"Pharmacological" analysis of atrial fibrillation maintenance mechanism: reentry, wavelets, or focal?

The primary electrophysiological mechanism of atrial fibrillation (AF) maintenance is poorly defined. AF mapping studies readily record focal activations (defining them as focal sources or breakthroughs) and "incomplete reentries" (defining them as reentries or would-be-reentries) but do not or rarely detect complete circular activations. Electrophysiological alterations induced by anti-AF drugs before AF cardioversion may help delineate the mechanism of AF maintenance. Cardioversion of AF by antiarrhythmic drugs is associated with prolongation of the AF cycle length and temporal excitable gap (t-EG), resulting in improvement in AF organization (AF-org), and with or without alterations in the refractory period, conduction velocity and wavelength. Such electrophysiological pattern is conceivable with termination of a single focal source but not a single reentry (Class III agents do not increase reentrant t-EG). Yet, a single focal source and multiple focal sources are plausible as the primary mechanism of AF maintenance prior drug administration. Improvement in AF-org caused by anti-AF agents before AF cardioversion is coherent with simultaneous multiple random reentries and wavelets. However, simultaneous multiple reentries are unlikely to occur regularly (most of the contemporary AF mapping studies report either a single reentry at a time or no reentry at all), and the ability of random wavelets to maintain AF is speculative. The conducted analysis inclines toward the focal source as the primary mechanism of AF maintenance.

Combination of frequency- and time-domain characteristics of the fibrillatory waves for enhanced prediction of persistent atrial fibrillation recurrence after catheter ablation

Catheter ablation (CA) remains the cornerstone alternative to cardioversion for sinus rhythm (SR) restoration in patients with atrial fibrillation (AF). Unfortunately, despite the last methodological and technological advances, this procedure is not consistently effective in treating persistent AF. Beyond introducing new indices to characterize the fibrillatory waves (f-waves) recorded through the preoperative electrocardiogram (ECG), the aim of this study is to combine frequency- and time-domain features to improve CA outcome prediction and optimize patient selection for the procedure, given the absence of any study that jointly analyzes information from both domains. Precisely, the f-waves of 151 persistent AF patients undergoing their first CA procedure were extracted from standard V1 lead. Novel spectral and amplitude features were derived from these waves and combined through a machine learning algorithm to anticipate the intervention mid-term outcome. The power rate index (φ), which estimates the power of the harmonic content regarding the dominant frequency (DF), yielded the maximum individual discriminant ability of 64% to discern between individuals who experienced a recurrence of AF and those who sustained SR after a 9-month follow-up period. The predictive accuracy was improved up to 78.5% when this parameter φ was merged with the amplitude spectrum area in the DF bandwidth (A M S A L F ) and the normalized amplitude of the f-waves into a prediction model based on an ensemble classifier, built by random undersampling boosting of decision trees. This outcome suggests that the synthesis of both spectral and temporal features of the f-waves before CA might enrich the prognostic knowledge of this therapy for persistent AF patients.

The frequency of atrial fibrillatory waves is modulated by the spatiotemporal pattern of acetylcholine release: a 3D computational study

In atrial fibrillation (AF), the ECG P-wave, which represents atrial depolarization, is replaced with chaotic and irregular fibrillation waves (f waves). The f-wave frequency, F f, shows significant variations over time. Cardiorespiratory interactions regulated by the autonomic nervous system have been suggested to play a role in such variations. We conducted a simulation study to test whether the spatiotemporal release pattern of the parasympathetic neurotransmitter acetylcholine (ACh) modulates the frequency of atrial reentrant circuits. Understanding parasympathetic involvement in AF may guide more effective treatment approaches and could help to design autonomic markers alternative to heart rate variability (HRV), which is not available in AF patients. 2D tissue and 3D whole-atria models of human atrial electrophysiology in persistent AF were built. Different ACh release percentages (8% and 30%) and spatial ACh release patterns, including spatially random release and release from ganglionated plexi (GPs) and associated nerves, were considered. The temporal pattern of ACh release, ACh(t), was simulated following a sinusoidal waveform of frequency 0.125 Hz to represent the respiratory frequency. Different mean concentrations ( A C h ¯ ) and peak-to-peak ranges of ACh (ΔACh) were tested. We found that temporal variations in F f, F f(t), followed the simulated temporal ACh(t) pattern in all cases. The temporal mean of F f(t), F ¯ f , depended on the fibrillatory pattern (number and location of rotors), the percentage of ACh release nodes and A C h ¯ . The magnitude of F f(t) modulation, ΔF f, depended on the percentage of ACh release nodes and ΔACh. The spatial pattern of ACh release did not have an impact on F ¯ f and only a mild impact on ΔF f. The f-wave frequency, being indicative of vagal activity, has the potential to drive autonomic-based therapeutic actions and could replace HRV markers not quantifiable from AF patients.

Study of ECG-derived atrial fibrillatory rate for prediction of the outcome of cardioversion of short duration atrial fibrillation (CASAF)

AIMS

The present study aimed at testing the hypothesis that atrial fibrillatory rate (AFR) is predictive of sinus rhythm maintenance after electrical cardioversion.

METHODS AND RESULTS

The study comprised 32 patients admitted for cardioversion of atrial fibrillation of short duration (mean duration 3.8 ± 7.7 days). AFR was estimated using frequency power spectrum analysis of QRST-cancelled ECG. At six-weeks follow-up 22% of the patients had relapsed to AF. The pre-cardioversion mean AFR of those was 332 ± 64 fpm compared to 378 ± 59 fpm among patients maintaining sinus rhythm (p = 0.12).

CONCLUSION

AFR was not predictive of sinus rhythm maintenance in patients of short duration AF undergoing cardioversion. This is in stark contrast with the earlier reported findings.

CLINICAL TRIAL REGISTRATION

NCT02112318 (http://www.

CLINICALTRIALS

gov).

Heart rate characteristic based modelling of atrial fibrillatory rate using implanted cardiac monitor data

Objective. The objective of the present study is to investigate the feasibility of using heart rate characteristics to estimate atrial fibrillatory rate (AFR) in a cohort of atrial fibrillation (AF) patients continuously monitored with an implantable cardiac monitor. We will use a mixed model approach to investigate population effect and patient specific effects of heart rate characteristics on AFR, and will correct for the effect of previous ablations, episode duration, and onset date and time.Approach. The f-wave signals, from which AFR is estimated, were extracted using a QRST cancellation process of the AF episodes in a cohort of 99 patients (67% male; 57 ± 12 years) monitored for 9.2(0.2-24.3) months as median(min-max). The AFR from 2453 f-wave signals included in the analysis was estimated using a model-based approach. The association between AFR and heart rate characteristics, prior ablations, and episode-related features were modelled using fixed-effect and mixed-effect modelling approaches.Main results. The mixed-effect models had a better fit to the data than fixed-effect models showing h.c. of determination (R2 = 0.49 versusR2 = 0.04) when relating the variations of AFR to the heart rate features. However, when correcting for the other factors, the mixed-effect model showed the best fit (R2 = 0.04). AFR was found to be significantly affected by previous catheter ablations (p< 0.05), episode duration (p< 0.05), and irregularity of theRRinterval series (p< 0.05).Significance. Mixed-effect models are more suitable for AFR modelling. AFR was shown to be faster in episodes with longer duration, less organizedRRintervals and after several ablation procedures.

A comparative study of the performance of methods for f-wave extraction

Objective.This study proposes a novel technique for atrial fibrillatory waves (f-waves) extraction and investigates the performance of the proposed method comparing with different f-wave extraction methods.Approach.We propose a novel technique combining a periodic component analysis (PiCA) and echo state network (ESN) for f-waves extraction, denoted PiCA-ESN. PiCA-ESN benefits from the advantages of using both source separation and nonlinear adaptive filtering. PiCA-ESN is evaluated by comparing with other state-of-the-art approaches, which include template subtraction technique based on principal component analysis, spatiotemporal cancellation, nonlinear adaptive filtering using an echo state neural network, and a source separation technique based on PiCA. Quality assessment is performed on a recently published reference database including a large number of simulated ECG signals in atrial fibrillation (AF). The performance of the f-wave extraction methods is evaluated in terms of signal quality metrics (SNR, ΔSNR) and robustness of f-wave features.Main results.The proposed method offers the best signal quality performance, with a ΔSNR of approximately 22 dB across all 8 sets of the reference database, as well as the most robust extraction of f-wave features, with 75% of all estimates of dominant atrial frequency well below 1 Hz.

A subspace projection approach to quantify respiratory variations in the f-wave frequency trend

Background: The autonomic nervous system (ANS) is known as a potent modulator of the initiation and perpetuation of atrial fibrillation (AF), hence information about ANS activity during AF may improve treatment strategy. Respiratory induced ANS variation in the f-waves of the ECG may provide such information.

Objective: This paper proposes a novel approach for improved estimation of such respiratory induced variations and investigates the impact of deep breathing on the f-wave frequency in AF patients.

Methods: A harmonic model is fitted to the f-wave signal to estimate a high-resolution f-wave frequency trend, and an orthogonal subspace projection approach is employed to quantify variations in the frequency trend that are linearly related to respiration using an ECG-derived respiration signal. The performance of the proposed approach is evaluated and compared to that of a previously proposed bandpass filtering approach using simulated f-wave signals. Further, the proposed approach is applied to analyze ECG data recorded for 5 min during baseline and 1 min deep breathing from 28 AF patients from the Swedish cardiopulmonary bioimage study (SCAPIS).

Results: The simulation results show that the estimates of respiratory variations obtained using the proposed approach are more accurate than estimates obtained using the previous approach. Results from the analysis of SCAPIS data show no significant differences between baseline and deep breathing in heart rate (75.5 ± 22.9 vs. 74 ± 22.3) bpm, atrial fibrillation rate (6.93 ± 1.18 vs. 6.94 ± 0.66) Hz and respiratory f-wave frequency variations (0.130 ± 0.042 vs. 0.130 ± 0.034) Hz. However, individual variations are large with changes in heart rate and atrial fibrillatory rate in response to deep breathing ranging from −9% to +5% and −8% to +6%, respectively and there is a weak correlation between changes in heart rate and changes in atrial fibrillatory rate (r = 0.38, p &lt; 0.03).

Conclusion: Respiratory induced f-wave frequency variations were observed at baseline and during deep breathing. No significant changes in the magnitude of these variations in response to deep breathing was observed in the present study population.

Respiratory Induced Modulation in f-Wave Characteristics During Atrial Fibrillation

The autonomic nervous system (ANS) is an important factor in cardiac arrhythmia, and information about ANS activity during atrial fibrillation (AF) may contribute to personalized treatment. In this study we aim to quantify respiratory modulation in the f-wave frequency trend from resting ECG. First, an f-wave signal is extracted from the ECG by QRST cancelation. Second, an f-wave model is fitted to the f-wave signal to obtain a high resolution f-wave frequency trend and an index for signal quality control ( S ). Third, respiratory modulation in the f-wave frequency trend is extracted by applying a narrow band-pass filter. The center frequency of the band-pass filter is determined by the respiration rate. Respiration rate is estimated from a surrogate respiration signal, obtained from the ECG using homomorphic filtering. Peak conditioned spectral averaging, where spectra of sufficient quality from different leads are averaged, is employed to obtain a robust estimate of the respiration rate. The envelope of the filtered f-wave frequency trend is used to quantify the magnitude of respiratory induced f-wave frequency modulation. The proposed methodology is evaluated using simulated f-wave signals obtained using a sinusoidal harmonic model. Results from simulated signals show that the magnitude of the respiratory modulation is accurately estimated, quantified by an error below 0.01 Hz, if the signal quality is sufficient ( S > 0 . 5 ). The proposed method was applied to analyze ECG data from eight pacemaker patients with permanent AF recorded at baseline, during controlled respiration, and during controlled respiration after injection of atropine, respectively. The magnitude of the respiratory induce f-wave frequency modulation was 0.15 ± 0.01, 0.18 ± 0.02, and 0.17 ± 0.03 Hz during baseline, controlled respiration, and post-atropine, respectively. Our results suggest that parasympathetic regulation affects the magnitude of respiratory induced f-wave frequency modulation.

Minor allele of GJA1 gene polymorphism is associated with higher heart rate during atrial fibrillation

Atrial fibrillation (AF) tachycardia causes heart failure and requires more attention. The genetic background of individual heart rate (HR) variations during AF are unclear. We hypothesized that HR-associated single nucleotide polymorphisms (SNPs) reported in Genome-Wide Association Studies (GWAS) are also associated with HR during AF. We enrolled patients with persistent AF (311 for screening and 146 for replication) who underwent AF ablation and were genotyped for the 21 h-associated SNPs reported in GWAS. The patients underwent 24-h Holter monitoring before AF ablation and electrophysiological study after AF ablation during sinus rhythm. Only the GJA1 SNP rs1015451 (T>C) was significantly associated with total HR (TT 110,643 ± 17,542 beats/day, TC 116,350 ± 19,060 beats/day, CC 122,163 ± 25,684 beats/day, P = 8.5 × 10⁻⁴). We also confirmed this significant association in the replication set. The intra-atrial conduction was faster in AF patients with the GJA1 minor allele than in those without it. Multivariate analysis revealed the presence of a GJA1 SNP rs1015451 additive model, female gender, lower left ventricular ejection fraction, and higher 1:1 atrioventricular nodal conduction were independently associated with higher HR during AF. The GJA1 SNP might be a new genetic marker for AF tachycardia.

Effect of selective IK,ACh inhibition by XAF-1407 in an equine model of tachypacing-induced persistent atrial fibrillation

BACKGROUND AND PURPOSE

Inhibition of the G-protein gated ACh-activated inward rectifier potassium current, I_K,ACh may be an effective atrial selective treatment strategy for atrial fibrillation (AF). Therefore, the anti-arrhythmic and electrophysiological properties of a novel putatively potent and highly specific I_K,ACh inhibitor, XAF-1407 (3-methyl-1-[5-phenyl-4-[4-(2-pyrrolidin-1-ylethoxymethyl)-1-piperidyl]thieno[2,3-d]pyrimidin-6-yl]azetidin-3-ol), were characterised for the first time in vitro and investigated in horses with persistent AF.

EXPERIMENTAL APPROACH

The pharmacological ion channel profile of XAF-1407 was investigated using cell lines expressing relevant ion channels. In addition, eleven horses were implanted with implantable cardioverter defibrillators enabling atrial tachypacing into self-sustained AF. The electrophysiological effects of XAF-1407 were investigated after serial cardioversions over a period of 1 month. Cardioversion success, drug-induced changes of atrial tissue refractoriness, and ventricular electrophysiology were assessed at baseline (day 0) and days 3, 5, 11, 17, and 29 after AF induction.

KEY RESULTS

XAF-1407 potently and selectively inhibited K_ir 3.1/3.4 and K_ir 3.4/3.4, underlying the I_K,ACh current. XAF-1407 treatment in horses prolonged atrial effective refractory period as well as decreased atrial fibrillatory rate significantly (~20%) and successfully cardioverted AF, although with a decreasing efficacy over time. XAF-1407 shortened atrioventricular-nodal refractoriness, without effect on QRS duration. QTc prolongation (4%) within 15 min of drug infusion was observed, however, without any evidence of ventricular arrhythmia.

CONCLUSION AND IMPLICATIONS

XAF-1407 efficiently cardioverted sustained tachypacing-induced AF of short duration in horses without notable side effects. This supports I_K,ACh inhibition as a potentially safe treatment of paroxysmal AF in horses, suggesting potential clinical value for other species including humans.

Longitudinal study of electrical, functional and structural remodelling in an equine model of atrial fibrillation

Background

Large animal models are important in atrial fibrillation (AF) research, as they can be used to study the pathophysiology of AF and new therapeutic approaches. Unlike other animal models, horses spontaneously develop AF and could therefore serve as a bona fide model in AF research. We therefore aimed to study the electrical, functional and structural remodelling caused by chronic AF in a horse model.

Method

Nine female horses were included in the study, with six horses tachypaced into self-sustained AF and three that served as a time-matched sham-operated control group. Acceleration in atrial fibrillatory rate (AFR), changes in electrocardiographic and echocardiographic variables and response to medical treatment (flecainide 2 mg/kg) were recorded over a period of 2 months. At the end of the study, changes in ion channel expression and fibrosis were measured and compared between the two groups.

Results

AFR increased from 299 ± 33 fibrillations per minute (fpm) to 376 ± 12 fpm (p < 0.05) and atrial function (active left atrial fractional area change) decreased significantly during the study (p < 0.05). No changes were observed in heart rate or ventricular function. The AF group had more atrial fibrosis compared to the control group (p < 0.05). No differences in ion channel expression were observed.

Conclusion

Horses with induced AF show signs of atrial remodelling that are similar to humans and other animal models.

Reference database and performance evaluation of methods for extraction of atrial fibrillatory waves in the ECG

OBJECTIVE

This study proposes a reference database, composed of a large number of simulated ECG signals in atrial fibrillation (AF), for investigating the performance of methods for extraction of atrial fibrillatory waves (f-waves).

APPROACH

The simulated signals are produced using a recently published and validated model of 12-lead ECGs in AF. The database is composed of eight signal sets together accounting for a wide range of characteristics known to represent major challenges in f-wave extraction, including high heart rates, high morphological QRST variability, and the presence of ventricular premature beats. Each set contains 30 5 min signals with different f-wave amplitudes. The database is used for the purpose of investigating the statistical association between different indices, designed for use with either real or simulated signals.

MAIN RESULTS

Using the database, available at the PhysioNet repository of physiological signals, the performance indices unnormalized ventricular residue (uVR), designed for real signals, and the root mean square error, designed for simulated signals, were found to exhibit the strongest association, leading to the recommendation that uVR should be used when characterizing performance in real signals.

SIGNIFICANCE

The proposed database facilitates comparison of the performance of different f-wave extraction methods and makes it possible to express performance in terms of the error between simulated and extracted f-wave signals.

The stationary wavelet transform as an efficient reductor of powerline interference for atrial bipolar electrograms in cardiac electrophysiology

OBJECTIVE

The most relevant source of signal contamination in the cardiac electrophysiology (EP) laboratory is the ubiquitous powerline interference (PLI). To reduce this perturbation, algorithms including common fixed-bandwidth and adaptive-notch filters have been proposed. Although such methods have proven to add artificial fractionation to intra-atrial electrograms (EGMs), they are still frequently used. However, such morphological alteration can conceal the accurate interpretation of EGMs, specially to evaluate the mechanisms supporting atrial fibrillation (AF), which is the most common cardiac arrhythmia. Given the clinical relevance of AF, a novel algorithm aimed at reducing PLI on highly contaminated bipolar EGMs and, simultaneously, preserving their morphology is proposed.

APPROACH

The method is based on the wavelet shrinkage and has been validated through customized indices on a set of synthesized EGMs to accurately quantify the achieved level of PLI reduction and signal morphology alteration. Visual validation of the algorithm's performance has also been included for some real EGM excerpts.

MAIN RESULTS

The method has outperformed common filtering-based and wavelet-based strategies in the analyzed scenario. Moreover, it possesses advantages such as insensitivity to amplitude and frequency variations in the PLI, and the capability of joint removal of several interferences.

SIGNIFICANCE

The use of this algorithm in routine cardiac EP studies may enable improved and truthful evaluation of AF mechanisms.

Atrial fibrillation frequency tracking in ambulatory ECG signals: The significance of signal quality assessment

An approach to atrial fibrillation (AF) frequency tracking in long-term ambulatory ECG recordings is presented, comprising f-wave extraction, dominant atrial frequency (DAF) tracking, and signal quality assessment. Since poor signal quality is commonly encountered in ambulatory monitoring, a recently proposed index is employed to assess f-wave signal quality in a database containing 38 patients with permanent AF. The index ensures that DAF outliers, typically associated with poor-quality segments, are excluded from further analysis. 40% of all 5-s signal segments were excluded from the database due to poor quality. The exclusion of DAF outliers significantly reduces the standard deviation of the frequency estimates (p≤0.01), allowing more reliable evaluation of the difference between day- and night-time DAF. The results show that signal quality assessment plays a central role in DAF tracking, and therefore should be employed in ambulatory monitoring.

Is extensive atrial fibrosis in the setting of heart failure associated with a reduced atrial fibrillation burden?

Atrial fibrillation (AF) affects 10-50% of patients with chronic heart failure (HF) and is associated with poor long-term prognosis. AF is commonly associated with atrial structural remodeling (ASR), principally characterized by atrial dilatation and fibrosis. However, the occurrence of AF in the full spectrum of ASR encountered in patients with HF is poorly defined. Experimental studies have presented evidence that extensive ASR can be accompanied with a reduced burden of AF, secondary to a prominent depression of atrial excitability. This reduction in AF burden is associated with severe atrial fibrosis rather than with dilatation. Clinical studies of patients with HF point to the possibility that advanced ASR is associated with a less frequent AF occurrence than moderate ASR. Our goal in this review is to introduce the hypothesis that AF is less likely to occur in severe versus moderate atrial ASR in the setting of HF and that it is severe atrial fibrosis-associated depression of atrial excitability that reduces AF burden.

Effect of flecainide on atrial fibrillatory rate in a large animal model with induced atrial fibrillation

Background

Atrial fibrillatory cycle length has been considered one of the indices of atrial electrical remodelling during atrial fibrillation (AF), which can be assessed from surface ECG by computer-assisted calculation of atrial fibrillatory rate (AFR). Horses have been suggested as a bona fide model for AF studies since horses too, develop lone AF, however data on AF characteristics in horses are extremely sparse and non-invasive characterization of AF complexity using surface ECG processing has not been reported.

Aim

The aim was to study characteristics of induced AF and its modification by flecainide.

Methods

The study group consisted on 3 horses with spontaneous persistent AF and 13 with pace-induced AF. Seven horses were treated with saline (control) and eight with flecainide (2 mg/kg). ECGs were analysed using spatiotemporal cancellation of QRST complexes and calculation of AFR from the residual atrial signal.

Results

At AF onset, AFR was 295 ± 52 fibrillations per minute (fpm) in the horses with induced AF treated with flecainide, 269 ± 36 fpm in the control group (ns), and 364 ± 26 fpm in the horses with spontaneous persistent AF (P < 0.05 compared to the control group). Flecainide caused a decrease in AFR in all animals and restored sinus rhythm in the animals with induced AF. In the control animals, AFR increased from 269 ± 36 fpm to a plateau of 313 ± 14 fpm before decreasing to 288 ± 28 fpm during the last 10% of the AF episodes preceding spontaneous conversion (P < 0.05).

Conclusion

AFR in horses with induced AF resembles AFR in humans with paroxysmal AF. Flecainide caused a rapid decrease in AFR in all horses, further supporting the method to be a non-invasive technique to study the effect of antiarrhythmic compounds.

Autonomic influence on atrial fibrillatory process: head-up and head-down tilting

BACKGROUND

Changes in the autonomic nervous system (ANS) tone are present before, during, and after episodes of atrial fibrillation (AF). Atrial fibrillatory rate (AFR, the inverse of the atrial cycle length) has been used as a surrogate marker for local refractoriness and is a key characteristic of the fibrillatory process in patients with AF. Aim of this study is to assess changes in AFR, as an effect of autonomic balance change.

METHODS

Forty patients undergoing cardiac cardioversion for symptomatic persistent AF were included in the study. Surface ECG was recorded during rest, head-down (HDT, -30°), and head-up tilt (HUT, +60°). A median value of AFR was computed in each phase of the protocol.

RESULTS

AFR decreased during HDT compared to the baseline (B) condition in all patients but three (median AFR_B = 391 fpm vs. AFR_HDT = 377 fpm, p < .0001). HUT increased AFR, making it significantly higher than HDT and baseline conditions (median AFR_HUT = 396 fpm, p < .0001 vs. B and HDT). Heart rate (HR) increased during HUT, but had a heterogeneous behavior in the population during HDT: about one third of the patients had an HR lower during HDT than during baseline, whereas the remaining two third had an increase in HR during HDT.

CONCLUSIONS

Dominant sympathetic/vagal tone during HUT/HDT significantly affects AFR, increasing/decreasing in respect to baseline. It may be worth exploring the possibility that patients with AF of shorter duration can convert to sinus rhythm during HDT.