Measured and Simulated P Waves in Normal Subjects Reflect Complex Atrial Anatomy

Introduction: The shape of the P wave can yield important information about the substrate of atrial fibrillation (AF). On the routine 12-lead ECG, P waves have a smooth appearance. Computer simulation studies with realistic atrial models have shown highly complex P-wave shapes with details that were linked to structural features of the atria. We assessed the true shape of the P wave in control subjects. Methods: We recorded 184-channel high-resolution ECGs in 6 healthy volunteers and averaged over 300 beats for each. Beats were aligned on their P waves. Alignment was based on a compound signal of all 184 channels to reduce the effect of noise on alignment. In addition, 12-lead ECGs were simulated using a single patient-tailored heart-torso model with detailed atrial anatomy. Results: Averaging reduced the noise level to less than 2 microvolt (uV) peak-to-peak. Signal features of a few uV amplitude and less than 5 milliseconds (ms) duration could be reliably distinguished. Measured P waves had 4 to 5 separate peaks that were reproducible between recordings. Simulated P waves demonstrated similar complexity, which was related to structural discontinuities in the computer model of the atria. Conclusions: The true shape of the P wave is very irregular and reflects the complex anatomy of the atria. High-resolution electrocardiography is necessary to reliably assess P-wave shape.Optimization of noninvasive assessment of the substrate for atrial fibrillatio

Zwitterionische Nanopartikel

The invention relates to a zwitterionic nanoparticle comprising at least one nanoparticle and a zwitterionic shell which encloses the nanoparticle. The invention further relates to a composition, a method for binding a zwitterionic nanoparticle, and the use of a zwitterionic nanoparticle

The ECG as a tool to determine atrial fibrillation complexity

The use of the ECG for atrial fibrillation (AF) in clinical daily practice is still limited to its diagnosis. Recent research shows however that ECG-derived parameters can also be used to assess the spatiotemporal properties of AF. Specifically, the complexity of the f-waves in the ECG reflects the complexity of the fibrillatory conduction during AF and therefore can be used for quantification of the degree of electrophysiological alterations in the atria. This information might be useful for guiding AF therapy and might form the basis for classification of AF. This review focuses on technical and mathematical aspects of ECG-based atrial complexity assessment and its potential ability to guide treatment strategies

Body-Surface Atrial Signals Analysis Based on Spatial Frequency Distribution: Comparison Between Different Signal Transformations

In contrast to electrograms, Body-Surface Potential Mapping (BSPM) records the global atrial activity, at the expenses of a lower spatial accuracy. The aim of this study is to investigate whether BSPM recordings can discriminate persistent patients undergoing electrical cardiover-sion, based on the body-surface normalized AF spatial frequency distribution. High-density BSPMs (120 anterior, 64 posterior electrodes) were recorded in 63 patients with persistent AF. For each patient and electrode recording, the frequency content of AF was analyzed on the raw signal, and also by means of the normalized correlation function, and by Singular Spectrum Analysis (SSA). In order to compare the body-surface spatial distributions of AF frequency in all patients, these distributions were first normalized, before performing statistical analysis. We found that the distribution of AF frequency on the body-surface, and its interpretation, are strongly dependent on the specific method employed. Moreover, the estimated body-surface AF frequency was greater over the central posterior and the right anterior BSPM locations. Finally, SSA-based decomposition followed by frequency analysis could discriminate AF patients recurring 4 to 6 weeks after electrical cardioversion from those who did not, based on the frequency content in the proximity of V1

Use of Normalized Correlation Function to Discriminate Outcome of Persistent Patients Undergoing Electrical Cardioversion

Atrial activity (AA) during atrial fibrillation (AF) is a process characterized by different short- and long-term recurrent behaviors. In this work we hypothesize that the features derived from these behaviors contain an information on the lead locations that discriminate the most between persistent AF patients recurring after electrical cardioversion from those who do not. Body surface potential maps (BSPMs, 184 electrodes) were recorded in 63 patients in persistent AF prior to electrical cardioversion (32 recurrences after 4-6 weeks). A correlation function (CF) was computed for each electrode, and normalized in order to make it independent of its magnitude. Finally, the first min and max values of the normalized CF from each electrode were used to discriminate patients outcome. The corresponding spatial maps showed that electrodes with the largest values of normalized CF are located on the front of the torso, centered around V1. A Wilcoxon rank-sum test was used to compare maps of recurrent and non-recurrent AF patients and find electrodes with significantly different magnitude. A significant difference was observed on the upper and lower parts of the torso, with higher values for the non-recurrent AF patients (higher recurrence of the underlying AA propagation patterns). When looking at the energy computed on each electrode, this parameter was not able to distinguish among the two groups

A novel framework for noninvasive analysis of short-term atrial activity dynamics during persistent atrial fibrillation

ECG-based representation of atrial fibrillation (AF) progression is currently limited. We propose a novel framework for a more sensitive noninvasive characterization of the AF substrate during persistent AF. An atrial activity (AA) recurrence signal is computed from body surface potential map (BSPM) recordings, and a set of characteristic indices is derived from it which captures the short- and long-term recurrent behaviour in the AA patterns. A novel measure of short- and longterm spatial variability of AA propagation is introduced, to provide an interpretation of the above indices, and to test the hypothesis that the variability in the oscillatory content of AA is due mainly to a spatially uncoordinated propagation of the AF waveforms. A simple model of atrial signal dynamics is proposed to confirm this hypothesis, and to investigate a possible influence of the AF substrate on the short-term recurrent behaviour of AA propagation. Results confirm the hypothesis, with the model also revealing the above influence. Once the characteristic indices are normalized to remove this influence, they show to be significantly associated with AF recurrence 4 to 6 weeks after electrical cardioversion. Therefore, the proposed framework improves noninvasive AF substrate characterization in patients with a very similar substrate