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Background: Sequentially mapped complex fractionated atrial electrograms (CFAE) and dominant frequency (DF) sites have been targeted during catheter ablation for atrial fibrillation (AF). However, these strategies have yielded variable success and have not been shown to correlate consistently with AF dynamics. Here, we evaluated whether the spatiotemporal stability of CFAE and DF may be a better marker of AF sustenance and termination. Methods: Eighteen sheep with 12 weeks of “one-kidney, one-clip” hypertension underwent open-chest studies. A total of 42 self-terminating (28–100 s) and 6 sustained (>15 min) AF episodes were mapped using a custom epicardial plaque and analyzed in 4-s epochs for CFAE, using the NavX CFE-m algorithm, and DF, using a Fast Fourier Transform. The spatiotemporal stability index (STSI) was calculated using the intraclass correlation coefficient of consecutive AF epochs. Results: A total of 67,733 AF epochs were analyzed. During AF initiation, mean CFE-m and the STSI of CFE-m/DF were similar between sustained and self-terminating episodes, although median DF was higher in sustained AF (p=0.001). During sustained AF, the STSI of CFE-m increased significantly (p=0.02), whereas mean CFE-m (p=0.5), median DF (p=0.07), and the STSI of DF remained unchanged (p=0.5). Prior to AF termination, the STSI of CFE-m was significantly lower (p

Ablation strategies targeting areas of complex fractionated atrial electrograms are not successful for treatment of atrial fibrillation. Fractionation of atrial electrograms may have multiple causes of both pathologic and nonpathologic origin. In order to gain insight into the definitions used for determining areas of fractionation, a literature search was performed using a systematic approach. A PubMed search for studies describing fractionation during human atrial electrophysiologic measurements resulted in 348 articles that were screened for new definitions of fractionation. The 24 studies remaining after screening described 11 different visual definitions for fractionation, 3 automated complex fractionated atrial electrogram detection programs, and 7 new parameters for measuring fractionation. Five different definitions for continuous electrical activity were presented. Electrode properties were often not described, and endocardial bipolar recordings in recent studies used electrode diameters ranging from 1 to 8 mm with interelectrode distance of 2-5 mm. In summary, no uniform definition or recording method is used for measuring fractionation of cardiac atrial electrograms. The different electrophysiologic causes of fractionation and the influence of recording device properties on fractionation complicate identification of true pathologic inhomogeneous conduction. The first step in discrimination between origins of fractionation may be accomplished by relating electrogram morphology to spatial patterns of activation. Before revisiting ablation of areas with fractionated electrograms, we need to determine the correct method for identifying pathologic fractionation. [ABSTRACT FROM AUTHOR]

Background Sequentially mapped complex fractionated atrial electrograms (CFAE) and dominant frequency (DF) sites have been targeted during catheter ablation for atrial fibrillation (AF). However, these strategies have yielded variable success and have not been shown to correlate consistently with AF dynamics. Here, we evaluated whether the spatiotemporal stability of CFAE and DF may be a better marker of AF sustenance and termination. Methods Eighteen sheep with 12 weeks of “one-kidney, one-clip” hypertension underwent open-chest studies. A total of 42 self-terminating (28–100 s) and 6 sustained (>15 min) AF episodes were mapped using a custom epicardial plaque and analyzed in 4-s epochs for CFAE, using the NavX CFE-m algorithm, and DF, using a Fast Fourier Transform. The spatiotemporal stability index (STSI) was calculated using the intraclass correlation coefficient of consecutive AF epochs. Results A total of 67,733 AF epochs were analyzed. During AF initiation, mean CFE-m and the STSI of CFE-m/DF were similar between sustained and self-terminating episodes, although median DF was higher in sustained AF ( p =0.001). During sustained AF, the STSI of CFE-m increased significantly ( p =0.02), whereas mean CFE-m ( p =0.5), median DF ( p =0.07), and the STSI of DF remained unchanged ( p =0.5). Prior to AF termination, the STSI of CFE-m was significantly lower ( p <0.001), with a physiologically non-significant decrease in median DF (−0.3 Hz, p =0.006) and no significant changes in mean CFE-m ( p =0.14) or the STSI of DF ( p =0.06). Conclusions Spatiotemporal stabilization of CFAE favors AF sustenance and its destabilization heralds AF termination. The STSI of CFE-m is more representative of AF dynamics than are the STSI of DF, sequential mean CFE-m, or median DF. [ABSTRACT FROM AUTHOR]

Ablation of persistent atrial fibrillation (persAF) targeting complex fractionated atrial electrograms (CFAEs) detected by automated algorithms has produced conflicting outcomes in previous electrophysiological studies. We hypothesize that the differences in these algorithms could lead to discordant CFAE classifications by the available mapping systems, giving rise to potential disparities in CFAE-guided ablation. This study reports the results of a head-to-head comparison of CFAE detection performed by NavX (St. Jude Medical) versus CARTO (Biosense Webster) on the same bipolar electrogram data (797 electrograms) from 18 persAF patients. We propose revised thresholds for both primary and complementary indices to minimize the differences in CFAE classification performed by either system. Using the default thresholds [NavX: CFE-Mean ≤ 120 ms; CARTO: ICL ≥ 7], NavX classified 70 % of the electrograms as CFAEs, while CARTO detected 36 % (Cohen's kappa κ ≈ 0.3, P < 0.0001). Using revised thresholds found using receiver operating characteristic curves [NavX: CFE-Mean ≤ 84 ms, CFE-SD ≤ 47 ms; CARTO: ICL ≥ 4, ACI ≤ 82 ms, SCI ≤ 58 ms], NavX classified 45 %, while CARTO detected 42 % (κ ≈ 0.5, P < 0.0001). Our results show that CFAE target identification is dependent on the system and thresholds used by the electrophysiological study. The thresholds found in this work counterbalance the differences in automated CFAE classification performed by each system. This could facilitate comparisons of CFAE ablation outcomes guided by either NavX or CARTO in future works. [ABSTRACT FROM AUTHOR]

Background The pathophysiological relevance of complex fractionated atrial electrograms (CFAE) in atrial fibrillation (AF) remains poorly understood. Objective The aim of this study was to comprehensively investigate how bipolar CFAE correlates with unipolar electrogram fractionation and the underlying electrophysiological substrate of AF. Methods Ten-second unipolar AF electrograms were recorded using a high-density electrode from the left atrium of 20 patients with AF (10 with persistent AF and 10 with paroxysmal AF) undergoing cardiac surgery. Semiautomated bipolar CFAE algorithms: complex fractionated electrogram-mean, interval confidence interval, continuous electrical activity, average complex interval, and shortest complex interval were evaluated against AF substrate complexity measures following fibrillation wave reconstruction derived from local unipolar activation time. The effect of interelectrode spacing and electrode orientation on bipolar CFAE was also examined. Results All 5 semiautomated bipolar CFAE algorithms showed poor correlation with each other and AF substrate complexity measures (conduction velocity, number of waves or breakthroughs per AF cycle, and electrical dissociation). Bipolar CFAE also correlated poorly with fractionation index derived from unipolar electrograms. Increased interelectrode spacing resulted in an increase in bipolar CFAE detected except for the interval confidence interval algorithm. CFAE appears unaffected by bipolar electrode orientation (vertical vs horizontal). By contrast, unipolar fractionation index correlated well with AF substrate complexity measures and can be regarded as a marker for conduction block. Conclusion The lack of pathophysiological relevance of bipolar CFAE analysis may in part contribute to the divergent and limited success rates of catheter ablation strategies targeting CFAE. [ABSTRACT FROM AUTHOR]

Aims: In patients with atrial fibrillation (AF), complex fractionated atrial electrograms (CFAE) have been shown to be located at the anatomic sites of ganglionated plexi (GP). This study aimed at investigating the contribution of parasympathetic activity to formation of CFAE. Methods: Twelve patients (aged 55 ± 11 years, five females) with paroxysmal AF were studied. Following electroanatomical mapping of the left atrium, GP were identified by high frequency stimulation (HFS), 12-24 V in a conscious state, and assessment of CFAE during AF was performed with the use of dedicated software. Fractionated activity was measured at each GP site by interval confidence levels (ICL) and average complex interval (ACI), and was compared to measurements obtained 1 min after intravenous administration of 1 mg of atropine. Results: In total, 30 out of 48 GP could be identified by HFS. CFAE were detected at all sites where GP were found. ICL was significantly lower after atropine administration only at ARGP (5.4 ± 2.7 vs. 2.8 ± 2.1, p = 0.028), whereas no significant difference was detected pre- or post-atropine at any GP in ACI. Considering all fractionation values from the four GP, a statistically significant reduction of the ICL score was observed (4.6 ± 3.4 vs. 5.8 ± 2.9, p = 0.03) after atropine administration, whereas no significant differences were observed in the ACI score (144.5 ± 24.0 post-atropine vs. 146.7 ± 27.7 pre-atropine, p = 0.620). The average RR interval became significantly shorter post-atropine (575.8 ± 139.1 vs. 637.2 ± 158.7, p = 0.004). Conclusion: Our data do not support the hypothesis that parasympathetic activity plays the dominant role in electrogram fractionation. [ABSTRACT FROM AUTHOR]

Background: Complex fractionated atrial electrograms are used as potential targets for catheter ablation therapy of atrial fibrillation. Although fibrosis has been associated with the presence of fractionated electrograms, characterizing the substrate through the inspection of electrograms is challenging. Objective: This study sought to determine how progression of microfibrosis and slow conduction affect electrogram morphology. Methods: A microstructure computer model representing a monolayer of cardiac cells was developed. Slow conduction was induced by: (1) sodium channel blockade, (2) uniform reduction in cell-to-cell coupling, and (3) microfibrosis incorporated as a set of collagenous septa disconnecting transverse coupling. The density (0 to 30%) and length (30 to 945 μm) of these collagenous septa were varied. Unipolar and bipolar electrograms were computed during paced rhythm for a set of electrodes with different tip sizes. Results: The analysis of unipolar electrograms with realistic temporal and spatial filtering showed that increasing the density and length of collagenous septa decreased conduction velocity by up to 75% and increased the amount of fractionation (up to 14 deflections) and asymmetry of the electrograms. In contrast, slow conduction induced by sodium channel blockade or uniformly reduced coupling did not result in electrogram fractionation. When a larger electrode was used, electrogram amplitude was smaller and fractionation increased in a substrate-dependent way. Conclusion: Microscale obstacles cause significant changes to electrogram waveforms. Conduction velocity and electrogram amplitude and degree of fractionation can be used to discriminate the nature of the substrate and characteristics of fibrosis, giving rise to slow conduction. [Copyright &y& Elsevier]

Aims: To investigate the relationship of complex fractionated atrial electrograms (CFAEs) with the activity of the ganglionated plexi (GP) in the cardiac autonomic nervous system. [ABSTRACT FROM PUBLISHER]

The aim of this work is twofold. First we focus on the complex phenomenon of electrogram fractionation, due to the presence of discontinuities in the conduction properties of the cardiac tissue in a bidomain model. Numerical simulations of paced activation may help to understand the role of the membrane ionic currents and of the changes in cellular coupling in the formation of conduction blocks and fractionation of the electrogram waveform. In particular, we show that fractionation is independent of I Na alterations and that it can be described by the bidomain model of cardiac tissue. Moreover, some deflections in fractionated electrograms may give nonlocal information about the shape of damaged areas, also revealing the presence of inhomogeneities in the intracellular conductivity of the medium at a distance. The second point of interest is the analysis of the effects of space-time discretization on numerical results, especially during slow conduction in damaged cardiac tissue. Indeed, large discretization steps can induce numerical artifacts such as slowing down of conduction velocity, alteration in extracellular and transmembrane potential waveforms or conduction blocks, which are not predicted by the continuous bidomain model. Several possible numerical and physiological explanations of these effects are given. Essentially, the discrete system obtained at the end of the approximation process may be interpreted as a discrete model of the cardiac tissue made up of isopotential cells where the effective intracellular conductivity tensor depends on the space discretization steps; the increase of these steps results in an increase of the effective intracellular resistance and can induce conduction blocks if a certain critical value is exceeded. [ABSTRACT FROM AUTHOR]

Background: The exact pathophysiology of atrial fibrillation (AF) remains incompletely understood and treatment of AF is associated with high recurrence rates. Persistence of AF is rooted in the presence of electropathology, defined as complex electrical conduction disorders caused by structural damage of atrial tissue. The atrial fibrillation fingerprinting (AFFIP) study aims to characterize electropathology, enabling development of a novel diagnostic instrument to predict AF onset and early progression., Hypotheses: History of AF, development of post-operative AF, age, gender, underlying heart disease, and other clinical characteristics impact the degree of electropathology., Methods: This study is a prospective observational study with a planned duration of 48 months. Three study groups are defined: (1) patients with (longstanding) persistent AF, (2) patients with paroxysmal AF, and (3) patients without a history of AF, all undergoing open-chest cardiac surgery. Intra-operative high-resolution epicardial mapping is performed to identify the patient-specific electrical profile, whereas the patient-specific biological profile is assessed by evaluating proteostasis markers in blood samples and atrial appendage tissue samples. Post-operative continuous rhythm monitoring is performed for detection of early post-operative AF. Late post-operative AF (during 5-year follow-up) is documented by either electrocardiogram or 24-hour Holter registration., Results: The required sample size for this study is estimated at 447 patients. Up till now, 105 patients were included, of whom 36 have a history of AF., Conclusion: The AFFIP study will elucidate whether electrophysiological and structural characteristics represent a novel diagnostic tool, the AF fingerprint, to predict onset and early progression of AF in cardiac surgery patients., (© 2020 The Authors. Clinical Cardiology published by Wiley Periodicals, Inc.)

Aims: Catheter ablation is an effective technique for terminating atrial arrhythmia. However, given a high atrial fibrillation (AF) recurrence rate, optimal ablation strategies have yet to be defined. Computer modelling can be a powerful aid but modelling of fibrosis, a major factor associated with AF, is an open question. Several groups have proposed methodologies based on imaging data, but no comparison to determine which methodology best corroborates clinically observed reentrant behaviour has been performed. We examined several methodologies to determine the best method for capturing fibrillation dynamics., Methods and Results: Patient late gadolinium-enhanced magnetic resonance imaging data were transferred onto a bilayer atrial computer model and used to assign fibrosis distributions. Fibrosis was modelled as conduction disturbances (lower conductivity, edge splitting, or percolation), transforming growth factor-β1 ionic channel effects, myocyte-fibroblast coupling, and combinations of the preceding. Reentry was induced through pulmonary vein ectopy and the ensuing rotor dynamics characterized. Non-invasive electrocardiographic imaging data of the patients in AF was used for comparison. Electrograms were computed and the fractionation durations measured over the surface. Edge splitting produced more phase singularities from wavebreaks than the other representations. The number of phase singularities seen with percolation was closer to the clinical values. Addition of fibroblast coupling had an organizing effect on rotor dynamics. Simple tissue conductivity changes with ionic changes localized rotors over fibrosis which was not observed with clinical data., Conclusion: The specific representation of fibrosis has a large effect on rotor dynamics and needs to be carefully considered for patient specific modelling., (Published on behalf of the European Society of Cardiology. All rights reserved. © The Author 2016. For Permissions, please email: journals.permissions@oup.com.)