Nonhomogeneous local atrial activity during acute atrial fibrillation: spectral and dynamic analysis

Velocity characteristics of atrial fibrillation sources determined by electrographic flow mapping before and after catheter ablation

BACKGROUND

Electrographic-Flow-(EGF)-Mapping is a novel method to identify Atrial Fibrillation (AF) drivers. Sources of excitation during AF can be characterized and monitored.

OBJECTIVE

The aim of this study was to evaluate the correlation between velocity of EGF around a respective AF source and its spatial variability (SV) and stability (SST).

METHODS

25 patients with AF were included in this study (persistent: n = 24, long-standing persistent: n = 1; mean age 70 ± 8.3 years, male: n = 17). Focal impulse and Rotor-Mapping (FIRM) was performed in addition to pulmonary vein isolation. One-minute epochs of unipolar electrograms recorded via a 64-pole basket catheter in both atria were re-analyzed with EGF-Mapping. SST was calculated as the percentage of time in which a source was detected.

RESULTS

AF sources identified with EGF-Mapping show a wide range of SV during 1 min covering between 0.12% and 38% of the recorded basket-catheter surface. The 12 atria where the sources showed highest temporal stability (TS; between 34% and 97% of 1 min recorded) and those 12 with the lowest TS (between 11 and 20%) differed significantly in their velocities (17.8 el/s vs 12.2 el/s; p < 0.01). In 11 atria ablation caused an average decrease of TS by 47% and of velocity by 27% while SV more than doubled.

CONCLUSION

Less stable AF-sources with high spatial variability showed reduced excitation propagation velocity while stable AF sources displayed a high average velocity in their vicinity. Importantly, catheter ablation reduced stability of sources and velocity suggesting a role of these parameters in guidance of ablation.

CONDENSED ABSTRACT

Electrographic Flow (EGF)-Mapping is a novel method to identify Atrial Fibrillation (AF) drivers based on modeling of an electrical potential surface and subsequent flow analysis. Sources of excitation during AF can be characterized and monitored. The aim of this study was to evaluate the correlation between velocity of EGF around a respective AF source and its spatial variability and stability. Less stable AF sources with high spatial variability showed reduced excitation propagation velocity while very stable AF sources displayed a high average velocity in their vicinity. Catheter ablation reduced stability of sources and velocity.

Is human atrial fibrillation stochastic or deterministic?-Insights from missing ordinal patterns and causal entropy-complexity plane analysis

The mechanism of atrial fibrillation (AF) maintenance in humans is yet to be determined. It remains controversial whether cardiac fibrillatory dynamics are the result of a deterministic or a stochastic process. Traditional methods to differentiate deterministic from stochastic processes have several limitations and are not reliably applied to short and noisy data obtained during clinical studies. The appearance of missing ordinal patterns (MOPs) using the Bandt-Pompe (BP) symbolization is indicative of deterministic dynamics and is robust to brief time series and experimental noise. Our aim was to evaluate whether human AF dynamics is the result of a stochastic or a deterministic process. We used 38 intracardiac atrial electrograms during AF from the coronary sinus of 10 patients undergoing catheter ablation of AF. We extracted the intervals between consecutive atrial depolarizations (AA interval) and converted the AA interval time series to their BP symbolic representation (embedding dimension 5, time delay 1). We generated 40 iterative amplitude-adjusted, Fourier-transform (IAAFT) surrogate data for each of the AA time series. IAAFT surrogates have the same frequency spectrum, autocorrelation, and probability distribution with the original time series. Using the BP symbolization, we compared the number of MOPs and the rate of MOP decay in the first 1000 timepoints of the original time series with that of the surrogate data. We calculated permutation entropy and permutation statistical complexity and represented each time series on the causal entropy-complexity plane. We demonstrated that (a) the number of MOPs in human AF is significantly higher compared to the surrogate data (2.7 ± 1.18 vs. 0.39 ± 0.28, p < 0.001); (b) the median rate of MOP decay in human AF was significantly lower compared with the surrogate data (6.58 × 10^-3 vs. 7.79 × 10^-3, p < 0.001); and (c) 81.6% of the individual recordings had a rate of decay lower than the 95% confidence intervals of their corresponding surrogates. On the causal entropy-complexity plane, human AF lay on the deterministic part of the plane that was located above the trajectory of fractional Brownian motion with different Hurst exponents on the plane. This analysis demonstrates that human AF dynamics does not arise from a rescaled linear stochastic process or a fractional noise, but either a deterministic or a nonlinear stochastic process. Our results justify the development and application of mathematical analysis and modeling tools to enable predictive control of human AF.

Spectral Analysis of Atrial Fibrillation Cycle Lengths Comparison Between Fast Fourier Transform Analysis and Autocorrelation Function Analysis Using Multipurpose Physio-Informatic Analysis Software

BACKGROUND

Fast Fourier transform (FFT) analysis is a popular method of spectral analysis of atrial fibrillation cycle lengths (AFCL). Autocorrelation function (ACF) analysis is also available, so the aim of this study was to elucidate the relationship between FFT and ACF analyses in the spectral analysis of AFCLs.

METHODS AND RESULTS

A total of 75 atrial fibrillation (AF) data from 39 patients were subjected to analysis. The dominant frequencies (DFs) from 4 different spectral resolutions of the FFT and peak AFCL from the ACF analysis were compared. In the FFT analysis using rectified signals, the DF was influenced by spectral resolution, no matter how the signals were tapered by the Hanning or Hamming window or filtered with the low-pass filter. There was a significant relationship between the DF from each spectral resolution and the peak AFCL. The DF from the 4,096-point FFT analysis had the strongest relationship to the peak AFCL with the smallest difference, when using 30-s AF data. In a study of the different lengths of the atrial fibrillation data, the DF also had a strong correlation to the peak AFCL with a small difference.

CONCLUSIONS

The peak AFCL obtained from ACF analysis was not of the same quality as that from FFT analysis, but had the same value as the DF from FFT analysis.

Left atrial dilatation resulting from chronic mitral regurgitation decreases spatiotemporal organization of atrial fibrillation in left atrium

Atrial conduction properties have been shown to differ among animal atrial fibrillation (AF) models of rapid atrial pacing (RAP), chronic mitral regurgitation (MR), and control. We hypothesized that these conduction differences would continue with the onset of AF, which would affect AF spatiotemporal organization, resulting in model-specific characteristics of AF. With frequency domain analysis of electrograms acquired from high-density optical mapping, AF from the right (RA) and left (LA) atrium in animals with RAP and MR were compared with control animals. At follow-up, the hearts were excised and perfused, and optical action potentials were recorded from a 2 × 2-cm area each of the RA and LA free wall with a 16 × 16 photodiode array. AF was induced with extra stimuli, several 2.4-s AF episodes were recorded in each dog, and a fast Fourier transform was calculated. The dominant frequency (DF) was determined, and the organization (organization index, OI) was calculated as the ratio of the area under the dominant peak and its harmonics to the total area of the spectrum. All possible pairs of electrograms for each episode were cross-correlated. LA AF in the chronic MR model showed an increase in the highest DF, the number of DF domains, and in frequency gradient compared with AF in control or RAP models. In addition, there was a decrease in OI and in the correlation coefficients in the LA of the MR model. These results suggest that the AF substrate in the MR model may be different from that of control or RAP models.

Experimental and clinical AF mechanisms: bridging the divide

There is general agreement that AF is most likely a reentrant rhythm disturbance. However, the precise pathophysiological bases for its initiation and maintenance have not been fully resolved. In the original description of the multiple wavelet hypothesis of atrial fibrillation, as put forward by Moe et al. and later substantiated by Allessie et al., the wavelets were thought to move randomly throughout the atria. However, more recent studies that have applied high resolution mapping of wave propagation and rigorous analyses in the time and frequency domains to long episodes of AF, have provided evidence that atrial fibrillation is not random, but is accompanied by a high degree of spatiotemporal periodicity. This has led to the hypothesis that maintenance of AF may depend on the uninterrupted periodic activity of a small number of discrete reentrant sites, established by the interaction of propagating waves with anatomical heterogeneities in the atria. It has been proposed also that the rapidly successive wave fronts emanating from these sources propagate through both atria and interact with anatomical and/or functional obstacles, leading to fragmentation and wavelet formation. In support of this idea, observations made during radiofrequency ablation of AF in humans suggest that, in some patients, a single, repetitive focal source of activity propagate impulses from an individual pulmonary vein to the remainder of the atrium as fibrillatory waves. These studies underscore the need for identification of continuing AF sources at localized sites, and of transient AF "triggers", which may involve normal or abnormal pacemaker mechanisms or even reentrant activity, and of the manner in which electrical activity initiated by such triggers interacts with the normally propagating electrical waves to initiate fibrillatory activity in the atria.

Cholinergic atrial fibrillation in a computer model of a two-dimensional sheet of canine atrial cells with realistic ionic properties

Classical concepts of atrial fibrillation (AF) have been rooted in Moe's multiple-wavelet hypothesis and simple cellular-automaton computer model. Recent experimental work has raised questions about the multiple-wavelet mechanism, suggesting a discrete "driver region" underlying AF. We reexplored the theoretical basis for AF with a 2-dimensional computer model of a 5x10-cm sheet of atrial cells with realistic ionic and coupling properties. Vagal actions were formulated based on patch-clamp studies of acetylcholine (ACh) effects. In control, a single extrastimulus resulted in a highly meandering unstable spiral wave. Simulated electrograms showed fibrillatory activity, with a dominant frequency (DF, 6.5 Hz) that correlated with the mean rate. Uniform ACh reduced core meander of the spiral wave by approximately 70% (as measured by the standard deviation of spiral-wave tip position) and accelerated the DF to 17.0 Hz. Simulated vagally induced refractoriness heterogeneity caused wavefront breakup as accelerated reentrant activity in regions of short refractoriness impinged on regions unable to respond in a 1:1 fashion because of longer refractoriness. In 7 simulations spanning the range of conditions giving sustained AF, 5 were maintained by single dominant spiral waves. On average, 3.0+/-1.3 wavelets were present (range, 1 to 7). Most wavelets were short-lived and did not contribute to AF maintenance. In contrast to predictions of the multiple-wavelet hypothesis, but in agreement with recent experimental evidence, our model indicates that AF can result from relatively stable primary spiral-wave generators and is significantly organized. Our results suggest that vagal AF may arise from ACh-induced stabilization of the primary spiral-wave generator and disorganization of the heterogeneous tissue response. The full text of this article is available at http://www.circresaha.org.

Spectral characteristics of human atrial fibrillation waves of the right atrial free wall with respect to the duration of atrial fibrillation and effect of class I antiarrhythmic drugs

The aim of this study was to use fast Fourier transform analysis to clarify the characteristics of human atrial fibrillation (AF) waves with respect to the duration of AF and the effect of class I antiarrhythmic drugs. Twenty-two patients (10 paroxysmal AF, 12 persistent AF) without organic heart disease were studied by conventional electrophysiological methods. Electrograms were recorded from the right atrial free wall during AF and spectral analysis was performed for 35s (16 consecutive 4096-ms epochs with 50% overlap) and the fibrillation cycle length (FCL) was calculated from the peak frequency. Mean FCL and SD were determined from 16-epoch data, and the temporal variability of FCL was defined as the SD of FCL. Paroxysmal AF had a longer mean FCL than persistent AF (178+/-26ms vs 139+/-16 ms, p<0.001) and AF duration had a significant inverse correlation with mean FCL (r=-0.79, p<0.001). The temporal variability of FCL was significantly greater in paroxysmal AF than in persistent AF (p<0.05) and there was a significant positive correlation between the mean FCL and the temporal variability of FCL (r=0.66, p<0.001). In 8 of 18 patients given a class I antiarrhythmic drug (cibenzoline or procainamide), AF was terminated and in those patients the mean FCLs before administration of class I drugs were significantly greater than in patients without AF termination. With respect to mean FCL before drug administration, conversion occurred in 100% of patients with FCL > or =168 ms and in 17% of those with FCL <168 ms. A longer duration of AF shortens the mean FCL, which is consistent with atrial electrical remodeling. Class I drugs prolong the mean FCL above a critical level and will terminate AF, which can be estimated from the mean FCL before drug administration.

Spatially distributed dominant excitation frequencies reveal hidden organization in atrial fibrillation in the Langendorff-perfused sheep heart

INTRODUCTION

Atrial fibrillation (AF) is characterized by complex wave propagation, yet periodic excitation suggesting a high degree of organization may be revealed during sustained AF. We provide a systematic quantification of the spatial distribution of dominant frequencies (DFs) of local excitation on the epicardium of the right atrial (RA) free wall and left atrial (LA) appendage of the isolated sheep heart during AF. The data reveal, for the first time, hidden organization, independent of the activation sequences or nature of electrograms.

METHODS AND RESULTS

In 13 Langendorff-perfused sheep hearts, AF was induced in presence of 0.1 to 0.6 microM acetylcholine. Video movies (potentiometric dye di-4-ANEPPS) of the RA and LA (>30,000 and >20,000 pixels, respectively) were obtained at 120 frames/sec and a biatrial electrogram was recorded. Spectral analyses were performed on movies with DF maps constructed. During AF, the activity formed stable discrete domains with uniform DFs within each domain. Acceleration of AF increased the number of domains (R = 0.81, P < 0.0001) and the DF variance (R = 0.63, P < 0.001), indicating a decrease in organization. Also, the LA was faster and more homogeneous, with smaller number of DF domains, compared to the RA (P < 0.00001).

CONCLUSION

In this model, AF is characterized by multiple domains with distinct DFs on the atrial epicardium. The decrease in domain area with increased rate suggests that AF results from high-frequency impulses that undergo spectral transformations. The LA is generally faster and more organized than the RA, suggesting that the sources for the impulses are localized to the LA.

Temporal organization of atrial activity and irregular ventricular rhythm during spontaneous atrial fibrillation: an in vivo study in the horse

INTRODUCTION

Atrial fibrillation (AF) is common in healthy horses. We studied the temporal organization of AF to test the hypothesis that the arrhythmia is governed by a high degree of periodicity and therefore is not random in the horse. Further, we surmised that concealed conduction of AF impulses in the AV node results in an inverse relationship between AF frequency and ventricular frequency.

METHODS AND RESULTS

Fast Fourier transform (FFT) analysis of atrial activity was done on signal-averaged ECGs (n = 11) and atrial electrograms (n = 3) of horses with AF at control (C), after quinidine sulfate (22 mg/kg by mouth every 2 hours) at 50% time to conversion (T50), and immediately before conversion (T90) to sinus rhythm. FFT always revealed a single dominant frequency peak. The mean dominant frequency decreased until conversion (C = 6.84 +/- 0.85 Hz, T50 = 4.87 +/- 1.5 Hz, T90 = 3.41 +/- 1.18 Hz; P < 0.001). Mean AA intervals (n = 500) gradually increased after quinidine. Mean RR intervals (n = 500), standard deviation of the mean (SDM), Poincaré plots, and serial autocorrelograms (SACs) of 500 RR intervals were measured at C and T90 to determine the ventricular response to AF and quinidine-induced changes in the variability of the ventricular response. Mean RR interval and SDM were reduced after quinidine (C = 1431 +/- 266 msec and 695 +/- 23 msec; T90 = 974 +/- 116 msec and 273 +/- 158 msec, respectively; P < 0.01). Poincaré plots and SAC at C and at T90 revealed a significant correlation of consecutive RR intervals typical of a system with a deterministic behavior. At T90, the variability of RR intervals was reduced and the overall periodicity of RR intervals was increased after quinidine administration.

CONCLUSION

In the horse, AF is a complex arrhythmia characterized by a high degree of underlying periodicity. The inverse AA-to-RR interval relationship and reduced variability of RR intervals after quinidine suggest that the ventricular response during AF results from rate-dependent concealment of AF wavelets bombarding the AV node, which nevertheless results in a significant degree of short-term predictability of beat-to-beat changes in RR intervals.

Chaos and the transition to ventricular fibrillation: a new approach to antiarrhythmic drug evaluation

Sudden cardiac death resulting from ventricular fibrillation can be separated into 2 components: initiation of tachycardia and degeneration of tachycardia to fibrillation. Clinical drug studies such as CAST and SWORD demonstrated that focusing exclusively on the first component is inadequate as a therapeutic modality. The hope for developing effective pharmacological therapy rests on a comprehensive understanding of the second component, the transition from tachycardia to fibrillation. We summarize evidence that the transition from tachycardia to fibrillation is a transition to spatiotemporal chaos, with similarities to the quasiperiodic transition to chaos seen in fluid turbulence. In this scenario, chaos results from the interaction of multiple causally independent oscillatory motions. Simulations in 2-dimensional cardiac tissue suggest that the destabilizing oscillatory motions during spiral-wave reentry arise from restitution properties of action potential duration and conduction velocity. The process of spiral-wave breakup in simulated cardiac tissue predicts remarkably well the sequence by which tachycardia degenerates to fibrillation in real cardiac tissue. Modifying action potential duration and conduction velocity restitution characteristics can prevent spiral-wave breakup in simulated cardiac tissue, suggesting that drugs with similar effects in real cardiac tissue may have antifibrillatory efficacy (the Restitution Hypothesis). If valid for the real heart, the Restitution Hypothesis will support a new paradigm for antiarrhythmic drug classification, incorporating an antifibrillatory profile based on effects on cardiac restitution and the traditional antitachycardia profile (classes 1 through 4).

Spatiotemporal periodicity during atrial fibrillation in the isolated sheep heart

BACKGROUND

The activation patterns that underlie the irregular electrical activity during atrial fibrillation (AF) have traditionally been described as disorganized or random. Recent studies, based predominantly on statistical methods, have provided evidence that AF is spatially organized. The objective of this study was to demonstrate the presence of spatial and temporal periodicity during AF.

METHODS AND RESULTS

We used a combination of high-resolution video imaging, ECG recordings, and spectral analysis to identify sequential wave fronts with temporal periodicity and similar spatial patterns of propagation during 20 episodes of AF in 6 Langendorff-perfused sheep hearts. Spectral analysis of AF demonstrated multiple narrow-band peaks with a single dominant peak in all cases (mean, 9.4+/-2.6 Hz; cycle length, 112+/-26 ms). Evidence of spatiotemporal periodicity was found in 12 of 20 optical recordings of the right atrium (RA) and in all (n=19) recordings of the left atrium (LA). The cycle length of spatiotemporal periodic waves correlated with the dominant frequency of their respective optical pseudo-ECGs (LA: R2=0.99, slope=0.94 [95% CI, 0.88 to 0.99]; RA: R2=0.97, slope=0.92 [95% CI, 0.80 to 1.03]). The dominant frequency of the LA pseudo-ECG alone correlated with the global bipolar atrial EG (R2=0.76, slope=0.75 [95% CI, 0.52 to 0.99]). In specific examples, sources of periodic activity were seen as rotors in the epicardial sheet or as periodic breakthroughs that most likely represented transmural pectinate muscle reentry. However, in the majority of cases, periodic waves were seen to enter the mapping area from the edge of the field of view.

CONCLUSIONS

Reentry in anatomically or functionally determined circuits forms the basis of spatiotemporal periodic activity during AF. The cycle length of sources in the LA determines the dominant peak in the frequency spectra in this experimental model of AF.

Quasiperiodicity and chaos in cardiac fibrillation

In cardiac fibrillation, disorganized waves of electrical activity meander through the heart, and coherent contractile function is lost. We studied fibrillation in three stationary forms: in human chronic atrial fibrillation, in a stabilized form of canine ventricular fibrillation, and in fibrillation-like activity in thin sheets of canine and human ventricular tissue in vitro. We also created a computer model of fibrillation. In all four studies, evidence indicated that fibrillation arose through a quasiperiodic stage of period and amplitude modulation, thus exemplifying the "quasiperiodic transition to chaos" first suggested by Ruelle and Takens. This suggests that fibrillation is a form of spatio-temporal chaos, a finding that implies new therapeutic approaches.

Mode switch despite undersensing of atrial fibrillation in DDD pacing

Mode switching algorithms are commonly used to protect the ventricles against high rates induced by atrial tachycardia. In the case of atrial fibrillation (AF), the response of these algorithms depends on the quality of atrial sensing. The Chorum 7234 DDDR pacemaker uses a new mode switching algorithm, based on a statistical analysis of the atrial rhythm. It includes two criteria of diagnosis: "high" if more than 28 of 32 cycles are abnormally accelerated; and "low" if more than 36 of 64 cycles are abnormally accelerated.

METHODS

From a taped database of electrophysiological studies, episodes of AF lasting more than 2 minutes were selected. A tape recorder replayed the atrial signals into an external Chorum device. Each episode was replayed eight times with a programmed atrial sensitivity increasing from 0.4-2.0 mV. For each criterion of diagnosis and each programmed sensitivity, the percentage of atrial sensing, the time to switching, and the mean ventricular rate were measured. Ten episodes of AF from 10 patients (9 men and 1 woman; ages 62 +/- 16 years) were included: 1.95 +/- 0.97 mV and 196 +/- 64 ms. The sensitivity of the algorithm to diagnose atrial tachycardia reached 100%, for an atrial sensitivity set between 0.4 and 1.0 mV. The mean percentages of atrial sensed events were 74% +/- 18% and 46% +/- 9% for the "high" and "low" criteria, respectively. The mean diagnostic times were 28 +/- 26 seconds and 68 +/- 27 seconds, respectively. Sensing of < 23% of AF events resulted in failure to diagnose the arrhythmias by both algorithms. In the event of diagnostic failure, the mean ventricular pacing rate was 79 +/- 9 ppm.

CONCLUSION

Up to an atrial sensitivity of 1 mV, 100% of AF episodes were diagnosed. The Chorum mode switching algorithms are 100% reliable if > 45% of the AF waves are sensed. In the event of switching failure, the ventricle is protected by an average rate remaining below 80 ppm.

Characterization of left atrial appendage Doppler flow in atrial fibrillation and flutter by Fourier analysis

The aim of this study was to characterize left atrial appendage mechanical function in atrial fibrillation and flutter by Fourier analysis to analyze frequency and regularity of flow. Left atrial appendage function is central to a patient's risk for thromboembolism. Although the function of the appendage can be analyzed by Doppler echocardiography in sinus rhythm, its mechanical function in atrial fibrillation and flutter has not been well characterized. This lack of adequate definition is caused by the complexity and temporal variability of the Doppler flow profiles. We assessed left atrial appendage function in 21 cases of atrial fibrillation (n - 11) and flutter (n = 10) and five in sinus rhythm with transesophageal Doppler echocardiography. Doppler profiles were examined by Fourier analysis, and the power spectra compared and analyzed between patients with atrial fibrillation and flutter. Left atrial appendage Doppler flow in atrial fibrillation produced Fourier spectra over a narrow band of frequencies with a peak frequency of 6.2 +/- 1.0 Hz, significantly higher than in atrial flutter (3.9 +/- 0.6 Hz, p < 0.00001). Additionally, a significant difference in subharmonic modulation (spectral power below the peak frequency) was observed between atrial appendage flow in atrial fibrillation and flutter, because 37% +/- 16% of the total spectral power was achieved before the dominant frequency in atrial fibrillation compared with 20% +/- 14% in atrial flutter (p = 0.02). Conversely, patients in sinus rhythm exhibited broad-banded Fourier spectra with most of the power in discrete frequency spikes at harmonics above the fundamental frequency with very little subharmonic modulation (1% +/- 0.05%). Left atrial appendage function in atrial fibrillation and flutter can be well characterized by Fourier analysis of Doppler flow. Atrial fibrillation has higher dominant frequencies and greater subharmonic modulation compared with flutter. Moreover, atrial fibrillation demonstrated quasiperiodic contraction patterns typically found in chaotic systems. Fourier analysis of left atrial appendage contraction patterns may therefore have significant promise in providing insights into mechanisms of atrial fibrillation and thromboembolism.

Chaos and chaos control in biology

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