Frequency analysis of atrial fibrillation surface and intracardiac electrograms during pulmonary vein isolation

Higher F-wave frequency associates with poor procedural success rate after Maze procedure

OBJECTIVES

Persistent atrial fibrillation (AF) causes atrial remodeling, which causes myocardial fibrosis and micro-reentry. Fibrosis may reduce wave voltage and micro-reentry may enhance the dominant frequency (DF) of the F-wave. We investigated whether the DF predicts procedural success by the Maze procedure.

METHODS

In 138 consecutive patients who underwent mitral valve surgery and a modified Cox-Maze III procedure for persistent AF in Nagoya University in 2002-2018, 96 (70%) were successfully cardioverted (group S); 42 had persistent or relapsed AF after surgery (group F). Patient data were compared between the groups. Cut-off values were determined by an ROC analysis and predictors of procedural success were evaluated. The DF was obtained from the F-wave of V1 by a high-speed Fourier analysis using the CEPAS software program.

RESULTS

Group F showed a significantly larger LA diameter, better LVEF, lower F-wave voltage, higher DF, and longer duration of AF. The cut-off values were as follows: LA diameter, 56 mm; EF, 64.5%; F-wave voltage, 0.13 mV; DF, 7.3 Hz; and duration of AF, 44 months. Each factor showed statistical significance in a univariate analysis; DF lost significance in the multivariate analysis. The higher (DF ≥ 7.3 Hz) and lower voltage group (≤ 0.13 mV) showed the worst procedural success rate (36%), while the lower DF (< 7.3 Hz) and higher voltage group (> 0.13 mV) showed a good rate (86%).

CONCLUSIONS

The DF of the F-wave is a useful predictor of procedural success after the Maze procedure in addition to the voltage of F-wave.

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.

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.

The impact of the dominant frequency of body surface electrocardiography in patients with persistent atrial fibrillation

The dominant frequency (DF) of atrial fibrillation (AF) reflects atrial electrical activity. However, the relationship between DF measured using surface electrocardiography (ECG) and AF ablation success remains unclear. This study aimed to clarify whether the DF of surface ECG in patients with persistent AF could predict arrhythmia recurrence after catheter ablation. We investigated 125 patients with persistent AF who underwent catheter ablation between January 2009 and December 2016. Thirty-four patients (27%) had arrhythmia recurrence after catheter ablation. These patients showed a significantly high DF value in leads aVL (7.2 ± 0.7 Hz vs 6.6 ± 0.9 Hz, p < 0.001) and V1 (7.4 ± 0.8 Hz vs 6.7 ± 0.7 Hz, p < 0.001). We set the cutoff value of DF as 6.9 Hz in lead aVL (sensitivity, 80%; specificity, 63%) and as 7.1 Hz in lead V1 (sensitivity, 72%; specificity, 67%). Patients with DF < 6.9 Hz in lead aVL showed a significantly higher recurrence-free rate than those with DF ≥ 6.9 Hz (88% vs 45%; p < 0.001). Patients with DF of < 7.1 Hz in lead V1 showed a significantly higher recurrence-free rate than those with DF of  ≥ 7.1 (87% vs 47%; p < 0.001). Patients with a high DF in leads aVL and V1 showed a lower success rate of persistent AF ablation. The DF measured from surface ECG can be a useful marker to predict ablation success.

Severe and uniform bi-atrial remodeling measured by dominant frequency analysis in persistent atrial fibrillation unresponsive to ablation

BACKGROUND

High values of ECG and intracardiac dominant frequency (DF) are indicative of significant atrial remodeling in persistent atrial fibrillation (peAF). We hypothesized that patients with peAF unresponsive to ablation display higher ECG and intracardiac DFs than those remaining in sinus rhythm (SR) on the long term.

METHODS

Forty consecutive patients underwent stepwise ablation for peAF (sustained duration 19 ± 11 months). Electrograms were recorded before ablation at 13 left atrium (LA) sites and at the right atrial appendage (RAA) and coronary sinus (CS) synchronously to the ECG. DF was defined as the highest peak within the power spectrum.

RESULTS

peAF was terminated within the LA 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 12 NLT patients had a recurrence. Of the LT patients, 71% had a recurrence (20/28, LT_Rec), while 29% remained in SR throughout the follow-up (8/28, LT_SR). DF values and correlations between pairs of LA appendage (LAA), RAA, and CS DFs showed distinctive patterns among the subgroups. The NLT subgroup displayed the highest ECG and intracardiac DFs, with strong intragroup homogeneity between pairs of CS and LAA DFs, and to a lesser extent between pairs of CS and RAA DFs. Conversely, the LT_SR subgroup showed the lowest DFs, with significant intragroup heterogeneity between pairs of CS and both LAA and RAA DFs.

CONCLUSIONS

Patients with peAF unresponsive to ablation show high surface and intracardiac DFs indicative of severe and uniform bi-atrial remodeling.

Diagnosis and management of atrial fibrillation: an overview

Atrial fibrillation (AF) has been defined as the new cardiovascular "epidemic". Its prevalence is rising in developed countries, and the associated social and economic costs are high. In the last few years, there has been an increasing interest in understanding the mechanisms of AF and its management. New pharmacotherapies together with novel techniques for surgical and catheter treatment of AF have been developed, allowing the maintenance of sinus rhythm and the alleviation of symptoms in a large number of patients with AF. However, there are still some challenges that need to be addressed. This article gives an overview of the current state of the art on novel techniques for diagnosis and management of AF.

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.