Atrial Fibrillation Dominant Frequency Research Articles

Letter by Platonov et al Regarding Article, “Dominant Frequency of Atrial Fibrillation Correlates Poorly With Atrial Fibrillation Cycle Length”

To the Editor: We have read with interest the article by Elvan et al,1 who studied the agreement between the dominant frequency (DF) of atrial fibrillation (AF) and local atrial fibrillation cycle length (AFCL). They suggested that high-frequency sites, being a potential target for ablation, should be localized using AFCL as estimated from endocardial electrograms and not by selecting the largest spectral peak as DF. The authors refer to the study by Ng et al,2 which demonstrated that signal amplitude and AFCL variability affect …

Response to Letter Regarding Article, “Dominant Frequency of Atrial Fibrillation Correlates Poorly With Atrial Fibrillation Cycle Length”

Frequency-domain analysis has been considered as an alternative way to visualize atrial fibrillation (AF) electrograms for estimating the rate and regularity of activation without having to measure intervals in the time domain. In a response to our article,1 Platonov et al counter that AF cycle length (AFCL) estimation is too complex and that a method for finding the fundamental or dominant frequency (DF) is to be preferred. Although we agree that it is …

Circadian variation in dominant atrial fibrillation frequency in persistent atrial fibrillation

Circadian variation in atrial fibrillation (AF) frequency is explored in this paper by employing recent advances in signal processing. Once the AF frequency has been estimated and tracked by a hidden Markov model approach, the resulting trend is analyzed for the purpose of detecting and characterizing the presence of circadian variation. With cosinor analysis, the results show that the short-term variations in the AF frequency exceed the variation that may be attributed to circadian. Using the autocorrelation method, circadian variation was found in 13 of 18 ambulatory ECG recordings (Holter) acquired from patients with long-standing persistent AF. Using the ensemble correlation method, the highest AF frequency usually occurred during the afternoon, whereas the lowest usually occurred during late night. It is concluded that circadian variation is present in most patients with long-standing persistent AF though the short-term variation in the AF frequency is considerable and should be taken into account.

Letter by Berenfeld and Jalife Regarding Article “Dominant Frequency of Atrial Fibrillation Correlates Poorly With Atrial Fibrillation Cycle Length”

To the Editor: We read with interest the recent article by Elvan et al in Circulation: Arrhythmia and Electrophysiology .1 They compared the reliability of time-domain versus frequency-domain methods in determining the local activation rate in patients during atrial fibrillation (AF).2 The study provided potentially important information regarding the analysis of unipolar versus bipolar recordings. Unfortunately, essential details regarding the methods used for both the time-domain and the frequency-domain analyses were not presented. For example, information on the noise and frequency rejection criteria used for determination of AF cycle length in the time domain was nowhere to be found. Also crucial information on the …

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Dominant Frequency of Atrial Fibrillation Correlates Poorly With Atrial Fibrillation Cycle Length

Localized sites of high frequency during atrial fibrillation (AF) are used as target sites to eliminate AF. Spectral analysis is used experimentally to determine these sites. The purpose of this study was to compare dominant frequencies (DF) with AF cycle length (AFCL) of unipolar and bipolar recordings. Left and right atrial endocardial electrograms were recorded during AF in 40 patients with lone AF, using two 20-polar catheters. Mean age was 53+/-9.9 years. Unipolar and bipolar electrograms were recorded simultaneously during 16 seconds at 2 right and 4 left atrial sites. AFCLs and DFs were determined. QRS subtraction was performed in unipolar signals. DFs were compared with mean, median, and mode of AFCLs; 4800 unipolar and 2400 bipolar electrograms were analyzed. Intraclass correlation was poor for all spectral analysis protocols. Best correlation was accomplished with DFs from unipolar electrograms compared with median AFCL (intraclass correlation coefficient, 0.67). A gradient in median AFCL of >25% was detected in 16 of 40 patients. In 13 of 16 patients (81%) with a frequency gradient of >25%, the site with highest frequency was located in the left atrium (posterior left atrium in 8 patients). The site with shortest median AFCL and highest DF corresponded in 25% if unipolar and in 31% if bipolar electrograms were analyzed. DFs from unipolar and bipolar electrograms recorded during AF correlated poorly with mean, median, and mode AFCL. If a frequency gradient >25% existed, the site with highest DF corresponded to the site of shortest median AFCL in only 25% of patients. Because spectral analysis is being used to identify ablation sites, these data may have important clinical implications.

Ranolazine Exerts Potent Effects on Atrial Electrical Properties and Abbreviates Atrial Fibrillation Duration in the Intact Porcine Heart

In vitro studies and ambulatory ECG recordings from the MERLIN TIMI-36 clinical trial suggest that the novel antianginal agent ranolazine may have the potential to suppress atrial arrhythmias. However, there are no reports of effects of ranolazine on atrial electrophysiologic properties in large intact animals. In 12 closed-chest anesthetized pigs, effects of intravenous ranolazine (approximately 9 microM plasma concentration) on multisite atrial effective refractory period (ERP), conduction time (CT), and duration and inducibility of atrial fibrillation (AF) initiated by intrapericardial acetylcholine were investigated. Ranolazine increased ERP by a median of 45 ms (interquartile range 29-50 ms; P < 0.05, n = 6) in right and left atria compared to control at pacing cycle length (PCL) of 400 ms. However, ERP increased by only 28 (24-34) ms in right ventricle (P < 0.01, n = 6). Ranolazine increased atrial CT from 89 (71-109) ms to 98 (86-121) ms (P = 0.04, n = 6) at PCL of 400 ms. Ranolazine decreased AF duration from 894 (811-1220) seconds to 621 (549-761) seconds (P = 0.03, n = 6). AF was reinducible in 1 of 6 animals after termination with ranolazine compared with all 6 animals during control period (P = 0.07). Dominant frequency (DF) of AF was reduced by ranolazine in left atrium from 11.7 (10.7-20.5) Hz to 7.6 (2.9-8.8) Hz (P = 0.02, n = 6). Ranolazine, at therapeutic doses, increased atrial ERP to greater extent than ventricular ERP and prolonged atrial CT in a frequency-dependent manner in the porcine heart. AF duration and DF were also reduced by ranolazine. Potential role of ranolazine in AF management merits further investigation.

Relationship between the spectral characteristics of atrial fibrillation and atrial tachycardias that occur after catheter ablation of atrial fibrillation

During catheter ablation of complex fractionated atrial electrograms, persistent atrial fibrillation (AF) may convert to an atrial tachycardia (AT). The purpose of this study was to investigate the possible mechanisms of AT by examining the spectral and electrophysiologic characteristics of AF and ATs that occur after catheter ablation of AF. The subjects of this study were 33 consecutive patients with persistent AF who had conversion of AF to AT during ablation of AF (group I) and 20 consecutive patients who underwent ablation of persistent AT that developed more than 1 month after AF ablation (group II). Spectral analysis of the coronary sinus (CS) electrograms and lead V(1) was performed during AF at baseline, before conversion, and during AT. The spatial relationship between the AT mechanism and ablation sites was examined. A spectral component with a frequency that matched the frequency of AT was present in the baseline periodogram of AF more often in group I (52%) than in group II (20%, P = .02). Ablation resulted in a decrease in the dominant frequency of AF but not in the frequency of the spectral component that matched the AT. There was a significant direct relationship between the baseline dominant frequency of AF and the frequency of AT in the CS in group I (r = 0.76, P <.0001) but not in group II (r = 0.38, P = .09). ATs were macroreentrant in 64% and 60% of patients in groups I and II, respectively (P = .8). The AT site was more likely to be distant (>1 cm) from AF ablation sites in group I (70%) than in group II (35%, P = .007). The findings of this study suggest that ATs observed during ablation of AF often may be drivers of AF that become manifest after elimination of higher-frequency sources and fibrillatory conduction.

Frequency Tracking of Atrial Fibrillation Using Hidden Markov Models

A hidden Markov model (HMM) is employed to improve noise robustness when tracking the dominant frequency of atrial fibrillation (AF) in the electrocardiogram (ECG). Following QRST cancellation, a sequence of observed frequency states is obtained from the residual ECG, using the short-time Fourier transform. Based on the observed state sequence, the Viterbi algorithm retrieves the optimal state sequence by exploiting the state transition matrix, incorporating knowledge on AF characteristics, and the observation matrix, incorporating knowledge of the frequency estimation method and signal-to-noise ratio (SNR). The tracking method is evaluated with simulated AF signals to which noise, obtained from ECG recordings, has been added at different SNRs. The results show that the use of HMM improves performance considerably by reducing the rms error associated with frequency tracking: at 4-dB SNR, the rms error drops from 0.2 to 0.04 Hz.

Effects of Two Different Catheter Ablation Techniques on Spectral Characteristics of Atrial Fibrillation

The aim of this study was to determine the effects of circumferential pulmonary vein ablation (CPVA) and electrogram-guided ablation (EGA) on the spectral characteristics of atrial fibrillation (AF) and the relationship between changes in dominant frequency (DF) and clinical outcome. Circumferential pulmonary vein ablation and EGA have been used to eliminate AF. Spectral analysis may identify high-frequency sources. In 84 consecutive patients, CPVA (n = 42) or EGA (n = 42) was performed for paroxysmal (n = 49) or persistent (n = 35) AF. During EGA, complex electrograms were targeted. Lead V1 and electrograms from the left atrium and coronary sinus were analyzed to determine the DF of AF before and after ablation. The left atrial DF was higher in persistent (5.83 +/- 0.86 Hz) than paroxysmal AF (5.33 +/- 0.76 Hz, p = 0.03). There was a frequency gradient from the left atrium to the coronary sinus (p = 0.02). Circumferential pulmonary vein ablation and EGA resulted in a similar decrease in DF (18 +/- 17% vs. 17 +/- 15%, p = 0.8). During a mean follow-up of 9 +/- 6 months, the change in DF after CPVA was similar among patients with and without recurrent AF. An acute decrease in DF after EGA was associated with freedom from recurrent AF only in patients with persistent AF (19 +/- 14% vs. 3 +/- 6%, p = 0.02). Both CPVA and EGA decrease the DF of AF, consistent with elimination of high-frequency sources. Whereas the efficacy of EGA is associated with a decrease in DF in patients with persistent AF, the efficacy of CPVA is independent of changes in DF. This suggests that CPVA and EGA eliminate different mechanisms in the genesis of persistent AF.

The Mechanisms of an Increased Dominant Frequency in the Left Atrial Posterior Wall During Atrial Fibrillation in Acute Atrial Dilatation

Previous studies have shown that the highest dominant frequency (DF) is located in the left atrium (LA) during atrial fibrillation (AF) in pacing-induced AF. However, there have been few studies on the mechanisms of the increased DF of AF during acute atrial dilatation. The purpose of this study was to investigate the mechanisms of the increased maximal DF (max DF) in pacing-induced AF during acute atrial dilatation. In eight Langendorff-perfused canine hearts (26 +/- 2 kg), noncontact balloon catheters were placed into the right atrium (RA) and LA, respectively. AF was induced by extrastimulation pre- and postdilatation in the atrium (0 and 15 cm H(2)O, respectively). Fast Fourier transformation analysis was performed to analyze the max DF and harmonic index (HI) from the bi-atrial unipolar virtual electrograms during AF. The fibrillation cycle lengths were obtained from different atrial sites. The number of wavefronts was analyzed during AF. The frequency of regional splitting was defined as the number of wavefront splits per second in different atrial regions during AF. The percentage of the low-voltage zones (<0.5 mV) was defined as the ratio of the area of the low-voltage zones to the total atrial surface area. The DF was measured during AF. The shortest fibrillation cycle length was located in the LA posterior wall and became shorter during acute atrial dilatation. The max DF was located in the LA posterior wall and increased during acute atrial dilatation (7.1 +/- 0.8 vs 8.8 +/- 2.1, P = 0.02). The max DF of the LA correlated with the wavefront number (r = 0.797, P < 0.001 predilatation; r = 0.860, P < 0.001 postdilatation). The splitting of wavefronts facilitated the formation of new wavefronts. During acute atrial dilatation, the frequency of regional splitting was closely correlated with the percentage of the low-voltage zones (r = 0.876, P < 0.001). Furthermore, the LA posterior wall had a higher percentage of the low-voltage zones than the other sites. In acute atrial dilatation, the percentage of the low-voltage zones increased, especially in the LA posterior wall, which correlated with the regional splitting of the AF wavefronts. The increase in the splitting facilitated the formation of new wavefronts and resulted in a higher max DF during acute atrial dilatation.

Dominant frequency of atrial fibrillation estimated from the surface ECG

Dominant frequency of atrial fibrillation estimated from the surface ECG