Understanding and Interpreting Dominant Frequency Analysis of AF Electrograms

Long-term atrial arrhythmia characterization and treatment efficacy evaluation using non-invasive echocardiography-based electromechanical cycle length mapping: a case series

Background

Atrial fibrillation (AF) is a prevalent cardiac condition characterized by irregular heart rhythm. Conventional non-invasive diagnostic techniques, while useful, have limitations in providing comprehensive information for treatment planning. To address this gap, electromechanical cycle length mapping (ECLM), a non-invasive echocardiography-based technique, has emerged as a promising approach. Electromechanical cycle length mapping offers quantitative and spatially specific insights into atrial electromechanical activation rate mapping, thereby enhancing our understanding of arrhythmia disease progression in AF patients.

Case summary

In this case series, we present two patient cases demonstrating the potential utility of ECLM in monitoring and evaluating treatment responses in atrial arrhythmia. The 1st case involved a 61-year-old male with persistent AF who underwent multiple procedures, including direct current cardioversion (DCCV) and radiofrequency ablation. Over three different DCCV encounters, pre- and post-procedure ECLM scans were performed, and the results showed the localization and incomplete elimination of arrhythmic triggers post-DCCV, which were used as early indicators of AF recurrence. The 2nd case involved a 71-year-old male with paroxysmal AF who also underwent cardioversion and ablation procedures. Electromechanical cycle length mapping imaging demonstrated a progressive reduction and elimination of arrhythmia triggers after each encounter, resulting in long-term maintenance of sinus rhythm.

Discussion

The findings from this case series highlight the potential of ECLM as a non-invasive imaging tool for long-term monitoring and evaluating immediate and long-term treatment responses in AF patients. The integration of ECLM with standard echocardiograms holds promise in guiding clinical decisions and improving patient outcomes in managing atrial fibrillation.

Standardized 2D atrial mapping and its clinical applications

The visualization and comparison of electrophysiological information in the atrium among different patients could be facilitated by a standardized 2D atrial mapping. However, due to the complexity of the atrial anatomy, unfolding the 3D geometry into a 2D atrial mapping is challenging. In this study, we aim to develop a standardized approach to achieve a 2D atrial mapping that connects the left and right atria, while maintaining fixed positions and sizes of atrial segments across individuals. Atrial segmentation is a prerequisite for the process. Segmentation includes 19 different segments with 12 segments from the left atrium, 5 segments from the right atrium, and two segments for the atrial septum. To ensure consistent and physiologically meaningful segment connections, an automated procedure is applied to open up the atrial surfaces and project the 3D information into 2D. The corresponding 2D atrial mapping can then be utilized to visualize different electrophysiological information of a patient, such as activation time patterns or phase maps. This can in turn provide useful information for guiding catheter ablation. The proposed standardized 2D maps can also be used to compare more easily structural information like fibrosis distribution with rotor presence and location. We show several examples of visualization of different electrophysiological properties for both healthy subjects and patients affected by atrial fibrillation. These examples show that the proposed maps provide an easy way to visualize and interpret intra-subject information and perform inter-subject comparison, which may provide a reference framework for the analysis of the atrial fibrillation substrate before treatment, and during a catheter ablation procedure.

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.

Electromechanical Cycle Length Mapping for atrial arrhythmia detection and cardioversion success assessment

BACKGROUND

Direct current cardioversion (DCCV) is an established treatment to acutely convert atrial fibrillation (AF) to normal sinus rhythm. Yet, more than 70% of patients revert to AF shortly thereafter. Electromechanical Cycle Length Mapping (ECLM) is a high framerate, spectral analysis technique shown to non-invasively characterize electromechanical activation in paced canines and re-entrant flutter patients. This study assesses ECLM feasibility to map and quantify atrial arrhythmic electromechanical activation rates and inform on 1-day and 1-month DCCV response.

METHODS

Forty-five subjects (30 AF; 15 healthy sinus rhythm (SR) controls) underwent transthoracic ECLM in four standard apical 2D echocardiographic views. AF patients were imaged within 1 h pre- and post-DCCV. 3D-rendered atrial ECLM cycle length (CL) maps and spatial CL histograms were generated. CL dispersion and percentage of arrhythmic CLs≤333ms across the entire atrial myocardium were computed transmurally. ECLM results were subsequently used as indicators of DCCV success.

RESULTS

ECLM successfully confirmed the electrical atrial activation rates in 100% of healthy subjects (R2=0.96). In AF, ECLM maps localized the irregular activation rates pre-DCCV and confirmed successful post-DCCV with immediate reduction or elimination. ECLM metrics successfully distinguished DCCV 1-day and 1-month responders from non-responders, while pre-DCCV ECLM values independently predicted AF recurrence within 1-month post-DCCV.

CONCLUSIONS

ECLM can characterize electromechanical activation rates in AF, quantify their extent, and identify and predict short- and long-term AF recurrence. ELCM constitutes thus a noninvasive arrhythmia imaging modality that can aid clinicians in simultaneous AF severity quantification, prediction of AF DCCV response, and personalized treatment planning.

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

BACKGROUND

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

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.

Dynamics of Intraprocedural Dominant Frequency Identifies Ablation Outcome in Persistent Atrial Fibrillation

Background: The role of dominant frequency (DF) in tracking the efficiency of a stepwise catheter ablation (step-CA) in persistent atrial fibrillation (peAF) remains poorly studied. We hypothesized that the DF time-course during step-CA displays divergent patterns between patients in whom a step-CA successfully restores long-term sinus rhythm (SR) and those with recurrence. Methods: This study involved 40 consecutive patients who underwent a step-CA for peAF (sustained duration 19 ± 11 months). Dominant frequency was computed on electrograms recorded from the right and left atrial appendages (RAA; LAA) and the coronary sinus before and during the step-CA synchronously to the 12-lead ECG. Dominant frequency was defined as the highest peak within the power spectrum. Results: Persistent atrial fibrillation was terminated by a step-CA in 28 patients [left-terminated (LT)], whereas 12 patients remaining in AF after ablation [not left-terminated (NLT)] were cardioverted. Over a mean follow-up of 34 ± 14 months, all NLT patients had a recurrence. Among the 28 LT patients, 20 had a recurrence, while 8 remained in SR throughout follow-up. The RAA and V₁ DF had the best predictive values of the procedural failure to terminate AF (area under the curve; AUC 0.84, p < 0.05). A decision tree model including a decrease in LAA DF ≥ 6.61% during the first 20 min following pulmonary vein isolation (PVI) and a baseline RAA DF <5.6 Hz predicted long-term SR restoration with a sensitivity of 83% and a specificity of 93% (p < 0.05). Conclusion: This study found that high baseline DF values are predictive of unfavorable ablation outcomes. The reduction of the LAA DF at early ablation steps following PVI is associated with procedural AF termination and long-term SR maintenance.

Convolutional neural network for classification of eight types of arrhythmia using 2D time-frequency feature map from standard 12-lead electrocardiogram

Electrocardiograms (ECGs) are widely used for diagnosing cardiac arrhythmia based on the deformation of signal shapes due to changes in various heart diseases. However, these abnormal signs may not be observed in some 12 ECG channels, depending on the location, the heart shape, and the type of cardiac arrhythmia. Therefore, it is necessary to closely and comprehensively observe ECG records acquired from 12 channel electrodes to diagnose cardiac arrhythmias accurately. In this study, we proposed a clustering algorithm that can classify persistent cardiac arrhythmia as well as episodic cardiac arrhythmias using the standard 12-lead ECG records and the 2D CNN model using the time–frequency feature maps to classify the eight types of arrhythmias and normal sinus rhythm. The standard 12-lead ECG records were provided by China Physiological Signal Challenge 2018 and consisted of 6877 patients. The proposed algorithm showed high performance in classifying persistent cardiac arrhythmias; however, its accuracy was somewhat low in classifying episodic arrhythmias. If our proposed model is trained and verified using more clinical data, we believe it can be used as an auxiliary device for diagnosing cardiac arrhythmias.

Mapping Technologies for Catheter Ablation of Atrial Fibrillation Beyond Pulmonary Vein Isolation

Catheter ablation remains the most effective and relatively minimally invasive therapy for rhythm control in patients with AF. Ablation has consistently shown a reduction of arrhythmia-related symptoms and significant improvement in patients’ quality of life compared with medical treatment. The ablation strategy relies on a well-established anatomical approach of effective pulmonary vein isolation. Additional anatomical targets have been reported with the aim of increasing procedure success in complex substrates. However, larger ablated areas with uncertainty of targeting relevant regions for AF initiation or maintenance are not exempt from the potential risk of complications and pro-arrhythmia. Recent developments in mapping tools and computational methods for advanced signal processing during AF have reported novel strategies to identify atrial regions associated with AF maintenance. These novel tools – although mainly limited to research series – represent a significant step forward towards the understanding of complex patterns of propagation during AF and the potential achievement of patient-tailored AF ablation strategies for the near future.

Relationship between dominant frequency, organization index, and left atrial size in patients with atrial fibrillation

INTRODUCTION

Frequency domain analysis is a methodology for quantifying the organization of atrial fibrillation (AF) pattern to understand the pathophysiology of the electrical mechanism. We aimed to investigate whether the dominant frequency (DF) and organization index (OI) can indicate left atrial (LA) dilatation in patients with AF.

METHODS AND RESULTS

This observational, retrospective, single-center cohort study assessed 100 patients with persistent AF. The study population was divided into two groups based on an anterior-posterior LA dimension (LAD of 50 mm) measured by transthoracic echocardiography. The groups were one-to-one propensity score-matched. Frequency domain analysis was performed using signals at leads II and V1 on surface electrocardiogram to calculate the DF and OI. In all patients, the DF was shown to have an inverse relationship with LAD (R = -.369, p < .001 in lead II; R = -.330, p = .001 in lead V1), while the OI was directly associated with LAD (R = .234, p = .190 in lead II; R = .283, p = .004 in lead V1). However, no significant relationship between the signal amplitude and LAD was observed. Compared to patients with LAD ≤ 50 mm, those with LAD > 50 mm had a lower DF (5.057 ± 0.740 vs. 4.542 ± 0.898, p = .002) and higher OI (0.261 ± 0.104 vs. 0.322 ± 0.116, p = .007) in lead V1. These findings were consistent with those found in lead II.

CONCLUSION

Patients with persistent AF and a larger LA size had a significantly higher OI and lower DF than those with a smaller LA size. Atrial electrical properties of structural remodeling are associated with increased organization of atrial signals.

A robust wavelet-based approach for dominant frequency analysis of atrial fibrillation in body surface signals

OBJECTIVE

Atrial dominant frequency (DF) maps undergoing atrial fibrillation (AF) presented good spatial correlation with those obtained with the non-invasive body surface potential mapping (BSPM). In this study, a robust BSPM-DF calculation method based on wavelet analysis is proposed.

APPROACH

Continuous wavelet transform along 40 scales in the pseudo-frequency range of 3-30 Hz is performed in each BSPM signal using a Gaussian mother wavelet. DFs are estimated from the intervals between the peaks, representing the activation times, in the maximum energy scale. The results are compared with the traditionally widely applied Welch periodogram and the robustness was tested on different protocols: increasing levels of white Gaussian noise, artificial DF harmonics presence and reduction in the number of leads. A total of 11 AF simulations and 12 AF patients are considered in the analysis. For each patient, intracardiac electrograms were acquired in 15 locations from both atria. The accuracy of both methods was assessed by calculating the absolute errors of the highest DF _BSPM (HDF _BSPM ) with respect to the atrial HDF, either simulated or intracardially measured, and assumed correct if ≤1 Hz. The spatial distribution of the errors between torso DFs and atrial HDFs were compared with atria driving mechanism locations. Torso HDF regions, defined as portions of the maps with [Formula: see text] Hz were identified and the percentage of the torso occuping these regions was compared between methods. The robustness of both methods to white Gaussian noise, ventricular influence and harmonics, and to lower spatial resolution BSPM lead layouts was analyzed: computer AF models (567 leads vs 256 leads down to 16 leads) and patient data (67 leads vs 32 and 16 leads).

MAIN RESULTS

The proposed method allowed an improvement in non-invasive estimation of the atria HDF. For the models the median relative errors were 7.14% for the wavelet-based algorithm vs 60.00% for the Welch method; in patients, the errors were 10.03% vs 12.66%, respectively. The wavelet method outperformed the Welch approach in correct estimations of atrial HDFs in models (81.82% vs 45.45%, respectively) and patients (66.67% vs 41.67%). A low positive BSPM-DF map correlation was seen between the techniques (0.47 for models and 0.63 for patients), highlighting the overall differences in DF distributions. The wavelet-based algorithm was more robust to white Gaussian noise, residual ventricular activity and harmonics, and presented more consistent results in lead layouts with low spatial resolution.

SIGNIFICANCE

Estimation of atrial HDFs using BSPM is improved by the proposed wavelet-based algorithm, helping to increase the non-invasive diagnostic ability in AF.

Characterization of atrial arrhythmias in body surface potential mapping: A computational study

PURPOSE

Atrial tachycardia (AT), flutter (AFL) and fibrillation (AF) are very common cardiac arrhythmias and are driven by localized sources that can be ablation targets. Non-invasive body surface potential mapping (BSPM) can be useful for early diagnosis and ablation planning. We aimed to characterize and differentiate the arrhythmic mechanisms behind AT, AFL and AF from the BSPM perspective using basic features reflecting their electrophysiology.

METHODS

19 simulations of 567-lead BSPMs were used to obtain dominant frequency (DF) maps and estimate the atrial driving frequencies using the highest DF (HDF). Regions with |DF-HDF|≤1Hz were segmented and characterized (size, area); the spatial distribution of the differences |DF-atrialHDFestimate| was qualitatively analyzed. Phase singularity points (SPs) were detected on maps generated with Hilbert transform after band-pass filtering around the HDF (±1Hz). Connected SPs along time (filaments) and their histogram (heatmaps) were used for rotational activity characterization (duration, spatiotemporal stability). Results were reproduced in clinical layouts (252 to 12 leads) and with different rotations and translations of the atria within the torso, and compared with the original 567-lead outcomes using structural similarity index (SSIM) between maps, sensitivity and precision in SP detection and direct feature comparison. Random forest and least-square based algorithms were used to classify the arrhythmias and their mechanisms' location, respectively, based on the obtained features.

RESULTS

Frequency and phase analyses revealed distinct behavior between arrhythmias. AT and AFL presented uniform DF maps with low variance, while AF maps were more heterogeneous. Lower differences from the atrial HDF regions correlated with the driver location. Rotational activity was most stable in AFL, followed by AT and AF. Features were robust to lower spatial resolution layouts and modifications in the atrial geometry; DF and heatmaps presented decreasing SSIM along the layouts. The classification of the arrhythmias and their mechanisms' location achieved balanced accuracy of 72.0% and 73.9%, respectively.

CONCLUSION

Non-invasive characterization of AT, AFL and AF based on realistic models highlights intrinsic differences between the arrhythmias, enhancing the BSPM utility as an auxiliary clinical tool.

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.

Systematic differences of non-invasive dominant frequency estimation compared to invasive dominant frequency estimation in atrial fibrillation

Non-invasive analysis of atrial fibrillation (AF) using body surface mapping (BSM) has gained significant interest, with attempts at interpreting atrial spectro-temporal parameters from body surface signals. As these body surface signals could be affected by properties of the torso volume conductor, this interpretation is not always straightforward. This paper highlights the volume conductor effects and influences of the algorithm parameters for identifying the dominant frequency (DF) from cardiac signals collected simultaneously on the torso and atrial surface. Bi-atrial virtual electrograms (VEGMs) and BSMs were recorded simultaneously for 5 min from 10 patients undergoing ablation for persistent AF. Frequency analysis was performed on 4 s segments. DF was defined as the frequency with highest power between 4 and 10 Hz with and without applying organization index (OI) thresholds. The volume conductor effect was assessed by analyzing the highest DF (HDF) difference of each VEGM HDF against its BSM counterpart. Significant differences in HDF values between intra-cardiac and torso signals could be observed, independent of OI threshold. This difference increases with increasing endocardial HDF (BSM-VEGM median difference from -0.13 Hz for VEGM HDF at 6.25 ± 0.25 Hz to -4.24 Hz at 9.75 ± 0.25 Hz), thereby confirming the theory of the volume conductor effect in real-life situations. Applying an OI threshold strongly affected the BSM HDF area size and location and atrial HDF area location. These results suggest that volume conductor and measurement algorithm effects must be considered for appropriate clinical interpretation.

Full Band Spectra Analysis of Gait Acceleration Signals for Peripheral Arterial Disease Patients

Peripheral arterial disease (PAD) is an artherosclerotic occlusive disorder of distal arteries, which can give rise to the intermittent claudication (IC) phenomenon, i.e., limb pain and necessity to stop. PAD patients with IC have altered their gait, increasing the fall risk. Several gait analysis works have studied acceleration signals (from sensors) to characterize the gait. One common technique is spectral analysis. However, this approach mainly uses dominant frequency (f_d ) to characterize gait patterns, and in a narrow spectral band, disregarding the full spectra information. We propose to use a full band spectral analysis (up to 15 Hz) and the fundamental frequency (f₀) in order to completely characterize gait for both control subjects and PAD patients. Acceleration gait signals were recorded using an acquisition equipment consisting of four wireless sensor nodes located at ankle and hip height on both sides. Subjects had to walk, free-fashion, up to 10 min. The analysis of the periodicity of the gait acceleration signals, showed that f₀ is statistically higher (p < 0.05) in control subjects (0.9743 ± 0.0716) than in PAD patients (0.8748 ± 0.0438). Moreover, the spectral envelope showed that, in controls, the power spectral density distribution is higher than in PAD patients, and that the power concentration is hither around the f_d . In conclusion, full spectra analysis allowed to better characterize gait in PAD patients than classical spectral analysis. It allowed to better discriminate PAD patients and control subjects, and it also showed promising results to assess severity of PAD.

Hierarchical Algorithms for Causality Retrieval in Atrial Fibrillation Intracavitary Electrograms

Multichannel intracavitary electrograms (EGMs) are acquired at the electrophysiology laboratory to guide radio frequency catheter ablation of patients suffering from atrial fibrillation. These EGMs are used by cardiologists to determine candidate areas for ablation (e.g., areas corresponding to high dominant frequencies or complex fractionated electrograms). In this paper, we introduce two hierarchical algorithms to retrieve the causal interactions among these multiple EGMs. Both algorithms are based on Granger causality, but other causality measures can be easily incorporated. In both cases, they start by selecting a root node, but they differ on the way in which they explore the set of signals to determine their cause-effect relationships: either testing the full set of unexplored signals (GS-CaRe) or performing a local search only among the set of neighbor EGMs (LS-CaRe). The ensuing causal model provides important information about the propagation of the electrical signals inside the atria, uncovering wavefronts and activation patterns that can guide cardiologists towards candidate areas for catheter ablation. Numerical experiments, on both synthetic signals and annotated real-world signals, show the good performance of the two proposed approaches.

Sample Entropy Analysis of Noisy Atrial Electrograms during Atrial Fibrillation

Most cardiac arrhythmias can be classified as atrial flutter, focal atrial tachycardia, or atrial fibrillation. They have been usually treated using drugs, but catheter ablation has proven more effective. This is an invasive method devised to destroy the heart tissue that disturbs correct heart rhythm. In order to accurately localise the focus of this disturbance, the acquisition and processing of atrial electrograms form the usual mapping technique. They can be single potentials, double potentials, or complex fractionated atrial electrogram (CFAE) potentials, and last ones are the most effective targets for ablation. The electrophysiological substrate is then localised by a suitable signal processing method. Sample Entropy is a statistic scarcely applied to electrograms but can arguably become a powerful tool to analyse these time series, supported by its results in other similar biomedical applications. However, the lack of an analysis of its dependence on the perturbations usually found in electrogram data, such as missing samples or spikes, is even more marked. This paper applied SampEn to the segmentation between non-CFAE and CFAE records and assessed its class segmentation power loss at different levels of these perturbations. The results confirmed that SampEn was able to significantly distinguish between non-CFAE and CFAE records, even under very unfavourable conditions, such as 50% of missing data or 10% of spikes.

Identification and annotation of multiple periodic pulse trains using dominant frequency and graph search: Applications in atrial fibrillation rotor detection

Biological signals, such as intracardiac electrograms during atrial fibrillation (AF), can contain multiple periodic components or peaks. We propose a method for identifying individual periodic peak trains in signals containing multiple such periodic sequences. We use dominant frequency-based periodicity detection along with a graph search algorithm to identify the most dominant periodic activation set or peaks of interest. We then remove these peaks and iterate until all periodic sequences are identified. The proposed method is tested on simulated AF intra-cardiac electrograms with periodic activation trains of three distinct frequencies corrupted by noise and complex aperiodic signal features. The method is shown to have high accuracy (up to 100% sensitivity and 100% specificity) in detecting the three individual periodic peak trains. The method has application in biomedical signal analysis, such as detecting the periodic activations of a rotor, amidst other periodic activations during AF.

An interactive platform to guide catheter ablation in human persistent atrial fibrillation using dominant frequency, organization and phase mapping

BACKGROUND AND OBJECTIVE

Optimal targets for persistent atrial fibrillation (persAF) ablation are still debated. Atrial regions hosting high dominant frequency (HDF) are believed to participate in the initiation and maintenance of persAF and hence are potential targets for ablation, while rotor ablation has shown promising initial results. Currently, no commercially available system offers the capability to automatically identify both these phenomena. This paper describes an integrated 3D software platform combining the mapping of both frequency spectrum and phase from atrial electrograms (AEGs) to help guide persAF ablation in clinical cardiac electrophysiological studies.

METHODS

30s of 2048 non-contact AEGs (EnSite Array, St. Jude Medical) were collected and analyzed per patient. After QRST removal, the AEGs were divided into 4s windows with a 50% overlap. Fast Fourier transform was used for DF identification. HDF areas were identified as the maximum DF to 0.25Hz below that, and their centers of gravity (CGs) were used to track their spatiotemporal movement. Spectral organization measurements were estimated. Hilbert transform was used to calculate instantaneous phase.

RESULTS

The system was successfully used to guide catheter ablation for 10 persAF patients. The mean processing time was 10.4 ± 1.5min, which is adequate comparing to the normal electrophysiological (EP) procedure time (120∼180min).

CONCLUSIONS

A customized software platform capable of measuring different forms of spatiotemporal AEG analysis was implemented and used in clinical environment to guide persAF ablation. The modular nature of the platform will help electrophysiological studies in understanding of the underlying AF mechanisms.

Maximum likelihood cardiac conduction velocity estimation from sequential mapping in the presence of activation time noise with unknown variances

The cardiac conduction velocity (CV) can be estimated by analysing the activation times (ATs) and the locations of the electrodes that are used for the intracardiac electrogram (IEGM) recording. Here, we study the problem of the CV estimation in sequential mapping without using any independent electrogram as a time alignment reference. We assume that the IEGMs are sequentially recorded from several sites, where at each site, at least two of the catheter's electrodes are in contact with the cardiac tissue. We consider the planar wavefront with stable CV that propagates within the recording sites throughout our data collection period. Assuming the zero-mean Gaussian AT estimation error, we derive the maximum likelihood estimations of the CV and AT at a desired location on the cardiac shell. The CV is estimated when the variance of the AT estimation error and the time delay between the sequential recordings are unknown variables. Our simulation results show that the proposed method can precisely estimate the CV of the planar wavefront.

Several insights into the preprocessing of electrograms in atrial fibrillation for dominant frequency analysis

Background

Dominant frequency (DF) analysis of atrial electrograms has become an important method in characterizing atrial fibrillation (AF). As a classic method, Botteron’s approach is widely used in the preprocessing of frequency analysis during AF. It includes three steps: (1) band-pass filtering at 40–250 Hz, (2) absolute value, and (3) low-pass filtering at 20 Hz. This paper aims to expound the necessity and adjustability of each step.

Methods and results

Unipolar epicardial mapping signals were recorded during AF from eight mongrel dogs with cholinergic AF model. Episodes of these data were randomly selected to evaluate the impact of different pass bands and the necessity of low-pass filtering with 20 Hz cutoff frequency. Each episode of AF signal is 5 s long with a sampling rate of 2 kHz. Simulated electrograms were adopted to discuss the role of taking absolute value. Furthermore, direct spectral analysis method (FFT et al.) is compared with Botteron’s preprocessing approach. According to our statistical analysis, the pass band of 40–250 Hz was not the best, while 20–100 Hz presented the high accuracy rate of DF. From the comparing result of direct FFT without Botteron’s approach we deduced that the rectification of absolute value was meaningful for the fundamental atrial frequency. The final step, 20 Hz low-pass filter can completely be omitted in DF analysis. In consideration of the demand for real-time distribution of DF in clinical or experimental situations, down-sampling method and the impact of ventricular artifacts on DF was also discussed.

Conclusion

In the actual application of the three preprocessing steps, the pass band selection of band-pass filter can be adjusted and the rectification of taking absolute value is important. Nevertheless, the final step of 20 Hz low-pass filter is totally unnecessary. In real-time signal processing situations, taking down-sampling method and ignoring the ventricular artifacts can also have high performance in DF analysis of atrial electrograms.

Development of an alert system for subjects with paroxysmal atrial fibrillation

Background

Knowledge of the onset of atrial fibrillation (AF) episodes in patients with paroxysmal atrial fibrillation (PAF) will enable them to better manage this condition. Current advances in mobile technology allow RR interval data to be obtained in real time. An analysis technique using RR interval data is presented with a view to alert a subject before a PAF episode.

Method

The method is based on a time series of standard deviation and 0.99 quantile values of the spectral entropy, constructed from RR data. The RR data are taken from three time periods. The first time period has no occurrences of AF for 45 min to either side of the time period. The second time period just precedes an AF attack. Both of these are of thirty minutes duration. The third time period of approximately 5 min follows the second, and is when AF occurs.

Results

Twenty-two PAF subjects were studied and in all cases there was a steady increase in the values of these indices as the onset of the AF attack approached.

Conclusion

This method of analysis of RR interval data shows potential use to alert a PAF subject before the onset of an AF episode.

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A method to alert the PAF subject before the onset of paroxysms of AF, based on a time series of standard deviation and 0.99 quantile values of the spectral entropy, obtained from the RR interval data.

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The RR data used in analysis each subject was obtained from three time periods. The first two are of thirty minute duration while the third set is of 5 min duration.

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RR data from the first time period had no occurrences of AF, 45 min on either side of it. The time period of the second set just precedes an AF attack. The third set which follows the second is when AF occurs.

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22 PAF subjects were studied and in all cases there was a steady increase in the values of the standard deviation and 0.99 quantile values of the spectral entropy.

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Such a signature of these indices shows that this analysis technique of RR data could be useful to PAF patients to better manage the onset of AF attacks.

Atrial electromechanical cycle length mapping in paced canine hearts in vivo

Atrial arrhythmias affect millions of people worldwide. Characterization and study of arrhythmias in the atria in the clinic is currently performed point by point using mapping catheters capable of generating maps of the electrical activation rate or cycle length. In this paper, we describe a new ultrasound-based mapping technique called electromechanical cycle length mapping (ECLM) capable of estimating the electromechanical activation rate, or cycle length, i.e., the rate of the mechanical activation of the myocardium which follows the electrical activation. ECLM relies on frequency analysis of the incremental strain within the atria and can be performed in a single acquisition. ECLM was validated in a canine model paced from the left atrial appendage, against pacing rates within the reported range of cycle lengths previously measured during atrial arrhythmias such as atrial fibrillation. Correlation between the global estimated electromechanical cycle lengths and pacing rates was shown to be excellent (slope = 0.983, intercept = 3.91, r(2) = 0.9999). The effect of the number of cardiac cycles on the performance of ECLM was also investigated and the reproducibility of ECLM was demonstrated (error between consecutive acquisitions for all pacing rates: 6.3 ± 4.3%). These findings indicate the potential of ECLM for noninvasively characterizing atrial arrhythmias and provide feedback on the treatment planning of catheter ablation procedures in the clinic.

A preliminary study on atrial epicardial mapping signals based on Graph Theory

In order to get a better understanding of atrial fibrillation, we introduced a method based on Graph Theory to interpret the relations of different parts of the atria. Atrial electrograms under sinus rhythm and atrial fibrillation were collected from eight living mongrel dogs with cholinergic AF model. These epicardial signals were acquired from 95 unipolar electrodes attached to the surface of the atria and four pulmonary veins. Then, we analyzed the electrode correlations using Graph Theory. The topology, the connectivity and the parameters of graphs during different rhythms were studied. Our results showed that the connectivity of graphs varied from sinus rhythm to atrial fibrillation and there were parameter gradients in various parts of the atria. The results provide spatial insight into the interaction between different parts of the atria and the method may have its potential for studying atrial fibrillation.

Evaluating epicardial mapping electrogram by the method of dominant frequency and Lorenz plot

The methods of dominant frequency and Lorenz plot are used in this study to evaluate the activation rate and the activation rate variability of cardiac signals during atrial fibrillation. An epicardial mapping system was applied to acquire the atrial electrogram of mongrel dogs. The dominant frequency and Lorenz plot of each signal from various myocardial regions of the atria were analyzed. Our results show that both a frequency gradient and a variability gradient exist in the atria and the roots of pulmonary veins. The dominant frequencies of the anterior atria are higher than the posterior ones and the activation variability of both atria was higher than those of the pulmonary veins. A combination of these two methods may provide a more comprehensive understanding of the electrophysiology mechanism associated with atrial fibrillation.

Comparison of spectral estimators for characterizing fractionated atrial electrograms

Background

Complex fractionated atrial electrograms (CFAE) acquired during atrial fibrillation (AF) are commonly assessed using the discrete Fourier transform (DFT), but this can lead to inaccuracy. In this study, spectral estimators derived by averaging the autocorrelation function at lags were compared to the DFT.

Method

Bipolar CFAE of at least 16 s duration were obtained from pulmonary vein ostia and left atrial free wall sites (9 paroxysmal and 10 persistent AF patients). Power spectra were computed using the DFT and three other methods: 1. a novel spectral estimator based on signal averaging (NSE), 2. the NSE with harmonic removal (NSH), and 3. the autocorrelation function average at lags (AFA). Three spectral parameters were calculated: 1. the largest fundamental spectral peak, known as the dominant frequency (DF), 2. the DF amplitude (DA), and 3. the mean spectral profile (MP), which quantifies noise floor level. For each spectral estimator and parameter, the significance of the difference between paroxysmal and persistent AF was determined.

Results

For all estimators, mean DA and mean DF values were higher in persistent AF, while the mean MP value was higher in paroxysmal AF. The differences in means between paroxysmals and persistents were highly significant for 3/3 NSE and NSH measurements and for 2/3 DFT and AFA measurements (p<0.001). For all estimators, the standard deviation in DA and MP values were higher in persistent AF, while the standard deviation in DF value was higher in paroxysmal AF. Differences in standard deviations between paroxysmals and persistents were highly significant in 2/3 NSE and NSH measurements, in 1/3 AFA measurements, and in 0/3 DFT measurements.

Conclusions

Measurements made from all four spectral estimators were in agreement as to whether the means and standard deviations in three spectral parameters were greater in CFAEs acquired from paroxysmal or in persistent AF patients. Since the measurements were consistent, use of two or more of these estimators for power spectral analysis can be assistive to evaluate CFAE more objectively and accurately, which may lead to improved clinical outcome. Since the most significant differences overall were achieved using the NSE and NSH estimators, parameters measured from their spectra will likely be the most useful for detecting and discerning electrophysiologic differences in the AF substrate based upon frequency analysis of CFAE.

Dynamic time warping applied to estimate atrial fibrillation temporal organization from the surface electrocardiogram

Atrial fibrillation (AF) is the most commonly diagnosed arrhythmia in clinical practice. However, the mechanisms responsible for its induction and maintenance still are not fully understood. To this respect, analysis of the electrical activity organization within the atria could play an important role in their proper interpretation. Although many algorithms to quantify AF organization from invasive electrograms can be found in the literature, a reduced number of indirect estimators from the standard ECG have been proposed to date. Furthermore, these surface methods can only yield a global AF organization assessment, blurring the possible information that each individual fibrillatory (f) wave may provide. To this respect, the present manuscript proposes a novel method for direct and short-time AF organization estimation from single-lead surface ECG recordings. Through the computation of morphological variations among f waves, the temporal arrhythmia organization is estimated. The f waves are individually extracted and delineated from the atrial activity signal, making use of a dynamic time warping approach. The proposed algorithm was tested on real AF surface recordings in order to discriminate atrial signals with different organization degrees, obtaining a diagnostic accuracy higher than 88%. In addition, its performance was validated by comparison with two temporal organization measures from invasive unipolar electrograms of both atria, providing statistically significant linear correlations between invasive and non-invasive estimates. As a consequence, new standpoints are opened through this work in the non-invasive analysis of AF, where the individualized study of each f wave could assess short-time AF organization, would improve the understanding of AF mechanisms and become useful for its clinical treatment.

Novel methods for characterization of paroxysmal atrial fibrillation in human left atria

INTRODUCTION

More effective methods for characterizing 3D electrical activity in human left atrium (LA) are needed to identify substrates/triggers and microreentrant circuit for paroxysmal atrial fibrillation (PAF). We describe a novel wavelet-based approach and wave-front centroid tracking that have been used to reconstruct regional activation frequency and electrical activation pathways from non-contact multi-electrode array.

METHODS

Data from 13 patients acquired prior to ablation for PAF with a 64 electrode noncontact catheter positioned in the LA were analysed. Unipolar electrograms were reconstructed at 2048 locations across each LA endocardial surface. Weighted fine- and coarse-scale electrograms were constructed by wavelet decomposition and combined with peak detection to identify atrial fibrillation (AF) activation frequency and fractionated activity at each site. LA regions with upper quartile AF frequencies were identified for each patient. On the other hand, a wave-front centroid tracking approach was introduced for this first time to detect macro-reentrant circuit during PAF.

RESULTS

The results employing wavelet-based analysis on atrial unipolar electrograms are validated by the signals recorded simultaneously via the contacted ablation catheter and visually tracking the 3D spread of activation through the interest region. Multiple connected regions of high frequency electrical activity were seen; most often in left superior pulmonary vein (10/12), septum (9/12) and atrial roof (9/12), as well as the ridge (8/12). The wave-front centroid tracking approach detects a major macro circuit involving LPVs, PLA, atrial floor, MV, septum, atrial roof and ridge. The regions with high frequency by wave-front tracking are consistent with the results using wavelet approach and our clinical observations.

CONCLUSIONS

The wavelet-based technique and wave-front centroid tracking approach provide a robust means of extracting spatio-temporal characteristics of PAF. The approach could facilitate accurate identification of pro-arrhythmic substrate and triggers, and therefore, to improve success rate of catheter ablation for AF.

Benchmarking electrophysiological models of human atrial myocytes

Mathematical modeling of cardiac electrophysiology is an insightful method to investigate the underlying mechanisms responsible for arrhythmias such as atrial fibrillation (AF). In past years, five models of human atrial electrophysiology with different formulations of ionic currents, and consequently diverging properties, have been published. The aim of this work is to give an overview of strengths and weaknesses of these models depending on the purpose and the general requirements of simulations. Therefore, these models were systematically benchmarked with respect to general mathematical properties and their ability to reproduce certain electrophysiological phenomena, such as action potential (AP) alternans. To assess the models' ability to replicate modified properties of human myocytes and tissue in cardiac disease, electrical remodeling in chronic atrial fibrillation (cAF) was chosen as test case. The healthy and remodeled model variants were compared with experimental results in single-cell, 1D and 2D tissue simulations to investigate AP and restitution properties, as well as the initiation of reentrant circuits.

Ablation of complex fractionated atrial electrograms in catheter ablation for AF; where have we been and where are we going?

Catheter ablation for persistent AF remains a challenge to the ablator as the disease is now outside the veins and cannot be tackled by pulmonary vein isolation alone. In this article we describe targeting complex fractionated atrial electrograms (CFAE) as a method to guide atrial substrate modification.

Processing and analysis of cardiac optical mapping data obtained with potentiometric dyes

Optical mapping has become an increasingly important tool to study cardiac electrophysiology in the past 20 years. Multiple methods are used to process and analyze cardiac optical mapping data, and no consensus currently exists regarding the optimum methods. The specific methods chosen to process optical mapping data are important because inappropriate data processing can affect the content of the data and thus alter the conclusions of the studies. Details of the different steps in processing optical imaging data, including image segmentation, spatial filtering, temporal filtering, and baseline drift removal, are provided in this review. We also provide descriptions of the common analyses performed on data obtained from cardiac optical imaging, including activation mapping, action potential duration mapping, repolarization mapping, conduction velocity measurements, and optical action potential upstroke analysis. Optical mapping is often used to study complex arrhythmias, and we also discuss dominant frequency analysis and phase mapping techniques used for the analysis of cardiac fibrillation.

Electropathological substrate detection of persistent atrial fibrillation--a novel method to analyze unipolar electrograms of noncontact mapping

Radiofrequency catheter ablation as a curative method for atrial fibrillation (AF) has become increasingly popular. Patients with paroxysmal AF have been treated by catheter ablation with great success, but so far this treatment has been less effective for patients with persistent AF. Usually there are multiple triggers or substrates during persistent AF and their exact locations are unclear. On the other hand, the non-contact mapping system (Ensite 3000, St Jude Medical) producing thousands of virtual endocardial electrograms, has gradually become accepted as a powerful tool to use on patients before and after ablation. Effective mathematical tools to detect the substrates of AF from unipolar electrograms produced by the non-contact mapping are few, though many methods are available for performing this task with bipolar electrograms. In this work, we introduce for the first time a simple and efficient approach to automatically and systematically determine the substrate of persistent AF in order to guide catheter ablation via the non-contact mapping.

Spectral profiles of complex fractionated atrial electrograms are different in longstanding and acute onset atrial fibrillation atrial electrogram spectra

Spectral Profiles of CFAE.

BACKGROUND

Spectral analysis of complex fractionated atrial electrograms (CFAE) may be useful for gaining insight into mechanisms underlying paroxysmal and longstanding atrial fibrillation (AF). The commonly used dominant frequency (DF) measurement has limitations.

METHOD

CFAE recordings were acquired from outside the 4 pulmonary vein ostia and at 2 left atrial free wall sites in 10 paroxysmal and 10 persistent AF patients. Two consecutive 8s-series were analyzed from recordings >16s in duration. Power spectra were computed for each 8s-series in the range 3-12 Hz and normalized. The mean and standard deviation of normalized power spectra (MPS and SPS, respectively) were compared for paroxysmal versus persistent CFAE. Also, the DF and its peak amplitude (ADF) were compared for pulmonary vein sites only. Power spectra were computed using ensemble average and Fourier methods.

RESULTS

No significant changes occurred in any parameter from the first to second recording sequence. For both sequences, MPS and SPS were significantly greater, and DF and ADF were significantly less, in paroxysmals versus persistents. The MPS and ADF measurements from ensemble spectra produced the most significant differences in paroxysmals versus persistents (P < 0.0001). DF differences were less significant, which can be attributed to the relatively high variability of DF in paroxysmals. The MPS was correlated to the duration of uninterrupted persistent AF prior to electrophysiologic study (P = 0.01), and to left atrial volume for all AF (P < 0.05).

CONCLUSIONS

The MPS and ADF measurements introduced in this study are probably superior to DF for discerning power spectral differences in paroxysmal versus longstanding CFAE. (J Cardiovasc Electrophysiol, Vol. 23, pp. 971-979, September 2012).

Left atrial flutter accelerates during ablation of atrial fibrillation: a paradoxical effect of electrical remodelling

AIMS

Atrial fibrillation (AF)-induced electrical remodelling causes shortening of refractory period and slowing of conduction velocity. During the course of catheter ablation of AF, there are often transitions from AF to left atrial flutter (AFL) and from faster to slower AFL. The purpose of this study was to characterize the time course of change in AFL rate during AF ablation.

METHODS AND RESULTS

Fourier transformation was performed on 16 s segments of coronary sinus and ablation catheter bipolar electrograms. Ablation-induced AF-to-AFL and AFL-to-AFL transitions were defined as a sudden drop in the dominant frequency (DF) of at least 10 bpm, followed by a regular rhythm. Forty-five transitions were detected in 24 ablation procedures. The mean DF in AF was 5.31 ± 0.79 Hz, which was significantly faster than AFL, 4.52 ± 0.62 Hz (P< 0.05). The mean ΔDF at transitions was -51 ± 16 bpm in AF and -40 ± 14 bpm in AFL. Dominant frequency slope was positive (rate increased) after all the transitions during AF (P< 0.0001) and in 11 of 14 transitions in AFL (P= 0.033). The time constant of the DF recovery curve was 161 ± 105 s.

CONCLUSIONS

After ablation-induced transition from AF to AFL, or faster to slower AFL, there is a progressive increase in AFL rate over time. The mechanism of this acceleration is uncertain, but the time constant of this rate increase is consistent with the recovery of the slow/ultraslow sodium current in the setting of established electrical remodelling.

QRS subtraction for atrial electrograms: flat, linear and spline interpolations

The main objective of this article is to implement and compare QRS subtraction techniques for intra-cardiac atrial electrograms based on using the surface ECG as a reference. A band-pass filter between 8 and 20 Hz followed by rectification, and then a low-pass filter at 6 Hz are used for QRS detection. QRS subtraction was performed using three different approaches: flat, linear and spline interpolations. QRS subtraction affects the power of the signals but it normally does not affect the dominant frequency. The average power of the atrial electrograms after QRS subtraction is significantly reduced for frequencies above 10 Hz.