Spectral and spatiotemporal variability ECG parameters linked to catheter ablation outcome in persistent atrial fibrillation.

With the increasing prevalence of atrial fibrillation (AF), there is a strong clinical interest in determining whether a patient suffering from persistent AF will benefit from catheter ablation (CA) therapy at long term. This work presents several regression models based on noninvasive measures automatically computed from the standard 12-lead electrocardiogram (ECG) such as AF dominant frequency (DF), spectral concentration and spatiotemporal variability (STV). Sixty-two AF patients referred to CA were enrolled in this study. Forty-seven of them had no recurrence after CA during an average follow-up of 14 ± 8 months. The ECG features were extracted from an ECG recorded before the CA intervention and they were combined by means of logistic regression. The combination of DF and STV values from different precordial leads reached AUC = 0.939, outperforming the best results by using only one kind of features, such as DF (AUC = 0.801), and yielding a global accuracy of 93.5% for discriminating the best long-term responders to CA. These results point out the need to take into consideration the spatial variation of spectral ECG parameters to build predictive models dealing with AF.

Non-invasive prediction of catheter ablation outcome in persistent atrial fibrillation by fibrillatory wave amplitude computation in multiple electrocardiogram leads.

BACKGROUND: Catheter ablation (CA) of persistent atrial fibrillation (AF) is challenging, and reported results are capable of improvement. A better patient selection for the procedure could enhance its success rate while avoiding the risks associated with ablation, especially for patients with low odds of favorable outcome. CA outcome can be predicted non-invasively by atrial fibrillatory wave (f-wave) amplitude, but previous works focused mostly on manual measures in single electrocardiogram (ECG) leads only. AIM: To assess the long-term prediction ability of f-wave amplitude when computed in multiple ECG leads. METHODS: Sixty-two patients with persistent AF (52 men; mean age 61.5±10.4years) referred for CA were enrolled. A standard 1-minute 12-lead ECG was acquired before the ablation procedure for each patient. F-wave amplitudes in different ECG leads were computed by a non-invasive signal processing algorithm, and combined into a mutivariate prediction model based on logistic regression. RESULTS: During an average follow-up of 13.9±8.3months, 47 patients had no AF recurrence after ablation. A lead selection approach relying on the Wald index pointed to I, V1, V2 and V5 as the most relevant ECG leads to predict jointly CA outcome using f-wave amplitudes, reaching an area under the curve of 0.854, and improving on single-lead amplitude-based predictors. CONCLUSION: Analysing the f-wave amplitude in several ECG leads simultaneously can significantly improve CA long-term outcome prediction in persistent AF compared with predictors based on single-lead measures.

Empirical mode decomposition of multiple ECG leads for catheter ablation long-term outcome prediction in persistent atrial fibrillation.

Predictive models arouse increasing interest in clinical practice, not only to improve successful intervention rates but also to extract information of diverse physiological disorders. This is the case of persistent atrial fibrillation (AF), the most common cardiac arrhythmia in adults. Currently, catheter ablation (CA) is one of the preferred therapies to face this disease. However, selecting the best responders to CA by standard noninvasive techniques such as the electrocardiogram (ECG) remains a challenge. This work presents different predictive models for determining long-term CA outcome based on the dominant frequency (DF) of atrial activity measured in the ECG. The ensemble empirical mode decomposition (EEMD) is employed to obtain the intrinsic mode functions (IMFs) composing the ECG signal in each lead. The IMF DFs computed in multiple leads are then combined into a logistic regression (LR) model. The IMF DF features are discriminant enough to reach 79% accuracy for long-term CA outcome prediction, outperforming other methods based on DF computation. Our study shows EEMD as a valuable alternative to extract clinically relevant spectral information from AF ECGs and confirms the advantage of LR to build multivariate predictive models as compared with univariate analysis.

Noninvasive prediction of catheter ablation acute outcome in persistent atrial fibrillation based on logistic regression of ECG fibrillatory wave amplitude and spatio-temporal variability.

Catheter ablation (CA) is increasingly employed to treat persistent atrial fibrillation (AF), yet assessment of procedural AF termination is still a subject of debate in the medical community. This has motivated the development of different criteria based on the standard electrocardiogram (ECG) to characterize ablation immediate effectiveness. However, most of conventional descriptors are merely computed in one ECG lead, thus neglecting significant information provided by the other leads. The present study proposes a novel predictor of CA outcome by exploiting a subset of the 12 leads in the standard ECG. Our method predicts the need for electrical cardioversion subsequent to CA by suitably combining two sets of multilead features, namely, a measure of fibrillatory wave amplitude and an index of AF spatio-temporal variability per lead. These features are obtained on a reduced-rank approximation determined by principal component analysis emphasizing the highest-variance components in the multilead atrial activity signal, and are then combined by logistic regression. On a database of over 50 persistent AF patients, our method provides reliable predictive measures and proves more robust and informative than classical AF descriptors.

Multidimensional characterization of fibrillatory wave amplitude on surface ECG to describe catheter ablation impact on persistent atrial fibrillation.

Radiofrequency catheter ablation (CA) is increasingly employed to treat persistent atrial fibrillation (AF). Nevertheless, its success is not always guaranteed, as selection of patients who could positively respond to this therapy does not rely on systematic criteria and still remains an open issue. Moreover, very little is known about the quantitative effects of this treatment over AF electrophysiology, so their quantitative evaluation is not a trivial task. In this contribution, ablation impact is quantified by a descriptor of fibrillatory wave (f-wave) amplitude, so far regarded as a predictor of short-term CA outcome. By means of principal component analysis (PCA), surface electrocardiogram (ECG) spatial diversity is exploited and contributions from all leads are combined to describe average f-wave peak-to-peak amplitude, whose value is automatically computed by an algorithm based on cubic spline interpolation. Our work demonstrates how CA influences f-wave amplitude during the procedure as quantified by ECG inter-lead spatial variability. In addition, we show how such variations depend on procedural outcome and the duration of the postoperative blanking period.

Predicting catheter ablation outcome in persistent atrial fibrillation using atrial dominant frequency and related spectral features.

Pre-procedural atrial fibrillation dominant frequency (AFDF) has been reported to play a role as a predictor of catheter ablation (CA) outcome for the treatment of persistent atrial fibrillation (AF). The present study analyzes some spectral features of the atrial signal aimed at evaluating the quality of surface AFDF estimation and discusses their predictive power. First, automated extraction of surface atrial activity (AA) on pre-procedural 12-lead ECG recordings is performed by means of an independent component analysis (ICA) method. AFDF is then estimated by means of short-time Fourier analysis of the extracted atrial sources and simultaneous endocardial electrograms (EGM) used as reference. On a database of 20 patients in persistent AF undergoing CA, AFDF does not appear to play a role as a predictor of CA outcome at follow-up, neither on ECG nor on EGM recordings. The quality of surface AFDF estimation is assessed by means of the correlation coefficient r between surface and EGM AFDF, as well as the spectral concentration (SC) of the estimated atrial signal. It is shown that the quality of surface AFDF estimation is significantly lower for non-terminating CA procedures, both in terms of r and SC. The latter, in particular, seems to play a significant role in distinguishing terminating from non-terminating CA procedures and therefore in the non-invasive prediction of CA outcome.

Hepatico-tricuspid isthmus ablation for typical-like atrial flutter by femoral approach in absence of the inferior vena cava: use of magnetic navigation and three-dimensional mapping with image integration.

The previously unknown congenital absence of inferior vena cava, an otherwise benign condition, may create difficulties for catheter ablation of arrhythmias. We describe a case of a typical-like atrial flutter, in which magnetic navigation was important for conserving the femoral approach. Electroanatomic mapping with image integration helped define the critical isthmus between the ostia of the suprahepatic veins and the tricuspid valve.

Non-invasive prediction of catheter ablation outcome in persistent atrial fibrillation by exploiting the spatial diversity of surface ECG.

Atrial fibrillation (AF) is the most common cardiac arrhythmia encountered in clinical practice. Radiofrequency catheter ablation (CA) is becoming one of the most widely employed therapies. Yet selection of patients who will benefit from this treatment remains a challenging task. Previous works have examined several electrocardiogram (ECG) parameters as potential predictors of CA success, such as fibrillatory wave (f-wave) amplitude. However, they require a manual computation and consider only a subset of electrodes, so inter-lead spatial variability of the 12-lead ECG is not fully exploited. The present study puts forward an automatic procedure for f-wave amplitude computation to non-invasively predict CA outcome. An extension of this quantitative measure to the whole set of leads is also proposed, based on Principal Component Analysis (PCA). We show that exploiting the spatial diversity present in the surface ECG not only improves the robustness to electrode selection but also increases the predictive power of the amplitude parameter.

Ablation of post-myocardial infarction focal ventricular tachycardia.

In the chronic phase of myocardial infarction, the presence of scar areas allows the development of macro-reentries which become the most frequent mechanism underlying ventricular tachycardia (VT). A focal mechanism has been already described in the presence of scar in animal models or in humans but only during surgery. We report a case of focal automatic VT arising from postinfarction scar fibrosis, successfully mapped and ablated during an electro-physiological procedure.

Robotic magnetic navigation for ablation of human arrhythmias: initial experience.

BACKGROUND: Magnetic navigation system (MNS) (Niobe, Stereotaxis, Saint-Louis, Missouri, USA) allows remote control of a radiofrequency ablation catheter using a steerable magnetic field and a catheter advancement system. AIMS: We report our initial experience of ablation of human arrhythmias using the MNS. METHODS: Eighty-four patients (mean age 54+/-17years; 39 women) had an electrophysiologic study followed by ablation with the MNS using non-irrigated 4, 8 and 3.5mm-tip catheters with three distal magnets. All patients were symptomatic, with commonly-accepted indications for ablation: atrioventricular nodal re-entrant tachycardia (AVNRT; n=37); typical atrial flutter (n=15); accessory pathway (n=12); atypical atrial flutter (n=7); ventricular tachycardia (n=7); atrial tachycardia (n=3); paroxysmal atrial fibrillation (n=3). Electroanatomical mapping was used for atrial flutter, atrial fibrillation, atrial tachycardia and ventricular tachycardia procedures (29 patients, 34%). RESULTS: Ablation was performed successfully in 69 (82%) patients. In 15 patients (18%), MNS technique was unsuccessful: seven typical atrial flutters, four accessory pathways, two left atrial flutters after atrial fibrillation ablation, one ventricular tachycardia and one AVNRT; in all these cases except one typical atrial flutter and two left atrial flutters, success was obtained by switching to the manual technique by means of an irrigated catheter. Total fluoroscopy time was 14+/-11minutes; operator exposure fluoroscopy time was 1.5+/-0.6minutes; procedure time was 169+/-72minutes. CONCLUSION: MNS ablation is a feasible treatment for various human arrhythmias, with a high success rate. Mapping with a magnetic catheter is safe. However, magnetic ablation of typical atrial flutter remains challenging, probably because of insufficient pressure for cavotricuspid isthmus ablation.