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. 2016 May 26;22(1):e12369. doi: 10.1111/anec.12369

Spectral Analysis of Electrocardiograms in Patients with Inducible Atrial Fibrillation after Catheter Ablation Predicts Sinus Rhythm Maintenance

Stavros Stavrakis 1,✉, John W Dyer 1, Benjamin J Scherlag 1, Zeeshan Khan 1, Paul Yeung 1, Jawad Chohan 1, Sunny S Po 1
PMCID: PMC6931444  PMID: 27226336

Abstract

Background

We aimed to develop a novel predictive marker for atrial fibrillation (AF) recurrence in patients with inducible AF after catheter ablation, based on power spectral analysis of baseline and postablation electrocardiograms.

Methods

Twenty‐five patients who had undergone their first AF ablation procedure (pulmonary vein isolation and ganglionated plexi ablation) and had inducible AF after ablation were included. A 30‐second interval of AF was chosen for each patient before and after ablation, and a periodogram of the atrial activity was computed. A ratio of the power in the dominant frequency to the power in the remainder of the periodogram (DFR) was calculated.

Results

Eight (32%) patients had recurrent AF at 1 year. The clinical and echocardiographic characteristics of patients with and without recurrence were similar (P > 0.05). After ablation, there was organization of atrial activity, evidenced by an increase in the DFR (0.28 ± 0.22 vs 0.53 ± 0.29; P = 0.001). The percent change in DFR before and after ablation (median [interquartile range]) was significantly higher in patients without AF recurrence (120% [30% to 344%] vs 3% [−27% to 66%]; P = 0.01). Receiver operating curve (ROC) analysis demonstrated that a less than 16% increase in DFR postablation was able to predict recurrence of AF (area under ROC curve = 0.82; P = 0.03) with 75% sensitivity and 94% specificity.

Conclusion

AF ablation leads to variable organization of atrial activity. Organization of atrial activity after AF ablation is associated with lower 1‐year recurrence rates and may be used intraprocedurally after as a novel end point for AF ablation. Larger prospective studies are warranted.

Keywords: atrial fibrillation, electrocardiography, spectral analysis, catheter ablation

Atrial fibrillation (AF) is the most common clinically significant cardiac arrhythmia.1 Catheter ablation is currently the treatment of choice for maintenance of sinus rhythm in patients with symptomatic, drug‐refractory paroxysmal or persistent AF,2, 3 but its long‐term efficacy is relatively poor.4, 5 However, catheter ablation is associated with a major complication rate of about 6%.2, 3 Several factors have been associated with decreased efficacy of catheter ablation, including increased left atrial volumes,6 sleep apnea,7 and left atrial fibrosis.8 Inducibility of AF after circumferential pulmonary vein (PV) isolation is also a significant predictor of AF recurrence,9, 10 but some studies questioned the reliability of noninducibility as a procedural end point, indicating that the predictive accuracy of this end point is rather poor.11 Given the poor long‐term efficacy of catheter ablation, a predictive marker for long‐term ablation success that can be assessed intraprocedurally and can possibly guide therapy is very attractive.

Ablation of the major ganglionated plexi (GP) has been shown to provide additional benefits to the standard circumferential PV isolation procedure in a recent randomized clinical trial.12 However, GP ablation may also lead to iatrogenic atrial macroreentrant tachycardias, by creating narrow channels within the left atrium.13 Therefore, a marker that allows avoiding the potential complications of GP ablation while maintaining its beneficial effect would be very helpful. In a recent experimental study, GP ablation was associated with distinct changes in the spectral characteristics of intracardiac atrial electrograms, such as a significant decrease in the dominant frequency and increase in the regularity index, a marker of organization of the atrial activity.14 Moreover, an increase in the organization index, based on spectral analysis of intracardiac electrograms, predicted conversion to sinus rhythm with flecainide in patients who remained in AF at the end of the catheter ablation procedure,15 while organization of the spectral characteristics of the surface electrocardiogram (ECG) was associated with sinus rhythm maintenance in patients undergoing electrical cardioversion of AF.16 In this study, we aimed to develop a novel predictive marker for AF recurrence in patients with inducible AF after catheter ablation, based on power spectral analysis comparison of baseline and postablation ECGs.

Methods

Seventy‐eight patients underwent their first ablation procedure for symptomatic, drug‐refractory paroxysmal or persistent AF at our institution between January 2012 and June 2013. Of those, 25 patients who had undergone their first AF ablation procedure for paroxysmal (n = 19) or persistent (n = 6) AF and had inducible AF after ablation were included in this study. In these patients, we analyzed the spectral content of composite atrial activity extracted from the 12‐lead ECG before and after undergoing catheter ablation for AF, which consisted of GP ablation plus PV isolation by radiofrequency applications.13 The ablation procedure was performed under general anesthesia in all patients. After transseptal puncture, an electroanatomical map (CARTO) of the left atrium and PVs was created. GP was identified using high‐frequency stimulation, which elicited a parasympathetic response at the respective areas, as previously described.13 The ablation procedures used an irrigated tip catheter (Thermocool; Biosense Webster, Inc., Diamond Bar, CA, USA) and followed a standard sequence as reported by Po et al.13 The superior left GP was ablated first, followed by the inferior left GP. Subsequently, the anterior right GP and inferior right GP were identified and ablated. After GP ablation, if the patient did not convert to sinus rhythm during GP ablation, direct current cardioversion was performed and PV isolation was done during distal coronary sinus pacing. A circular mapping catheter (Lasso, Biosense Webster, Inc.) was used to confirm entrance and exit block during PV isolation. After PV isolation was confirmed, burst atrial pacing (250 ms decrementing to 200 ms) was performed to induce any tachyarrhythmias. If a sustained atrial tachycardia was induced, this was mapped and ablated accordingly. If sustained AF was induced, the patient was cardioverted to sinus rhythm and the procedure was terminated.

Baseline clinical and echocardiographic data and 1‐year follow‐up data for each patient were obtained from a chart review. As part of our standard practice, all patients were followed at 1, 3, 6 and 12 months with an outpatient office visit. At each visit, a brief history and physical examination were performed, and a 12‐lead ECG and any cardiovascular events, including AF recurrence within the prior 3 months, were recorded.

Data Acquisition and Signal Processing

In 25 patients, a 12‐lead surface ECG was recorded during induced AF before and after GP ablation and PV antrum isolation. Data were sampled at 1000 Hz and prefiltered between 0.05 and 250 Hz. The atrial activity was extracted from the ECG using an independent component analysis (ICA) method.17 This method extracts a composite representation of all atrial activity, rather than the specific atrial activity seen in any one lead. The resulting atrial signal was then subjected to spectral analysis. The ICA method was chosen for analysis of the clinical data based on its more automated nature. Langley et al.18 suggested that the residual atrial signal is similar for a number of methods, including both QRST removal and ICA methods. Figure 1 shows the extracted composite atrial activity above the individual 12 leads of the 12‐lead ECG. It should be noted that the atrial signal has been magnified for clarity. A 30‐second interval of AF was chosen for each patient before and after ablation, after manually inspecting the AF tracings over a 3‐ to 5‐minute interval (when available) to ensure temporal stability. The extracted composite atrial signal was bandpass filtered, bidirectionally, between 3 and 35 Hz using a fourth‐order Butterworth filter that was maximally flat and had linear phase in the pass band. The filtered data were then subjected to a modified periodogram (MPDG), which was computed based on a fast Fourier transform (FFT), windowing the data with a Weierstrass (Gaussian) Window of sufficient width to minimize edge truncation effects. Computations were made using MATLAB technical computing software (MathWorks, Natick, MA, USA). A ratio of the power in the dominant frequency (within a 1‐Hz band) and all its harmonics to the power in the remainder of the periodogram (DFR) was computed. The investigator performing the spectral analysis was blinded to the clinical outcome data.

Figure 1.

Figure 1

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Global atrial activity extracted from the 12‐lead ECG. The global atrial activity is replicated on the right and left and magnified to show the morphology relative to the individual leads of the 12‐lead ECG.

Statistical Analysis

Continuous data are expressed as mean ± standard deviation if they are normally distributed and expressed as median (interquartile range) if they are nonnormally distributed. Categorical data are expressed as percentages. The change in DFR before and after ablation was compared using a paired t‐test. The percent change in DFR before and after ablation was compared between patients with and without a recurrence of AF using the Mann–Whitney test. Baseline clinical and echocardiographic data were compared between patients with or without recurrence using a t‐test or Fisher's exact test, for continuous and categorical data, respectively. Receiver operating characteristics (ROC) analysis was performed to evaluate the performance of the percent change in DFR before and after ablation as a discriminator of AF recurrence. The results were expressed as the area under the ROC curve and the 95% confidence interval (CI) for this area. Logistic regression analysis was used to identify predictors of AF recurrence, and the respective odds ratios (OR) with 95% CI were calculated. Probability values of ≤0.05 were considered to be statistically significant. All statistical analyses were performed using SAS 9.2 software (SAS Institute, Inc., Cary, NC, USA).

Results

The clinical and echocardiographic characteristics of the 25 patients included in the study are shown in Table 1. Most of them were middle‐aged men with normal ejection fraction and moderately dilated left atrium. Entrance and exit block was demonstrated for all PVs in each patient. Eight (32%) patients had recurrent AF at 1 year, documented by ECG. The clinical and echocardiographic characteristics of patients with and without recurrence were similar (P > 0.05; Table 1). DFR was not different before ablation between the two groups (0.31 ± 0.13 vs 0.26 ± 0.20; P = 0.51, in patients with and without recurrence, respectively). Based on the results of the spectral analysis, after ablation, there was organization of atrial activity, evidenced by a statistically significant increase in the DFR (0.28 ± 0.22 vs 0.53 ± 0.29; P = 0.001; Fig. 2). Figure 3 shows a representative spectral analysis of two patients, one with AF recurrence (patient 1) and one without AF recurrence (patient 2), before and after ablation. Patient 2 demonstrated significant degree of organization of atrial activity, whereas patient 1 did not show any organization of atrial activity. Note that in patient 2, the peaks in the spectral analysis represent harmonics of the dominant frequency.

Table 1.

Baseline Clinical and Echocardiographic Characteristics of the Patients

All patients (n = 25) No AF recurrence (n = 17) AF recurrence (n = 8) P Value
Age (years) 60.1 ± 8.8 58.3 ± 8.4 63.3 ± 8.7 0.19
Gender (M/F) 18/7 13/4 5/3 0.64
Paroxysmal AF (%) 76 71 88 0.62
Duration of AF (years) 5.7 ± 4.7 5.5 ± 4.6 6.1 ± 5.3 0.77
Hypertension (%) 60 59 63 1.0
Diabetes (%) 12 6 25 0.23
Sleep apnea (%) 16 12 25 0.57
Smoking (%) 24 24 22 1.0
LV ejection fraction (%) 61.4 ± 8.7 61.1 ± 8.4 62.3 ± 9.9 0.76
LA diameter (mm) 45.8 ± 8.7 46.1 ± 8.6 45.0 ± 10.1 0.82
LA volume index (mL/m2) 25.2 ± 9.2 25.8 ± 9.6 23.0 ± 8.1 0.59
Beta‐blockers (%) 60 65 50 0.67
ACE inhibitors (%) 36 29 50 0.39
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AF = atrial fibrillation; LV = left ventricle; LA = left atrium; ACE = angiotensin‐converting enzyme.

Figure 2.

Figure 2

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Dominant frequency ratio (DFR) increases after ablation, indicating greater spectral organization after catheter ablation.

Figure 3.

Figure 3

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Two patients with spectral analysis of global atrial activity before and after ablation, one with AF recurrence (patient 1) and another without AF recurrence (patient 2). For each patient, the upper panels (A and C) show the spectrum of the global atrial activity during AF before ablation and the lower panels (B and D) show the spectrum of the extracted global atrial activity during AF after ablation. Note that the degree of organization postablation differs between the two patients, with patient 2 showing significantly greater organization.

The percent change in DFR before and after ablation (median [interquartile range]) was significantly higher in patients without AF recurrence (120% [30% to 344%] vs 3% [−27% to 66%]; P = 0.01; Fig. 4). ROC analysis demonstrated that the discriminatory ability of the percent change in DFR before and after ablation to predict AF recurrences was reasonably good (area under the ROC curve = 0.82; 95% confidence interval 0.62–1.00; P = 0.01; Fig. 5). In addition, a less than 16% increase in DFR postablation was able to predict recurrence of AF with 75% sensitivity and 94% specificity. This corresponds to a positive and negative predictive value of 86% and 89%, respectively. However, no patients with a greater than 365% increase in DFR postablation experienced AF recurrence (Fig. 5). An increase in DFR postablation of >16% was a strong negative predictor of AF recurrence by univariate analysis (OR = 0.04; 95% CI: 0.01–0.39, P = 0.005). In contrast, none of the clinical or echocardiographic parameters examined were associated with AF recurrence (Table 2).

Figure 4.

Figure 4

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Percent change in DFR in patients with sinus rhythm versus patients who had recurrence of AF at 1 year. Median values and interquartile intervals are shown. Patients who maintained sinus rhythm had a significantly greater percent change in DFR postablation compared with those who had AF recurrence.

Figure 5.

Figure 5

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ROC curve for various degrees of atrial organization showing good accuracy, as indicated by an area under the curve of 0.82. Selected cutoff values of DFR change are shown.

Table 2.

Univariate Logistic Regression Analysis for Predictors of AF Recurrence

Parameter Odds Ratio 95% Confidence Interval P Value
Age 1.07 0.96 to 1.20 0.19
Female gender 4.67 0.76 to 30.11 0.11
Persistent AF 0.34 0.03 to 3.56 0.37
Duration of AF 1.03 0.87 to 1.24 0.76
Hypertension 1.17 0.21 to 6.55 0.86
Diabetes 5.33 0.41 to 70.19 0.20
Sleep apnea 5.33 0.41 to 70.19 0.20
Smoking 1.08 0.15 to 7.65 0.96
LV ejection fraction 0.98 0.89 to 1.09 0.75
LA volume index 1.11 0.93 to 1.33 0.29
Dominant frequency ratio >16% 0.04 0.01 to 0.39 0.005
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Discussion

We found that AF ablation leads to variable organization of atrial activity, as evidenced by an increase in the DFR index after ablation compared to before the procedure. Importantly, organization of atrial activity after AF ablation was associated with lower 1‐year AF recurrence rates. These results form the basis for the design of a larger study to investigate whether a marker such as the percent change in DFR after ablation may be used intraprocedurally as a novel end point for AF ablation. This is important in light of the fact that identification of the ideal candidate for catheter ablation remains a significant challenge. It is clear that AF is a heterogeneous disease with different electrophysiological substrates.2 Therefore, appropriate selection of a treatment strategy is imperative in improving patient outcomes. Currently, the selection of treatment strategy is largely based on a classification scheme, which divides AF into paroxysmal, persistent and long‐standing persistent.2 PV isolation is the mainstay treatment for paroxysmal AF, but it is generally believed that PV isolation alone is not enough to treat patients with persistent and long‐standing persistent AF.2 However, there is not a universal agreement as to which are the best substrate modification techniques in addition to PV isolation in this patient population.19, 20 Although rotor ablation has been proposed in some studies as a novel end point for ablation of persistent AF,21, 22 this is still considered investigational, as the ablation results were not reproducible in all centers.23 Based on our results, it is possible that a subset of patients with persistent AF, specifically those in whom ablation leads to a significant organization of atrial activity, may be treated with reasonable success with just PV isolation plus GP ablation. However, even some patients with paroxysmal AF may require additional substrate modification, if PV isolation and GP ablation do not result in a decrease in the electrical complexity (increase in the DFR). Consistent with our data, other recent studies have shown that spectral analysis parameters can predict spontaneous conversion of recent onset AF24 or sinus rhythm maintenance after cardioversion of AF.16 Collectively, these data suggest that information obtained by spectral analysis of the ECG during AF may contribute to individualize treatment strategies for AF.

These results are consistent with a prior animal study from our laboratory, in which GP ablation markedly attenuated complex fractionated electrograms (CFAEs) and increased the organization of atrial electrograms (decrease in dominant frequency and increase in regularity index) during acetylcholine‐induced AF.14 Organized AF episodes induced at the end of the ablation procedure may represent a different form of AF, which may be more amenable to treatment with antiarrhythmic drugs. We have previously demonstrated two different forms of AF in a single, acute experimental preparation.25 The focal form, arising from PV or non‐PV atrial sites, was resistant to propafenone administration and was characterized by significant regions of continuous and intermittent CFAE. After GP ablation at the PV‐atrial junctions and along the ligament of Marshall, a reentrant form of AF could be induced, which was readily terminated by the same dose of propafenone shown to be ineffective against the focal form. Moreover, the atrial electrograms recorded during the reentrant form of AF were essentially devoid of CFAE and showed extensive areas of organized electrograms in both the right and left atria and PVs, even though the ECG continued to produce irregular ventricular activity consistent with AF. In a clinical study, Pachon et al.26 used fast Fourier transform to identify two distinct types of atrial myocardium (compact and fibrillar myocardium) based on spectral analysis of atrial electrograms and demonstrated a very high success rate (94% at 9 months) in 35 patients undergoing AF ablation which targeted clusters of fibrillar myocardium forming AF nests with higher frequencies than the surrounding atrial myocardium, presumably the sites where focal AF originated.

Prediction of the outcome of a rhythm control strategy, either cardioversion or catheter ablation, is a very attractive concept. Several studies have investigated the predictive value of different parameters used as potential markers of AF recurrence after clinical interventions, including cardioversion and catheter ablation. Using a similar marker as in our study, Tuan et al.15 showed that an increase in the organization index of the coronary sinus electrograms (calculated as the ratio of the power under the dominant frequency and its harmonics divided by the total power in the frequency spectrum) predicted conversion to sinus rhythm after flecainide infusion in patients who remained in AF at the end of the catheter ablation procedure. Another study indicated that a higher degree of AF signal organization (lower harmonic decay) was associated with sinus rhythm maintenance in patients undergoing electrical cardioversion of AF, and performed better as a predictive marker compared with other clinical parameters.16 In a different study, the combination of a time domain (sample entropy) and a frequency domain (fibrillatory wave power) marker proved to be a very good predictor of AF recurrence after cardioversion.27 The above studies, as well as ours, highlight the notion that a more organized form of AF at baseline, or organization of AF following an intervention, is associated with a lower risk of AF recurrence and suggest that noninvasive ECG‐based assessment of AF substrate complexity may play an important role in predicting AF recurrences. Nonetheless, the multitude of parameters used in different studies to characterize the AF substrate hinder the interpretation of the clinical significance of AF substrate assessment and call for a standardization of the techniques used to analyze AF complexity.28 Further studies are required to clarify these issues.

In our study, other clinical parameters, including age, structural heart disease or left atrial size, did not predict AF recurrence. In a similar study, the preprocedure signal‐averaged P wave duration, which reflects atrial dysfunction, but not other traditional clinical parameters, was significantly associated with AF recurrence after PV isolation.29 Our results contrast with previous studies that showed that such clinical parameters are associated with AF recurrences.6, 30 This discrepancy may be explained by the inclusion of different populations in each study. In addition, patients with inducible AF at the end of the ablation procedure may represent a different subgroup with distinct electrophysiological properties, which differ from those that do not have inducible AF. Consistent with this notion are the results of a previous randomized study, which demonstrated that further ablation of fractionated electrograms in order to attain noninducibility in patients with inducible AF after PV isolation increased the long‐term success rate of the procedure.9 Finally, we cannot exclude the presence of an unknown confounding factor which is associated with both the outcome and the organization of atrial activity and is responsible for the results.

Clinical Implications

In light of the relatively poor long‐term success rate of AF ablation,4, 5 an accurate predictive marker of sinus rhythm maintenance following AF ablation would greatly facilitate patient selection and increase the success rate of the procedure. We have demonstrated that a less than optimal degree of organization of atrial activity (less than 16% increase in DFR) postablation was able to predict AF recurrence at 1 year with a very high degree of specificity. Spectral analysis of the ECG may be used intraprocedurally as a marker of adequate AF ablation, especially in cases where AF is still inducible at the end of the procedure.

Study Limitations

In this study, autonomic denervation (GP ablation) was done in addition to PV isolation, as part of the ablation procedure. Whether these results apply to PV isolation alone remains to be determined. However, given that PV isolation interrupts at least some of the main left atrial GP,31 we expect that similar results would be obtained with PV isolation alone. This technique is limited to patients with inducible AF at the end of the procedure. However, these are the patients in whom additional ablation is likely to be required.9 Since additional ablation may increase the risk of producing left atrial flutter,9 a predictive marker of AF recurrence may be very useful, in order to guide the need for further ablation. Although these data are promising, they cannot be considered definitive, given our limited sample size and the retrospective nature of the analysis. Larger prospective studies are warranted to confirm these findings.

Conclusion

AF ablation leads to variable organization of atrial activity. Importantly, organization of atrial activity after AF ablation predicted a significantly lower 1‐year recurrence rate and may be used intraprocedurally as a novel end point for AF ablation. Larger prospective studies are warranted to confirm these findings.

Ann Noninvasive Electrocardiol 2017;22(1):e12369, DOI: 10.1111/anec.12369

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