High-density mapping of electrically induced atrial fibrillation in humans

Catheter ablation for atrial fibrillation: indications and future perspective

Recent advances in techniques, technologies and proven superiority over anti-arrhythmic drugs have made catheter ablation the cornerstone of management for atrial fibrillation (AF), which has shown a steady increase in prevalence in the ageing population worldwide. The aim of therapeutic interventions is to achieve stable sinus rhythm that would improve the quality of life and reduce the risk of AF-associated complications. Pulmonary veins (PVs) were first described as the source of initiation of ectopic triggers driving AF, which led to the establishment of PV isolation (PVI) as the most widely practiced procedure to treat AF. Antral PVI is still recognized as the stand-alone ablation strategy for newly diagnosed paroxysmal AF (PAF). However, in non-PAF patients, PVI seems to be inadequate and several adjunctive strategies, including ablation of left atrial posterior wall and non-PV triggers, AF mapping and ablation of rotors and drivers, ethanol infusion of vein of Marshall and renal denervation, etc. have been reported with mixed results. Recent trials have also documented the benefits of early rhythm control in preventing cardiovascular events in addition to slowing the progression of PAF to more persistent forms. Similarly, very late relapse of the arrhythmia after successful PVI has drawn attention to the critical role of non-PV triggers and highlighted their relevance as potential ablation targets during repeat procedures. Ablation technology is also under constant evolution with the introduction of non-thermal energy sources and new tools to create durable lesions. This review summarizes the indications, advancements, and future perspective of AF ablation.

Identification of Critical Slowing of Conduction Using Unipolar Atrial Voltage and Fractionation Mapping

BACKGROUND

Ablation strategies targeting fractionated or low-voltage potentials have been widely used in patients with persistent types of atrial fibrillation (AF). However, recent studies have questioned their role in effectively representing sites of conduction slowing, and thus arrhythmogenic substrates.

OBJECTIVES

The authors studied the relationship between local conduction velocity (CV) and the occurrence of fractionated and/or low-voltage potentials in order to identify areas with critically slowing of conduction.

METHODS

Intraoperative epicardial mapping was performed during sinus rhythm. Unipolar potentials with an amplitude <1.0 mV were initially classified as low-voltage and potentials with ≥3 deflections as fractionation. A range of thresholds were also explored. Local CV was computed using discrete velocity vectors.

RESULTS

A total of 319 patients were included. Fractionated, low-voltage potentials were rare, accounting for only 0.36% (Q1-Q3: 0.15%-0.78%) of all atrial sites. Local CV at sites with fractionated, low-voltage potentials (46.0 cm/s [Q1-Q3: 22.6-72.7 cm/s]) was lowest compared with sites with either low-voltage, nonfractionated potentials (64.5 cm/s [Q1-Q3: 34.8-99.4 cm/s]) or fractionated, high-voltage potentials (65.9 cm/s [Q1-Q3: 41.7-92.8 cm/s]; P < 0.001). Slow conduction areas (CV <50 cm/s) could be most accurately identified by using a low voltage threshold (<1 mV) and a minimum of 3 deflections (positive predictive value: 54.2%-70.7%), although the overall sensitivity remained low (0.1%-1.9%).

CONCLUSIONS

Sites with fractionated, low-voltage potentials have substantially slower local CV compared with sites with either low-voltage, nonfractionated potentials or fractionated, high-voltage potentials. However, the strong inverse relationship between the positive predictive value and sensitivity of a combined voltage and fractionation threshold for slowed conduction is likely to complicate the use of these signal-based ablation approaches in AF patients.

Conduction Velocity and Anisotropic Properties of Fibrillation Waves During Acutely Induced and Long-Standing Persistent AF

BACKGROUND

Quantified features of local conduction heterogeneity due to pathological alterations of myocardial tissue could serve as a marker for the degree of electrical remodeling and hence be used to determine the stage of atrial fibrillation (AF).

OBJECTIVES

In this study, the authors investigated whether local directional heterogeneity (LDH) and anisotropy ratio, derived from estimated local conduction velocities (CVs) during AF, are suitable electrical parameters to stage AF.

METHODS

Epicardial mapping (244-electrode array, interelectrode distance 2.25 mm) of the right atrium was performed during acute atrial fibrillation (AAF) (n = 25, 32 ± 11 years of age) and during long-standing persistent atrial fibrillation (LSPAF) (n = 23, 64 ± 9 years of age). Episodes of 9 ± 4 seconds of AF were analyzed. Local CV vectors were constructed to assess the degree of anisotropy. Directions and magnitudes of individual vectors were compared with surrounding vectors to identify LDH.

RESULTS

Compared with the entire AAF group, LSPAF was characterized by slower conduction (71.5 ± 6.8 cm/s vs 67.6 ± 5.6 cm/s; P = 0.037) with a larger dispersion (1.59 ± 0.21 vs 1.95 ± 0.17; P < 0.001) and temporal variability (32.0 ± 4.7 cm/s vs 38.5 ± 3.3 cm/s; P < 0.001). Also, LSPAF was characterized by more LDH (19.6% ± 4.4% vs 26.0% ± 3.4%; P < 0.001) and a higher degree of anisotropy (1.38 ± 0.07 vs 1.51 ± 0.14; P < 0.001). Compared with the most complex type of AAF (type III), LSPAF was still associated with a larger CV dispersion, higher temporal variability of CV, and larger amount of LDH.

CONCLUSIONS

Increasing AF complexity was associated with increased spatiotemporal variability of local CV vectors, local conduction heterogeneity, and anisotropy ratio. By using these novel parameters, LSPAF could potentially be discriminated from the most complex type of AAF. These observations may indicate pathological alterations of myocardial tissue underlying progression of AF.

Automated prediction of isthmus areas in scar-related atrial tachycardias using artificial intelligence

INTRODUCTION

Ablation of scar-related reentrant atrial tachycardia (SRRAT) involves identification and ablation of a critical isthmus. A graph convolutional network (GCN) is a machine learning structure that is well-suited to analyze the irregularly-structured data obtained in mapping procedures and may be used to identify potential isthmuses.

METHODS

Electroanatomic maps from 29 SRRATs were collected, and custom electrogram features assessing key tissue and wavefront properties were calculated for each point. Isthmuses were labeled off-line. Training data was used to determine the optimal GCN parameters and train the final model. Putative isthmus points were predicted in the training and test populations and grouped into proposed isthmus areas based on density and distance thresholds. The primary outcome was the distance between the centroids of the true and closest proposed isthmus areas.

RESULTS

A total of 193 821 points were collected. Thirty isthmuses were detected in 29 tachycardias among 25 patients (median age 65.0, 5 women). The median (IQR) distance between true and the closest proposed isthmus area centroids was 8.2 (3.5, 14.4) mm in the training and 7.3 (2.8, 16.1) mm in the test group. The mean overlap in areas, measured by the Dice coefficient, was 11.5 ± 3.2% in the training group and 13.9 ± 4.6% in the test group.

CONCLUSION

A GCN can be trained to identify isthmus areas in SRRATs and may help identify critical ablation targets.

Impact of age-related gut microbiota dysbiosis and reduced short-chain fatty acids on the autonomic nervous system and atrial fibrillation in rats

Objective

Aging is the most significant contributor to the increasing prevalence of atrial fibrillation (AF). Dysbiosis of gut microbiota has been implicated in age-related diseases, but its role in AF development remains unclear. This study aimed to investigate the correlations between changes in the autonomic nervous system, short-chain fatty acids (SCFAs), and alterations in gut microbiota in aged rats with AF.

Methods

Electrophysiological experiments were conducted to assess AF induction rates and heart rate variability in rats. 16S rRNA gene sequences extracted from fecal samples were used to assess the gut microbial composition. Gas and liquid chromatography-mass spectroscopy was used to identify SCFAs in fecal samples.

Results

The study found that aged rats exhibited a higher incidence of AF and reduced heart rate variability compared to young rats. Omics research revealed disrupted gut microbiota in aged rats, specifically a decreased Firmicutes to Bacteroidetes ratio. Additionally, fecal SCFA levels were significantly lower in aged rats. Importantly, correlation analysis indicated a significant association between decreased SCFAs and declining heart rate variability in aged rats.

Conclusions

These findings suggest that SCFAs, as metabolites of gut microbiota, may play a regulatory role in autonomic nervous function and potentially influence the onset and progression of AF in aged rats. These results provide novel insights into the involvement of SCFAs and autonomic nervous system function in the pathogenesis of AF. These results provide novel insights into the involvement of SCFAs and autonomic nervous system function in the pathogenesis of AF.

RETRO-mapping: A novel algorithm automating wavefront categorization using activation mapping during persistent atrial fibrillation demonstrates a reduction in wavefront collisions following pulmonary vein isolation

RETRO-mapping was developed to automate activation mapping of atrial fibrillation (AF). We used the algorithm to study the effect of pulmonary vein isolation (PVI) on the frequency of focal, planar, and colliding wavefronts in persistent AF. An AFocusII catheter was placed on the left atrial endocardium to record 3 s of AF at six sites pre and post-PVI in patients undergoing wide circumferential PVI for persistent AF. RETRO-mapping analyzed each segment in 2 ms time windows for evidence of focal, planar, and colliding waveforms and the automated categorizations manually validated. Ten patients were recruited. A total of 360 s of data in 120 segments of 3 s from 60 left atrial locations were analyzed. RETRO-map was highly effective at identifying focal waves and collisions during AF. PVI significantly reduced collision frequency but not focal and planar activation frequency. However, there was a significant reduction in the dispersion of activation directions. Larger studies may help determine factors associated with successful clinical outcome.

Computational Modeling and Simulation of the Fibrotic Human Atria

Patient-specific modeling of atrial electrical activity enables the execution of simulations that can provide mechanistic insights and provide novel solutions to vexing clinical problems. The geometry and fibrotic remodeling of the heart can be reconstructed from clinical-grade medical scans and used to inform personalized models with detail incorporated at the cell- and tissue-scale to represent changes in image-identified diseased regions. Here, we provide a rubric for the reconstruction of realistic atrial models from pre-segmented 3D renderings of the left atrium with fibrotic tissue regions delineated, which are the output from clinical-grade systems for quantifying fibrosis. We then provide a roadmap for using those models to carry out patient-specific characterization of the fibrotic substrate in terms of its potential to harbor reentrant drivers via cardiac electrophysiology simulations.

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.

Massive Atrial Thrombosis: A Serious Complication of the Maze Procedure Triggered by Heparin-Induced Thrombocytopenia (HIT)

Atrial fibrillation is one of the most common cardiac arrhythmias, classically presenting with an "irregularly irregular" rhythm with or without chest pain, palpitations, shortness of breath, lightheadedness, or fatigue. The maze procedure is an open-heart operation that creates a carefully designed maze of incisions and ablations in the atrial myocardium. Although it is a common procedure, serious complications may happen. Herein, we report on a 76-year-old man who presented with chest pain and atrial fibrillation and was found to have multi-vessel disease on a coronary angiogram. He underwent coronary artery bypass and the COX-maze procedure, which was complicated by a massive thrombosis in the atria and the superior vena cava following the ablation line, secondary to heparin-induced thrombocytopenia, which is extremely rare. The central focus of this paper is to present this rare complication to stress the importance of rigorous follow-up and anticoagulation therapy in patients undergoing the maze procedure. To our knowledge, we are the first to report such a rare case of diffuse large atrial thrombi triggered by heparin-induced thrombocytopenia (HIT) type II after a COX-maze procedure.

High Dominant Frequencies and Fractionated Potentials Do Not Indicate Focal or Rotational Activation During AF

BACKGROUND

Dominant frequencies (DFs) or complex fractionated atrial electrograms (CFAEs), indicative of focal sources or rotational activation, are used to identify target sites for atrial fibrillation (AF) ablation in clinical studies, although the relationship among DF, CFAE, and activation patterns remains unclear.

OBJECTIVES

This study sought to investigate the relationship between patterns of activation underlying DF and CFAE sites during AF.

METHODS

Epicardial high-resolution mapping of the right and left atrium including Bachmann's bundle was performed in 71 participants. We identified the highest dominant frequency (DF_max) and highest degree of CFAE (CFAE_max) with the use of existing clinical criteria and classified patterns of activation as focal or rotational activation and smooth propagation, conduction block (CB), collision and remnant activity, and fibrillation potentials as single, double, or fractionated potentials containing, respectively, 1, 2, or 3 or more negative deflections. Relationships among activation patterns, DF_max, and potential types were investigated.

RESULTS

DF_max were primarily located at the left atrioventricular groove and did not harbor focal activation (proportion focal waves: 0% [IQR: 0%-2%]). Compared with non-DF_max sites, DF_max were characterized by more frequent smooth propagation (22% [IQR: 7%-48%] vs 17% [IQR: 11%-24%]; P = 0.001), less frequent conduction block (69% [IQR: 51%-81%] vs 74% [IQR: 69%-78%]; P = 0.006), a higher proportion of single potentials (72% [IQR: 55%-84%] vs 6%1 [IQR: 55%-65%]; P = 0.003), and a lower proportion of fractionated potentials (4% [IQR: 1%-11%] vs 12% [IQR: 9%-15%]; P = 0.004). CFAE_max were mainly found at the pulmonary veins area, and only 1% [IQR: 0%-2%] of all CFAE_max contained focal activation. Compared with non-CFAE_max sites, CFAE_max sites were characterized by less frequent smooth propagation (1% [IQR: 0%-1%] vs 17% [IQR: 12%-24%]; P < 0.001) and more frequent remnant activity (20% [IQR: 12%-29%] vs 8% [IQR: 5%-10%]; P < 0.001), and harbored predominantly fractionated potentials (52% [IQR: 43%-66%] vs 12% [IQR: 9%-14%]; P < 0.001).

CONCLUSIONS

Focal or rotational patterns of activation were not consistently detected at DF_max domains and CFAE_max sites. These findings do not support the concept of targeting DF_max or CFAE_max according to existing criteria for AF ablation.

Multiplatform modeling of atrial fibrillation identifies phospholamban as a central regulator of cardiac rhythm

Atrial fibrillation (AF) is a common and genetically inheritable form of cardiac arrhythmia; however, it is currently not known how these genetic predispositions contribute to the initiation and/or maintenance of AF-associated phenotypes. One major barrier to progress is the lack of experimental systems to investigate the effects of gene function on rhythm parameters in models with human atrial and whole-organ relevance. Here, we assembled a multi-model platform enabling high-throughput characterization of the effects of gene function on action potential duration and rhythm parameters using human induced pluripotent stem cell-derived atrial-like cardiomyocytes and a Drosophila heart model, and validation of the findings using computational models of human adult atrial myocytes and tissue. As proof of concept, we screened 20 AF-associated genes and identified phospholamban loss of function as a top conserved hit that shortens action potential duration and increases the incidence of arrhythmia phenotypes upon stress. Mechanistically, our study reveals that phospholamban regulates rhythm homeostasis by functionally interacting with L-type Ca2+ channels and NCX. In summary, our study illustrates how a multi-model system approach paves the way for the discovery and molecular delineation of gene regulatory networks controlling atrial rhythm with application to AF.

Electrogram Morphology Recurrence for Mapping Persistent Atrial Fibrillation: Initial vs Redo Catheter Ablation

BACKGROUND

Electrogram (EGM) morphology recurrence (EMR) mapping of persistent atrial fibrillation (AF) quantifies consistency of activation and is expected to be high and rapid near AF drivers.

OBJECTIVES

The purpose of this study was to compare EMR in left atria (LA) and right atria (RA) in patients undergoing first vs redo ablation for persistent AF.

METHODS

Multisite LA/RA mapping (LA: 281 ± 176 sites/patient; RA: 239 ± 166 sites/patient) before persistent AF ablation was performed in 42 patients (30 males, age 63 ± 9 years) undergoing first (Group 1, n = 32) or redo ablation (Group 2, n = 10). After cross-correlation of each automatically detected EGM with every other EGM per recording, the most recurrent electrogram morphology was identified and its frequency (Rec%) and recurrence cycle length (CLR) were computed.

RESULTS

In Groups 1 and 2, minimum CLR was 172.8 ± 26.0 milliseconds (LA: 178.2 ± 37.6 milliseconds, RA: 204.4 ± 34.0 milliseconds, P = 0.0005) and 186.5 ± 28.3 milliseconds (LA: 196.1 ± 38.1 milliseconds vs RA: 199.0 ± 30.2 milliseconds, P = 0.75), with Rec% 94.7% ± 10% and 93.8% ± 9.2%. Group 2 minimum CLR was not different from Group 1 (P = 0.20). Shortest CLR was in the LA in 84% of Group 1 and 50% of Group 2 patients (P = 0.04). Only 1 of 10 patients in Group 2 had the shortest CLR in the pulmonary veins (PVs) compared with 19 of 32 in Group 1 (P = 0.01). Most sites (77.6%) had Rec% <50%.

CONCLUSIONS

EMR identified the shortest CLR sites in the PVs in 59% of patients undergoing initial persistent AF ablation, consistent with reported success rates of ∼50% for PV isolation. The majority of sites have low recurrence and may reflect bystander sites not critical for maintaining AF. EMR provides a robust new method for quantifying consistency and rapidity of activation direction at multiple atrial sites.

Machine Learning to Identify Patients at Risk of Developing New-Onset Atrial Fibrillation after Coronary Artery Bypass

BACKGROUND

This study aims to get an effective machine learning (ML) prediction model of new-onset postoperative atrial fibrillation (POAF) following coronary artery bypass grafting (CABG) and to highlight the most relevant clinical factors.

METHODS

Four ML algorithms were employed to analyze 394 patients undergoing CABG, and their performances were compared: Multivariate Adaptive Regression Spline, Neural Network, Random Forest, and Support Vector Machine. Each algorithm was applied to the training data set to choose the most important features and to build a predictive model. The better performance for each model was obtained by a hyperparameters search, and the Receiver Operating Characteristic Area Under the Curve metric was selected to choose the best model. The best instances of each model were fed with the test data set, and some metrics were generated to assess the performance of the models on the unseen data set. A traditional logistic regression was also performed to be compared with the machine learning models.

RESULTS

Random Forest model showed the best performance, and the top five predictive features included age, preoperative creatinine values, time of aortic cross-clamping, body surface area, and Logistic Euro-Score.

CONCLUSIONS

The use of ML for clinical predictions requires an accurate evaluation of the models and their hyperparameters. Random Forest outperformed all other models in the clinical prediction of POAF following CABG.

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.

Regions of Highly Recurrent Electrogram Morphology With Low Cycle Length Reflect Substrate for Atrial Fibrillation

Traditional anatomically guided ablation and attempts to perform electrogram-guided atrial fibrillation (AF) ablation (CFAE, DF, and FIRM) have not been shown to be sufficient treatment for persistent AF. Using biatrial high-density electrophysiologic mapping in a canine rapid atrial pacing model of AF, we systematically investigated the relationship of electrogram morphology recurrence (EMR) (Rec% and CL_R) with established AF electrogram parameters and tissue characteristics. Rec% correlates with stability of rotational activity and with the spatial distribution of parasympathetic nerve fibers. These results have indicated that EMR may therefore be a viable therapeutic target in persistent AF.

Outcome of New-Onset Postoperative Atrial Fibrillation After Cardiac Surgery in Adults With Congenital Heart Disease

BACKGROUND

Postoperative atrial fibrillation (POAF) is one of the most common complications after cardiac surgery. POAF is associated with a longer hospital stay, higher healthcare resource utilization, and higher risk of morbidity and mortality. As a result, the American and European guidelines recommend the use of beta-blockers and amiodarone for the prevention of POAF, and in turn, avoid the complications associated with POAF.

OBJECTIVES

The purpose of this study was to determine the incidence, risk factors, and prognostic implications of new-onset POAF after cardiac surgery in adults with congenital heart disease (CHD).

METHODS

A retrospective study was conducted among adults with CHD who underwent cardiac surgery (2003-2019). POAF and late-onset atrial fibrillation (AF) were defined as AF occurring within and after 30 days postoperatively, respectively.

RESULTS

Of 1,598 patients (mean age 39 ± 13 years, 51% men), 335 (21%) developed POAF. Risk factors associated with POAF were older age, hypertension, left atrial (LA) reservoir strain and right atrial (RA) dysfunction, and nonsystemic atrioventricular valve regurgitation. Of 1,291 patients (81%) with follow-up ≥12 months, the annual incidence of late-onset AF was 1.5% and was higher in patients with POAF compared with those without POAF (5.9% vs 0.4%; P < 0.001). Risk factors associated with late-onset AF were POAF, older age, severe CHD, and LA and RA dysfunction. Of the 1,291 patients, 63 (5%) died during follow-up, and the risk factors associated with all-cause mortality were older age, severe CHD, hypertension, left ventricular systolic dysfunction, and LA and RA dysfunction. POAF was not associated with all-cause mortality.

CONCLUSIONS

POAF was common in adults with CHD and was associated with late-onset AF but not all-cause mortality. Atrial dysfunction was independently associated with POAF, late-onset AF, and all-cause mortality. These risk factors can be used to identify patients at risk for POAF and provide a foundation for prospective studies assessing the efficacy of prophylactic therapies in this population.

The physics of heart rhythm disorders

The global burden caused by cardiovascular disease is substantial, with heart disease representing the most common cause of death around the world. There remains a need to develop better mechanistic models of cardiac function in order to combat this health concern. Heart rhythm disorders, or arrhythmias, are one particular type of disease which has been amenable to quantitative investigation. Here we review the application of quantitative methodologies to explore dynamical questions pertaining to arrhythmias. We begin by describing single-cell models of cardiac myocytes, from which two and three dimensional models can be constructed. Special focus is placed on results relating to pattern formation across these spatially-distributed systems, especially the formation of spiral waves of activation. Next, we discuss mechanisms which can lead to the initiation of arrhythmias, focusing on the dynamical state of spatially discordant alternans, and outline proposed mechanisms perpetuating arrhythmias such as fibrillation. We then review experimental and clinical results related to the spatio-temporal mapping of heart rhythm disorders. Finally, we describe treatment options for heart rhythm disorders and demonstrate how statistical physics tools can provide insights into the dynamics of heart rhythm disorders.

Relationships Between Atrial Flutter and Fibrillation: The Border Zone

Atrial flutter and fibrillation have been inextricably linked in the study of electrophysiology. With astute clinical observation, advanced diagnostic equipment in the Electrophysiology Laboratory, and thoughtful study of animal models, the mechanism and inter-relationship between the 2 conditions have been elucidated and will be reviewed in this article. Though diagnosis and management of these conditions have many similarities, the mechanisms by which they develop and persist are quite unique.

Clinical Relevance of Sinus Rhythm Mapping to Quantify Electropathology Related to Atrial Fibrillation

Progression of AF is accompanied by structural and electrical remodelling, resulting in complex electrical conduction disorders. This is defined as electropathology and it increases with the progression of AF. The severity of electropathology, thus, defines the stage of AF and is a major determinant of effectiveness of AF therapy. As specific features of AF-related electropathology are still unknown, it is essential to first quantify the electrophysiological properties of atrial tissue and then to examine the inter- and intra-individual variation during normal sinus rhythm. Comparison of these parameters between patients with and without a history of AF unravels quantified electrophysiological features that are specific to AF patients. This can help to identify patients at risk for early onset or progression of AF. This review summarises current knowledge on quantified features of atrial electrophysiological properties during sinus rhythm and discusses its relevance in identifying AF-related electropathology.

Reproducibility and stability of atrial fibrillation drivers identified by an automated algorithm: CARTOFINDER

BACKGROUND

The characteristics of atrial fibrillation (AF) drivers identified by CARTOFINDER have not been thoroughly evaluated. Therefore, the current study was sought to validate the reliability of AF drivers.

METHODS

The reliability of focal and rotational activation identified by CARTOFINDER during AF was assessed by the sequential recordings in each site before and after pulmonary vein isolation (PVI) in 27 persistent AF patients. The primary outcome measures were the reproducibility rate during the sequential recordings and the stability rate between pre- and post-PVI.

RESULTS

Among 32,135 points in 509 sites, focal activation was identified in 1775 points (5.5%) with a repetition of 11 (6-26) times during the recording. Rotational activation was identified in 132 points (0.4%) with a repetition number of 21 (14-21) times. AF drivers had significantly higher voltage and shorter AF cycle length than non-AF driver sites. The reproducibility rate of focal activation during the sequential recordings was 57.8% and increased with the repetition number. The reproducibility rate of rotational activation was 37.4%. The prevalence and the reproducibility rate of focal activation in post-PVI were significantly lower than pre-PVI (5.3% versus 6.0%, P = 0.02; 53.4% versus 63.6%, P < 0.001). The stability rate of focal activation between pre- and post-PVI was only 28.3% but increased with the repetition number. There was no stable rotational activation between pre- and post-PVI.

CONCLUSIONS

The reproducibility of AF drivers, especially focal activation, identified by CARTOFINDER is relatively favorable, but the stability between pre- and post-PVI was poor. These results depended on the repetition number during the recording.

Role of interatrial conduction in atrial fibrillation. Mechanistic insights from renewal theory-based fibrillatory dynamic analysis

Background

Interatrial conduction has been postulated to play an important role in atrial fibrillation (AF). The pathways involved in interatrial conduction during AF remain incompletely defined.

Objective

We recently showed physiological assessment of fibrillatory dynamics could be performed using renewal theory, which determines rates of phase singularity formation (λ_f) and destruction (λ_d). Using the renewal approach, we aimed to understand the role of the interatrial septum and other electrically coupled regions during AF.

Method

RENEWAL-AF is a prospective multicenter observational study recruiting AF ablation patients (ACTRN 12619001172190). We studied unipolar electrograms obtained from 16 biatrial locations prior to ablation using a 16-electrode Advisor HD Grid catheter. Renewal rate constants λ_f and λ_d were calculated, and the relationships between these rate constants in regions of interatrial connectivity were examined.

Results

Forty-one AF patients (28.5% female) were recruited. A positive linear correlation was observed between λ_f and λ_d (1) across the interatrial septum (λ_f r² = 0.5, P < .001, λ_d r² = 0.45, P < .001), (2) in regions connected by the Bachmann bundle (right atrial appendage–left atrial appendage λ_f r² = 0.29, P = .001; λ_d r² = 0.2, P = .008), and (3) across the inferior interatrial routes (cavotricuspid isthmus–left atrial septum λ_f r² = 0.67, P < .001; λ_d r² = 0.55, P < .001). Persistent AF status and left atrial volume were found to be important effect modifiers of the degree of interatrial renewal rate statistical correlation.

Conclusion

Our findings support the role of interseptal statistically determined electrical disrelation in sustaining AF. Additionally, renewal theory identified preferential conduction through specific interatrial pathways during fibrillation. These findings may be of importance in identifying clinically significant targets for ablation in AF patients.

Instability of rotational activation as atrial fibrillation drivers: assessment by ExTRa Mapping system

BACKGROUND

ExTRa Mapping™ has developed to visualize rotational activation as atrial fibrillation(AF) drivers. The current study was sought to evaluate the instability of AF drivers by ExTRa Mapping™.

METHODS

Variation of non-passively activated ratio(%NP) among 3-time repetitive recordings before and after pulmonary vein isolation(PVI) in left atrium was assessed in 26 persistent AF patients. The recoding time was set at 5 seconds or 8 seconds for the respective patients. The outcome measures included %NP at each recording, mean value of the 3-time recordings, and the instability index, which was defined as maximum difference per mean %NP×100 (%).

RESULTS

Total 683 sites 2049 recordings were assessed. Mean %NP was 33.3(23.3-42.7)%, and higher in sites with severe(≥50%) and patchy low voltage area than those without, but not in those with severe complex fractionated atrial electrogram area. There was significant correlation between actual and mean %NP (R = 0.86, P<0.001), but maximum difference among the repetitive recordings was 16(10-24) %. The instability index of %NP was 55.9(30.9-83.6)%, and significantly lower at the recordings of 8 seconds compared with 5 seconds (50.6[28.6-78.4]% versus 60.4[35.0-90.0]%, P = 0.004). Furthermore, it was higher at sites with lower reliability of the recordings. After PVI, mean %NP significantly decreased (28.7[18.3-36.7]% versus 37.7[28.7-45.7]%, P<0.001), but the instability index significantly increased compared with those before PVI (60.0[35.0-92.7]% versus 48.9[29.1-75.0]%, P = 0.001).

CONCLUSION

Rotational activation as AF drivers assessed by ExTRa Mapping™ is unstable, and repetitive and longer recording is required for the reliable assessment even after PVI. This article is protected by copyright. All rights reserved.

An Exploratory Study on Vectorcardiographic Identification of the Site of Origin of Focally Induced Premature Depolarizations in Horses, Part I: The Atria

In human cardiology, the anatomical origin of atrial premature depolarizations (APDs) is derived from P wave characteristics on a 12-lead electrocardiogram (ECG) and from vectorcardiography (VCG). The objective of this study is to differentiate between anatomical locations of APDs and to differentiate APDs from sinus rhythm (SR) based upon VCG characteristics in seven horses without cardiovascular disease. A 12-lead ECG was recorded under general anaesthesia while endomyocardial atrial pacing was performed (800−1000 ms cycle length) at the left atrial free wall and septum, right atrial free wall, intervenous tubercle, as well as at the junction with the cranial and caudal vena cava. Catheter positioning was guided by 3D electro-anatomical mapping and transthoracic ultrasound. The VCG was calculated from the 12-lead ECG using custom-made algorithms and was used to determine the mean electrical axis of the first and second half of the P wave. An ANOVA for spherical data was used to test if the maximal directions between each paced location and the maximal directions between every paced location and SR were significantly (p < 0.05) different. Atrial pacing data were not available from the LA septum in three horses, the intervenous tubercle in two horses, and from the LA free wall in one horse. The directions of the maximal electrical axes showed significant differences between all paced locations and between the paced locations and SR. The current results suggest that VCG is useful for identifying the anatomical origin of an atrial ectopy.

Characterization of persistent atrial fibrillation with non-contact charge density mapping and relationship to voltage

BACKGROUND

Despite studies using localized high density contact mapping and lower resolution panoramic approaches, the mechanisms that sustain human persistent atrial fibrillation (AF) remain unresolved. Voltage mapping is commonly employed as a surrogate of atrial substrate to guide ablation procedures.

OBJECTIVE

To study the distribution and temporal stability of activation during persistent AF using a global non-contact charge density approach and compare the findings with bipolar contact mapping.

METHODS

Patients undergoing either redo or de novo ablation for persistent AF underwent charge density and voltage mapping to guide the ablation procedure. Offline analysis was performed to measure the temporal stability of three specific charge density activation (CDA) patterns, and the degree of spatial overlap between CDA patterns and low voltage regions.

RESULTS

CDA was observed in patient-specific locations that partially overlapped, comprising local rotational activity (18% of LA), local irregular activity (41% of LA), and focal activity (39% of LA). Local irregular activity had the highest temporal stability. LA voltage was similar in regions with and without CDA.

CONCLUSION

In persistent AF, CDA patterns appear unrelated to low voltage areas but occur in varying locations with high temporal stability.

Non-contact whole-chamber charge density mapping of the left ventricle: preclinical evaluation in a sheep model

BACKGROUND

Conventional contact-based electroanatomic mapping is poorly suited for rapid or dynamic ventricular arrhythmias. Whole-chamber charge density (CD) mapping could efficiently characterize complex ventricular tachyarrhythmias and yield insights into their underlying mechanisms.

OBJECTIVE

This study sought to evaluate the feasibility and accuracy of non-contact whole-chamber left ventricular (LV) CD mapping, and to characterize CD activation patterns during sinus rhythm, ventricular pacing, and ventricular fibrillation (VF).

METHODS

Ischemic scar as defined by CD amplitude thresholds was compared to late gadolinium enhancement criteria on magnetic resonance imaging using an iterative closest point algorithm. Electrograms recorded at sites of tissue contact were compared to the nearest non-contact CD-derived electrograms to calculate signal morphology cross-correlations and time differences. Regions of consistently slow conduction were examined relative to areas of scar and to localized irregular activation (LIA) during VF.

RESULTS

Areas under receiver operating characteristic curves (AUCs) of CD-defined dense and total LV scar were 0.92 ± 0.03 and 0.87 ± 0.06, with accuracies of 0.86±0.03 and 0.80±0.05, respectively. Morphology cross-correlation between 8,677 contact and corresponding non-contact electrograms was 0.93±0.10, with a mean time difference of 2.5±5.6 msec. Areas of consistently slow conduction tended to occur at scar borders and exhibited spatial agreement with LIA during VF (AUC 0.90±0.02).

CONCLUSION

Non-contact LV CD mapping can accurately delineate ischemic scar. CD-derived ventricular electrograms correlate strongly with conventional contact-based electrograms. Regions with consistently slow conduction are often at scar borders and tend to harbor LIA during VF.

Computational Analysis of Mapping Catheter Geometry and Contact Quality Effects on Rotor Detection in Atrial Fibrillation

Atrial fibrillation (AF) is the most common cardiac arrhythmia and catheter mapping has been proved to be an effective approach for detecting AF drivers to be targeted by ablation. Among drivers, the so-called rotors have gained the most attention: their identification and spatial location could help to understand which patient-specific mechanisms are acting, and thus to guide the ablation execution. Since rotor detection by multi-electrode catheters may be influenced by several structural parameters including inter-electrode spacing, catheter coverage, and endocardium-catheter distance, in this study we proposed a tool for testing the ability of different catheter shapes to detect rotors in different conditions. An approach based on the solution of the monodomain equations coupled with a modified Courtemanche ionic atrial model, that considers an electrical remodeling, was applied to simulate spiral wave dynamics on a 2D model for 7.75 s. The developed framework allowed the acquisition of unipolar signals at 2 KHz. Two high-density multipolar catheters were simulated (Advisor™ HD Grid and PentaRay^®) and placed in a 2D region in which the simulated spiral wave persists longer. The configuration of the catheters was then modified by changing the number of electrodes, inter-electrodes distance, position, and atrial-wall distance for assessing how they would affect the rotor detection. In contact with the wall and at 1 mm distance from it, all the configurations detected the rotor correctly, irrespective of geometry, coverage, and inter-electrode distance. In the HDGrid-like geometry, the increase of the inter-electrode distance from 3 to 6 mm caused rotor detection failure at 2 mm distance from the LA wall. In the PentaRay-like configuration, regardless of inter-electrode distance, rotor detection failed at 3 mm endocardium-catheter distance. The asymmetry of this catheter resulted in rotation-dependent rotor detection. To conclude, the computational framework we developed is based on realistic catheter shapes designed with parameter configurations which resemble clinical settings. Results showed it is well suited to investigate how mapping catheter geometry and location affect AF driver detection, therefore it is a reliable tool to design and test new mapping catheters.

Ultra-high-density mapping and ablation strategy for multiple scar-related right atrial tachycardias in patients without previous cardiac surgery

BACKGROUND

Catheter ablation of right atrial (RA) tachycardia in patients who have extensive spontaneous RA scarring is challenging due to the complex substrate and the potential for multiple inducible atrial tachycardias (ATs).

METHODS

Eighteen patients with scar-related RA AT and no prior cardiac surgery were enrolled. A total of 52 different ATs (mean 3.2 ± 1.5 ATs per patient) were observed. We endeavored to complete activation maps for 45 ATs.

RESULTS

By analyzing activation maps, we classified ATs into six categories. The discrepant location and extension of ESAs were associated with different AT mechanisms.

CONCLUSIONS

Multiple scar-related RA ATs were observed in patients without previous cardiac surgery. The detailed activation patterns of these ATs could be clearly demonstrated by using an ultra-high-density mapping system.

Critical appraisal of technologies to assess electrical activity during atrial fibrillation: a position paper from the European Heart Rhythm Association and European Society of Cardiology Working Group on eCardiology in collaboration with the Heart Rhythm Society, Asia Pacific Heart Rhythm Society, Latin American Heart Rhythm Society and Computing in Cardiology

We aim to provide a critical appraisal of basic concepts underlying signal recording and processing technologies applied for (i) atrial fibrillation (AF) mapping to unravel AF mechanisms and/or identifying target sites for AF therapy and (ii) AF detection, to optimize usage of technologies, stimulate research aimed at closing knowledge gaps, and developing ideal AF recording and processing technologies. Recording and processing techniques for assessment of electrical activity during AF essential for diagnosis and guiding ablative therapy including body surface electrocardiograms (ECG) and endo- or epicardial electrograms (EGM) are evaluated. Discussion of (i) differences in uni-, bi-, and multi-polar (omnipolar/Laplacian) recording modes, (ii) impact of recording technologies on EGM morphology, (iii) global or local mapping using various types of EGM involving signal processing techniques including isochronal-, voltage- fractionation-, dipole density-, and rotor mapping, enabling derivation of parameters like atrial rate, entropy, conduction velocity/direction, (iv) value of epicardial and optical mapping, (v) AF detection by cardiac implantable electronic devices containing various detection algorithms applicable to stored EGMs, (vi) contribution of machine learning (ML) to further improvement of signals processing technologies. Recording and processing of EGM (or ECG) are the cornerstones of (body surface) mapping of AF. Currently available AF recording and processing technologies are mainly restricted to specific applications or have technological limitations. Improvements in AF mapping by obtaining highest fidelity source signals (e.g. catheter-electrode combinations) for signal processing (e.g. filtering, digitization, and noise elimination) is of utmost importance. Novel acquisition instruments (multi-polar catheters combined with improved physical modelling and ML techniques) will enable enhanced and automated interpretation of EGM recordings in the near future.

Very long term outcome after linear versus electrogram guided ablation for persistent atrial fibrillation

The optimal ablation strategy for persistent atrial fibrillation (PsAF) remains to be defined. We sought to compare very long-term outcomes between linear ablation and electrogram (EGM)-guided ablation for PsAF. In a retrospective analysis, long-term arrhythmia-free survival compared between two propensity-score matched cohorts, one with pulmonary vein isolation (PVI) and linear ablation including roof/mitral isthmus line (LINE-group, n = 52) and one with PVI and EGM-guided ablation (EGM-group; n = 52). Overall, 99% of patients underwent successful PVI. Complete block following linear ablation was achieved for 94% of roof lines and 81% of mitral lines (both lines blocked in 75%). AF termination by EGM-guided ablation was accomplished in 40% of patients. Non-PV foci were targeted in 7 (13%) in the LINE-group and 5 (10%) patients in the EGM-group (p = 0.76). During 100 ± 28 months of follow-up, linear ablation was associated with superior arrhythmia-free survival after the initial and last procedure (1.8 ± 0.9 procedures) compared with EGM-group (Logrank test: p = 0.0001 and p = 0.045, respectively). In multivariable analysis, longer AF duration and EGM-guided ablation remained as independent predictors of atrial arrhythmia recurrence. Linear ablation might be a more effective complementary technique to PVI than EGM-guided ablation for PsAF ablation.

Atrial Flutter Mechanism Detection Using Directed Network Mapping

Atrial flutter (AFL) is a common atrial arrhythmia typically characterized by electrical activity propagating around specific anatomical regions. It is usually treated with catheter ablation. However, the identification of rotational activities is not straightforward, and requires an intense effort during the first phase of the electrophysiological (EP) study, i.e., the mapping phase, in which an anatomical 3D model is built and electrograms (EGMs) are recorded. In this study, we modeled the electrical propagation pattern of AFL (measured during mapping) using network theory (NT), a well-known field of research from the computer science domain. The main advantage of NT is the large number of available algorithms that can efficiently analyze the network. Using directed network mapping, we employed a cycle-finding algorithm to detect all cycles in the network, resembling the main propagation pattern of AFL. The method was tested on two subjects in sinus rhythm, six in an experimental model of in-silico simulations, and 10 subjects diagnosed with AFL who underwent a catheter ablation. The algorithm correctly detected the electrical propagation of both sinus rhythm cases and in-silico simulations. Regarding the AFL cases, arrhythmia mechanisms were either totally or partially identified in most of the cases (8 out of 10), i.e., cycles around the mitral valve, tricuspid valve and figure-of-eight reentries. The other two cases presented a poor mapping quality or a major complexity related to previous ablations, large areas of fibrotic tissue, etc. Directed network mapping represents an innovative tool that showed promising results in identifying AFL mechanisms in an automatic fashion. Further investigations are needed to assess the reliability of the method in different clinical scenarios.

Fibrotic Remodeling during Persistent Atrial Fibrillation: In Silico Investigation of the Role of Calcium for Human Atrial Myofibroblast Electrophysiology

During atrial fibrillation, cardiac tissue undergoes different remodeling processes at different scales from the molecular level to the tissue level. One central player that contributes to both electrical and structural remodeling is the myofibroblast. Based on recent experimental evidence on myofibroblasts' ability to contract, we extended a biophysical myofibroblast model with Ca2+ handling components and studied the effect on cellular and tissue electrophysiology. Using genetic algorithms, we fitted the myofibroblast model parameters to the existing in vitro data. In silico experiments showed that Ca2+ currents can explain the experimentally observed variability regarding the myofibroblast resting membrane potential. The presence of an L-type Ca2+ current can trigger automaticity in the myofibroblast with a cycle length of 799.9 ms. Myocyte action potentials were prolonged when coupled to myofibroblasts with Ca2+ handling machinery. Different spatial myofibroblast distribution patterns increased the vulnerable window to induce arrhythmia from 12 ms in non-fibrotic tissue to 22 ± 2.5 ms and altered the reentry dynamics. Our findings suggest that Ca2+ handling can considerably affect myofibroblast electrophysiology and alter the electrical propagation in atrial tissue composed of myocytes coupled with myofibroblasts. These findings can inform experimental validation experiments to further elucidate the role of myofibroblast Ca2+ handling in atrial arrhythmogenesis.

A New Vision at the Interface of Atrial Fibrillation and Stroke

Introduction: Current evidence questions the linear sequence traditionally described in atrial fibrillation, blood stasis, intracavitary thrombus, and embolization to the central nervous system. Currently, new perspectives have been described based on questions from the linearly traditional chronology of events; it is within this scope that the article has its objective.

Evidences: The association of the two entities is biologically plausible and supported by different cohorts with a higher risk of developing atrial fibrillation, especially in the cardioembolic form. Concepts (temporal dissociation, biological gradient, etc.) determine the existence of other factors associated with cardioembolism, not exclusively by atrial fibrillation. The entire cascade of events associated with myopathy and atrial remodeling can generate damage to the myocyte and amplify the prothrombotic status. It is important to clarify that atrial myopathy can present itself as atrial fibrillation initially or not, but should always be considered thrombogenic in all the contexts of their clinical presentation. Considering atrial heart disease as a cause of embolic stroke, it could explain that one-third of strokes are considered cryptogenic.

Conclusions: The traditional model exclusively associating the presence of atrial fibrillation in the genesis of thromboembolism is incomplete. The concept of atrial cardiopathy where cardioembolism occurs in a non-atrial fibrillation dependent manner fits better with current data. The future challenge is to effectively detect the various manifestations of atrial heart disease, generating direct implications for the identification of patients at risk of stroke and also for better management after a cardioembolic event.

Conduction Heterogeneity: Impact of Underlying Heart Disease and Atrial Fibrillation

OBJECTIVES

The goal of this study is to investigate the impact of various underlying heart diseases (UHDs) and prior atrial fibrillation (AF) episodes on conduction heterogeneity.

BACKGROUND

It is unknown whether intra-atrial conduction during sinus rhythm differs between various UHD or is influenced by AF episodes.

METHODS

Epicardial sinus rhythm mapping of the right atrium, Bachmann's bundle (BB), left atrium and pulmonary vein area was performed in 447 participants (median age: 67 [interquartile range (IQR): 59 to 73] years) with or without AF undergoing cardiac surgery for ischemic heart disease, (ischemic and) valvular heart disease, or congenital heart disease. Conduction times (CTs) were defined as Δ local activation time between 2 adjacent electrodes and used to assess frequency (CTs ≥ 4 ms) and magnitude of conduction disorders (in increments of 10 ms).

RESULTS

When comparing the 3 types of UHD, there were no differences in frequencies and magnitude of CTs at all locations (p ≥ 0.017 and p ≥ 0.005, respectively). Prior AF episodes were associated with conduction slowing throughout both atria (14.9% [IQR: 11.8 to 17.0] vs. 12.8% [IQR: 10.9 to 14.6]; p < 0.001). At BB, CTs with magnitudes ≥30 ms were more common in patients with AF (n = 56.2% vs. n = 36.0%; p < 0.004).

CONCLUSIONS

UHD has no impact on the frequency and severity of conduction disorders. AF episodes are associated with more conduction disorders throughout both atria and with more severe conduction disorders at BB. The next step will be to determine the relevance of these conduction disorders for AF development and maintenance.

First Evidence of Atrial Conduction Disorders in Pediatric Patients With Congenital Heart Disease

This study sought to investigate whether pediatric patients with congenital heart disease (CHD) already have atrial conduction disorders early in life. The authors conducted first-in-children epicardial mapping in 10 pediatric patients with CHD undergoing primary open heart surgery. Areas of conduction delay (CD) and block (CB) were present in all patients and were particularly observed at Bachmann's bundle (CD: 4.9%; CB: 2.3%), followed by the right atrium (CD: 3.7%; CB: 1.6%) and, to a lesser degree, the left atrium (CD: 1.8%; CB: 1.0%). Conduction abnormalities may by aggravated over time (e.g., aging, residual lesions, or valvular dysfunction), predisposing these patients to atrial arrhythmias early in life.

Automatic reconstruction of the left atrium activation from sparse intracardiac contact recordings by inverse estimate of fibre structure and anisotropic conduction in a patient-specific model

AIMS

Electric conduction in the atria is direction-dependent, being faster in fibre direction, and possibly heterogeneous due to structural remodelling. Intracardiac recordings of atrial activation may convey such information, but only with high-quality data. The aim of this study was to apply a patient-specific approach to enable such assessment even when data are scarce, noisy, and incomplete.

METHODS AND RESULTS

Contact intracardiac recordings in the left atrium from nine patients who underwent ablation therapy were collected before pulmonary veins isolation and retrospectively included in the study. The Personalized Inverse Eikonal Model from cardiac Electro-Anatomical Maps (PIEMAP), previously developed, has been used to reconstruct the conductivity tensor from sparse recordings of the activation. Regional fibre direction and conduction velocity were estimated from the fitted conductivity tensor and extensively cross-validated by clustered and sparse data removal. Electrical conductivity was successfully reconstructed in all patients. Cross-validation with respect to the measurements was excellent in seven patients (Pearson correlation r > 0.93) and modest in two patients (r = 0.62 and r = 0.74). Bland-Altman analysis showed a neglectable bias with respect to the measurements and the limit-of-agreement at -22.2 and 23.0 ms. Conduction velocity in the fibre direction was 82 ± 25 cm/s, whereas cross-fibre velocity was 46 ± 7 cm/s. Anisotropic ratio was 1.91±0.16. No significant inter-patient variability was observed. Personalized Inverse Eikonal model from cardiac Electro-Anatomical Maps correctly predicted activation times in late regions in all patients (r = 0.88) and was robust to a sparser dataset (r = 0.95).

CONCLUSION

Personalized Inverse Eikonal model from cardiac Electro-Anatomical Maps offers a novel approach to extrapolate the activation in unmapped regions and to assess conduction properties of the atria. It could be seamlessly integrated into existing electro-anatomic mapping systems. Personalized Inverse Eikonal model from cardiac Electro-Anatomical Maps also enables personalization of cardiac electrophysiology models.

A hybrid approach to complex arrhythmias

Despite many years of research, the different aspects of the mechanism of atrial fibrillation (AF) are still incompletely understood. And although the latest guidelines recommend catheter ablation with pulmonary vein isolation as a rhythm control strategy, long-term results in persistent and long-standing persistent AF are suboptimal. Historically, a mechanistic-based patient-tailored approach for the treatment of AF was impossible because of the lack real-time mapping techniques and advanced ablation tools. Therefore, surgeons created lesion sets based upon the anatomy of both atria and the safety of the incisions made by the knife. These complex open-heart procedures had to be performed through a sternotomy on the arrested heart and where therefore not generally adopted. The use of controlled energy sources such as cryothermy and radiofrequency where the first step to make the creation of these lesions less complex. With the development and improvement of electrophysiology techniques and catheters, this invasive and solely anatomical approach could again be partially redesigned. Now less invasive, it prepared the way for collaboration between electrophysiologists working on the endocardial side of the heart and cardiac surgeons providing epicardial access. The introduction of video-assisted technology and hybrid procedures has further increased the possibilities of new successful therapies. Now more than 40 years since the beginning of this exciting maze of AF procedures and still working towards a less aggressive and more comprehensive approach we give an overview of the history of the different minimally invasive surgical solutions and of the hybrid approach.

Investigational Anti-Atrial Fibrillation Pharmacology and Mechanisms by Which Antiarrhythmics Terminate the Arrhythmia: Where Are We in 2020?

Antiarrhythmic drugs remain the mainstay therapy for patients with atrial fibrillation (AF). A major disadvantage of the currently available anti-AF agents is the risk of induction of ventricular proarrhythmias. Aiming to reduce this risk, several atrial-specific or -selective ion channel block approaches have been introduced for AF suppression, but only the atrial-selective inhibition of the sodium channel has been demonstrated to be valid in both experimental and clinical studies. Among the other pharmacological anti-AF approaches, “upstream therapy” has been prominent but largely disappointing, and pulmonary delivery of anti-AF drugs seems to be promising. Major contradictions exist in the literature about the electrophysiological mechanisms of AF (ie, reentry or focal?) and the mechanisms by which anti-AF drugs terminate AF, making the search for novel anti-AF approaches largely empirical. Drug-induced termination of AF may or may not be associated with prolongation of the atrial effective refractory period. Anti-AF drug research has been largely based on the “suppress reentry” ideology; however, results of the AF mapping studies increasingly indicate that nonreentrant mechanism(s) plays an important role in the maintenance of AF. Also, the analysis of anti-AF drug-induced electrophysiological alterations during AF, conducted in the current study, leans toward the focal source as the prime mechanism of AF maintenance. More effort should be placed on the investigation of pharmacological suppression of the focal mechanisms.

Atrial Remodeling in Atrial Fibrillation. Comorbidities and Markers of Disease Progression Predict Catheter Ablation Outcome

Atrial fibrillation is the most common supraventricular arrhythmia affecting an increasing proportion of the population in which mainstream therapy, i.e. catheter ablation, provides freedom from arrhythmia in only a limited number of patients. Understanding the mechanism is key in order to find more effective therapies and to improve patient selection. In this review, the structural and electrophysiological changes of the atrial musculature that constitute atrial remodeling in atrial fibrillaton and how risk factors and markers of disease progression can predict catheter ablation outcome will be discussed in detail.

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.

Identification of local atrial conduction heterogeneities using high-density conduction velocity estimation

Aims

Accurate determination of intra-atrial conduction velocity (CV) is essential to identify arrhythmogenic areas. The most optimal, commonly used, estimation methodology to measure conduction heterogeneity, including finite differences (FiD), polynomial surface fitting (PSF), and a novel technique using discrete velocity vectors (DVV), has not been determined. We aim (i) to identify the most suitable methodology to unravel local areas of conduction heterogeneities using high-density CV estimation techniques, (ii) to quantify intra-atrial differences in CV, and (iii) to localize areas of CV slowing associated with paroxysmal atrial fibrillation (PAF).

Methods and results

Intra-operative epicardial mapping (>5000 sites, interelectrode distances 2 mm) of the right and left atrium and Bachmann’s bundle (BB) was performed during sinus rhythm (SR) in 412 patients with or without PAF. The median atrial CV estimated using the DVV, PSF, and FiD techniques was 90.0 (62.4–116.8), 92.0 (70.6–123.2), and 89.4 (62.5–126.5) cm/s, respectively. The largest difference in CV estimates was found between PSF and DVV which was caused by smaller CV magnitudes detected only by the DVV technique. Using DVV, a lower CV at BB was found in PAF patients compared with those without atrial fibrillation (AF) [79.1 (72.2–91.2) vs. 88.3 (79.3–97.2) cm/s; P < 0.001].

Conclusions

Areas of local conduction heterogeneities were most accurately identified using the DVV technique, whereas PSF and FiD techniques smoothen wavefront propagation thereby masking local areas of conduction slowing. Comparing patients with and without AF, slower wavefront propagation during SR was found at BB in PAF patients, indicating structural remodelling.

Rotor Drivers in Induction and Maintenance of Atrial Fibrillation

Atrial fibrillation is the most common arrhythmia in clinical practice. It is associated with an increased risk of stroke, chronic heart failure, and sudden cardiac death. Our options of restoring and maintaining sinus rhythm have a very limited effect, both in the case of antiarrhythmic and catheter treatment. Catheter ablation has proven to be a more effective approach than antiarrhythmic therapy. The success rate of the procedure reaches 70%. However, radiofrequency ablation is associated with a risk of complications, with 4.5% of patients likely to develop major complications, including tamponade (1.31%), femoral pseudoaneurysm (0.71%), and death (0.15%). Given the generally recognized dominant role of the pulmonary veins in the induction of atrial fibrillation, their electrical isolation has become the recommended tactic of the catheter approach. In the case of patients with paroxysmal form of atrial fibrillation, the success rate of the procedure reaches 87%. Unfortunately, in the case of persistent forms of atrial fibrillation, the effectiveness of the primary procedure decreases to 28% and reaches 51% with repeated interventions. In addition to the anatomically oriented isolation of the pulmonary veins, a number of strategies have been proposed to reach the secondary zones of atrial fibrillation induction. The results of recent studies on the effectiveness of strategies for ablation of rotor regions and their role in the induction and maintenance of AF may lead to the further development of catheter ablation techniques and an individual radiofrequency ablation approach in a particular patient.

Computational modeling identifies embolic stroke of undetermined source patients with potential arrhythmic substrate

Cardiac magnetic resonance imaging (MRI) has revealed fibrosis in embolic stroke of undetermined source (ESUS) patients comparable to levels seen in atrial fibrillation (AFib). We used computational modeling to understand the absence of arrhythmia in ESUS despite the presence of putatively pro-arrhythmic fibrosis. MRI-based atrial models were reconstructed for 45 ESUS and 45 AFib patients. The fibrotic substrate's arrhythmogenic capacity in each patient was assessed computationally. Reentrant drivers were induced in 24/45 (53%) ESUS and 22/45 (49%) AFib models. Inducible models had more fibrosis (16.7 ± 5.45%) than non-inducible models (11.07 ± 3.61%; p<0.0001); however, inducible subsets of ESUS and AFib models had similar fibrosis levels (p=0.90), meaning that the intrinsic pro-arrhythmic substrate properties of fibrosis in ESUS and AFib are indistinguishable. This suggests that some ESUS patients have latent pre-clinical fibrotic substrate that could be a future source of arrhythmogenicity. Thus, our work prompts the hypothesis that ESUS patients with fibrotic atria are spared from AFib due to an absence of arrhythmia triggers.

Characterization of cardiac electrogram signals in atrial arrhythmias

Despite significant advancements in 3D cardiac mapping systems utilized in daily electrophysiology practices, the characterization of atrial substrate remains crucial for the comprehension of supraventricular arrhythmias. During mapping, intracardiac electrograms (EGM) provide specific information that the cardiac electrophysiologist is required to rapidly interpret during the course of a procedure in order to perform an effective ablation. In this review, EGM characteristics collected during sinus rhythm (SR) in patients with paroxysmal atrial fibrillation (pAF) are analyzed, focusing on amplitude, duration and fractionation. Additionally, EGMs recorded during atrial fibrillation (AF), including complex fractionated atrial EGMs (CFAE), may also provide precious information. A complete understanding of their significance remains lacking, and as such, we aimed to further explore the role of CFAE in strategies for ablation of persistent AF. Considering focal atrial tachycardias (AT), current cardiac mapping systems provide excellent tools that can guide the operator to the site of earliest activation. However, only careful analysis of the EGM, distinguishing low amplitude high frequency signals, can reliably identify the absolute best site for RF. Evaluating macro-reentrant atrial tachycardia circuits, specific EGM signatures correspond to particular electrophysiological phenomena: the careful recognition of these EGM patterns may in fact reveal the best site of ablation. In the near future, mathematical models, integrating patient-specific data, such as cardiac geometry and electrical conduction properties, may further characterize the substrate and predict future (potential) reentrant circuits.

Endo-Epicardial Mapping of In Vivo Human Sinoatrial Node Activity

OBJECTIVES

The aim of the current study was to examine electrophysiological characteristics of sinoatrial node (SAN) activity from an endo-epicardial perspective.

BACKGROUND

Electrophysiological properties of the in vivo human SAN and its exit pathways remain poorly understood.

METHODS

Twenty patients (75% male; median age 66 years [59 to 73 years]) with structural heart disease underwent simultaneous endo-epicardial mapping (256 unipolar electrodes, interelectrode distance 2 mm). Conduction times, endo-epicardial delays (EEDs), and R/S ratio were examined in the surrounding 10 mm of SAN activation. Areas of conduction block were defined as conduction delays ≥12 ms and endo-epicardial asynchrony as EED ≥15 m.

RESULTS

Three distinct activation patterns were observed in a total of 28 SAN-focal activation patterns (SAN-FAPs) (4 patients exhibited >1 different exit site), including SAN activation patterns with: 1) solely an endocardial exit site (n = 10 [36%]); 2) solely an epicardial exit site (n = 13 [46%]); and 3) simultaneously activated endo-epicardial exit sites (n = 5 [18%]). Median (interquartile range) EED at the origin of the SAN-FAP was 10 ms (6 to 14 ms) and the prevalence of endo-epicardial asynchrony in the surroundings of the SAN-FAP was 5% (2% to 18%). Electrograms at the origin of the SAN-FAPs exhibited significantly larger R-peaks in the mid right atrium (RA) compared with the superior RA (mid R/S ratio 0.15 [0.067 to 0.34] vs. superior R/S ratio 0.045 [0.026 to 0.062]; p = 0.004). Conduction velocity within a distance of 10 mm from the SAN-FAP was 125 cm/s (80 to 250 cm/s). All 6 SAN-FAPs at the mid RA were observed in patients with a history of atrial fibrillation.

CONCLUSIONS

Variations in activation patterns of the SAN observed in this study highlight the complex 3-dimensional SAN geometry and indicate the presence of interindividual differences in SAN exit pathways. Solely in patients with a history of atrial fibrillation, SAN activity occurred more caudally, which indicates changes in preferential SAN exit pathways.

The Impact of Filter Settings on Morphology of Unipolar Fibrillation Potentials

Using unipolar atrial electrogram morphology as guidance for ablative therapy is regaining interest. Although standardly used in clinical practice during ablative therapy, the impact of filter settings on morphology of unipolar AF potentials is unknown. Thirty different filters were applied to 2,557,045 high-resolution epicardial AF potentials recorded from ten patients. Deflections with slope ≤ - 0.05 mV/ms and amplitude ≥ 0.3 mV were marked. High-pass filtering decreased the number of detected potentials, deflection amplitude, and percentage of fractionated potentials (≥ 2 deflections) as well as fractionation delay time (FDT) and increased percentage of single potentials. Low-pass filtering decreased the number of potentials, percentage of fractionated potentials, whereas deflection amplitude, percentage of single potentials, and FDT increased. Notch filtering (50 Hz) decreased the number of potentials and deflection amplitude, whereas the percentage of complex fractionated potentials (≥ 3 deflections) increased. Filtering significantly impacted morphology of unipolar fibrillation potentials, becoming a potential source of error in identification of ablative targets. Graphical Abstract Impact of filtering on morphology of unipolar AF potentials. High-pass, low-pass and notch filters were applied to 2,557,045 high-resolution epicardial AF potentials recorded from ten patients. Filtering significantly impacted AF potential morphology, i.e., number of detected potentials, peak-to-peak amplitude, number of deflections, and fractionation delay time. CFP, complex fractionated potential (≥ 3 deflections); DP, double potential (two deflections); FDT, fractionation delay time; SP, single potential (one deflection).

Inverse mechano-electrical reconstruction of cardiac excitation wave patterns from mechanical deformation using deep learning

The inverse mechano-electrical problem in cardiac electrophysiology is the attempt to reconstruct electrical excitation or action potential wave patterns from the heart's mechanical deformation that occurs in response to electrical excitation. Because heart muscle cells contract upon electrical excitation due to the excitation-contraction coupling mechanism, the resulting deformation of the heart should reflect macroscopic action potential wave phenomena. However, whether the relationship between macroscopic electrical and mechanical phenomena is well-defined and unique enough to be utilized for an inverse imaging technique in which mechanical activation mapping is used as a surrogate for electrical mapping has yet to be determined. Here, we provide a numerical proof-of-principle that deep learning can be used to solve the inverse mechano-electrical problem in phenomenological two- and three-dimensional computer simulations of the contracting heart wall, or in elastic excitable media, with muscle fiber anisotropy. We trained a convolutional autoencoder neural network to learn the complex relationship between electrical excitation, active stress, and tissue deformation during both focal or reentrant chaotic wave activity and, consequently, used the network to successfully estimate or reconstruct electrical excitation wave patterns from mechanical deformation in sheets and bulk-shaped tissues, even in the presence of noise and at low spatial resolutions. We demonstrate that even complicated three-dimensional electrical excitation wave phenomena, such as scroll waves and their vortex filaments, can be computed with very high reconstruction accuracies of about 95% from mechanical deformation using autoencoder neural networks, and we provide a comparison with results that were obtained previously with a physics- or knowledge-based approach.

Non-paroxysmal atrial fibrillation mapping: characterization of the electrophysiological substrate using a novel integrated mapping technique

AIMS

Clinical outcomes after radiofrequency catheter ablation (RFCA) remain suboptimal in the treatment of non-paroxysmal atrial fibrillation (AF). Electrophysiological mapping may improve understanding of the underlying mechanisms. To describe the arrhythmia substrate in patients with persistent (Pers) and long-standing persistent (LSPers) AF, undergoing RFCA, using an integrated mechanism mapping technique.

METHODS AND RESULTS

Patients underwent high-density electroanatomical mapping before and after catheter ablation. Integrated maps characterized electrogram (EGM) cycle length (CL) in regions with repetitive-regular (RR) activations, stable wavefront propagation, fragmentation, and peak-to-peak bipolar voltage. Among 83 patients (72% male, 60 ± 11 years old), RR activations were identified in 376 regions (mean CL 180 ± 31 ms). PersAF patients (n = 43) showed more RR sites per patient (5.3 ± 2.4 vs. 3.7 ± 2.1, P = 0.002) with faster CL (166 ± 29 vs. 190 ± 29 ms; P < 0.001) and smaller surface area of fragmented EGMs (15 ± 14% vs. 27 ± 17%, P < 0.001) compared with LSPersAF. The post-ablation map in 50 patients remaining in AF, documented reduction of the RR activities per patient (1.5 ± 0.7 vs. 3.7 ± 1.4, P < 0.001) and area of fragmentation (22 ± 17% vs. 8 ± 9%, P < 0.001). Atrial fibrillation termination during ablation occurred at RR sites (0.48 ± 0.24 mV; 170.5 ± 20.2 ms CL) in 31/33 patients (94%). At the latest follow-up, arrhythmia freedom was higher among patients receiving ablation >75% of RR sites (Q4 82.6%, Q3 63.1%, Q2 35.1%, and Q1 0%; P < 0.001).

CONCLUSION

The integrated mapping technique allowed characterization of multiple arrhythmic substrates in non-paroxysmal AF patients. This technique might serve as tool for a substrate-targeted ablation approach.

Unsupervised Classification of Atrial Electrograms for Electroanatomic Mapping of Human Persistent Atrial Fibrillation

OBJECTIVE

Ablation treatment for persistent atrial fibrillation (persAF) remains challenging due to the absence of a 'ground truth' for atrial substrate characterization and the presence of multiple mechanisms driving the arrhythmia. We implemented an unsupervised classification to identify clusters of atrial electrograms (AEGs) with similar patterns, which were then validated by AEG-derived markers.

METHODS

956 bipolar AEGs were collected from 11 persAF patients. CARTO variables (Biosense Webster; ICL, ACI and SCI) were used to create a 3D space, and subsequently used to perform an unsupervised classification with k-means. The characteristics of the identified groups were investigated using nine AEG-derived markers: sample entropy (SampEn), dominant frequency, organization index (OI), determinism, laminarity, recurrence rate (RR), peak-to-peak (PP) amplitude, cycle length (CL), and wave similarity (WS).

RESULTS

Five AEG classes with distinct characteristics were identified (F = 582, P<0.0001). The presence of fractionation increased from class 1 to 5, as reflected by the nine markers. Class 1 (25%) included organized AEGs with high WS, determinism, laminarity, and RR, and low SampEn. Class 5 (20%) comprised fractionated AEGs with in low WS, OI, determinism, laminarity, and RR, and in high SampEn. Classes 2 (12%), 3 (13%) and 4 (30%) suggested different degrees of AEG organization.

CONCLUSIONS

Our results expand and reinterpret the criteria used for automated AEG classification. The nine markers highlighted electrophysiological differences among the five classes found by the k-means, which could provide a more complete characterization of persAF substrate during ablation target identification in future clinical studies.