Right atrial organization and wavefront analysis in atrial fibrillation

Dynamic time warping applied to estimate atrial fibrillation temporal organization from the surface electrocardiogram

Atrial fibrillation (AF) is the most commonly diagnosed arrhythmia in clinical practice. However, the mechanisms responsible for its induction and maintenance still are not fully understood. To this respect, analysis of the electrical activity organization within the atria could play an important role in their proper interpretation. Although many algorithms to quantify AF organization from invasive electrograms can be found in the literature, a reduced number of indirect estimators from the standard ECG have been proposed to date. Furthermore, these surface methods can only yield a global AF organization assessment, blurring the possible information that each individual fibrillatory (f) wave may provide. To this respect, the present manuscript proposes a novel method for direct and short-time AF organization estimation from single-lead surface ECG recordings. Through the computation of morphological variations among f waves, the temporal arrhythmia organization is estimated. The f waves are individually extracted and delineated from the atrial activity signal, making use of a dynamic time warping approach. The proposed algorithm was tested on real AF surface recordings in order to discriminate atrial signals with different organization degrees, obtaining a diagnostic accuracy higher than 88%. In addition, its performance was validated by comparison with two temporal organization measures from invasive unipolar electrograms of both atria, providing statistically significant linear correlations between invasive and non-invasive estimates. As a consequence, new standpoints are opened through this work in the non-invasive analysis of AF, where the individualized study of each f wave could assess short-time AF organization, would improve the understanding of AF mechanisms and become useful for its clinical treatment.

A novel approach to propagation pattern analysis in intracardiac atrial fibrillation signals

The purpose of this study is to investigate propagation patterns in intracardiac signals recorded during atrial fibrillation (AF) using an approach based on partial directed coherence (PDC), which evaluates directional coupling between multiple signals in the frequency domain. The PDC is evaluated at the dominant frequency of AF signals and tested for significance using a surrogate data procedure specifically designed to assess causality. For significantly coupled sites, the approach allows also to estimate the delay in propagation. The methods potential is illustrated with two simulation scenarios based on a detailed ionic model of the human atrial myocyte as well as with real data recordings, selected to present typical propagation mechanisms and recording situations in atrial tachyarrhythmias. In both simulation scenarios the significant PDCs correctly reflect the direction of coupling and thus the propagation between all recording sites. In the real data recordings, clear propagation patterns are identified which agree with previous clinical observations. Thus, the results illustrate the ability of the novel approach to identify propagation patterns from intracardiac signals during AF, which can provide important information about the underlying AF mechanisms, potentially improving the planning and outcome of arrhythmia ablation.

Toward discerning the mechanisms of atrial fibrillation from surface electrocardiogram and spectral analysis

Atrial fibrillation (AF) is the main cause of stroke and the most common sustained arrhythmia, afflicting about 2.3 million Americans. Clinical treatment and management of AF would benefit from a noninvasive and global assessment of the arrhythmia; however, that avenue seems currently limited in part by our poor understanding of arrhythmia itself. Experimental studies of AF in the isolated sheep heart demonstrated that high-frequency sources in the posterior wall of the left atrium drive the fibrillatory activity throughout both atria. Motivated by those results and by a growing body of work investigating how measurements of the cycle length of activity in patients during AF can contribute to its treatment, we focused our analysis on the dispersion of dominant frequency (DF) of the activity during AF in humans. Using electroanatomic mapping and Fourier methods, we generated 3-dimensional intracardiac DF maps of the atria in patients before AF ablation procedures and identified relatively small high-DF (HDF) sites. In patients with paroxysmal AF, the HDF sites are often localized to the posterior left atrium near the ostia of the pulmonary veins. In contrast, patients with permanent AF demonstrate HDF sites that are more often localized to the atria than the posterior left atrium-pulmonary vein junction. In our study, ablation at HDF sites resulted in significant slowing of the arrhythmia and termination of sustained AF in 87% of patients with paroxysmal AF. Furthermore, we found that abolishing, by ablation, preexisting left atrium to right atrium DF gradients predicted long-term freedom of AF in both paroxysmal and persistent AF patients. Overall, the analysis of intracardiac electrical recordings in the frequency domain has greatly enhanced our understanding of its underlying mechanisms and may contribute to monitoring drug effects and guide ablation procedures aiming at its termination. On the other hand, current body surface mapping methods have also suggested better correlations between surface AF frequency and intracardiac local DFs as compared with spatiotemporal activation patterns. Therefore, further study of the correlation of spectral observables obtained from the atria and from the surface electrocardiogram during AF seems to have the potential to advance our ability to diagnose and discern mechanisms of AF noninvasively.