Dominant frequency and organization index maps in a realistic three-dimensional computational model of atrial fibrillation

Surface electrocardiogram f wave analysis in patients with atrial fibrillation undergoing thoracoscopic epicardial ablation

OBJECTIVES

To investigate the predictive values of surface electrocardiogram-derived parameters in patients with atrial fibrillation who underwent thoracoscopic epicardial ablation.

METHODS

The present study included 102 patients with atrial fibrillation who underwent thoracoscopic epicardial ablation and whose baseline 12-lead electrocardiograms were available. Frequency domain analysis was performed to calculate the electrocardiogram-derived parameters. Cox proportional hazards regression was used to identify predictive risk factors for postoperative recurrence.

RESULTS

At 36-month interval, the overall rate of freedom from atrial tachyarrhythmia without antiarrhythmic drugs was 58.5%. The results of the univariable and multivariable analyses showed that larger left atrial diameter (hazard ratio: 1.074, 95% confidence interval: 1.021-1.130, P = 0.006) was an independent risk factor for atrial fibrillation recurrence, while higher fibrillatory wave amplitude was a protective factor (hazard ratio: 0.292, 95% confidence interval: 0.157-0.542, P < 0.001). The associations were clarified by the restricted cubic splines. The dominant frequency and organization index were not identified as statistically significant parameters.

CONCLUSIONS

The fibrillatory wave amplitude has the highest predictive value for atrial fibrillation recurrence in electrocardiogram-derived parameters. Together with left atrial diameter, it may help identify patients in whom thoracoscopic ablation is likely to be effective.

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.

Recurrence quantification analysis for fine-scale characterisation of arrhythmic patterns in cardiac tissue

This paper uses recurrence quantification analysis (RQA) combined with entropy measures and organization indices to characterize arrhythmic patterns and dynamics in computer simulations of cardiac tissue. We performed different simulations of cardiac tissues of sizes comparable to the human heart atrium. In these simulations, we observed four classic arrhythmic patterns: a spiral wave anchored to a highly fibrotic region resulting in sustained re-entry, a meandering spiral wave, fibrillation, and a spiral wave anchored to a scar region that breaks up into wavelets away from the main rotor. A detailed analysis revealed that, within the same simulation, maps of RQA metrics could differentiate regions with regular AP propagation from ones with chaotic activity. In particular, the combination of two RQA metrics, the length of the longest diagonal string of recurrence points and the mean length of diagonal lines, was able to identify the location of rotor tips, which are the active elements that maintain spiral waves and fibrillation. By proposing low-dimensional models based on the mean value and spatial correlation of metrics calculated from membrane potential time series, we identify RQA-based metrics that successfully separate the four different types of cardiac arrhythmia into distinct regions of the feature space, and thus might be used for automatic classification, in particular distinguishing between fibrillation driven by self-sustaining chaos and that created by a persistent rotor and wavebreak. We also discuss the practical applicability of such an approach.

Simultaneous Whole-Chamber Non-contact Mapping of Highest Dominant Frequency Sites During Persistent Atrial Fibrillation: A Prospective Ablation Study

Purpose

Sites of highest dominant frequency (HDF) are implicated by many proposed mechanisms underlying persistent atrial fibrillation (persAF). We hypothesized that prospectively identifying and ablating dynamic left atrial HDF sites would favorably impact the electrophysiological substrate of persAF. We aim to assess the feasibility of prospectively identifying HDF sites by global simultaneous left atrial mapping.

Methods

PersAF patients with no prior ablation history underwent global simultaneous left atrial non-contact mapping. 30 s of electrograms recorded during AF were exported into a bespoke MATLAB interface to identify HDF regions, which were then targeted for ablation, prior to pulmonary vein isolation. Following ablation of each region, change in AF cycle length (AFCL) was documented (≥ 10 ms considered significant). Baseline isopotential maps of ablated regions were retrospectively analyzed looking for rotors and focal activation or extinction events.

Results

A total of 51 HDF regions were identified and ablated in 10 patients (median DF 5.8Hz, range 4.4-7.1Hz). An increase in AFCL of was seen in 20 of the 51 regions (39%), including AF termination in 4 patients. 5 out of 10 patients (including the 4 patients where AF termination occurred with HDF-guided ablation) were free from AF recurrence at 1 year. The proportion of HDF occurrences in an ablated region was not associated with change in AFCL (τ = 0.11, p = 0.24). Regions where AFCL decreased by 10 ms or more (i.e., AF disorganization) after ablation also showed lowest baseline spectral organization (p < 0.033 for any comparison). Considering all ablated regions, the average proportion of HDF events which were also HRI events was 8.0 ± 13%. Focal activations predominated (537/1253 events) in the ablated regions on isopotential maps, were modestly associated with the proportion of HDF occurrences represented by the ablated region (Kendall's τ = 0.40, p < 0.0001), and very strongly associated with focal extinction events (τ = 0.79, p < 0.0001). Rotors were rare (4/1253 events).

Conclusion

Targeting dynamic HDF sites is feasible and can be efficacious, but lacks specificity in identifying relevant human persAF substrate. Spectral organization may have an adjunctive role in preventing unnecessary substrate ablation. Dynamic HDF sites are not associated with observable rotational activity on isopotential mapping, but epi-endocardial breakthroughs could be contributory.

A Review on Atrial Fibrillation (Computer Simulation and Clinical Perspectives)

Atrial fibrillation (AF), a heart condition, has been a well-researched topic for the past few decades. This multidisciplinary field of study deals with signal processing, finite element analysis, mathematical modeling, optimization, and clinical procedure. This article is focused on a comprehensive review of journal articles published in the field of AF. Topics from the age-old fundamental concepts to specialized modern techniques involved in today’s AF research are discussed. It was found that a lot of research articles have already been published in modeling and simulation of AF. In comparison to that, the diagnosis and post-operative procedures for AF patients have not yet been totally understood or explored by the researchers. The simulation and modeling of AF have been investigated by many researchers in this field. Cellular model, tissue model, and geometric model among others have been used to simulate AF. Due to a very complex nature, the causes of AF have not been fully perceived to date, but the simulated results are validated with real-life patient data. Many algorithms have been proposed to detect the source of AF in human atria. There are many ablation strategies for AF patients, but the search for more efficient ablation strategies is still going on. AF management for patients with different stages of AF has been discussed in the literature as well but is somehow limited mostly to the patients with persistent AF. The authors hope that this study helps to find existing research gaps in the analysis and the diagnosis of AF.

Drivers in AF colocate to sites of electrogram organization and rapidity: Potential synergy between spectral analysis and STAR mapping approaches in prioritizing drivers for ablation

INTRODUCTION

Stochastic trajectory analysis of ranked signals (STAR) mapping has recently been used to ablate persistent atrial fibrillation (AF) with high rates of AF termination and long-term freedom from AF in small, single-arm studies. We hypothesized that rapidity and organization markers would correlate with early sites of activation (ESA).

METHODS

Patients undergoing persistent AF ablation as part of the STAR mapping study were included. Five-minute unipolar basket recordings used to create STAR maps were used to determine the minimum-cycle length (Min-CL) and CL variability (CLV) at each electrode to identify the site of the fastest Min-CL and lowest CLV across the left atrium (LA). The location of ESA targeted with ablation was compared with these sites. Dominant frequency was assessed at ESA and compared with that of neighboring electrodes to assess for regional gradients.

RESULTS

Thirty-two patients were included with 83 ESA ablated, with an ablation response at 73 sites (24 AF termination and 49 CL slowing ≥30 ms). Out of these, 54 (74.0%) and 56 (76.7%) colocated to sites of fastest Min-CL and lowest CLV, respectively. Regional CL and frequency gradients were demonstrable at majority of ESA. ESA colocating to sites of fastest Min-CL and lowest CLV were more likely to terminate AF with ablation (odds ratio, 34 and 29, respectively, P = .02). These showed a moderate sensitivity (74.0% Min-CL and 75.3% CLV) and specificity (66.7% Min-CL and 76.9% CLV) in predicting ESA with an ablation response.

CONCLUSIONS

ESA correlate with rapidity and organization markers. Further work is needed to clarify any role for spectral analysis in prioritizing driver ablation.

Characterization of drivers maintaining atrial fibrillation: Correlation with markers of rapidity and organization on spectral analysis

BACKGROUND

Better characterization of drivers in atrial fibrillation (AF) may facilitate their identification.

OBJECTIVE

The purpose of this study was to demonstrate that certain driver characteristics are associated with greater mechanistic importance in maintaining AF.

METHODS

Persistent AF was mapped in patients using the CARTOFINDER system with a 64-pole basket catheter to identify and ablate drivers with rotational or focal activity after pulmonary vein isolation. An ablation response was defined as cycle length (CL) slowing ≥30 ms or AF termination. Driver sites with an ablation response were correlated to sites of fastest CL, highest dominant frequency (DF), and greatest organization (lowest cycle length variability [CLV] and highest regularity index [RI]). Parameters predicting AF termination with driver ablation were evaluated.

RESULTS

All 29 patients had ≥1 driver identified. Forty-four potential drivers were identified. The predefined ablation response occurred with 39 drivers (89%): 23 rotational and 16 focal. During a 30-second recording, each driver occurred 8.7 ± 5.4 times and completed 3.1 ± 0.9 consecutive repetitions per occurrence. Driver sites correlated best with markers of organization, corresponding to the site of lowest CLV (29/39 [74%]) and highest RI (26/39 [67%]). Correlation with sites of fastest CL and highest DF was poor (17/39 and 15/39, respectively) and depended on driver temporal stability. Greater temporal stability (3.4 ± 0.9 vs 2.7 ± 0.6; P = .001) and driver correlation with sites of lowest CLV and highest RI (both P <.001) predicted AF termination with ablation.

CONCLUSION

Intermittent focal or rotational drivers were identified in all patients. Drivers consistently correlated to organization markers. Greater temporal stability and organization predicted AF termination with driver ablation.

Three-dimensional cardiac computational modelling: methods, features and applications

The combination of computational models and biophysical simulations can help to interpret an array of experimental data and contribute to the understanding, diagnosis and treatment of complex diseases such as cardiac arrhythmias. For this reason, three-dimensional (3D) cardiac computational modelling is currently a rising field of research. The advance of medical imaging technology over the last decades has allowed the evolution from generic to patient-specific 3D cardiac models that faithfully represent the anatomy and different cardiac features of a given alive subject. Here we analyse sixty representative 3D cardiac computational models developed and published during the last fifty years, describing their information sources, features, development methods and online availability. This paper also reviews the necessary components to build a 3D computational model of the heart aimed at biophysical simulation, paying especial attention to cardiac electrophysiology (EP), and the existing approaches to incorporate those components. We assess the challenges associated to the different steps of the building process, from the processing of raw clinical or biological data to the final application, including image segmentation, inclusion of substructures and meshing among others. We briefly outline the personalisation approaches that are currently available in 3D cardiac computational modelling. Finally, we present examples of several specific applications, mainly related to cardiac EP simulation and model-based image analysis, showing the potential usefulness of 3D cardiac computational modelling into clinical environments as a tool to aid in the prevention, diagnosis and treatment of cardiac diseases.

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.

Mathematical approaches to understanding and imaging atrial fibrillation: significance for mechanisms and management

Atrial fibrillation (AF) is the most common sustained arrhythmia in humans. The mechanisms that govern AF initiation and persistence are highly complex, of dynamic nature, and involve interactions across multiple temporal and spatial scales in the atria. This article aims to review the mathematical modeling and computer simulation approaches to understanding AF mechanisms and aiding in its management. Various atrial modeling approaches are presented, with descriptions of the methodological basis and advancements in both lower-dimensional and realistic geometry models. A review of the most significant mechanistic insights made by atrial simulations is provided. The article showcases the contributions that atrial modeling and simulation have made not only to our understanding of the pathophysiology of atrial arrhythmias, but also to the development of AF management approaches. A summary of the future developments envisioned for the field of atrial simulation and modeling is also presented. The review contends that computational models of the atria assembled with data from clinical imaging modalities that incorporate electrophysiological and structural remodeling could become a first line of screening for new AF therapies and approaches, new diagnostic developments, and new methods for arrhythmia prevention.