Bipolar electrogram shannon entropy at sites of rotational activation: implications for ablation of atrial fibrillation

Left atrial spatial entropy: a novel tool for electrophysiological substrate characterization in atrial fibrillation

Background

Electrical remodeling has been linked to the progression and recurrence of atrial fibrillation (AF) after catheter ablation (CA). Substrate mapping based solely on a voltage amplitude electrogram (EGM) does not provide a comprehensive understanding of the left atrial (LA) disease. The aim of this study is to assess left atrial spatial entropy (LASE) from voltage maps routinely obtained during AF ablation to further characterize the LA substrate.

Materials and Methods

High-density electroanatomic maps (EAMs) of 27 patients with paroxysmal or persistent AF undergoing routine CA were prospectively collected. Computational post-processing was performed on the voltage maps. Using the Shannon entropy model, the probability distribution of the amplitude range values associated with each point of the map was used to measure LASE. Finally, correlations between LASE and clinical and electrophysiological characteristics of AF were explored.

Results

LASE differentiated between patients with paroxysmal and persistent AF (6.45 ± 0.41 vs. 5.87 ± 0.53; p = 0.028) and patients with normal and abnormal LA substrate (6.42 ± 0.42 vs. 5.87 ± 0.56; p = 0.043), independent of the basal rhythm during EM acquisition (6.33 ± 0.41 vs. 6.11 ± 0.63; p = 0.619). Accordance between LASE and EAMs was assessed by ROC analysis (AUC: 0.81; C.I.: 0.62-0.99; Youden index: 6.06; sensitivity: 80%; and specificity: 80%). Patients with the lowest LASE reported AF recurrence at the follow-up.

Conclusion

LASE may play a role in the further characterization of the LA substrate and the type of AF, independent of basal rhythm.

Mechanistic Insights From Trials of Atrial Fibrillation Ablation: Charting a Course for the Future

Success rates for catheter ablation of atrial fibrillation (AF), particularly persistent AF, remain suboptimal. Pulmonary vein isolation has been the cornerstone for catheter ablation of AF for over a decade. While successful for most patients, pulmonary vein isolation alone is still insufficient for a substantial minority. Frustratingly, multiple clinical trials testing a diverse array of additional ablation approaches have led to mixed results, with no current strategy that improves AF outcomes beyond pulmonary vein isolation in all patients. Nevertheless, this large collection of data could be used to extract important insights regarding AF mechanisms and the diversity of the AF syndrome. Mechanistically, the general model for arrhythmogenesis prompts the need for tools to individually assess triggers, drivers, and substrates in individual patients. A key goal is to identify those who will not respond to pulmonary vein isolation, with novel approaches to phenotyping that may include mapping to identify alternative drivers or critical substrates. This, in turn, can allow for the implementation of phenotype-based, targeted approaches that may categorize patients into groups who would or would not be likely to respond to catheter ablation, pharmacological therapy, and risk factor modification programs. One major goal is to predict individuals in whom additional empirical ablation, while feasible, may be futile or lead to atrial scarring or proarrhythmia. This work attempts to integrate key lessons from successful and failed trials of catheter ablation, as well as models of AF, to suggest future paradigms for AF treatment.

Observable Atrial and Ventricular Fibrillation Episode Durations Are Conformant With a Power Law Based on System Size and Spatial Synchronization

BACKGROUND

Atrial fibrillation (AF) and ventricular fibrillation (VF) episodes exhibit varying durations, with some spontaneously ending quickly while others persist. A quantitative framework to explain episode durations remains elusive. We hypothesized that observable self-terminating AF and VF episode lengths, whereby durations are known, would conform with a power law based on the ratio of system size and correlation length ([Formula: see text].

METHODS

Using data from computer simulations (2-dimensional sheet and 3-dimensional left-atrial), human ischemic VF recordings (256-electrode sock, n=12 patients), and human AF recordings (64-electrode basket-catheter, n=9 patients; 16-electrode high definition-grid catheter, n=42 patients), conformance with a power law was assessed using the Akaike information criterion, Bayesian information criterion, coefficient of determination (R2, significance=P<0.05) and maximum likelihood estimation. We analyzed fibrillatory episode durations and [Formula: see text], computed by taking the ratio between system size ([Formula: see text], chamber/simulation size) and correlation length (xi, estimated from pairwise correlation coefficients over electrode/node distance).

RESULTS

In all computer models, the relationship between episode durations and [Formula: see text] was conformant with a power law (Aliev-Panfilov R2: 0.90, P<0.001; Courtemanche R2: 0.91, P<0.001; Luo-Rudy R2: 0.61, P<0.001). Observable clinical AF/VF durations were also conformant with a power law relationship (VF R2: 0.86, P<0.001; AF basket R2: 0.91, P<0.001; AF grid R2: 0.92, P<0.001). [Formula: see text] also differentiated between self-terminating and sustained episodes of AF and VF (P<0.001; all systems), as well as paroxysmal versus persistent AF (P<0.001). In comparison, other electrogram metrics showed no statistically significant differences (dominant frequency, Shannon Entropy, mean voltage, peak-peak voltage; P>0.05).

CONCLUSIONS

Observable fibrillation episode durations are conformant with a power law based on system size and correlation length.

Comparison of electrogram characteristics in persistent atrial fibrillation

INTRODUCTION

Multiple analysis techniques evaluate electrograms during atrial fibrillation (AF), but none have been established to guide catheter ablation. This study compares electrogram properties recorded from multiple right (RA) and left atrial (LA) sites.

METHODS

Multisite LA/RA mapping (281 ± 176/239 ± 166 sites/patient) was performed in 42 patients (30 males, age 63 ± 9 years) undergoing first (n = 32) or redo-AF ablation (n = 10). All electrogram recordings were visually reviewed and artifactual signals were excluded leaving a total of 21 846 for analysis. Electrogram characteristics evaluated were cycle length (CL), amplitude, Shannon's entropy (ShEn), fractionation interval, dominant frequency, organizational index, and cycle length of most recurrent morphology (CLR ) from morphology recurrence plot analysis.

RESULTS

Electrogram characteristics were correlated to each other. All pairwise comparisons were significant (p < .001) except for dominant frequency and CLR (p = .59), and amplitude and dominant frequency (p = .38). Only ShEn and fractionation interval demonstrated a strong negative correlation (r = -.94). All other pairwise comparisons were poor to moderately correlated. The relationships are highly conserved among patients, in the RA versus LA, and in those undergoing initial versus redo ablations. Antiarrhythmic drug therapy did not have a significant effect on electrogram characteristics, except minimum ShEn. Electrogram characteristics associated with ablation outcome were shorter minimum CLR , lower minimum ShEn, and longer mimimum CL. There was minimal overlap between the top 10 sites identified by one electrogram characteristic and the top 10 sites identified by the other 10 characteristics.

CONCLUSION

Multiple techniques can be employed for electrogram analysis in AF. In this analysis of eight different electrogram characteristics, seven were poorly to moderately correlated and do not identify similar locations. Only some characteristics were predictive of ablation outcome. Further studies to consider electrogram properties, perhaps in combination, for categorizing and/or mapping AF are warranted.

Vector Field Heterogeneity for the Assessment of Locally Disorganised Cardiac Electrical Propagation Wavefronts From High-Density Multielectrodes

High-density multielectrode catheters are becoming increasingly popular in cardiac electrophysiology for advanced characterisation of the cardiac tissue, due to their potential to identify impaired sites. These are often characterised by abnormal electrical conduction, which may cause locally disorganised propagation wavefronts. To quantify it, a novel heterogeneity parameter based on vector field analysis is proposed, utilising finite differences to measure direction changes between adjacent cliques. The proposed Vector Field Heterogeneity metric has been evaluated on a set of simulations with controlled levels of organisation in vector maps, and a variety of grid sizes. Furthermore, it has been tested on animal experimental models of isolated Langendorff-perfused rabbit hearts. The proposed parameter exhibited superior capturing ability of heterogeneous propagation wavefronts compared to the classical Spatial Inhomogeneity Index, and simulations proved that the metric effectively captures gradual increments in disorganisation in propagation patterns. Notably, it yielded robust and consistent outcomes for [Formula: see text] grid sizes, underscoring its suitability for the latest generation of orientation-independent cardiac catheters.

A Data-Driven Preprocessing Framework for Atrial Fibrillation Intracardiac Electrocardiogram Analysis

Atrial Fibrillation (AF) is the most common cardiac arrhythmia. Signal-processing approaches are widely used for the analysis of intracardiac electrograms (iEGMs), which are collected during catheter ablation from patients with AF. In order to identify possible targets for ablation therapy, dominant frequency (DF) is widely used and incorporated in electroanatomical mapping systems. Recently, a more robust measure, multiscale frequency (MSF), for iEGM data analysis was adopted and validated. However, before completing any iEGM analysis, a suitable bandpass (BP) filter must be applied to remove noise. Currently, no clear guidelines for BP filter characteristics exist. The lower bound of the BP filter is usually set to 3-5 Hz, while the upper bound (BP¯th) of the BP filter varies from 15 Hz to 50 Hz according to many researchers. This large range of BP¯th subsequently affects the efficiency of further analysis. In this paper, we aimed to develop a data-driven preprocessing framework for iEGM analysis, and validate it based on DF and MSF techniques. To achieve this goal, we optimized the BP¯th using a data-driven approach (DBSCAN clustering) and demonstrated the effects of different BP¯th on subsequent DF and MSF analysis of clinically recorded iEGMs from patients with AF. Our results demonstrated that our preprocessing framework with BP¯th = 15 Hz has the best performance in terms of the highest Dunn index. We further demonstrated that the removal of noisy and contact-loss leads is necessary for performing correct data iEGMs data analysis.

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.

A Review of Healthy and Fibrotic Myocardium Microstructure Modeling and Corresponding Intracardiac Electrograms

Computational simulations of cardiac electrophysiology provide detailed information on the depolarization phenomena at different spatial and temporal scales. With the development of new hardware and software, in silico experiments have gained more importance in cardiac electrophysiology research. For plane waves in healthy tissue, in vivo and in silico electrograms at the surface of the tissue demonstrate symmetric morphology and high peak-to-peak amplitude. Simulations provided insight into the factors that alter the morphology and amplitude of the electrograms. The situation is more complex in remodeled tissue with fibrotic infiltrations. Clinically, different changes including fractionation of the signal, extended duration and reduced amplitude have been described. In silico, numerous approaches have been proposed to represent the pathological changes on different spatial and functional scales. Different modeling approaches can reproduce distinct subsets of the clinically observed electrogram phenomena. This review provides an overview of how different modeling approaches to incorporate fibrotic and structural remodeling affect the electrogram and highlights open challenges to be addressed in future research.

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.

Computational modeling of atrial fibrillation

With the aging society, the prevalence of atrial fibrillation (AF) continues to increase. Nevertheless, there are still limitations in antiarrhythmic drugs (AAD) or catheter interventions for AF. If it is possible to predict the outcome of AF management according to various AADs or ablation lesion sets through computational modeling, it will be of great clinical help. AF computational modeling has been utilized for in-silico arrhythmia research and enabled high-density entire chamber mapping, reproducible condition control, virtual intervention, not possible clinically or experimentally, in-depth mechanistic research. With the recent development of computer science and technology, more sophisticated and faster computational modeling has become available for clinical application. In particular, it can be applied to determine the extra-PV target of persistent AF catheter ablation or to select the AAD with the best effect. AF computational modeling combined with artificial intelligence is expected to contribute to precision medicine for more diverse uses in the future. Therefore, in this review, we will deal with the history, development, and various applications of computation modeling.

Current progress of computational modeling for guiding clinical atrial fibrillation ablation

Atrial fibrillation (AF) is one of the most common arrhythmias, associated with high morbidity, mortality, and healthcare costs, and it places a significant burden on both individuals and society. Anti-arrhythmic drugs are the most commonly used strategy for treating AF. However, drug therapy faces challenges because of its limited efficacy and potential side effects. Catheter ablation is widely used as an alternative treatment for AF. Nevertheless, because the mechanism of AF is not fully understood, the recurrence rate after ablation remains high. In addition, the outcomes of ablation can vary significantly between medical institutions and patients, especially for persistent AF. Therefore, the issue of which ablation strategy is optimal is still far from settled. Computational modeling has the advantages of repeatable operation, low cost, freedom from risk, and complete control, and is a useful tool for not only predicting the results of different ablation strategies on the same model but also finding optimal personalized ablation targets for clinical reference and even guidance. This review summarizes three-dimensional computational modeling simulations of catheter ablation for AF, from the early-stage attempts such as Maze III or circumferential pulmonary vein isolation to the latest advances based on personalized substrate-guided ablation. Finally, we summarize current developments and challenges and provide our perspectives and suggestions for future directions.

Novel mapping techniques for rotor core detection using simulated intracardiac electrograms

BACKGROUND

Catheter ablation is associated with limited success rates in patients with persistent atrial fibrillation (AF). Currently, existing mapping systems fail to identify critical target sites for ablation. Recently, we proposed and validated several techniques (multiscale frequency [MSF], Shannon entropy [SE], kurtosis [Kt], and multiscale entropy [MSE]) to identify pivot point of rotors using ex-vivo optical mapping animal experiments. However, the performance of these techniques is unclear for the clinically recorded intracardiac electrograms (EGMs), due to the different nature of the signals.

OBJECTIVE

This study aims to evaluate the performance of MSF, MSE, SE, and Kt techniques to identify the pivot point of the rotor using unipolar and bipolar EGMs obtained from numerical simulations.

METHODS

Stationary and meandering rotors were simulated in a 2D human atria. The performances of new approaches were quantified by comparing the "true" core of the rotor with the core identified by the techniques. Also, the performances of all techniques were evaluated in the presence of noise, scar, and for the case of the multielectrode multispline and grid catheters.

RESULTS

Our results demonstrate that all the approaches are able to accurately identify the pivot point of both stationary and meandering rotors from both unipolar and bipolar EGMs. The presence of noise and scar tissue did not significantly affect the performance of the techniques. Finally, the core of the rotors was correctly identified for the case of multielectrode multispline and grid catheter simulations.

CONCLUSION

The core of rotors can be successfully identified from EGMs using novel techniques; thus, providing motivation for future clinical implementations.

Optimizing Multiscale Entropy Approach for Rotor Core Identification using Simulated Intracardiac Electrograms

Atrial Fibrillation (AF) is most common sustained cardiac arrhythmia and a precursor to many fatal cardiac conditions. Catheter ablation, which is a minimally invasive treatment, is associated with limited success rates in patients with persistent AF. Rotors are believed to maintain AF and core of rotors are considered to be robust targets for ablation. Recently, multiscale entropy (MSE) was proposed to identify the core of rotors in ex-vivo rabbit hearts. However, MSE technique is sensitive to intrinsic parameters, such as scale factor and template dimension, that may lead to an imprecise estimation of entropy measures. The purpose of this research is optimize MSE approach to improve its accuracy and sensitivity in rotor core identification using simulated EGMs from human atrial model. Specifically, we have identified the optimal time scale factor (τopt) and optimal template dimension (Τopt) that are needed for efficient rotor core identification. The τopt was identified to be 10, using a convergence graph, and the Τopt (~20 ms) remained the same at different sampling rates, indicating that optimized MSE will be efficient in identifying core of the rotor irrespective of the signal acquisition system.

Insights Into the Spatiotemporal Patterns of Complexity of Ventricular Fibrillation by Multilead Analysis of Body Surface Potential Maps

BACKGROUND

Ventricular fibrillation (VF) is the main cause of sudden cardiac death, but its mechanisms are still unclear. We propose a noninvasive approach to describe the progression of VF complexity from body surface potential maps (BSPMs).

METHODS

We mapped 252 VF episodes (16 ± 10 s) with a 252-electrode vest in 110 patients (89 male, 47 ± 18 years): 50 terminated spontaneously, otherwise by electrical cardioversion (DCC). Changes in complexity were assessed between the onset ("VF start") and the end ("VF end") of VF by the nondipolar component index (N D I B S P M ), measuring the fraction of energy nonpreserved by an equivalent 3D dipole from BSPMs. Higher NDI reflected lower VF organization. We also examined other standard body surface markers of VF dynamics, including fibrillatory wave amplitude (A BSPM ), surface cycle length (BsCL BSPM ) and Shannon entropy (S h E n B S P M ). Differences between patients with and without structural heart diseases (SHD, 32 vs. NSHD, 78) were also tested at those stages. Electrocardiographic features were validated with simultaneous endocardium cycle length (CL) in a subset of 30 patients.

RESULTS

All BSPM markers measure an increase in electrical complexity during VF (p < 0.0001), and more significantly in NSHD patients. Complexity is significantly higher at the end of sustained VF episodes requiring DCC. Intraepisode intracardiac CL shortening (VF start 197 ± 24 vs. VF end 169 ± 20 ms; p < 0.0001) correlates with an increase in NDI, and decline in surface CL, f-wave amplitude, and entropy (p < 0.0001). In SHD patients VF is initially more complex than in NSHD patients (N D I B S P M , p = 0.0007; S h E n B S P M , p < 0.0001), with moderately slower (BsCL BSPM , p = 0.06), low-amplitude f-waves (A BSPM , p < 0.0001). In this population, lower NDI (p = 0.004) and slower surface CL (p = 0.008) at early stage of VF predict self-termination. In the NSHD group, a more abrupt increase in VF complexity is quantified by all BSPM parameters during sustained VF (p < 0.0001), whereas arrhythmia evolution is stable during self-terminating episodes, hinting at additional mechanisms driving VF dynamics.

CONCLUSION

Multilead BSPM analysis underlines distinct degrees of VF complexity based on substrate characteristics.

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.

Granger Causality-Based Analysis for Classification of Fibrillation Mechanisms and Localization of Rotational Drivers

BACKGROUND

The mechanisms sustaining myocardial fibrillation remain disputed, partly due to a lack of mapping tools that can accurately identify the mechanism with low spatial resolution clinical recordings. Granger causality (GC) analysis, an econometric tool for quantifying causal relationships between complex time-series, was developed as a novel fibrillation mapping tool and adapted to low spatial resolution sequentially acquired data.

METHODS

Ventricular fibrillation (VF) optical mapping was performed in Langendorff-perfused Sprague-Dawley rat hearts (n=18), where novel algorithms were developed using GC-based analysis to (1) quantify causal dependence of neighboring signals and plot GC vectors, (2) quantify global organization with the causality pairing index, a measure of neighboring causal signal pairs, and (3) localize rotational drivers (RDs) by quantifying the circular interdependence of neighboring signals with the circular interdependence value. GC-based mapping tools were optimized for low spatial resolution from downsampled optical mapping data, validated against high-resolution phase analysis and further tested in previous VF optical mapping recordings of coronary perfused donor heart left ventricular wedge preparations (n=12), and adapted for sequentially acquired intracardiac electrograms during human persistent atrial fibrillation mapping (n=16).

RESULTS

Global VF organization quantified by causality pairing index showed a negative correlation at progressively lower resolutions (50% resolution: P=0.006, R2=0.38, 12.5% resolution, P=0.004, R2=0.41) with a phase analysis derived measure of disorganization, locations occupied by phase singularities. In organized VF with high causality pairing index values, GC vector mapping characterized dominant propagating patterns and localized stable RDs, with the circular interdependence value showing a significant difference in driver versus nondriver regions (0.91±0.05 versus 0.35±0.06, P=0.0002). These findings were further confirmed in human VF. In persistent atrial fibrillation, a positive correlation was found between the causality pairing index and presence of stable RDs (P=0.0005,R2=0.56). Fifty percent of patients had RDs, with a low incidence of 0.9±0.3 RDs per patient.

CONCLUSIONS

GC-based fibrillation analysis can measure global fibrillation organization, characterize dominant propagating patterns, and map RDs using low spatial resolution sequentially acquired data.

Challenges Associated with Interpreting Mechanisms of AF

Determining optimal treatment strategies for complex arrhythmogenesis in AF is confounded by the lack of consensus regarding the mechanisms causing AF. Studies report different mechanisms for AF, ranging from hierarchical drivers to anarchical multiple activation wavelets. Differences in the assessment of AF mechanisms are likely due to AF being recorded across diverse models using different investigational tools, spatial scales and clinical populations. The authors review different AF mechanisms, including anatomical and functional re-entry, hierarchical drivers and anarchical multiple wavelets. They then describe different cardiac mapping techniques and analysis tools, including activation mapping, phase mapping and fibrosis identification. They explain and review different data challenges, including differences between recording devices in spatial and temporal resolutions, spatial coverage and recording surface, and report clinical outcomes using different data modalities. They suggest future research directions for investigating the mechanisms underlying human AF.

Electrogram recording and analyzing techniques to optimize selection of target sites for ablation of cardiac arrhythmias

The extracellular electrogram is caused by transmembrane currents that flow into extracellular space during propagation of the electrical impulse. Electrograms are usually recorded in unipolar or bipolar mode that have different characteristics, but provide complementary information. Both recording modes have specific advantages, but also suffer from disadvantages. Techniques to circumvent some of the weaknesses are reviewed. The origin of remote and fractionated deflections and their relation with electrode characteristics are discussed. Epicardial and endocardial sites of origin and breakthrough sites as well as the effect of fatty tissue on extracellular electrograms are presented. Induction of tachycardia to assess the arrhythmogenic area is not always possible because of hemodynamic instability of the patient. Techniques to assess sites with high reentry vulnerability without induction of arrhythmias are outlined such as activation‐repolarization mapping and decremental stimulation. Pitfalls of substrate mapping and techniques to avoid them as omnipolar mapping and characterization of complex electrograms by entropy are presented. Technical aspects that influence electrogram morphology as electrode size, filtering, contact force, and catheter position are delineated. Data from the various publications suggest that a combination of unipolar and bipolar electrogram analysis techniques is helpful to optimize determination of target sites for ablation.

Evaluation of Multiscale Frequency Approach for Visualizing Rotors in Patients with Atrial Fibrillation

Atrial Fibrillation (AF) is most common cardiac arrhythmia. It is associated with increased risk of stroke, heart failure and sudden cardiac death. Catheter ablation is a treatment used to control AF and has had suboptimal success for patients with persistent AF, which is primarily maintained by rotors outside of the pulmonary veins (PV) region. The pivot point (core) of the rotor is considered an efficient target for ablation. Currently available electro-anatomical mapping systems cannot accurately predict the exact location of the pivot point of rotors outside of the PV region, so there is a need for novel approaches to accurately identify and distinguish sites for ablation. Recently, a multiscale frequency (MSF) technique was developed for accurate identification of the pivot point of rotors and validated using optical mapping experiments in exvivo rabbit hearts, where electrical activity can be directly visualized. However, the nature of optical signals and its spatial resolution are very different from clinical intracardiac electrograms (iEGM). Here we extend the MSF approach to 3D iEGM and compare its prediction with the traditional dominant frequency (DF) approach, using Pearson's correlation and earth mover's distance methods. Our results demonstrate that the similarity between MSF and DF are high in some regions, but very low in other spatial regions of the human atria. This indicates the inconsistency in the traditional DF approach in identifying pivot points and identifying such low similarity regions can be used to find sites for successful ablation.

Unraveling the Underlying Arrhythmia Mechanism in Persistent Atrial Fibrillation: Results From the STARLIGHT Study

BACKGROUND

The mechanisms that initiate and sustain persistent atrial fibrillation are not well characterized. Ablation results remain significantly worse than in paroxysmal atrial fibrillation in which the mechanism is better understood and subsequent targeted therapy has been developed. The aim of this study was to characterize and quantify patterns of activation during atrial fibrillation using contact mapping.

METHODS

Patients with persistent atrial fibrillation (n=14; mean age, 61±8 years; ejection fraction, 59±10%) underwent simultaneous biatrial contact mapping with 64 electrode catheters. The atrial electrograms were transformed into phase, and subsequent spatiotemporal mapping was performed to identify phase singularities (PSs).

RESULTS

PSs were located in both atria, but we observed more PSs in the left atrium compared with the right atrium (779±302, 552±235; P=0.015). Although some PSs of duration sufficient to complete >1 rotation were detected, the maximum PS duration was only 1150 ms, and the vast majority (97%) of PSs persisted for too short a period to complete a full rotation. Although in selected patients there was evidence of PS local clustering, overall, PSs were distributed globally throughout both chambers with no clear anatomic predisposition. In a subset of patients (n=7), analysis was repeated using an alternative established atrial PS mapping technique, which confirmed our initial findings.

CONCLUSIONS

No sustained rotors or localized drivers were detected, and instead, the mechanism of arrhythmia maintenance was consistent with the multiple wavelet hypothesis, with passive activation of short-lived rotational activity.

CLINICAL TRIAL REGISTRATION

URL: https://www.clinicaltrials.gov. Unique identifier: NCT01765075.

The stationary wavelet transform as an efficient reductor of powerline interference for atrial bipolar electrograms in cardiac electrophysiology

OBJECTIVE

The most relevant source of signal contamination in the cardiac electrophysiology (EP) laboratory is the ubiquitous powerline interference (PLI). To reduce this perturbation, algorithms including common fixed-bandwidth and adaptive-notch filters have been proposed. Although such methods have proven to add artificial fractionation to intra-atrial electrograms (EGMs), they are still frequently used. However, such morphological alteration can conceal the accurate interpretation of EGMs, specially to evaluate the mechanisms supporting atrial fibrillation (AF), which is the most common cardiac arrhythmia. Given the clinical relevance of AF, a novel algorithm aimed at reducing PLI on highly contaminated bipolar EGMs and, simultaneously, preserving their morphology is proposed.

APPROACH

The method is based on the wavelet shrinkage and has been validated through customized indices on a set of synthesized EGMs to accurately quantify the achieved level of PLI reduction and signal morphology alteration. Visual validation of the algorithm's performance has also been included for some real EGM excerpts.

MAIN RESULTS

The method has outperformed common filtering-based and wavelet-based strategies in the analyzed scenario. Moreover, it possesses advantages such as insensitivity to amplitude and frequency variations in the PLI, and the capability of joint removal of several interferences.

SIGNIFICANCE

The use of this algorithm in routine cardiac EP studies may enable improved and truthful evaluation of AF mechanisms.

Mapping and Imaging in Non-paroxysmal AF

Despite intense research efforts, maintenance of sinus rhythm in patients with non-paroxysmal AF remains challenging with suboptimal outcomes. A major limitation to the success of current ablation-based treatments is that our understanding of AF pathophysiology is incomplete. Advances in imaging and mapping tools have been reported to improve ablation outcomes. However, the role of these new approaches on the clinical care of patients with AF remains to be validated and better understood before wide adoption can occur. This article reviews the current techniques of imaging and mapping that can be applied in the management of patients with non-paroxysmal AF with a focus on their relevance to catheter ablation. Future applications and opportunities for new knowledge are also discussed.

Left atrial voltage mapping: defining and targeting the atrial fibrillation substrate

Low atrial endocardial bipolar voltage, measured during catheter ablation for atrial fibrillation (AF), is a commonly used surrogate marker for the presence of atrial fibrosis. Low voltage shows many useful associations with clinical outcomes, comorbidities and has links to trigger sites for AF. Several contemporary trials have shown promise in targeting low voltage areas as the substrate for AF ablation; however, the results have been mixed. In order to understand these results, a thorough understanding of voltage mapping techniques, the relationship between low voltage and the pathophysiology of AF, as well as the inherent limitations in voltage measurement are needed. Two key questions must be answered in order to optimally apply voltage mapping as the road map for ablation. First, are the inherent limitations of voltage mapping small enough as to be ignored when targeting specific tissue based on voltage? Second, can conventional criteria, using a binary threshold for voltage amplitude, truly define the extent of the atrial fibrotic substrate? Here, we review the latest clinical evidence with regard to voltage-based ablation procedures before analysing the utility and limitations of voltage mapping. Finally, we discuss omnipole mapping and dynamic voltage attenuation as two possible approaches to resolving these issues.

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

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

Pro-Arrhythmogenic Effects of Heterogeneous Tissue Curvature - A Suggestion for Role of Left Atrial Appendage in Atrial Fibrillation

BACKGROUND

The arrhythmogenic role of complex atrial morphology has not yet been clearly elucidated. We hypothesized that bumpy tissue geometry can induce action potential duration (APD) dispersion and wavebreak in atrial fibrillation (AF).

METHODS AND RESULTS

We simulated a 2D-bumpy atrial model by varying the degree of bumpiness, and 3D-left atrial (LA) models integrated by LA computed tomographic (CT) images taken from 14 patients with persistent AF. We also analyzed wave-dynamic parameters with bipolar electrograms during AF and compared them with LA-CT geometry in 30 patients with persistent AF. In the 2D-bumpy model, APD dispersion increased (P<0.001) and wavebreak occurred spontaneously when the surface bumpiness was greater, showing phase transition-like behavior (P<0.001). The bumpiness gradient 2D-model showed that spiral wave drifted in the direction of higher bumpiness, and phase singularity (PS) points were mostly located in areas with higher bumpiness. In the 3D-LA model, PS density was higher in the LA appendage (LAA) compared with other parts of the LA (P<0.05). In 30 persistent-AF patients, the surface bumpiness of LAA was 5.8-fold that of other LA parts (P<0.001), and exceeded critical bumpiness to induce wavebreak. Wave dynamics complexity parameters were consistently dominant in the LAA (P<0.001).

CONCLUSIONS

Bumpy tissue geometry promoted APD dispersion, wavebreak, and spiral wave drift in in-silico human atrial tissue, and corresponded to clinical electroanatomical maps.

Temporal stability and specificity of high bipolar electrogram entropy regions in sustained atrial fibrillation: Implications for mapping

BACKGROUND

The potential utility of entropy (En) for atrial fibrillation (AF) mapping has been demonstrated in previous studies by multiple groups, where an association between high bipolar electrogram (EGM) entropy and the pivot of rotors has been shown. Though En is potentially attractive new approach to ablation, no studies have examined its temporal stability and specificity, which are critical to the application of entropy to clinical ablation. In the current study, we sought to objectively measure the temporal stability and specificity of bipolar EGM entropy in medium to long term recordings using three studies: i) a human basket catheter AF study, ii) a tachypaced sheep AF study and iii) a computer simulation study.

OBJECTIVE

To characterize the temporal dynamics and specificity of Approximate, Sample and Shannon entropy (ApEn/SampEn/ShEn) in human (H), sheep (S), and computer simulated AF.

METHODS

64-electrode basket bi-atria sustained AF recordings (H:15 min; S:40 min) were separated into 5 s segments. ShEn/ApEn/SampEn were computed, and co-registered with NavX 3D maps. Temporal stability was determined in terms of: (i) global pattern stability of En and (ii) the relative stability the top 10% of En regions. To provide mechanistic insights into underlying mechanisms, stability characteristics were compared to models depicting various propagation patterns. To verify these results, cross-validation was performed across multiple En algorithms, across species, and compared with dominant frequency (DF) temporal characteristics. The specificity of En was also determined by looking at the association of En to rotors and areas of wave cross propagation.

RESULTS

Episodes of AF were analysed (H:26 epochs, 6040 s; S:15 epochs, 14,160 s). The global pattern of En was temporally unstable (CV- H:13.42% ± 4.58%; S:14.13% ± 8.13%; Friedman- H: p > 0.001; S: p > 0.001). However, within this dynamic flux, the top 10% of ApEn/SampEn/ShEn regions were relatively temporally stable (Kappa >0.6) whilst the top 10% of DF regions were unstable (Kappa <0.06). In simulated AF scenarios, the experimental data were optimally reproduced in the context of an AF pattern with stable rotating waves surrounded by wavelet breakup (Kappa: 0.610; p < 0.0001).

CONCLUSION

En shows global temporal instability, however within this dynamic flux, the top 10% regions exhibited relative temporal stability. This suggests that high En regions may be an appealing ablation target. Despite this, high En was associated with not just the pivot of rotors but also with areas of cross propagation, which suggests the need for future work before clinical application is possible.

Analytical approaches for myocardial fibrillation signals

Atrial and ventricular fibrillation are complex arrhythmias, and their underlying mechanisms remain widely debated and incompletely understood. This is partly because the electrical signals recorded during myocardial fibrillation are themselves complex and difficult to interpret with simple analytical tools. There are currently a number of analytical approaches to handle fibrillation data. Some of these techniques focus on mapping putative drivers of myocardial fibrillation, such as dominant frequency, organizational index, Shannon entropy and phase mapping. Other techniques focus on mapping the underlying myocardial substrate sustaining fibrillation, such as voltage mapping and complex fractionated electrogram mapping. In this review, we discuss these techniques, their application and their limitations, with reference to our experimental and clinical data. We also describe novel tools including a new algorithm to map microreentrant circuits sustaining fibrillation.

Characterizing Electrogram Signal Fidelity and the Effects of Signal Contamination on Mapping Human Persistent Atrial Fibrillation

Objective: Determining accurate intracardiac maps of atrial fibrillation (AF) in humans can be difficult, owing primarily to various sources of contamination in electrogram signals. The goal of this study is to develop a measure for signal fidelity and to develop methods to quantify robustness of observed rotational activity in phase maps subject to signal contamination.

Methods: We identified rotational activity in phase maps of human persistent AF using the Hilbert transform of sinusoidally recomposed signals, where localized ablation at rotational sites terminated fibrillation. A novel measure of signal fidelity was developed to quantify signal quality. Contamination is then introduced to the underlying electrograms by removing signals at random, adding noise to computations of cycle length, and adding realistic far-field signals. Mean tip number N and tip density δ, defined as the proportion of time a region contains a tip, at the termination site are computed to compare the effects of contamination.

Results: Domains of low signal fidelity correspond to the location of rotational cores. Removing signals and altering cycle length accounted for minor changes in tip density, while targeted removal of low fidelity electrograms can result in a significant increase in tip density and stability. Far-field contamination was found to obscure rotation at the termination site.

Conclusion: Rotational activity in clinical AF can produce domains of low fidelity electrogram recordings at rotational cores. Observed rotational patterns in phase maps appear most sensitive to far-field activation. These results may inform novel methods to map AF in humans which can be tested directly in patients at electrophysiological study and ablation.

Compass Mapping, Double Potentials, Activation Patterns Can Identify and Track Rotational Activity Sites in the Left Atrium of Humans with Persistent Atrial Fibrillation

BACKGROUND

Rotational circuits that occur between bipolar electrodes exhibit double potentials (DPs). It had been previously surmised that rotors could not be electrically tracked directly.

PURPOSE

Our purpose was twofold; first, to show that the use of compass mapping, one can regionally identify rotational activity; and second, to show that by combining simultaneous compass map recordings, standard narrow-adjacent bipolar, and unipolar recordings, that specific signature recording patterns emerge that allow one to identify the accurate time, location, and path of a rotational mechanism.

METHODS

This was an observational study in 20 patients with persistent atrial fibrillation in which the electrode configuration of a circular mapping catheter was changed to wide cross-circle electrode pairing (compass mapping). DPs were recorded and analyzed from 12 left atrial (LA) sites and identified electrical wavefront patterns and direction. A substudy analyzed transitions patterns with simultaneous narrow-adjacent bipolar and unipolar recordings.

RESULTS

Four wavefront patterns were identified: DPs, peripheral waves (PWs), distal peripheral waves and fibrillatory activity. DP wavefront patterns exhibited significantly shorter cycle lengths than PWs in 8 of 12 LA sites. Patients had 2.9± 2.1 regions that exhibited DPs. DPs of varying duration were found, few (25%) were of stable duration and location. Detailed electrical examination at the transition between a PW to a DP identified a highly consistent pattern of simultaneous reversal of activation sequence, a special form of Doppler effect for spiral waves as a rotor passes between 2 electrodes, and a ½ cycle drop-off of activation signals along the line of electrodes.

CONCLUSION

DP recordings in compass mode can provide a regional assessment for the existence of rotational activity. Simultaneous DP recordings in compass mode, narrow-adjacent bipolar, and unipolar recording provide an accurate assessment of the time, location, and path that a rotational mechanism breaches a perimeter of electrodes. Accurate time, location and path of perimeter breaches can be used to electrically track rotational mechanisms during atrial fibrillation.

Information Theory and Atrial Fibrillation (AF): A Review

Atrial Fibrillation (AF) is the most common cardiac rhythm disorder seen in hospitals and in general practice, accounting for up to a third of arrhythmia related hospitalizations. Unfortunately, AF treatment is in practice complicated by the lack of understanding of the fundamental mechanisms underlying the arrhythmia, which makes detection of effective ablation targets particularly difficult. Various approaches to AF mapping have been explored in the hopes of better pinpointing these effective targets, such as Dominant Frequency (DF) analysis, complex fractionated electrograms (CFAE) and unipolar reconstruction (FIRM), but many of these methods have produced conflicting results or require further investigation. Exploration of AF using information theoretic-based approaches may have the potential to provide new insights into the complex system dynamics of AF, whilst also providing the benefit of being less reliant on empirically derived definitions in comparison to alternate mapping approaches. This work provides an overview of information theory and reviews its applications in AF analysis, with particular focus on AF mapping. The works discussed in this review demonstrate how understanding AF from a signal property perspective can provide new insights into the arrhythmic phenomena, which may have valuable clinical implications for AF mapping and ablation in the future.

Multimodal Examination of Atrial Fibrillation Substrate: Correlation of Left Atrial Bipolar Voltage Using Multi-Electrode Fast Automated Mapping, Point-by-Point Mapping, and Magnetic Resonance Image Intensity Ratio

Background

Bipolar voltage mapping, as part of atrial fibrillation (AF) ablation, is traditionally performed in a point-by-point (PBP) approach using single-tip ablation catheters. Alternative techniques for fibrosis-delineation include fast-anatomical mapping (FAM) with multi-electrode circular catheters, and late gadolinium-enhanced magnetic-resonance imaging (LGE-MRI). The correlation between PBP, FAM, and LGE-MRI fibrosis assessment is unknown.

Objective

In this study, we examined AF substrate using different modalities (PBP, FAM, and LGE-MRI mapping) in patients presenting for an AF ablation.

Methods

LGE-MRI was performed pre-ablation in 26 patients (73% males, age 63±8years). Local image-intensity ratio (IIR) was used to normalize myocardial intensities. PBP- and FAM-voltage maps were acquired, in sinus rhythm, prior to ablation and co-registered to LGE-MRI.

Results

Mean bipolar voltage for all 19,087 FAM voltage points was 0.88±1.27mV and average IIR was 1.08±0.18. In an adjusted mixed-effects model, each unit increase in local IIR was associated with 57% decrease in bipolar voltage (p<0.0001). IIR of >0.74 corresponded to bipolar voltage <0.5 mV. A total of 1554 PBP-mapping points were matched to the nearest FAM-point. In an adjusted mixed-effects model, log-FAM bipolar voltage was significantly associated with log-PBP bipolar voltage (ß=0.36, p<0.0001). At low-voltages, FAM-mapping distribution was shifted to the left compared to PBP-mapping; at intermediate voltages, FAM and PBP voltages were overlapping; and at high voltages, FAM exceeded PBP-voltages.

Conclusion

LGE-MRI, FAM and PBP-mapping show good correlation in delineating electro-anatomical AF substrate. Each approach has fundamental technical characteristics, the awareness of which allows proper assessment of atrial fibrosis.

Novel Quantitative Analytical Approaches for Rotor Identification and Associated Implications for Mapping

GOAL

Clinical studies identifying rotors and confirming these sites for ablation in treating cardiac arrhythmias have had inconsistent results with the currently available analysis techniques. The aim of this study is to evaluate four new signal analysis approaches-multiscale frequency (MSF), Shannon entropy (SE), Kurtosis (Kt), and multiscale entropy (MSE)-in their ability to identify the pivot point of rotors.

METHODS

Optical mapping movies of ventricular tachycardia were used to evaluate the performance and robustness of SE, Kt, MSF, and MSE techniques with respect to several clinical limitations: decreased time duration, reduced spatial resolution, and the presence of meandering rotors. To quantitatively assess the robustness of the four techniques, results were compared to the "true" rotor(s) identified using optical mapping-based phase maps.

RESULTS

The results demonstrate that MSF, Kt, and MSE accurately identified both stationary and meandering rotors. In addition, these techniques remained accurate under simulated clinical limitations: shortened electrogram duration and decreased spatial resolution. Artifacts mildly affected the performance of MSF, Kt, and MSE, but strongly impacted the performance of SE.

CONCLUSION

These results motivate further validation using intracardiac electrograms to see if these approaches can map rotors in a clinical setting and whether they apply to more complex arrhythmias including atrial or ventricular fibrillation.

SIGNIFICANCE

New techniques providing more accurate rotor localization could improve characterization of arrhythmias and, in turn, offer a means to accurately evaluate whether rotor ablation is a viable and effective treatment for chaotic cardiac arrhythmias.

Virtual In-Silico Modeling Guided Catheter Ablation Predicts Effective Linear Ablation Lesion Set for Longstanding Persistent Atrial Fibrillation: Multicenter Prospective Randomized Study

Objective: Radiofrequency catheter ablation for persistent atrial fibrillation (PeAF) still has a substantial recurrence rate. This study aims to investigate whether an AF ablation lesion set chosen using in-silico ablation (V-ABL) is clinically feasible and more effective than an empirically chosen ablation lesion set (Em-ABL) in patients with PeAF. Methods: We prospectively included 108 patients with antiarrhythmic drug-resistant PeAF (77.8% men, age 60.8 ± 9.9 years), and randomly assigned them to the V-ABL (n = 53) and Em-ABL (n = 55) groups. Five different in-silico ablation lesion sets [1 pulmonary vein isolation (PVI), 3 linear ablations, and 1 electrogram-guided ablation] were compared using heart-CT integrated AF modeling. We evaluated the feasibility, safety, and efficacy of V-ABL compared with that of Em-ABL. Results: The pre-procedural computing time for five different ablation strategies was 166 ± 11 min. In the Em-ABL group, the earliest terminating blinded in-silico lesion set matched with the Em-ABL lesion set in 21.8%. V-ABL was not inferior to Em-ABL in terms of procedure time (p = 0.403), ablation time (p = 0.510), and major complication rate (p = 0.900). During 12.6 ± 3.8 months of follow-up, the clinical recurrence rate was 14.0% in the V-ABL group and 18.9% in the Em-ABL group (p = 0.538). In Em-ABL group, clinical recurrence rate was significantly lower after PVI+posterior box+anterior linear ablation, which showed the most frequent termination during in-silico ablation (log-rank p = 0.027). Conclusions: V-ABL was feasible in clinical practice, not inferior to Em-ABL, and predicts the most effective ablation lesion set in patients who underwent PeAF ablation.

Impact of number of co-existing rotors and inter-electrode distance on accuracy of rotor localization

BACKGROUND

Conflicting evidence exists on the efficacy of focal impulse and rotor modulation on atrial fibrillation ablation. A potential explanation is inaccurate rotor localization from multiple rotors coexistence and a relatively large (9-11mm) inter-electrode distance (IED) of the multi-electrode basket catheter.

METHODS AND RESULTS

We studied a numerical model of cardiac action potential to reproduce one through seven rotors in a two-dimensional lattice. We estimated rotor location using phase singularity, Shannon entropy and dominant frequency. We then spatially downsampled the time series to create IEDs of 2-30mm. The error of rotor localization was measured with reference to the dynamics of phase singularity at the original spatial resolution (IED=1mm). IED has a significant impact on the error using all the methods. When only one rotor is present, the error increases exponentially as a function of IED. At the clinical IED of 10mm, the error is 3.8mm (phase singularity), 3.7mm (dominant frequency), and 11.8mm (Shannon entropy). When there are more than one rotors, the error of rotor localization increases 10-fold. The error based on the phase singularity method at the clinical IED of 10mm ranges from 30.0mm (two rotors) to 96.1mm (five rotors).

CONCLUSIONS

The magnitude of error of rotor localization using a clinically available basket catheter, in the presence of multiple rotors might be high enough to impact the accuracy of targeting during AF ablation. Improvement of catheter design and development of high-density mapping catheters may improve clinical outcomes of FIRM-guided AF ablation.

The effect of activation rate on left atrial bipolar voltage in patients with paroxysmal atrial fibrillation

INTRODUCTION

Bipolar voltage is used during electroanatomic mapping to define abnormal myocardium, but the effect of activation rate on bipolar voltage is not known. We hypothesized that bipolar voltage may change in response to activation rate. By examining corresponding unipolar signals we sought to determine the mechanisms of such changes.

METHODS AND RESULTS

LA extrastimulus mapping was performed during CS pacing in 10 patients undergoing first time paroxysmal atrial fibrillation ablation. Bipolar and unipolar electrograms were recorded using a PentaRay catheter (4-4-4 spacing) and indifferent IVC electrode, respectively. An S1S2 pacing protocol was delivered with extrastimulus coupling interval reducing from 350 to 200 milliseconds. At each recording site (119 ± 37 per LA), bipolar peak-to-peak voltage, unipolar peak to peak voltage and activation delay between unipole pairs was measured. Four patterns of bipolar voltage/extrastimulus coupling interval curves were seen: voltage attenuation with plateau voltage >1 mV (48 ± 15%) or <1 mV (22 ± 15%), and voltage unaffected by coupling interval with plateau voltage >1 mV (17 ± 10%) or <1 mV (13 ± 8%). Electrograms showing bipolar voltage attenuation were associated with significantly greater unipolar voltage attenuation at low (25 ± 28 mV/s vs. 9 ± 11 mV/s) and high (23 ± 29 mV/s vs. 6 ± 12 mV/s) plateau voltage sites (P < 0.001). There was a small but significant increase in conduction delay between unipole pairs at sites showing bipolar voltage attenuation (P = 0.026).

CONCLUSIONS

Bipolar electrogram voltage is dependent on activation rate at a significant proportion of sites. Changes in unipolar voltage and timing underlie these effects. These observations have important implications for use of voltage mapping to delineate abnormal atrial substrate.

Atrial Electrogram Fractionation Distribution before and after Pulmonary Vein Isolation in Human Persistent Atrial Fibrillation-A Retrospective Multivariate Statistical Analysis

Purpose: Complex fractionated atrial electrograms (CFAE)-guided ablation after pulmonary vein isolation (PVI) has been used for persistent atrial fibrillation (persAF) therapy. This strategy has shown suboptimal outcomes due to, among other factors, undetected changes in the atrial tissue following PVI. In the present work, we investigate CFAE distribution before and after PVI in patients with persAF using a multivariate statistical model.

Methods: 207 pairs of atrial electrograms (AEGs) were collected before and after PVI respectively, from corresponding LA regions in 18 persAF patients. Twelve attributes were measured from the AEGs, before and after PVI. Statistical models based on multivariate analysis of variance (MANOVA) and linear discriminant analysis (LDA) have been used to characterize the atrial regions and AEGs.

Results: PVI significantly reduced CFAEs in the LA (70 vs. 40%; P < 0.0001). Four types of LA regions were identified, based on the AEGs characteristics: (i) fractionated before PVI that remained fractionated after PVI (31% of the collected points); (ii) fractionated that converted to normal (39%); (iii) normal prior to PVI that became fractionated (9%) and; (iv) normal that remained normal (21%). Individually, the attributes failed to distinguish these LA regions, but multivariate statistical models were effective in their discrimination (P < 0.0001).

Conclusion: Our results have unveiled that there are LA regions resistant to PVI, while others are affected by it. Although, traditional methods were unable to identify these different regions, the proposed multivariate statistical model discriminated LA regions resistant to PVI from those affected by it without prior ablation information.

Role of atrial wall thickness in wave-dynamics of atrial fibrillation

Background/Aims

Atrial anatomy and thickness may affect the electrical wave-dynamics of atrial fibrillation (AF). We explored the relationship between left atrial (LA) wall thickness (LAWT) or LA geometry and AF wave-dynamics.

Methods

We included 15 patients with persistent AF (age, 62.3 ± 11.9 years) who underwent AF catheter ablation. We measured the LAWT, LA endocardial curvature, and SD-curvature (surface bumpiness) from preprocedural computed tomography images. We compared those anatomical characteristics with electrophysiologic parameters such as dominant frequency (DF), Shannon entropy (ShEn), or complex fractionated atrial electrogram (CFAE)-cycle length (CL), calculated from intracardiac bipolar electrograms (300–500 points, 5 s), acquired during ablation procedures.

Results

1. LAWT (excluding fat) varied widely among patients, locations, and types of AF. LAWT was inversely correlated with LA volume (r = -0.565, p = 0.028) and positively correlated with SD-curvature (r = 0.272, p < 0.001). 2. LAWT was positively correlated with ShEn (r = 0.233, p < 0.001) and negatively correlated with CFAE-CL (r = -0.107, p = 0.038). 3. In the multivariate linear regression analyses for AF wave-dynamics parameters, DF (β = -0.29 [95% CI -0.44–-0.14], p < 0.001), ShEn (β = 0.19 [95% CI 0.12–0.25], p < 0.001), and CFAE-CL (β = 7.49 [95% CI 0.65–14.34], p = 0.032) were independently associated with LAWT.

Conclusion

Regional LAWT is associated with LA structural features, and has significant correlations with the wave-dynamics parameters associated with electrical wavebreaks or rotors in patients with persistent AF.

Ablation as targeted perturbation to rewire communication network of persistent atrial fibrillation

Persistent atrial fibrillation (AF) can be viewed as disintegrated patterns of information transmission by action potential across the communication network consisting of nodes linked by functional connectivity. To test the hypothesis that ablation of persistent AF is associated with improvement in both local and global connectivity within the communication networks, we analyzed multi-electrode basket catheter electrograms of 22 consecutive patients (63.5 ± 9.7 years, 78% male) during persistent AF before and after the focal impulse and rotor modulation-guided ablation. Eight patients (36%) developed recurrence within 6 months after ablation. We defined communication networks of AF by nodes (cardiac tissue adjacent to each electrode) and edges (mutual information between pairs of nodes). To evaluate patient-specific parameters of communication, thresholds of mutual information were applied to preserve 10% to 30% of the strongest edges. There was no significant difference in network parameters between both atria at baseline. Ablation effectively rewired the communication network of persistent AF to improve the overall connectivity. In addition, successful ablation improved local connectivity by increasing the average clustering coefficient, and also improved global connectivity by decreasing the characteristic path length. As a result, successful ablation improved the efficiency and robustness of the communication network by increasing the small-world index. These changes were not observed in patients with AF recurrence. Furthermore, a significant increase in the small-world index after ablation was associated with synchronization of the rhythm by acute AF termination. In conclusion, successful ablation rewires communication networks during persistent AF, making it more robust, efficient, and easier to synchronize. Quantitative analysis of communication networks provides not only a mechanistic insight that AF may be sustained by spatially localized sources and global connectivity, but also patient-specific metrics that could serve as a valid endpoint for therapeutic interventions.

Demystifying rotors and their place in clinical translation of atrial fibrillation mechanisms

Treatment of atrial fibrillation (AF), the most common arrhythmia in clinical practice, remains challenging. Improved understanding of underlying mechanisms is needed to improve therapy. Functional re-entry is central to AF maintenance. The first detailed, quantitative theory of functional re-entry, the 'leading circle' model, was developed 40 years ago. Subsequently, an alternative paradigm based on 'spiral waves' has evolved. Spiral-wave generators, or 'rotors', have been identified using advanced mapping methods in experimental and clinical AF. A central tool in the analysis of spiral-wave rotors is the phase transformation, allowing for easier visualization of rotors and tracking of 'phase singularity' points at the rotor tip. In contrast to leading circle theory, which is expressed in terms familiar to (and easily understood by) cardiologists, the ideas needed to understand rotors are much more theoretical and harder for clinicians to apply. In this Review, we summarize the basic notions of phase mapping and spiral-wave rotors, and the ways in which rotor sources might be involved in AF maintenance. We discuss competing observations about the role of spatially confined rotors, short-lived rotors clustered at the edge of fibrotic zones, endocardial-epicardial interactive breeder properties and transmural re-entry, as well as studies underway to resolve them. We conclude with consideration of the clinical relevance of the issues discussed and their potential implications for the management of patients with AF.

Rotor Tracking Using Phase of Electrograms Recorded During Atrial Fibrillation

Extracellular electrograms recorded during atrial fibrillation (AF) are challenging to interpret due to the inherent beat-to-beat variability in amplitude and duration. Phase mapping represents these voltage signals in terms of relative position within the cycle, and has been widely applied to action potential and unipolar electrogram data of myocardial fibrillation. To date, however, it has not been applied to bipolar recordings, which are commonly acquired clinically. The purpose of this study is to present a novel algorithm for calculating phase from both unipolar and bipolar electrograms recorded during AF. A sequence of signal filters and processing steps are used to calculate phase from simulated, experimental, and clinical, unipolar and bipolar electrograms. The algorithm is validated against action potential phase using simulated data (trajectory centre error <0.8 mm); between experimental multi-electrode array unipolar and bipolar phase; and for wavefront identification in clinical atrial tachycardia. For clinical AF, similar rotational content (R 2 = 0.79) and propagation maps (median correlation 0.73) were measured using either unipolar or bipolar recordings. The algorithm is robust, uses standard signal processing techniques, and accurately quantifies AF wavefronts and sources. Identifying critical sources, such as rotors, in AF, may allow for more accurate targeting of ablation therapy and improved patient outcomes.

Development of a novel probabilistic algorithm for localization of rotors during atrial fibrillation

Atrial fibrillation (AF) is an irregular heart rhythm that can lead to stroke and other heart-related complications. Catheter ablation has been commonly used to destroy triggering sources of AF in the atria and consequently terminate the arrhythmia. However, efficient and accurate localization of the AF sustaining sources known as rotors is a major challenge in catheter ablation. In this paper, we developed a novel probabilistic algorithm that can adaptively guide a Lasso diagnostic catheter to locate the center of a rotor. Our algorithm uses a Bayesian updating approach to search for and locate rotors based on the characteristics of electrogram signals collected at every catheter placement. The algorithm was evaluated using a 10 × 10 cm 2 D atrial tissue simulation of the Nygren human atrial cell model and was able to successfully guide the catheter to the rotor center in 3.37 ± 1.05 (mean±std) steps (including placement at the center) when starting from any location on the tissue. Our novel automated algorithm can potentially play a significant role in patient-specific ablation of AF sources and increase the success of AF elimination procedures.

Effect of spatial resolution and filtering on mapping cardiac fibrillation

BACKGROUND

Endocardial mapping tools use variable interelectrode resolution, whereas body surface mapping tools use narrow bandpass filtering (BPF) to map fibrillatory mechanisms established by high-resolution optical imaging.

OBJECTIVE

The purpose of this study was to study the effect of resolution and BPF on the underlying mechanism being mapped.

METHODS

Hearts from 14 healthy New Zealand white rabbits were Langendorff perfused. We studied the effect of spatial resolution and BPF on the location and characterization of rotors by comparing phase singularities detected by high-resolution unfiltered optical maps and of fibrillating myocardium with decimated and filtered maps with simulated electrode spacing of 2, 5, and 8 mm.

RESULTS

As we decimated the maps with 2-mm, 5-mm, and 8-mm interelectrode spacing, the mean ( ± SD) number of rotors detected decreased from 10.2 ± 9.6, 1.6 ± 3.2, and 0.2 ± 0.5, respectively. Lowering the resolution led to synthesized pseudo-rotors that may be inappropriately identified. Applying a BPF led to fewer mean phase singularities detected (248 ± 207 vs 333 ± 130; P<.01), giving the appearance of pseudo-spatial stability measured as translation index (with BPF 3.6 ± 0.4 mm vs 4.0 ± 0.5 mm without BPF; P<.01) and pseudo-temporal stability with longer duration (70.0 ± 17.6 ms in BPF maps vs 44.1 ± 6.6 ms in unfiltered maps; P<.001) than true underlying fibrillating myocardium mapped.

CONCLUSION

Electrode resolution and BPF of electrograms can result in distortion of the underlying electrophysiology of fibrillation. Newer mapping techniques need to demonstrate sensitivity analysis to quantify the degree of distortion before clinical use to avoid inaccurate electrophysiologic interpretation.

Effect of the electrograms density in detecting and ablating the tip of the rotor during chronic atrial fibrillation: an in silico study

AIMS

Identification in situ of arrhythmogenic mechanisms could improve the rate of ablation success in atrial fibrillation (AF). Our research group reported that rotors could be located through dynamic approximate entropy (DApEn) maps. However, it is unknown how much the spatial resolution of catheter electrodes could affect substrates localization. The present work looked for assessing the electrograms (EGMs) spatial resolution needed to locate the rotor tip using DApEn maps.

METHODS AND RESULTS

A stable rotor in a two-dimensional computational model of human atrial tissue was simulated using the Courtemanche electrophysiological model and implementing chronic AF features. The spatial resolution is 0.4 mm (150 × 150 EGM). Six different lower resolution arrays were obtained from the initial mesh. For each array, DApEn maps were constructed using the inverse distance weighting (IDW) algorithm. Three simple ablation patterns were applied. The full DApEn map detected the rotor tip and was able to follow the small meander of the tip through the shape of the area containing the tip. Inverse distance weighting was able to reconstruct DApEn maps after applying different spatial resolutions. These results show that spatial resolutions from 0.4 to 4 mm accurately detect the rotor tip position. An ablation line terminates the rotor only if it crosses the tip and ends at a tissue boundary.

CONCLUSION

A previous work has shown that DApEn maps successfully detected simulated rotor tips using a high spatial resolution. In this work, it was evinced that DApEn maps could be applied using a spatial resolution similar to that available in commercial catheters, by adding an interpolation stage. This is the first step to translate this tool into medical practice with a view to the detection of ablation targets.

Anti-arrhythmic strategies for atrial fibrillation: The role of computational modeling in discovery, development, and optimization

Atrial fibrillation (AF), the most common cardiac arrhythmia, is associated with increased risk of cerebrovascular stroke, and with several other pathologies, including heart failure. Current therapies for AF are targeted at reducing risk of stroke (anticoagulation) and tachycardia-induced cardiomyopathy (rate or rhythm control). Rate control, typically achieved by atrioventricular nodal blocking drugs, is often insufficient to alleviate symptoms. Rhythm control approaches include antiarrhythmic drugs, electrical cardioversion, and ablation strategies. Here, we offer several examples of how computational modeling can provide a quantitative framework for integrating multiscale data to: (a) gain insight into multiscale mechanisms of AF; (b) identify and test pharmacological and electrical therapy and interventions; and (c) support clinical decisions. We review how modeling approaches have evolved and contributed to the research pipeline and preclinical development and discuss future directions and challenges in the field.

The Spatiotemporal Stability of Dominant Frequency Sites in In-Silico Modeling of 3-Dimensional Left Atrial Mapping of Atrial Fibrillation

BACKGROUND

We previously reported that stable rotors were observed in in-silico human atrial fibrillation (AF) models, and were well represented by dominant frequency (DF). We explored the spatiotemporal stability of DF sites in 3D-AF models imported from patient CT images of the left atrium (LA).

METHODS

We integrated 3-D CT images of the LA obtained from ten patients with persistent AF (male 80%, 61.8 ± 13.5 years old) into an in-silico AF model. After induction, we obtained 6 seconds of AF simulation data for DF analyses in 30 second intervals (T1-T9). The LA was divided into ten sections. Spatiotemporal changes and variations in the temporal consistency of DF were evaluated at each section of the LA. The high DF area was defined as the area with the highest 10% DF.

RESULTS

1. There was no spatial consistency in the high DF distribution at each LA section during T1-T9 except in one patient (p = 0.027). 2. Coefficients of variation for the high DF area were highly different among the ten LA sections (p < 0.001), and they were significantly higher in the four pulmonary vein (PV) areas, the LA appendage, and the peri-mitral area than in the other LA sections (p < 0.001). 3. When we conducted virtual ablation of 10%, 15%, and 20% of the highest DF areas (n = 270 cases), AF was changed to atrial tachycardia (AT) or terminated at a rate of 40%, 57%, and 76%, respectively.

CONCLUSIONS

Spatiotemporal consistency of the DF area was observed in 10% of AF patients, and high DF areas were temporally variable. Virtual ablation of DF is moderately effective in AF termination and AF changing into AT.