Quantification of synchronization during atrial fibrillation by Shannon entropy: validation in patients and computer model of atrial arrhythmias

A Divergence-Based Approach for the Identification of Atrial Fibrillation Focal Drivers From Multipolar Mapping: A Computational Study

The expanding role of catheter ablation of atrial fibrillation (AF) has stimulated the development of novel mapping strategies to guide the procedure. We introduce a novel approach to characterize wave propagation and identify AF focal drivers from multipolar mapping data. The method reconstructs continuous activation patterns in the mapping area by a radial basis function (RBF) interpolation of multisite activation time series. Velocity vector fields are analytically determined, and the vector field divergence is used as a marker of focal drivers. The method was validated in a tissue patch cellular automaton model and in an anatomically realistic left atrial (LA) model with Courtemanche-Ramirez-Nattel ionic dynamics. Divergence analysis was effective in identifying focal drivers in a complex simulated AF pattern. Localization was reliable even with consistent reduction (47%) in the number of mapping points and in the presence of activation time misdetections (noise <10% of the cycle length). Proof-of-concept application of the method to human AF mapping data showed that divergence analysis consistently detected focal activation in the pulmonary veins and LA appendage area. These results suggest the potential of divergence analysis in combination with multipolar mapping to identify AF critical sites. Further studies on large clinical datasets may help to assess the clinical feasibility and benefit of divergence analysis for the optimization of ablation treatment.

Information Theory and Atrial Fibrillation (AF): A Review

Atrial Fibrillation (AF) is the most common cardiac rhythm disorder seen in hospitals and in general practice, accounting for up to a third of arrhythmia related hospitalizations. Unfortunately, AF treatment is in practice complicated by the lack of understanding of the fundamental mechanisms underlying the arrhythmia, which makes detection of effective ablation targets particularly difficult. Various approaches to AF mapping have been explored in the hopes of better pinpointing these effective targets, such as Dominant Frequency (DF) analysis, complex fractionated electrograms (CFAE) and unipolar reconstruction (FIRM), but many of these methods have produced conflicting results or require further investigation. Exploration of AF using information theoretic-based approaches may have the potential to provide new insights into the complex system dynamics of AF, whilst also providing the benefit of being less reliant on empirically derived definitions in comparison to alternate mapping approaches. This work provides an overview of information theory and reviews its applications in AF analysis, with particular focus on AF mapping. The works discussed in this review demonstrate how understanding AF from a signal property perspective can provide new insights into the arrhythmic phenomena, which may have valuable clinical implications for AF mapping and ablation in the future.

Circadian Alterations in a Murine Model of Hypothalamic Glioma

The mammalian circadian system is controlled by a central oscillator located in the suprachiasmatic nuclei (SCN) of the hypothalamus, in which glia appears to play a prominent role. Gliomas originate from glial cells and are the primary brain tumors with the highest incidence and mortality. Optic pathway/hypothalamic gliomas account for 4–7% of all pediatric intracranial tumors. Given the anatomical location, which compromises both the circadian pacemaker and its photic input pathway, we decided to study whether the presence of gliomas in the hypothalamic region could alter circadian behavioral outputs. Athymic nude mice implanted with LN229 human glioma cells showed an increase in the endogenous period of the circadian clock, which was also less robust in terms of sustaining the free running period throughout 2 weeks of screening. We also found that implanted mice showed a slower resynchronization rate after an abrupt 6 h advance of the light-dark (LD) cycle, advanced phase angle, and a decreased direct effect of light in general activity (masking), indicating that hypothalamic tumors could also affect photic sensitivity of the circadian clock. Our work suggests that hypothalamic gliomas have a clear impact both on the endogenous pacemaking of the circadian system, as well as on the photic synchronization of the clock. These findings strongly suggest that the observation of altered circadian parameters in patients might be of relevance for glioma diagnosis.

Paroxysmal atrial fibrillation recognition based on multi-scale Rényi entropy of ECG

BACKGROUND

Atrial fibrillation (AF) is a common type of arrhythmia disease, which has a high morbidity and can lead to some serious complications. The ability to detect and in turn prevent AF is extremely significant to the patient and clinician.

OBJECTIVE

Using ECG to detect AF and develop a robust and effective algorithm is the primary objective of this study.

METHODS

Some studies show that after AF occurs, the regulatory mechanism of vagus nerve and sympathetic nerve will change. Each R-R interval will be absolutely unequal. After studying the physiological mechanism of AF, we will calculate the Rényi entropy of the wavelet coefficients of heart rate variability (HRV) in order to measure the complexity of PAF signals, as well as extract the multi-scale features of paroxysmal atrial fibrillation (PAF).

RESULTS

The data used in this study is obtained from MIT-BIH PAF Prediction Challenge Database and the correct rate in classifying PAF patients from normal persons is 92.48%.

CONCLUSIONS

The results of this experiment proved that AF could be detected by using this method and, in turn, provide opinions for clinical diagnosis.

Tracking rotors with minimal electrodes: modulation index-based strategy

BACKGROUND

High-frequency periodic sources during cardiac fibrillation can be detected by phase mapping techniques. To enable practical therapeutic options for modulating periodic sources (existing techniques require high density multielectrode arrays and real time simultaneous mapping capability), a method to identify electrogram morphologies colocalizing to rotors that can be implemented on few electrograms needs to be devised.

METHOD AND RESULTS

Multichannel ventricular fibrillation electrogram data from 7 isolated human hearts using Langendorff setup and intraoperative clinical data from 2 human hearts were included in the analysis. The spatial locations of rotors were identified using phase maps constructed from 112 electrograms. Electrograms were analyzed for repeating patterns and discriminating signal morphologies around the locations of rotors and nonrotors were identified and quantified. Features were extracted from the unipolar electrogram patterns, which corroborated well with the spatial location of rotors. The results suggest that using the proposed modulation index feature, and as low as 1 sample point in the vicinity of the rotors, an accuracy as high as 86% (P<0.001) was obtained in separating rotor locations versus nonrotor locations. The analysis of bipolar electrogram signatures in the vicinity of the rotor locations suggest that 62.5% of the rotors occur at locations where the bipolar electrogram demonstrates continuous activities during ventricular fibrillation.

CONCLUSIONS

Unipolar electrogram extracted modulation index-based detection of rotors is feasible with few electrodes and has greater detection rate than bipolar approach. This strategy may be suitable for nonarray-based single mapping catheter enabled detection of rotors.

Quantitative assessment of synchronization during atrial fibrillation based on a novel index

Atrial Fibrillation (AF), a chaotic rhythm classically considered with random electrical activity, is now demonstrated to show a certain degree of organization and synchronization. Rather than those traditional indices which always focus on the pairwise properties of adjacent signals, a new synchronization index-S estimator-is introduced in this paper to quantify the synchronization level for all the signals in a selected area. By evaluating a complement of the entropy of the normalized eigenvalues of the corresponding correlation matrix, S estimator is designed to be proportional to the amount of synchronization. 400 episodes of 64-channel epicardial signals acquired from four living mongrels were studied under normal sinus rhythm (SN) and AF. The results showed that there were significant decreases of S estimator for both anterior left atrium and anterior right atrium with the rhythm changing from SN to AF. After dividing the research area into eight subparts, S estimator is also capable to demonstrate the different synchronization level for each subpart and revealed the electrophysiology individual difference among four experimental subjects. In conclusion, S estimator succeeds in estimating the synchronization degree for multi-channel signals in a selected area, with no limits to the number of the signals to be analyzed. It can help us to distinguish the region with a high synchronization level during AF, which would be helpful to the clinical AF treatment and enhance our understanding of underlying mechanisms of AF.

Precursors of dancing and singing to music in three- to four-months-old infants

Dancing and singing to music involve auditory-motor coordination and have been essential to our human culture since ancient times. Although scholars have been trying to understand the evolutionary and developmental origin of music, early human developmental manifestations of auditory-motor interactions in music have not been fully investigated. Here we report limb movements and vocalizations in three- to four-months-old infants while they listened to music and were in silence. In the group analysis, we found no significant increase in the amount of movement or in the relative power spectrum density around the musical tempo in the music condition compared to the silent condition. Intriguingly, however, there were two infants who demonstrated striking increases in the rhythmic movements via kicking or arm-waving around the musical tempo during listening to music. Monte-Carlo statistics with phase-randomized surrogate data revealed that the limb movements of these individuals were significantly synchronized to the musical beat. Moreover, we found a clear increase in the formant variability of vocalizations in the group during music perception. These results suggest that infants at this age are already primed with their bodies to interact with music via limb movements and vocalizations.

Inhomogeneous point-process entropy: an instantaneous measure of complexity in discrete systems

Measures of entropy have been widely used to characterize complexity, particularly in physiological dynamical systems modeled in discrete time. Current approaches associate these measures to finite single values within an observation window, thus not being able to characterize the system evolution at each moment in time. Here, we propose a new definition of approximate and sample entropy based on the inhomogeneous point-process theory. The discrete time series is modeled through probability density functions, which characterize and predict the time until the next event occurs as a function of the past history. Laguerre expansions of the Wiener-Volterra autoregressive terms account for the long-term nonlinear information. As the proposed measures of entropy are instantaneously defined through probability functions, the novel indices are able to provide instantaneous tracking of the system complexity. The new measures are tested on synthetic data, as well as on real data gathered from heartbeat dynamics of healthy subjects and patients with cardiac heart failure and gait recordings from short walks of young and elderly subjects. Results show that instantaneous complexity is able to effectively track the system dynamics and is not affected by statistical noise properties.

The Harvard Beat Assessment Test (H-BAT): a battery for assessing beat perception and production and their dissociation

Humans have the abilities to perceive, produce, and synchronize with a musical beat, yet there are widespread individual differences. To investigate these abilities and to determine if a dissociation between beat perception and production exists, we developed the Harvard Beat Assessment Test (H-BAT), a new battery that assesses beat perception and production abilities. H-BAT consists of four subtests: (1) music tapping test (MTT), (2) beat saliency test (BST), (3) beat interval test (BIT), and (4) beat finding and interval test (BFIT). MTT measures the degree of tapping synchronization with the beat of music, whereas BST, BIT, and BFIT measure perception and production thresholds via psychophysical adaptive stair-case methods. We administered the H-BAT on thirty individuals and investigated the performance distribution across these individuals in each subtest. There was a wide distribution in individual abilities to tap in synchrony with the beat of music during the MTT. The degree of synchronization consistency was negatively correlated with thresholds in the BST, BIT, and BFIT: a lower degree of synchronization was associated with higher perception and production thresholds. H-BAT can be a useful tool in determining an individual's ability to perceive and produce a beat within a single session.

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.

Slow wave propagation and plasticity of interstitial cells of Cajal in the small intestine of diabetic rats

The number of myenteric interstitial cells of Cajal (ICC-MY), responsible for the generation and propagation of the slow wave in the small intestine, has been shown to decrease in diabetes, suggesting impairment of slow-wave (SW) propagation and related motility. To date, however, this expected decrease in SW propagation has neither been recorded nor analysed. Eleven rats were treated with streptozotocin and housed in pairs with 11 age-matched control animals. After 3 or 7 months, segments of duodenum, jejunum and ileum were isolated and divided into two parts. One part was processed for immediate freezing, cryosectioning and immunoprobing using anti-c-Kit antibody to quantify ICC-MY. The second part was superfused in a tissue bath, and SW propagation was recorded with 121 extracellular electrodes. In addition, a cellular automaton was developed to study the effects of increasing the number of inactive cells on overall propagation. The number of ICC-MY was significantly reduced after 3 months of diabetes, but rebounded to control levels after 7 months of diabetes. Slow-wave frequencies, velocities and extracellular amplitudes were unchanged at any stage of diabetes. The cellular automaton showed that SW velocity was not linearly related to the number of inactive cells. The depletion of ICC-MY is not as severe as is often assumed and in fact may rebound after some time. In addition, at least in the streptozotocin model, the initial reduction in ICC-MY is not enough to affect SW propagation. Diabetic intestinal dysfunction may therefore be more affected by impairments of other systems, such as the enteric system or the muscle cells.

Automatic reconstruction of activation and velocity maps from electro-anatomic data by radial basis functions

The integration of mapping techniques with suitable methods for the characterization and visualization of propagation patterns may enhance the targeting of critical arrhythmic areas, thus optimizing the ablative treatment of atrial arrhythmias. In this study, we tested the feasibility of an innovative approach for the automatic determination of activation and velocity maps from sparse data as provided by electro-anatomic mapping systems. The proposed algorithm reconstructed the activation process by a radial basis function (RBF) interpolation of mapping point latencies. Velocity vectors were analytically determined by differentiation of the interpolation function. The method was tested by a multistate cellular automaton simulation model, implemented on a CARTO-derived atrial endocardial surface, and reconstruction accuracy was evaluated as a function of the number of mapping points. The RBF algorithm accurately reconstructed wave propagation patterns in simulated tissues with homogeneous and heterogeneous conduction properties, consistently with the data access afforded by clinical practice. These preliminary results suggest the possible integration of the method with clinically-used mapping systems to favor the identification of specific propagation patterns and conduction disturbances.

A time-domain approach for the identification of atrial fibrillation drivers

The localization of atrial fibrillation (AF) driver sources, characterized by rapid and regular electrical activity, is crucial for an effective ablation treatment. This work proposes a double-criteria approach for the identification of AF drivers based on a time-domain evaluation of atrial rate and AF organization. These two features are quantified by the measurement of atrial cycle length (ACL) and wave-similarity (WS). Based on ACL/WS formalism, AF drivers can be operatively defined as sites displaying electrical activity with high-rate and high-similarity (HR AND HS). The capability of ACL/WS analysis to identify AF driver sites and distinguish them from non-critical areas is shown in representative examples. The double-criteria evaluation for the identification of AF drivers, provided by our time-domain approach, might open new perspectives for the development of electrogram-guided ablation strategies in the single patient.

Long-term biatrial recordings in post-operative atrial fibrillation

Although atrial fibrillation (AF) is a common complication of cardiac surgery, its pathophysiology remains unclear. The study of post-operative AF demands for the recording of cardiac electrical activity in correspondence of AF onset and progression. Long-term recordings in post-surgery patients could provide this information, but, to date, have been limited to surface signals, which precludes a characterization of the arrhythmic triggers and substrate. In this study we demonstrate the feasibility of a continuous long-term recording of atrial electrical activities from the right and left atria in post-surgery patients. Local atrial epicardial electrograms are acquired by positioning temporary pacing wires in the right and left atria at the end of the intervention, while three day recordings are obtained by a digital holter recorder, adapted to epicardial signal features. The capability of the system to map local atrial activity and the possibility to obtain quantitative information on atrial rate and synchronization from the processed epicardial signals are proven in representative examples. The quantitative description of local atrial properties opens new perspective in the investigation of post-surgery AF.

Spatial characteristics of atrial fibrillation electrocardiograms

BACKGROUND

The present study investigates spatial properties of atrial fibrillation (AF) by analyzing vectorcardiogram loops synthesized from 12-lead electrocardiograms (ECGs).

METHODS

After atrial signal extraction, spatial properties are characterized through analysis of successive, fixed-length signal segments and expressed in loop orientation, that is, azimuth and elevation, as well as in loop morphology, that is, planarity and planar geometry. It is hypothesized that more organized AF, expressed by a lower AF frequency, is associated with decreased variability in loop morphology. Atrial fibrillation frequency is determined using spectral analysis.

RESULTS

Twenty-six patients with chronic AF were analyzed using 60-second ECG recordings. Loop orientation was similar when determined from either entire 60- or 1-second segments. For 1-second segments, the correlation between AF frequency and the parameters planarity and planar geometry were 0.608 (P < .001) and 0.543 (P < .005), respectively.

CONCLUSIONS

Quantification of AF organization based on AF frequency and spatial characteristics from the ECG is possible. The results suggested a relatively weak coupling between loop morphology and AF frequency when determined from the surface ECG.

Comparative study of methods for ventricular activity cancellation in atrial electrograms of atrial fibrillation

Atrial fibrillation is a very common cardiovascular disease in clinical practice. One relevant issue to understand its pathophysiological mechanisms is the analysis and interpretation of atrial electrograms (AEG). To study these signals properly, ventricular activity has to be removed from the AEG. In this work, a new application of independent component analysis (ICA) to the AEG is presented, where ventricular activity is removed from atrial epicardial recordings making use of only one reference lead. Therefore the technique is suitable when multi-lead recordings are unavailable as in atrial implantable cardioverter defibrilators. In addition to the proposed new methodology this work also presents the first comparative study, making use of unipolar epicardial AEGs, among the ICA-based technique, template matching and subtraction (TMS), and adaptive ventricular cancellation (AVC) on a database of 20 patients. A performance comparative analysis was carried out by evaluating epicardial atrial waveform similarity (S) and ventricular depolarization reduction (VDR) as a function of atrial rhythm regularity on a beat-by-beat basis. Results indicate that, when the epicardial atrial rhythm is quite organized, ICA is able to preserve the atrial waveform very precisely and better than the other methods (median S = 99.64% +/- 0.31% in contrast to 95.18% +/- 2.71% for TMS and 94.76% +/- 4.12% for AVC). Moreover, ventricular reduction is the best for ICA (median VDR = 6.32 +/- 4.41 dB in contrast to 4.98 +/- 4.48 dB for TMS and 4.12 +/- 2.72 dB for AVC). On the other hand, when the atrial activity is disorganized, TMS notably improves performance (S = 97.72% +/- 1.87%), but ICA still is the best in waveform preservation (S = 98.22% +/- 1.53%) whereas AVC remains similar (S = 93.74% +/- 4.38%). In conclusion, ICA can be considered as notably the best approach to reduce ventricular activity from unipolar atrial electrograms in organized atrial arrhythmias. On the other hand, both TMS and ICA give quite similar results when the atrial arrhythmia is disorganized.