Laurent Uldry

Early Temporal and Spatial Regularization of Persistent Atrial Fibrillation Predicts Termination and Arrhythmia-Free Outcome

BACKGROUND Termination of persistent atrial fibrillation (AF) is a valuable ablation endpoint but is difficult to anticipate. We evaluated whether temporal and spatial indices of AF regularization predict intraprocedural AF termination and outcome. OBJECTIVE The purpose of this study was to test whether temporospatial organization of AF after pulmonary vein isolation (PVI) predicts whether subsequent stepwise ablation will terminate persistent AF or predict outcome. METHODS In 75 patients with persistent AF, we measured AF cycle length (AFCL), temporal regularity index (TRI, a spectral measure of timing regularity), and spatial regularity index (SRI, cycle-to-cycle variations in spatial vector) between right atrial appendage and proximal and distal coronary sinus before and during stepwise ablation to the endpoint of AF termination. RESULTS AF termination was achieved in 59 patients (79%) by ablation. AF terminated during PVI in 11 patients, who were excluded from analysis. In the remaining 48 patients, TRI and SRI increased during stepwise ablation, as compared with 16 patients without termination (P<.05). AFCL was prolonged in both groups. From receiver operating characteristics analysis of the first 22 patients (training set), a post-PVI TRI increase predicted AF termination in the latter 42 patients (test set) with a positive predictive value of 96%, negative predictive value of 53%, sensitivity of 71%, and specificity of 91%. Results were similar for SRI. After 36 months, higher arrhythmia-free outcome was observed in patients in whom PVI caused temporospatial regularization in AF. CONCLUSIONS Temporal and spatial regularization of persistent AF after PVI identifies patients in whom stepwise ablation subsequently terminates AF and prevents recurrence.

Adaptive tracking of EEG oscillations

Neuronal oscillations are an important aspect of EEG recordings. These oscillations are supposed to be involved in several cognitive mechanisms. For instance, oscillatory activity is considered a key component for the top-down control of perception. However, measuring this activity and its influence requires precise extraction of frequency components. This processing is not straightforward. Particularly, difficulties with extracting oscillations arise due to their time-varying characteristics. Moreover, when phase information is needed, it is of the utmost importance to extract narrow-band signals. This paper presents a novel method using adaptive filters for tracking and extracting these time-varying oscillations. This scheme is designed to maximize the oscillatory behavior at the output of the adaptive filter. It is then capable of tracking an oscillation and describing its temporal evolution even during low amplitude time segments. Moreover, this method can be extended in order to track several oscillations simultaneously and to use multiple signals. These two extensions are particularly relevant in the framework of EEG data processing, where oscillations are active at the same time in different frequency bands and signals are recorded with multiple sensors. The presented tracking scheme is first tested with synthetic signals in order to highlight its capabilities. Then it is applied to data recorded during a visual shape discrimination experiment for assessing its usefulness during EEG processing and in detecting functionally relevant changes. This method is an interesting additional processing step for providing alternative information compared to classical time-frequency analyses and for improving the detection and analysis of cross-frequency couplings.

Measures of spatiotemporal organization differentiate persistent from long-standing atrial fibrillation

AIMS This study presents an automatic diagnostic method for the discrimination between persistent and long-standing atrial fibrillation (AF) based on the surface electrocardiogram (ECG). METHODS AND RESULTS Standard 12-lead ECG recordings were acquired in 53 patients with either persistent (N= 20) or long-standing AF (N= 33), the latter including both long-standing persistent and permanent AF. A combined frequency analysis of multiple ECG leads followed by the computation of standard complexity measures provided a method for the quantification of spatiotemporal AF organization. All possible pairs of precordial ECG leads were analysed by this method and resulting organization measures were used for automatic classification of persistent and long-standing AF signals. Correct classification rates of 84.9% were obtained, with a predictive value for long-standing AF of 93.1%. Spatiotemporal organization as measured in lateral precordial leads V5 and V6 was shown to be significantly lower during long-standing AF than persistent AF, suggesting that time-related alterations in left atrial electrical activity can be detected in the ECG. CONCLUSION Accurate discrimination between persistent and long-standing AF based on standard surface recordings was demonstrated. This information could contribute to optimize the management of sustained AF, permitting appropriate therapeutic decisions and thereby providing substantial clinical cost savings.

Atrial septal pacing for the termination of atrial fibrillation: study in a biophysical model of human atria

AIMS While successful termination by pacing of organized atrial tachycardias has been observed in patients, single site rapid pacing has not yet led to conclusive results for the termination of atrial fibrillation (AF). The purpose of this study was to evaluate a novel atrial septal pacing algorithm for the termination of AF in a biophysical model of the human atria. METHODS AND RESULTS Sustained AF was generated in a model based on human magnetic resonance images and membrane kinetics. Rapid pacing was applied from the septal area following a dual-stage scheme: (i) rapid pacing for 10-30 s at pacing intervals 62-70% of AF cycle length (AFCL), (ii) slow pacing for 1.5 s at 180% AFCL, initiated by a single stimulus at 130% AFCL. Atrial fibrillation termination success rates were computed. A mean success rate for AF termination of 10.2% was obtained for rapid septal pacing only. The addition of the slow pacing phase increased this rate to 20.2%. At an optimal pacing cycle length (64% AFCL) up to 29% of AF termination was observed. CONCLUSION The proposed septal pacing algorithm could suppress AF reentries in a more robust way than classical single site rapid pacing. Experimental studies are now needed to determine whether similar termination mechanisms and rates can be observed in animals or humans, and in which types of AF this pacing strategy might be most effective.

Systematic comparison of non-invasive measures for the assessment of atrial fibrillation complexity: a step forward towards standardization of atrial fibrillation electrogram analysis

AIMS To present a comparison of electrocardiogram-based non-invasive measures of atrial fibrillation (AF) substrate complexity computed on invasive animal recordings to discriminate between short-term and long-term AF. The final objective is the selection of an optimal sub-set of measures for AF complexity assessment. METHODS AND RESULTS High-density epicardial direct contact mapping recordings (234 leads) were acquired from the right and the left atria of 17 goats in which AF was induced for 3 weeks (short-term AF group, N = 10) and 6 months (long-term AF group, N = 7). Several non-invasive measures of AF organization proposed in the literature in the last decade were investigated to assess their power in discriminating between the short-term and long-term group. The best performing measures were identified, which when combined attained a correct classification rate of 100%. Their ability to predict standard invasive AF complexity measures was also tested, showing an average R(2) of 0.73 ± 0.04. CONCLUSION An optimal set of measures of the AF substrate complexity was identified out of the set of non-invasive measures analysed in this study. These measures may contribute to improve patient-tailored diagnosis and therapy of sustained AF.

Adaptive Tracking of EEG Frequency Components

In this chapter, we propose a novel method for tracking oscillatory components in EEG signals by means of an adaptive filter bank. The specific utility of our tracking algorithm is to maximize the oscillatory behavior of its output rather than its spectral power, which shows interesting properties for the observation of neuronal oscillations. In addition, the structure of the filter bank allows for efficiently tracking multiple frequency components perturbed by noise, therefore providing a good framework for EEG spectral analysis. Moreover, our algorithm can be generalized to multivariate data analysis, allowing the simultaneous investigation of several EEG sensors. Thus, a more precise extraction of spectral information can be obtained from the EEG signal under study. After a short introduction, we present our algorithm as well as synthetic examples illustrating its potential. Then, the performance of the method on real EEG signals is presented for the tracking of both a single oscillatory component and multiple components. Finally, future lines of improvement as well as areas of applications are discussed.

Spontaneous termination of atrial fibrillation: Study of the effect of atrial geometry in a biophysical model

We studied the mechanisms of spontaneous termination of atrial fibrillation in a biophysical model of human atria, during the eight seconds preceding termination. The earliest detectable changes in the cycle length and the number of wavefronts occurred about three seconds prior to termination. We compared the mechanisms involved in the right and left atrium and investigated the effects of atrial geometry on the termination processes. We observed that cycle length started to increase 800 ms earlier in the left atrium than in the right atrium. Similarly, the number of wavefronts decreased even 1800 ms earlier in the left atrium than in the right one. Significantly fewer episodes terminated in the left atrium. Four areas of the atrial geometry showing distinct termination mechanisms were identified.

Optimization of antitachycardia pacing protocols applied to atrial fibrillation: Insights from a biophysical model

We present a model-based systematic study of antitachycardia pacing protocols applied to atrial fibrillation, focusing on the ability to achieve and maintain capture during pacing, as a function of both pacing site and period. We observed that pacing sites located away from anatomical obstacles led to faster and more robust capture. Moreover, after comparing burst and ramp pacing, our results indicate that in order to get capture it is necessary to pace at a fixed optimal period over a sufficient long time.

Studies of Therapeutic Strategies for Atrial Fibrillation Based on a Biophysical Model of the Human Atria

Atrial fibrillation (AF), the most common sustained form of cardiac arrhythmia, is an endemic disease with an increasing prevalence [14, 32]. Its polymorphic dynamical nature severely hampers the development of a single therapy effective in all individual patients [23, 24]. The limited understanding of the AF mechanisms indicates a clear medical need for improving current therapies, adapting them to various AF dynamics that can be found in different patient populations, and selecting the therapy that is optimal for an individual patient.

Study of the effect of rapid pacing of atrial fibrillation on the non-paced atrium

Purpose: Experimental studies showed that local capture of atrial fibrillation (AF) by rapid pacing was possible in humans. However, contradictory observations were reported on its effect at distant atrial sites. The present model-based study investigated the effect of rapid pacing on the paced and the non-paced atria. Methods: A biophysical model of AF based on a geometry from human MRI and a membrane kinetics model was used. Rapid AF pacing was applied during 30s in right atrial (RA) free wall or left atrial (LA) appendage at optimal pacing cycle lengths based on previous studies (RA:76 ms, LA:77ms). The pacing effect was characterized by measuring 256 electrograms evenly located in RA and LA, from which the following values were computed: AF cycle length (AFCL), number of wavefronts (#WF), percentage of excited tissue (ET) and AF organization index (OI) assessing spectral regularity and ranging from 0 to 1. Results: Pacing successfully induced local AF capture in the paced atrium with an AFCL close to the pacing cycle length. Local capture was accompanied by a significant (p<0.001) reduction in #WF and increase in ET and OI in the paced atrium. In the non-paced atrium, AFCL only slightly decreased while the effect on #WF was the opposite to what was observed in the paced atrium (increase) and ET did not change. Interestingly, the effect on OI was different when pacing from the LA (decrease in the non-paced atrium compared to no pacing) or the RA (increase). Conclusions: The effect of AF rapid pacing on the non-paced atrium showed an acceleration of AF with an increased number of wavefronts. However, the effect on AF organization was dependent on the pacing site, which could explain the contradictory results reported in humans.