Wave Similarity Mapping Shows the Spatiotemporal Distribution of Fibrillatory Wave Complexity in the Human Right Atrium During Paroxysmal and Chronic Atrial Fibrillation

Evaluation and optimization of novel extraction algorithms for the automatic detection of atrial activations recorded within the pulmonary veins during atrial fibrillation

Background and objective

The automated detection of atrial activations (AAs) recorded from intracardiac electrograms (IEGMs) during atrial fibrillation (AF) is challenging considering their various amplitudes, morphologies and cycle length. Activation time estimation is further complicated by the constant changes in the IEGM active zones in complex and/or fractionated signals. We propose a new method which provides reliable automatic extraction of intracardiac AAs recorded within the pulmonary veins during AF and an accurate estimation of their local activation times.

Methods

First, two recently developed algorithms were evaluated and optimized on 118 recordings of pulmonary vein IEGM taken from 35 patients undergoing ablation of persistent AF. The adaptive mathematical morphology algorithm (AMM) uses an adaptive structuring element to extract AAs based on their morphological features. The relative-energy algorithm (Rel-En) uses short- and long-term energies to enhance and detect the AAs in the IEGM signals. Second, following the AA extraction, the signal amplitude was weighted using statistics of the AA sequences in order to reduce over- and undersensing of the algorithms. The detection capacity of our algorithms was compared with manually annotated activations and with two previously developed algorithms based on the Teager–Kaiser energy operator and the AF cycle length iteration, respectively. Finally, a method based on the barycenter was developed to reduce artificial variations in the activation annotations of complex IEGM signals.

Results

The best detection was achieved using Rel-En, yielding a false negative rate of 0.76% and a false positive rate of only 0.12% (total error rate 0.88%) against expert annotation. The post-processing further reduced the total error rate of the Rel-En algorithm by 70% (yielding to a final total error rate of 0.28%).

Conclusion

The proposed method shows reliable detection and robust temporal annotation of AAs recorded within pulmonary veins in AF. The method has low computational cost and high robustness for automatic detection of AAs, which makes it a suitable approach for online use in a procedural context.

Classification of Fibrillation Organisation Using Electrocardiograms to Guide Mechanism-Directed Treatments

Background: Atrial fibrillation (AF) and ventricular fibrillation (VF) are complex heart rhythm disorders and may be sustained by distinct electrophysiological mechanisms. Disorganised self-perpetuating multiple-wavelets and organised rotational drivers (RDs) localising to specific areas are both possible mechanisms by which fibrillation is sustained. Determining the underlying mechanisms of fibrillation may be helpful in tailoring treatment strategies. We investigated whether global fibrillation organisation, a surrogate for fibrillation mechanism, can be determined from electrocardiograms (ECGs) using band-power (BP) feature analysis and machine learning. Methods: In this study, we proposed a novel ECG classification framework to differentiate fibrillation organisation levels. BP features were derived from surface ECGs and fed to a linear discriminant analysis classifier to predict fibrillation organisation level. Two datasets, single-channel ECGs of rat VF (n = 9) and 12-lead ECGs of human AF (n = 17), were used for model evaluation in a leave-one-out (LOO) manner. Results: The proposed method correctly predicted the organisation level from rat VF ECG with the sensitivity of 75%, specificity of 80%, and accuracy of 78%, and from clinical AF ECG with the sensitivity of 80%, specificity of 92%, and accuracy of 88%. Conclusion: Our proposed method can distinguish between AF/VF of different global organisation levels non-invasively from the ECG alone. This may aid in patient selection and guiding mechanism-directed tailored treatment strategies.

Temporal irregularity quantification and mapping of optical action potentials using wave morphology similarity

Background

Cardiac optical mapping enables direct and high spatio-temporal resolution recording of action potential (AP) morphology. Temporal alterations in AP morphology are both predictive and consequent of arrhythmia. Here we sought to test if methods that quantify regularity of recorded waveforms could be applied to detect and quantify periods of temporal instability in optical mapping datasets in a semi-automated, user-unbiased manner.

Methods and results

We developed, tested and applied algorithms to quantify optical wave similarity (OWS) to study morphological temporal similarity of optically recorded APs. Unlike other measures (e.g. alternans ratio, beat-to-beat variability, arrhythmia scoring), the quantification of OWS is achieved without a restrictive definition of specific signal points/features and is instead derived by analysing the complete morphology from the entire AP waveform.

Using model datasets, we validated the ability of OWS to measure changes in AP morphology, and tested OWS mapping in guinea pig hearts and mouse atria. OWS successfully detected and measured alterations in temporal regularity in response to several proarrhythmic stimuli, including alterations in pacing frequency, premature contractions, alternans and ventricular fibrillation.

Conclusion

OWS mapping provides an effective measure of temporal regularity that can be applied to optical datasets to detect and quantify temporal alterations in action potential morphology. This methodology provides a new metric for arrhythmia inducibility and scoring in optical mapping datasets.

Locating Atrial Fibrillation Rotor and Focal Sources Using Iterative Navigation of Multipole Diagnostic Catheters

Purpose

Multi-polar diagnostic catheters are used to construct the 3D electro-anatomic mapping of the atrium during atrial fibrillation (AF) ablation procedures; however, it remains unclear how to use the electrograms recorded by these catheters to locate AF-driving sites known as focal and rotor source types. The purpose of this study is to present the first algorithm to iteratively navigate a circular multi-polar catheter to locate AF focal and rotor sources without the need to map the entire atria.

Methods

Starting from an initial location, the algorithm, which was blinded to the location and type of the AF source, iteratively advanced a Lasso catheter based on its electrogram characteristics. The algorithm stopped the catheter when it located of an AF source and identified the type. The efficiency of the algorithm is validated using a set of simulated focal and rotor-driven arrhythmias in fibrotic human 2D and 3D atrial tissue.

Results

Our study shows the feasibility of locating AF sources with a success rate of greater than 95.25% within average 7.56 ± 2.28 placements independently of the initial position of the catheter and the source type.

Conclusions

The algorithm could play a critical role in clinical electrophysiology laboratories for mapping patient-specific ablation of AF sources located outside the pulmonary veins and improving the procedure success.

Electronic supplementary material

The online version of this article (10.1007/s13239-019-00414-5) contains supplementary material, which is available to authorized users.

A method for quantifying recurrent patterns of local wavefront direction during atrial fibrillation

INTRODUCTION

Spiral wave reentry is a potential mechanism of atrial fibrillation (AF), but is difficult to differentiate clinically from multiple wavelet breakup using standard bipolar recordings. We developed a new methodology using bipolar recordings to estimate the direction of local activation wavefronts during AF by calculating the electrogram conformation (Egm-C). We subsequently used recurrence quantification analysis (RQA) of Egm-C to differentiate regions of spiral wave reentry from wavelet breakup.

METHODS

A 2D computer simulation was created with regions containing a stable spiral wave and also regions of wavebreak. A grid of 40 × 40 unipolar electrodes was superimposed. At each site, the actual wavefront direction (WD) was determined by comparing relative activation timings of the local intracellular recordings, and the estimated wavefront direction (Egm-C) was determined from the morphology of the local bipolar electrogram. RQA of Egm-C was compared to RQA of actual WD in order to differentiate AF mechanisms.

RESULTS

RQA of actual WD and Egm-C both distinguished regions of spiral wave reentry from wavelet breakup with high correlation between the two methods (recurrence rate, r = 0.96; determinism, r = 0.61; line max, r = 0.95; entropy, r = 0.84; p < 0.001 for all). In areas of stable spiral wave reentry, the recurrence plots of both Egm-C and actual WD demonstrated stable, periodic dynamics, while regions of wavelet breakup demonstrated chaotic behavior largely devoid of repetitive activation patterns.

CONCLUSION

Calculation of Egm-C allows RQA to be performed on bipolar electrograms during AF and differentiates regions of spiral wave reentry from multiple wavelet breakup.

A note on stress-driven anisotropic diffusion and its role in active deformable media

We introduce a new model to describe diffusion processes within active deformable media. Our general theoretical framework is based on physical and mathematical considerations, and it suggests to employ diffusion tensors directly influenced by the coupling with mechanical stress. The proposed generalised reaction-diffusion-mechanics model reveals that initially isotropic and homogeneous diffusion tensors turn into inhomogeneous and anisotropic quantities due to the intrinsic structure of the nonlinear coupling. We study the physical properties leading to these effects, and investigate mathematical conditions for its occurrence. Together, the mathematical model and the numerical results obtained using a mixed-primal finite element method, clearly support relevant consequences of stress-driven diffusion into anisotropy patterns, drifting, and conduction velocity of the resulting excitation waves. Our findings also indicate the applicability of this novel approach in the description of mechano-electric feedback in actively deforming bio-materials such as the cardiac tissue.

Practical Considerations of Mapping Persistent Atrial Fibrillation With Whole-Chamber Basket Catheters

OBJECTIVES

This study sought to evaluate basket catheter deployment, catheter-tissue contact, and time-space stability of unipolar atrial electrograms (aEGMs) recorded in persistent atrial fibrillation (AF) patients.

BACKGROUND

Panoramic mapping of human AF using multiple-electrode basket catheters may identify AF sources. Although clinical results using this technique are provocative, questions remain about its effectiveness.

METHODS

Data were collected from patients (N = 25) undergoing catheter ablation for AF during the multicenter STARLIGHT (Signal Transfer of Atrial Fibrillation Data to Guide Human Treatment) trial (NCT01765075). Left and right aEGM signals were recorded using basket catheters during baseline AF, following ablation and during sinus rhythm. Data were analyzed for basket deployment, peak-to-peak voltage, and electrogram stability and organization. Electrogram stability and organization were evaluated via time-frequency analysis (TFA).

RESULTS

Basket catheters displayed equatorial bunching when deployed in atria. Interspline spacing ranged from 1.7 to 64.0 mm in the right atrial and from 1.5 to 85.08 mm in the left atrial basket. Approximately one-third of mapping electrodes failed to demonstrate a median peak-to-peak voltage >2× the low-voltage threshold. Time-space stability and organization was observed in 13 of 22 (59.09%) right atrial and 10 of 22 (45.45%) left atrial baskets.

CONCLUSIONS

Despite poor deployment and a large number of low-voltage electrodes, stability and organization was observed in about one-half of the mapped patients. Although this study suggests that basket catheters have limitations for patient-specific AF mapping, concordant activation occurs in some persistent AF patients, which may be amenable to high-density mapping techniques.

Searching for "order" in atrial fibrillation using electrogram morphology recurrence plots

BACKGROUND

Bipolar electrograms recorded during atrial fibrillation (AF) can have an appearance of chaotic/random behavior. The aim of this study was to use a novel electrogram morphology recurrence (EMR) analysis to quantify the level of order in the morphology patterns in AF.

METHODS

Rapid atrial pacing was performed in seven dogs at 600bpm for 3 weeks leading to sustained AF. Open chest high density electrical recordings were made in multiple atrial sites. EMR plots of bipolar electrograms at each site were created by cross-correlating morphologies of each detected activations with morphologies of every other activation. The following features of the EMR plots were quantified: recurrence rate (RR), determinism (DET), laminarity (LAM), average diagonal line length (L), trapping time (TT), divergence (DIV), and Shannon׳s entropy (ENTR). For each recording site, these measures were calculated for the normal sequence of morphologies and also after random shuffling of the electrogram orders.

RESULTS

Electrograms recordings from a total of 3961 sites had average cycle lengths of 104±22ms resulting in an average of 100±19 activations detected per 10-s recording and an average RR of 0.38±0.28 (range 0.02-1.00). Shuffling the order of the activation morphologies resulted in significant decreases in DET, LAM, L, TT, and ENTR and significant increases in DIV.

CONCLUSIONS

EMR plots of AF electrograms show varying rates of recurrence with patterns that suggest an underlying deterministic structure to the activation sequences. A better understanding of AF dynamics could lead to improved methods in mapping and treating AF.

Analysis of cardiac fibrillation using phase mapping

The sequence of myocardial electrical activation during fibrillation is complex and changes with each cycle. Phase analysis represents the electrical activation-recovery process as an angle. Lines of equal phase converge at a phase singularity at the center of rotation of a reentrant wave, and the identification of reentry and tracking of reentrant wavefronts can be automated. We examine the basic ideas behind phase analysis. With the exciting prospect of using phase analysis of atrial electrograms to guide ablation in the human heart, we highlight several recent developments in preprocessing electrograms so that phase can be estimated reliably.

The logical operator map identifies novel candidate markers for critical sites in patients with atrial fibrillation

The identification of suitable markers for critical patterns during atrial fibrillation (AF) may be crucial to guide an effective ablation treatment. Single parameter maps, based on dominant frequency and complex fractionated electrograms, have been proposed as a tool for electrogram-guided ablation, however the specificity of these markers is debated. Experimental studies suggest that AF critical patterns may be identified on the basis of specific rate and organization features, where rapid organized and rapid fragmented activities characterize respectively localized sources and critical substrates. In this paper we introduce the logical operator map, a novel mapping tool for a point-by-point identification and localization of AF critical sites. Based on advanced signal and image processing techniques, the approach combines in a single map electrogram-derived rate and organization features with tomographic anatomical detail. The construction of the anatomically-detailed logical operator map is based on the time-domain estimation of atrial rate and organization in terms of cycle length and wave-similarity, the logical combination of these indexes to obtain suitable markers of critical sites, and the multimodal integration of electrophysiological and anatomical information by segmentation and registration techniques. Logical operator maps were constructed in 14 patients with persistent AF, showing the capability of the combined rate and organization markers to identify with high selectivity the subset of electrograms associated with localized sources and critical substrates. The precise anatomical localization of these critical sites revealed the confinement of rapid organized sources in the left atrium with organization and rate gradients towards the surrounding tissue, and the presence of rapid fragmented electrograms in proximity of the sources. By merging in a single map the most relevant electrophysiological and anatomical features of the AF process, the logical operator map may have significant clinical impact as a direct, comprehensive tool to understand arrhythmia mechanisms in the single patient and guide more conservative, step-wise ablation.

Anatomic localization of rapid repetitive sources in persistent atrial fibrillation: fusion of biatrial CT images with wave similarity/cycle length maps

OBJECTIVES

The aim of this study was to investigate the anatomic distribution of critical sources in patients with atrial fibrillation (AF) by fusion of biatrial computed tomography (CT) images with cycle length (CL) and wave similarity (WS) maps.

BACKGROUND

Experimental and clinical studies show that atrial fibrillation (AF) may originate from rapid and repetitive (RR) sources of activation. Localization of RR sources may be crucial for an effective ablation treatment. Atrial electrograms showing rapid and repetitive activations can be identified by combining WS and CL analysis.

METHODS

Patients with persistent AF underwent biatrial electroanatomic mapping and pre-procedural CT cardiac imaging. WS and CL maps were constructed in 17 patients by calculating the degree of repetitiveness of activation waveforms (similarity index [S]) and the cycle length at each atrial site. WS/CL maps were then integrated with biatrial 3-dimensional CT reconstructions by a stochastic approach.

RESULTS

Repetitive sources of activation (S ≥ 0.5) were present in most patients with persistent AF (94%) and were mainly located at the pulmonary veins (82% of patients), at the superior caval vein (41%), on the anterior wall of the right atrium (23%), and at the left atrial appendage (23%). Potential driver sources showing both rapid and repetitive activations (CL = 140.7 ± 25.1 ms, S = 0.65 ± 0.15) were present only in a subset of patients (65%) and were confined to the pulmonary vein region (47% of patients) and left atrial appendage (12%). Differently, the repetitive activity of the superior caval vein was characterized by a slow activation rate (CL = 184.7 ± 14.6 ms).

CONCLUSIONS

The identification and localization of RR sources is feasible by fusion of biatrial anatomic images with WS/CL maps. Potential driver sources are present only in a subset of patients with persistent AF and are mainly located in the pulmonary vein region.

Loss of continuity in the thin epicardial layer because of endomysial fibrosis increases the complexity of atrial fibrillatory conduction

BACKGROUND

The transition from persistent to permanent atrial fibrillation (AF) is associated with increased complexity of fibrillatory conduction. We have investigated the spatial distribution of fibrillation waves and structural alterations in the atrial free walls in a goat model of AF.

METHODS AND RESULTS

AF was maintained for 3 weeks (short term [ST], persistent AF) or 6 months (long term [LT], permanent AF). Fibrillation patterns were assessed with epicardial mapping. The origin of fibrillation waves and sites of conduction abnormalities were more homogeneously distributed in LT than in ST goats. Histologically, the total area fraction occupied by fibrous tissue and the degree of perimysial fibrosis (separation between myocyte bundles) were not significantly different between groups. However, endomysial fibrosis (distance between myocytes within bundles) was significantly larger in LT goats, particularly in the outer millimeter of the atria. By contrast, myocyte diameters were larger in LT goats throughout the atrial walls. High-resolution optical mapping showed that epicardial wavefront expansion was slower and more anisotropic in LT than in ST goats. Finally, a mathematical model of a simplified atrial architecture confirmed the potential impact of epicardial endomysial fibrosis on AF complexity.

CONCLUSIONS

Altered propagation after 6 months of AF is consistent with homogeneous structural remodeling in the outer millimeter of the atria. Loss of continuity of the epicardial layer because of endomysial fibrosis may reduce its synchronizing effect, thereby increasing the complexity of fibrillatory conduction pathways. The exact distribution of fibrosis may be more important for the occurrence of conduction disturbances than the overall quantity.

Evaluation of the complexity of myocardial activation during ventricular fibrillation. An experimental study

INTRODUCTION AND OBJECTIVES

An experimental model is used to analyze the characteristics of ventricular fibrillation in situations of variable complexity, establishing relationships among the data produced by different methods for analyzing the arrhythmia.

METHODS

In 27 isolated rabbit heart preparations studied under the action of drugs (propranolol and KB-R7943) or physical procedures (stretching) that produce different degrees of change in the complexity of myocardial activation during ventricular fibrillation, use was made of spectral, morphological, and mapping techniques to process the recordings obtained with epicardial multielectrodes.

RESULTS

The complexity of ventricular fibrillation assessed by mapping techniques was related to the dominant frequency, normalized spectral energy, signal regularity index, and their corresponding coefficients of variation, as well as the area of the regions of interest identified on the basis of these parameters. In the multivariate analysis, we used as independent variables the area of the regions of interest related to the spectral energy and the coefficient of variation of the energy (complexity index=-0.005×area of the spectral energy regions -2.234×coefficient of variation of the energy+1.578; P=.0001; r=0.68).

CONCLUSIONS

The spectral and morphological indicators and, independently, those derived from the analysis of normalized energy regions of interest provide a reliable approach to the evaluation of the complexity of ventricular fibrillation as an alternative to complex mapping techniques.

Clinical mapping approach to diagnose electrical rotors and focal impulse sources for human atrial fibrillation

INTRODUCTION

The perpetuating mechanisms for human atrial fibrillation (AF) remain undefined. Localized rotors and focal beat sources may sustain AF in elegant animal models, but there has been no direct evidence for localized sources in human AF using traditional methods. We developed a clinical computational mapping approach, guided by human atrial tissue physiology, to reveal sources of human AF.

METHODS AND RESULTS

In 49 AF patients referred for ablation (62 ± 9 years; 30 persistent), we defined repolarization dynamics using monophasic action potentials (MAPs) and recorded AF activation from 64-pole basket catheters in left atrium and, in n = 20 patients, in both atria. Careful positioning of basket catheters was required for optimal mapping. AF electrograms at 64-128 electrodes were combined with repolarization and conduction dynamics to construct spatiotemporal AF maps. We observed sustained sources in 47/49 patients, in the form of electrical rotors (n = 57) and focal beats (n = 11) that controlled local atrial activation with peripheral wavebreak (fibrillatory conduction). Patients with persistent AF had more sources than those with paroxysmal AF (2.1 ± 1.0 vs 1.5 ± 0.8, P = 0.02), related to shorter cycle length (163 ± 19 milliseconds vs 187 ± 25 milliseconds, P < 0.001). Approximately one-quarter of sources lay in the right atrium.

CONCLUSIONS

Physiologically guided computational mapping revealed sustained electrical rotors and repetitive focal beats during human AF for the first time. These localized sources were present in 96% of AF patients, and controlled AF activity. These results provide novel mechanistic insights into human AF and lay the foundation for mechanistically tailored approaches to AF ablation.

Modifications in ventricular fibrillation and capture capacity induced by a linear radiofrequency lesion

INTRODUCTION AND OBJECTIVES

An analysis was made of the effects of a radiofrequency-induced linear lesion during ventricular fibrillation and the capacity to capture myocardium through high-frequency pacing.

METHODS

Using multiple epicardial electrodes, ventricular fibrillation was recorded in 22 isolated perfused rabbit hearts, analyzing the activation maps upon applying trains of stimuli at 3 different frequencies close to that of the arrhythmia: a) at baseline; b) after radio-frequency ablation to induce a lesion of the left ventricular free wall (length=10 [1] mm), and c) after lengthening the lesion (length=23 [2] mm).

RESULTS

Following lesion induction, the regularity of the recorded signals decreased and significant variations in the direction of the activation fronts were observed. On lengthening the lesion, there was a slight increase in the episodes with at least 3 consecutive captures when pacing at cycles 10% longer than the arrhythmia (baseline: 0.6 [0.7]; initial lesion: 1 [1], no significant differences; lengthened lesion: 3 [2.8]; P<.001), while a decrease was observed in those obtained upon pacing at cycles 10% shorter than the arrhythmia.

CONCLUSIONS

The radio-frequency -induced lesion increases the heterogeneity of myocardial activation during ventricular fibrillation and modifies arrival of the activation fronts in the adjacent zones. High-frequency pacing during ventricular fibrillation produces occasional captures during at least 3 consecutive stimuli. The lengthened lesion in turn slightly increases capture capacity when using cycles slightly longer than the arrhythmia.

Pathophysiological mechanisms of atrial fibrillation: a translational appraisal

Atrial fibrillation (AF) is an arrhythmia that can occur as the result of numerous different pathophysiological processes in the atria. Some aspects of the morphological and electrophysiological alterations promoting AF have been studied extensively in animal models. Atrial tachycardia or AF itself shortens atrial refractoriness and causes loss of atrial contractility. Aging, neurohumoral activation, and chronic atrial stretch due to structural heart disease activate a variety of signaling pathways leading to histological changes in the atria including myocyte hypertrophy, fibroblast proliferation, and complex alterations of the extracellular matrix including tissue fibrosis. These changes in electrical, contractile, and structural properties of the atria have been called "atrial remodeling." The resulting electrophysiological substrate is characterized by shortening of atrial refractoriness and reentrant wavelength or by local conduction heterogeneities caused by disruption of electrical interconnections between muscle bundles. Under these conditions, ectopic activity originating from the pulmonary veins or other sites is more likely to occur and to trigger longer episodes of AF. Many of these alterations also occur in patients with or at risk for AF, although the direct demonstration of these mechanisms is sometimes challenging. The diversity of etiological factors and electrophysiological mechanisms promoting AF in humans hampers the development of more effective therapy of AF. This review aims to give a translational overview on the biological basis of atrial remodeling and the proarrhythmic mechanisms involved in the fibrillation process. We pay attention to translation of pathophysiological insights gained from in vitro experiments and animal models to patients. Also, suggestions for future research objectives and therapeutical implications are discussed.

A time-domain approach for the identification of atrial fibrillation drivers

The localization of atrial fibrillation (AF) driver sources, characterized by rapid and regular electrical activity, is crucial for an effective ablation treatment. This work proposes a double-criteria approach for the identification of AF drivers based on a time-domain evaluation of atrial rate and AF organization. These two features are quantified by the measurement of atrial cycle length (ACL) and wave-similarity (WS). Based on ACL/WS formalism, AF drivers can be operatively defined as sites displaying electrical activity with high-rate and high-similarity (HR AND HS). The capability of ACL/WS analysis to identify AF driver sites and distinguish them from non-critical areas is shown in representative examples. The double-criteria evaluation for the identification of AF drivers, provided by our time-domain approach, might open new perspectives for the development of electrogram-guided ablation strategies in the single patient.

Fibrillatory conduction in the atrial free walls of goats in persistent and permanent atrial fibrillation

BACKGROUND

Over a time course of months, the stability of atrial fibrillation (AF) gradually increases and the efficacy of pharmacological cardioversion declines both in humans and in animal models. Changes in fibrillatory conduction over this period largely are unexplored.

METHODS AND RESULT

Goats were instrumented with an atrial endocardial pacemaker lead and a burst pacemaker. AF was maintained for 3 weeks (short-term AF [ST], n = 10) or 6 months (long-term AF [LT], n = 7). AF could be cardioverted pharmacologically at the early time point (persistent AF), but not at the later time point (permanent AF). At follow-up, a high-resolution mapping electrode was used to record epicardial conduction patterns in the free walls of the right atrium (RA) and left atrium (LA). A new method for mapping of fibrillation waves was used to describe AF conduction patterns. Wavefronts propagated uniformly during slow pacing in both groups, although conduction velocity was significantly lower in the LT group (LA, 93 ± 14 versus 72 ± 10 cm/s; RA, 94 ± 8 versus 78 ± 8 cm/s). Median AF cycle length (AFCL) was not significantly different between the groups. However, the LT group showed highly complex activation patterns during AF, with an increased number of simultaneously propagating waves (LT group RA, 8.4 ± 3.0 waves/AFCL; LA, 12.8 ± 2.4 waves/AFCL; versus ST group RA, 4.3 ± 2.2 waves/AFCL; LA, 4.5 ± 2.5 waves/AFCL). Fibrillation waves in the LT group showed pronounced dissociation with large activation time differences. The incidence of waves newly appearing within the recording area also was increased in both atria. These alterations in conduction were accompanied by myocyte hypertrophy and increased endomysial fibrosis.

CONCLUSIONS

Long-term AF in goats leads to dissociated conduction in the atrial free walls that may contribute to increased AF stability.

A novel approach to propagation pattern analysis in intracardiac atrial fibrillation signals

The purpose of this study is to investigate propagation patterns in intracardiac signals recorded during atrial fibrillation (AF) using an approach based on partial directed coherence (PDC), which evaluates directional coupling between multiple signals in the frequency domain. The PDC is evaluated at the dominant frequency of AF signals and tested for significance using a surrogate data procedure specifically designed to assess causality. For significantly coupled sites, the approach allows also to estimate the delay in propagation. The methods potential is illustrated with two simulation scenarios based on a detailed ionic model of the human atrial myocyte as well as with real data recordings, selected to present typical propagation mechanisms and recording situations in atrial tachyarrhythmias. In both simulation scenarios the significant PDCs correctly reflect the direction of coupling and thus the propagation between all recording sites. In the real data recordings, clear propagation patterns are identified which agree with previous clinical observations. Thus, the results illustrate the ability of the novel approach to identify propagation patterns from intracardiac signals during AF, which can provide important information about the underlying AF mechanisms, potentially improving the planning and outcome of arrhythmia ablation.

Comparison of several classifiers to evaluate endocardial electrograms fractionation in human

Complex fractionated atrial electrograms (CFAEs) may represent the electrophysiological substrate for atrial fibrillation (AF). Progress in signal processing algorithms to identify CFAEs sites is crucial for the development of AF ablation strategies. A novel algorithm for automated description of atrial electrograms (A-EGMs) fractionation based on wavelet transform and several statistical pattern recognition methods was proposed and new methodology of A-EGM processing was designed and tested. The algorithms for A-EGM classification were developed using normal density based classifiers, linear and high degree polynomial classifiers, nearest mean scaled classifiers, nonlinear classifiers, neural networks and j48. All classifiers were compared and tested using a representative set of 1.5 s A-EGMs (n = 68) ranked by 3 independent experts 100% coincidentialy into 4 classes of fractionation: 1 - organized atrial activity; 2 - mild; 3 - intermediate; 4 - high degree of fractionation. Feature extraction and well performing classification algorithms tested here showed maximal error of 15% and mean classification error across all implemented classifiers 9%, and the best mean classification error 5.9% (nearest mean classifier), and classification error of highly fractionated A-EGMs of approximately 9%.

Cardima Surgical Ablation System: a novel tool for cardiac ablation in the treatment of atrial fibrillation

Atrial fibrillation is a pervasive and difficult heart rhythm problem for more than 3 million Americans. Patients are plagued by myriad symptoms and are exposed to the risk of stroke. Attempts to restore normal rhythm with drug therapy have been largely unsuccessful and the complications associated with long-term anticoagulation to reduce stroke risk are appreciable. Much interest has therefore developed in nonpharmacological treatments, such as ablation. At present, the optimal ablation device and technique have yet to be found. The Cardima Surgical Ablation System is a newly developed apparatus delivering radiofrequency energy to the outside of the beating heart within a shielded, lighted, irrigated, suction sheath. It advances the field of surgical ablation by addressing many of the shortcomings of older ablating devices, such as target fixation, controlled energy delivery, prevention of collateral tissue damage and device conformability. In this publication we present the specific advantages and disadvantages of the system, discuss its possible role in atrial fibrillation treatment and compare its characteristics with other currently available devices.

A new approach to automated assessment of fractionation of endocardial electrograms during atrial fibrillation

Complex fractionated atrial electrograms (CFAEs) may represent the electrophysiological substrate for atrial fibrillation (AF). Progress in signal processing algorithms to identify sites of CFAEs is crucial for the development of AF ablation strategies. A novel algorithm for automated description of fractionation of atrial electrograms (A-EGMs) based on the wavelet transform has been proposed. The algorithm was developed and validated using a representative set of 1.5 s A-EGM (n = 113) ranked by three experts into four categories: 1-organized atrial activity; 2-mild; 3-intermediate; 4-high degree of fractionation. A tight relationship between a fractionation index and expert classification of A-EGMs (Spearman correlation rho = 0.87) was documented with a sensitivity of 82% and specificity of 90% for the identification of highly fractionated A-EGMs. This operator-independent description of A-EGM complexity may be easily incorporated into mapping systems to facilitate CFAE identification and to guide AF substrate ablation.

An automatic system for the analysis and classification of human atrial fibrillation patterns from intracardiac electrograms

This paper presents an automatic system for the analysis and classification of atrial fibrillation (AF) patterns from bipolar intracardiac signals. The system is made up of: 1) a feature-extraction module that defines and extracts a set of measures potentially useful for characterizing AF types on the basis of their degree of organization; 2) a feature-selection module (based on the Jeffries-Matusita distance and a branch and bound search algorithm) identifying the best subset of features for discriminating different AF types; and 3) a support vector machine technique-based classification module that automatically discriminates the AF types according to the Wells' criteria. The automatic system was applied on 100 intracardiac AF signal strips and on a selection of 11 representative features, demonstrating: a) the possibility to properly identify the most significant features for the discrimination of AF types; b) higher accuracy (97.7% using the seven most informative features) than the traditional maximum likelihood classifier; and c) effectiveness in AF classification also with few training samples (accuracy = 88.3% with only five training signals). Finally, the system identifies a combination of indices characterizing changes of morphology of atrial activation waves and perturbation of the isoelectric line as the most effective in separating the AF types.

Spatial characteristics of atrial fibrillation electrocardiograms

BACKGROUND

The present study investigates spatial properties of atrial fibrillation (AF) by analyzing vectorcardiogram loops synthesized from 12-lead electrocardiograms (ECGs).

METHODS

After atrial signal extraction, spatial properties are characterized through analysis of successive, fixed-length signal segments and expressed in loop orientation, that is, azimuth and elevation, as well as in loop morphology, that is, planarity and planar geometry. It is hypothesized that more organized AF, expressed by a lower AF frequency, is associated with decreased variability in loop morphology. Atrial fibrillation frequency is determined using spectral analysis.

RESULTS

Twenty-six patients with chronic AF were analyzed using 60-second ECG recordings. Loop orientation was similar when determined from either entire 60- or 1-second segments. For 1-second segments, the correlation between AF frequency and the parameters planarity and planar geometry were 0.608 (P < .001) and 0.543 (P < .005), respectively.

CONCLUSIONS

Quantification of AF organization based on AF frequency and spatial characteristics from the ECG is possible. The results suggested a relatively weak coupling between loop morphology and AF frequency when determined from the surface ECG.

Technical Considerations for Dominant Frequency Analysis

INTRODUCTION

Dominant frequency (DF) analysis of atrial electrograms has been used to characterize atrial fibrillation (AF). The aim of this study was to explore technical issues that may affect the estimation of local activation rate during AF using DF analysis.

METHODS AND RESULTS

Epicardial atrial electrograms recorded during AF from 10 dogs were used to evaluate the effects of unipolar versus bipolar recordings, bipolar electrode spacing, postrecording processing, far field ventricular depolarizations, ventricular template subtraction, and signal duration on DF analysis. Simulated electrograms were used to evaluate the effect of far field ventricular depolarizations and signal-to-noise ratio. DFs were compared with activation rates obtained by manual marking and the reproducibility of the DFs was evaluated. Bipolar electrograms were found to be preferable to unipolar electrograms. Preprocessing was a necessary step for bipolar signals, but also aided analysis of unipolar recordings. Ventricular far field depolarizations significantly affected DFs. Ventricular template subtraction helped DF analysis in signals with both minimal and significant ventricular components. A recording duration above 2 seconds was required for reliable DF measurements. Signal-to-noise ratios below 13 dB could also affect DF, particularly for signals with significant amplitude and frequency variation.

CONCLUSIONS

Various factors affect DF analysis. Proper interpretation of DF analysis requires careful evaluation of the AF signals and robust processing techniques.

Evaluating fluctuations in human atrial fibrillatory cycle length using monophasic action potentials

OBJECTIVE

To study fluctuations in intracardiac atrial fibrillation (AF) cycle length (CL).

BACKGROUND

Sites of short AF CL may be good ablation targets, and cycle lengthening predicts ablation success. However, the optimum method for measuring AF CL, and its stability, are unclear. We hypothesized that autocorrelation better estimates AF CL than spectral dominant frequency (DF), which is susceptible to double counting, using monophasic action potentials (MAPs) to separate atrial activation from artifact.

METHODS

In 28 patients with paroxysmal or persistent AF, we analyzed 49 AF epochs using MAPs at the high (HRA) and low (LRA) right atrium. We estimated AF CL over 2 seconds, 10 seconds, and 2 minutes using spectral DF and autocorrelation in MAPs and filtered bipoles.

RESULTS

In the HRA, manually measured CL was 167 +/- 25 ms. Spectral DF poorly estimated AF CL in bipolar signals (R = 0.31; P = NS), due to double counting, but accurately estimated MAP CL (R = 0.73, P < 0.001). Autocorrelation estimated MAP (R = 0.92; P < 0.001) and bipolar (R = 0.83; P < 0.001) CL, with lower errors than spectral DF (P < 0.0001). Over time, changes in DF consistently preceded reciprocal changes in organization (P < 0.001). Finally, excluding inaccurate spectra, DF and AF organization differed between HRA and LRA over 2 seconds, but correlated over 10 seconds and 2 minutes (P < 0.05).

CONCLUSIONS

AF CL is better estimated by autocorrelation than spectral DF, particularly for bipoles, and stable when measured for >10 seconds. Notably, changes in AF CL preceded reciprocal changes in organization, yet changes in organization did not precede changes in AF CL. These results may help to interpret AF CL fluctuations.

Deterioration of Organization in the First Minutes of Atrial Fibrillation: A Beat-to-Beat Analysis of Cycle Length and Wave Similarity

INTRODUCTION

It has been recently suggested that many episodes of atrial fibrillation (AF) may be partially organized at the onset and thus more suitable for antitachycardia pacing therapy. Nevertheless, the time course of organization in the first minutes of AF has not been quantified yet.

METHODS AND RESULTS

Twenty episodes of paroxysmal AF were studied. Electrograms were recorded from the right atrium (RA), distal (CSd), and proximal coronary sinus (CSp). The time course of AF cycle length (AFCL) and the regularity of wave morphology (similarity index S) were beat-to-beat measured at each recording site during the first 7 minutes of AF. AFCL and S showed a decreasing trend after the onset of AF. AFCL decreased from 208 +/- 31 to 171 +/- 21 msec (P < 0.001), from 206 +/- 40 to 169 +/- 23 msec (P < 0.001) and from 190 +/- 42 to 152 +/- 18 msec (P < 0.05), respectively, in RA, CSd, and CSp. Similarly, the similarity index decreased in CSd from 0.37 +/- 0.27 to 0.12 +/- 0.09 (P < 0.01) and in RA from 0.40 +/- 0.18 to 0.17 +/- 0.16 (P < 0.001). The 80% of the decrease occurred during the first 3 minutes of the arrhythmia, while after this time both cycle length and similarity index did not change significantly anymore. Conversely, the electrical activity in CSp was highly disorganized (S = 0.05 +/- 0.03) even in the first minute of AF, and no decreasing temporal trend was observed.

CONCLUSION

Higher levels of organization and longer fibrillation intervals exist at the onset of AF. The degree of organization of the electrical activity decays within less than 3 minutes. Since antitachycardia pacing success rate increases with high levels of organization, these results suggest an early delivery of pacing treatment.

Wave similarity of human ventricular fibrillation from bipolar electrograms

AIMS

The aim of this report was to review existing techniques for assessment of directionality in fibrillation and to describe the concept of wave similarity analysis in human VF.

METHODS

We applied a technique called wave similarity analysis to bipolar electrograms to study directionality during various rhythms (sinus rhythm, ventricular tachycardia and ventricular fibrillation) in humans. This technique uses the barycentre to determine the activation time and a similarity index is calculated using a technique described previously for AF studies.

RESULTS

We show here that using the wave similarity concept it is possible to recognize myocardial regions that are activated from multiple directions and differentiate those areas from regions that are activated by wave fronts in similar direction or at the exact mirror angle in ventricular fibrillation.

CONCLUSIONS

Wave similarity analysis provides a tool for assessing directional organization in human VF. This analysis of directional organization may have implications for the study of mechanisms of VF in the clinical arena.