR 0.35, 95% CI, 0.16 - 0.79, p=0.01), left atrial diameter (OR 0.52 per 1 cm increase, 95% CI 0.30 - 0.90, p=0.01), and LVEF (OR per 1% increase, 1.09, 95% CI, 1.02 - 1.16, p=0.006). The C-statistic was 0.78.- In patients with LVEF ≤ 35%, who are potential ICD candidates, treated with dofetilide as an initial anti-arrhythmic strategy for AF, drug discontinuation rates were high, and many underwent future AF ablation. However, most patients had improvement in LVEF, obviating the need for primary prevention ICD.



Circ Arrhythm Electrophysiol: 13 Jun 2020; epub ahead of print
Koene RJ, Menon V, Cantillon DJ, Dresing TJ, ... Lindsay BD, Wazni OM
Circ Arrhythm Electrophysiol: 13 Jun 2020; epub ahead of print | PMID: 32538135
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Abstract

Late I blocker GS967 Suppress Polymorphic VT in a Transgenic Rabbit Model of Long QT Type 2.

Hwang J, Kim TY, Terentyev D, Zhong M, ... Koren G, Choi BR

- Long QT syndrome (LQTS) has been associated with sudden cardiac death likely caused by early afterdepolarizations (EADs) and polymorphic ventricular tachycardias (PVTs). Suppressing the late sodium current (I) may counterbalance the reduced repolarization reserve in LQTS and prevent EADs and PVTs.- We tested the effects of the selective I blocker GS967 on PVT induction in a transgenic rabbit model of LQTS type 2 (LQT2) using intact heart optical mapping, cellular electrophysiology and confocal Ca imaging, and computer modeling.- GS967 reduced (ventricular fibrillation) VF induction under a rapid pacing protocol (n=7/14 hearts in control vs. 1/14 hearts at 100 nM) without altering APD or restitution and dispersion. GS967 suppressed PVT incidences by reducing Ca-mediated EADs and focal activity during isoproterenol perfusion (at 30 nM, n=7/12 and 100 nM n=8/12 hearts without EADs and PVTs). Confocal Ca imaging of LQT2 myocytes revealed that GS967 shortened Ca transient duration via accelerating Na/Ca exchanger (I)-mediated Ca efflux from cytosol, thereby reducing EADs. Computer modeling revealed that I potentiates EADs in the LQT2 setting through 1) providing additional depolarizing currents during AP plateau phase, 2) increasing intracellular Na (Na) that decreases the depolarizing I thereby suppressing the AP plateau and delaying the activation of slowly-activating delayed rectifier K channels (I), suggesting important roles of I in regulating Na.- Selective I blockade by GS967 prevents EADs and abolishes PVT in LQT2 rabbits by counterbalancing the reduced repolarization reserve and normalizing Na.



Circ Arrhythm Electrophysiol: 05 Jul 2020; epub ahead of print
Hwang J, Kim TY, Terentyev D, Zhong M, ... Koren G, Choi BR
Circ Arrhythm Electrophysiol: 05 Jul 2020; epub ahead of print | PMID: 32628505
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Abstract

Artificial Intelligence and Machine Learning in Arrhythmias and Cardiac Electrophysiology.

Feeny AK, Chung MK, Madabhushi A, Attia ZI, ... Turakhia MP, Wang PJ

Artificial intelligence (AI) and machine learning (ML) in medicine are currently areas of intense exploration, showing potential to automate human tasks and even perform tasks beyond human capabilities. Literacy and understanding of AI/ML methods are becoming increasingly important to researchers and clinicians. The first objective of this review is to provide the novice reader with literacy of AI/ML methods and provide a foundation for how one might conduct an ML study. We provide a technical overview of some of the most commonly used terms, techniques, and challenges in AI/ML studies, with reference to recent studies in cardiac electrophysiology to illustrate key points. The second objective of this review is to use examples from recent literature to discuss how AI and ML are changing clinical practice and research in cardiac electrophysiology, with emphasis on disease detection and diagnosis, prediction of patient outcomes, and novel characterization of disease. The final objective is to highlight important considerations and challenges for appropriate validation, adoption, and deployment of AI technologies into clinical practice.



Circ Arrhythm Electrophysiol: 05 Jul 2020; epub ahead of print
Feeny AK, Chung MK, Madabhushi A, Attia ZI, ... Turakhia MP, Wang PJ
Circ Arrhythm Electrophysiol: 05 Jul 2020; epub ahead of print | PMID: 32628863
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Abstract

Characterization of Lead Adherence Using Intravascular Ultrasound to Assess Difficulty of Transvenous Lead Extraction.

Beaser AD, Aziz Z, Besser SA, Jones CI, ... Tung R, Nayak HM

- Clinical factors associated with development of intravascular lead adherence (ILA) are unreliable predictors. Because vascular injury in the superior vena cava - right atrium (SVC-RA) during transvenous lead extraction (TLE) is more likely to occur in segments with higher degrees of ILA, reliable and accurate assessment of ILA is warranted. We hypothesized that intravascular ultrasound (IVUS) could accurately visualize and quantify ILA and degree of ILA correlates with TLE difficulty.- Serial imaging of leads occurred prior to TLE using IVUS. ILA areas were classified as high or low grade. Degree of extraction difficulty was assessed using 2 metrics and correlated with ILA grade. Lead extraction difficulty (LED) was calculated for each patient and compared to IVUS findings.- 158 vascular segments in 60 patients were analyzed: 141 (89%) low grade versus 17 (11%) high grade. Median extraction time (low=0 versus high grade=97 seconds, p<0.001) and median laser pulsations delivered (low=0 versus high grade=5852, p<0.001) were significantly higher in high grade segments. Most patients with low LED score had low ILA grades. 86% of patients with high LED score had low IVUS grade and the degree of TLE difficulty was similar to patients with low IVUS grades and LED scores.- IVUS is a feasible imaging modality that may be useful in characterizing ILA in the SVC-RA region. An ILA grading system using imaging correlates with extraction difficulty. Most patients with clinical factors associated with higher extraction difficulty may exhibit lower ILA and extraction difficulty based on IVUS imaging.



Circ Arrhythm Electrophysiol: 05 Jul 2020; epub ahead of print
Beaser AD, Aziz Z, Besser SA, Jones CI, ... Tung R, Nayak HM
Circ Arrhythm Electrophysiol: 05 Jul 2020; epub ahead of print | PMID: 32628867
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Abstract

Electrocardiogram Standards for Children and Young Adults Using Z-scores.

Bratincsák A, Kimata C, Limm-Chan BN, Vincent K, Williams M, Perry JC

- Normative ECG values for children are based on relatively few subjects and are not standardized, resulting in interpersonal variability of interpretation. Recent advances in digital technology allow a more quantitative, reproducible assessment of ECG variables. Our objective was to create the foundation of normative ECG standards in the young utilizing Z-scores.- One-hundred-and-two ECG variables were collected from a retrospective cohort of 27085 study subjects with no known heart condition, ages 0-39 years. The cohort was divided into 16 age groups by gender. Median, interquartile range and range were calculated for each variable adjusted to body surface area.- Normative standards were developed for all 102 ECG variables including heart rate; P, R, and T axis; R-T axis deviation; PR interval, QRS duration, QT and QTc interval; P, Q, R, S, and T amplitudes in 12 leads; as well as QRS and T wave integrals. Incremental Z-score values between -2.5 and 2.5 were calculated to establish upper and lower limits of normal. Historical ECG interpretative concepts were reassessed and new concepts observed.- Electronically acquired ECG values based on the largest pediatric and young adult cohort ever compiled provide the first detailed, standardized, quantitative foundation of traditional and novel ECG variables. Expression of ECG variables by Z-scores lends an objective and reproducible evaluation without interpreter bias that can lead to more confident establishment of ECG-disease correlations and improved automated ECG readings in high volume cardiac screening efforts in the young.



Circ Arrhythm Electrophysiol: 06 Jul 2020; epub ahead of print
Bratincsák A, Kimata C, Limm-Chan BN, Vincent K, Williams M, Perry JC
Circ Arrhythm Electrophysiol: 06 Jul 2020; epub ahead of print | PMID: 32634327
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Abstract

Machine Learning to Classify Intracardiac Electrical Patterns during Atrial Fibrillation.

Alhusseini MI, Abuzaid F, Rogers AJ, Zaman JAB, ... Rappel WJ, Narayan SM

- Advances in ablation for atrial fibrillation (AF) continue to be hindered by ambiguities in mapping, even between experts. We hypothesized that convolutional neural networks (CNN) may enable objective analysis of intracardiac activation in AF, which could be applied clinically if CNN classifications could also be explained.- We performed panoramic recording of bi-atrial electrical signals in AF. We used the Hilbert-transform to produce 175,000 image grids in 35 patients, labeled for rotational activation by experts who showed consistency but with variability (kappa=0.79). In each patient, ablation terminated AF. A CNN was developed and trained on 100,000 AF image grids, validated on 25,000 grids, then tested on a separate 50,000 grids.- In the separate test cohort (50,000 grids), CNN reproducibly classified AF image grids into those with/without rotational sites with 95.0% accuracy (CI 94.8-95.2%). This accuracy exceeded that of support vector machines, traditional linear discriminant and k-nearest neighbor statistical analyses. To probe the CNN, we applied Gradient-weighted Class Activation Mapping which revealed that the decision logic closely mimicked rules used by experts (C-statistic 0.96).- Convolutional neural networks improved the classification of intracardiac AF maps compared to other analyses, and agreed with expert evaluation. Novel explainability analyses revealed that the CNN operated using a decision logic similar to rules used by experts, even though these rules were not provided in training. We thus describe a scaleable platform for robust comparisons of complex AF data from multiple systems, which may provide immediate clinical utility to guide ablation.



Circ Arrhythm Electrophysiol: 05 Jul 2020; epub ahead of print
Alhusseini MI, Abuzaid F, Rogers AJ, Zaman JAB, ... Rappel WJ, Narayan SM
Circ Arrhythm Electrophysiol: 05 Jul 2020; epub ahead of print | PMID: 32631100
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Abstract

Endocardial-Epicardial Phase Mapping of Prolonged Persistent Atrial Fibrillation Recordings: High Prevalence of Dissociated Activation Patterns.

Parameswaran R, Kalman JM, Royse A, Goldblatt J, ... Gerstenfeld EP, Lee G

- Endocardial-epicardial dissociation (EED) and focal breakthroughs in humans with atrial fibrillation (AF) have been recently demonstrated using activation mapping of short 10-second AF segments. In the current study we used simultaneous endo-epi phase mapping to characterise endo-epi activation patterns on long segments of human persistent AF (PeAF).- Simultaneous intra-operative mapping of endo- and epicardial lateral RA wall was performed in patients with PeAF using two high-density grid catheters (16 electrodes, 3mm spacing). Filtered unipolar and bipolar electrograms (EGM\'s) of continuous 2-min AF recordings and electrodes locations were exported for phase analyses. We defined EED as phase difference of ≥20ms between paired endo-epi electrodes. Wavefronts (WF) were classified as rotations, single WF (SWF), focal waves or disorganised activity as per standard criteria. Endo-Epi WF patterns were simultaneously compared on dynamic phase maps. Complex fractionated EGM\'s were defined as bipolar EGM\'s with ≥5 directional changes occupying at least 70% of sample duration.- Fourteen patients with PeAF undergoing cardiac surgery were included. EED was seen in 50.3% of phase maps with significant temporal heterogeneity. Disorganised activity (Endo:41.3% vs Epi:46.8%, p=0.0194) and SWF (Endo:31.3% vs Epi:28.1%, p=0.129) were the dominant patterns. Transient rotations (Endo:22% vs Epi:19.2%, p=0.169; mean duration: 590±140ms) and non-sustained focal waves (Endo:1.2% vs Epi:1.6%, p=0.669) were also observed. Apparent transmural migration of rotational activations (n=6) from the epi- to the endocardium was seen in 2 patients. EGM fractionation was significantly higher in the epicardium than endocardium (61.2% vs 51.6%, p<0.0001).- Simultaneous endo-epi phase mapping of prolonged human PeAF recordings shows significant EED marked temporal heterogeneity, discordant and transitioning WF patterns and complex fractionations. No sustained focal activity was observed. Such complex 3D-interactions provide insight into why endocardial mapping alone may not fully characterise the AF mechanism and why endocardial ablation may not be sufficient.



Circ Arrhythm Electrophysiol: 06 Jul 2020; epub ahead of print
Parameswaran R, Kalman JM, Royse A, Goldblatt J, ... Gerstenfeld EP, Lee G
Circ Arrhythm Electrophysiol: 06 Jul 2020; epub ahead of print | PMID: 32634027
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