Identification of cardiac rhythm features by mathematical analysis of vector fields

Isochronal Apparent Dispersion at Early Activation Sites Accurately Identifies Outflow Tract Ventricular Ectopy Sites

BACKGROUND

Localisation of outflow tract (OT) premature ventricular complex (PVC) sites is guided by unipolar and bipolar local activation time (LAT). However, LAT-based localisation can be inaccurate if the site is intramural or distant. Deep foci produce rapid conduction velocity (CV) if the wavefront is tangential to the surface.

AIM

We evaluated whether supraphysiological CV, referred to as surface isochronal apparent dispersion (IAD) mapping, can be used to accurately differentiate right and left ventricular OT PVC origin, guiding the successful site for OT PVC ablation.

METHOD

Left ventricular OT mapping was performed if right ventricular OT mapping demonstrated a bipolar electrogram (EGM) <20 ms. The earliest EGMs underwent analysis of the following: first deflection bipolar EGM (bipolarearliest) to QRS, bipolarearliest to first deflection unipolar EGM (unipolarearliest), bipolarearliest to unipolar -dV/dTmax, unipolar -dV/dTmax to QRS, number of early LAT breakouts, and the surface area of the earliest isochronal breakout. Polynomial CV was calculated using a custom algorithm in MATLAB using cut-offs between 1 and 100,000 cm/s and used to create IAD, referred to as apparent dispersion index. The accuracy of IAD to distinguish between successful and unsuccessful OT sites was assessed and compared with conventional EGM indices.

RESULTS

Bipolarearliest to QRS (28.5±7.3 ms vs 17.8±5.7 ms; p<0.05) is superior to unipolar -dV/dtmax to QRS (0.4±26.4 ms vs -6.4±13.4 ms; p=0.25) in differentiating successful and unsuccessful OT PVC sites. An early isochronal breakout area of less than 1 cm2 and less than two breakouts indicates a successful side (both p<0.05). Bipolarearliest to unipolar -dV/dTmax and to unipolarearliest were not predictive (28.1±27.7 vs 24.2±13.3 ms; p=0.97 and 6.4±7.3 vs 6.4±5.8 ms; p=0.8, respectively). IAD appears to differentiate between successful and unsuccessful sites using an apparent dispersion index cut-off of 20,000 cm/s, with an accuracy of 93.8% and area under the receiver operator characteristic of 0.95.

CONCLUSIONS

IAD is a realistic two-dimensional interpretation of the three-dimensional activation mapping surface that may be associated with OT origins to guide a successful side of catheter ablation.

Vector Field Heterogeneity for the Assessment of Locally Disorganised Cardiac Electrical Propagation Wavefronts From High-Density Multielectrodes

High-density multielectrode catheters are becoming increasingly popular in cardiac electrophysiology for advanced characterisation of the cardiac tissue, due to their potential to identify impaired sites. These are often characterised by abnormal electrical conduction, which may cause locally disorganised propagation wavefronts. To quantify it, a novel heterogeneity parameter based on vector field analysis is proposed, utilising finite differences to measure direction changes between adjacent cliques. The proposed Vector Field Heterogeneity metric has been evaluated on a set of simulations with controlled levels of organisation in vector maps, and a variety of grid sizes. Furthermore, it has been tested on animal experimental models of isolated Langendorff-perfused rabbit hearts. The proposed parameter exhibited superior capturing ability of heterogeneous propagation wavefronts compared to the classical Spatial Inhomogeneity Index, and simulations proved that the metric effectively captures gradual increments in disorganisation in propagation patterns. Notably, it yielded robust and consistent outcomes for [Formula: see text] grid sizes, underscoring its suitability for the latest generation of orientation-independent cardiac catheters.

Atrial conduction velocity mapping: clinical tools, algorithms and approaches for understanding the arrhythmogenic substrate

Characterizing patient-specific atrial conduction properties is important for understanding arrhythmia drivers, for predicting potential arrhythmia pathways, and for personalising treatment approaches. One metric that characterizes the health of the myocardial substrate is atrial conduction velocity, which describes the speed and direction of propagation of the electrical wavefront through the myocardium. Atrial conduction velocity mapping algorithms are under continuous development in research laboratories and in industry. In this review article, we give a broad overview of different categories of currently published methods for calculating CV, and give insight into their different advantages and disadvantages overall. We classify techniques into local, global, and inverse methods, and discuss these techniques with respect to their faithfulness to the biophysics, incorporation of uncertainty quantification, and their ability to take account of the atrial manifold.

A Review on Atrial Fibrillation (Computer Simulation and Clinical Perspectives)

Atrial fibrillation (AF), a heart condition, has been a well-researched topic for the past few decades. This multidisciplinary field of study deals with signal processing, finite element analysis, mathematical modeling, optimization, and clinical procedure. This article is focused on a comprehensive review of journal articles published in the field of AF. Topics from the age-old fundamental concepts to specialized modern techniques involved in today’s AF research are discussed. It was found that a lot of research articles have already been published in modeling and simulation of AF. In comparison to that, the diagnosis and post-operative procedures for AF patients have not yet been totally understood or explored by the researchers. The simulation and modeling of AF have been investigated by many researchers in this field. Cellular model, tissue model, and geometric model among others have been used to simulate AF. Due to a very complex nature, the causes of AF have not been fully perceived to date, but the simulated results are validated with real-life patient data. Many algorithms have been proposed to detect the source of AF in human atria. There are many ablation strategies for AF patients, but the search for more efficient ablation strategies is still going on. AF management for patients with different stages of AF has been discussed in the literature as well but is somehow limited mostly to the patients with persistent AF. The authors hope that this study helps to find existing research gaps in the analysis and the diagnosis of AF.

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.

Activation During Sinus Rhythm in Ventricles With Healed Infarction: Differentiation Between Arrhythmogenic and Nonarrhythmogenic Scar

BACKGROUND

In infarct-related ventricular tachycardia (VT), the circuit often corresponds to a location characterized by activation slowing during sinus rhythm (SR). However, the relationship between activation slowing during SR and vulnerability for reentry and correlation to components of the VT circuit are unknown. This study examined the relationship between activation slowing during SR and vulnerability for reentry and correlated these areas with components of the circuit.

METHODS

In a porcine model of healed infarction, the spatial distribution of endocardial activation velocity was compared between SR and VT. Isthmus sites were defined using activation and entrainment mapping as areas exhibiting diastolic activity within the circuit while bystanders were defined as areas displaying diastolic activity outside the circuit.

RESULTS

Of 15 swine, 9 had inducible VT (5.2±3.0 per animal) while in 6 swine VT could not be induced despite stimulation from 4 RV and LV sites at 2 drive trains with 6 extra-stimuli down to refractoriness. Infarcts with VT had a greater magnitude of activation slowing during SR. A minimal endocardial activation velocity cutoff ≤0.1 m/s differentiated inducible from noninducible infarctions (P=0.015). Regions of maximal endocardial slowing during SR corresponded to the VT isthmus (area under curve=0.84 95% CI, 0.78-0.90) while bystander sites exhibited near-normal activation during SR. VT circuits were complex with 41.7% exhibiting discontinuous propagation with intramural bridges of slow conduction and delayed quasi-simultaneous endocardial activation. Regions forming the VT isthmus borders had faster activation during SR while regions forming the inner isthmus were activated faster during VT.

CONCLUSIONS

Endocardial activation slowing during SR may differentiate infarctions vulnerable for VT from those less vulnerable for VT. Sites of slow activation during SR correspond to sites forming the VT isthmus but not to bystander sites.

A work flow to build and validate patient specific left atrium electrophysiology models from catheter measurements

Biophysical models of the atrium provide a physically constrained framework for describing the current state of an atrium and allow predictions of how that atrium will respond to therapy. We propose a work flow to simulate patient specific electrophysiological heterogeneity from clinical data and validate the resulting biophysical models. In 7 patients, we recorded the atrial anatomy with an electroanatomical mapping system (St Jude Velocity); we then applied an S1-S2 electrical stimulation protocol from the coronary sinus (CS) and the high right atrium (HRA) whilst recording the activation patterns using a PentaRay catheter with 10 bipolar electrodes at 12 ± 2 sites across the atrium. Using only the activation times measured with a PentaRay catheter and caused by a stimulus applied in the CS with a remote catheter we fitted the four parameters for a modified Mitchell-Schaeffer model and the tissue conductivity to the recorded local conduction velocity restitution curve and estimated local effective refractory period. Model parameters were then interpolated across each atrium. The fitted model recapitulated the S1-S2 activation times for CS pacing giving a correlation ranging between 0.81 and 0.98. The model was validated by comparing simulated activations times with the independently recorded HRA pacing S1-S2 activation times, giving a correlation ranging between 0.65 and 0.96. The resulting work flow provides the first validated cohort of models that capture clinically measured patient specific electrophysiological heterogeneity.

Spiral wave classification using normalized compression distance: Towards atrial tissue spatiotemporal electrophysiological behavior characterization

Analysis of electrical activation patterns such as re-entries during atrial fibrillation (Afib) is crucial in understanding arrhythmic mechanisms and assessment of diagnostic measures. Spiral waves are a phenomena that provide intuitive basis for re-entries occurring in cardiac tissue. Distinct spiral wave behaviors such as stable spiral waves, meandering spiral waves, and spiral wave break-up may have distinct electrogram manifestations on a mapping catheter. Hence, it is desirable to have an automated classification of spiral wave behavior based on catheter recordings for a qualitative characterization of spatiotemporal electrophysiological activity on atrial tissue. In this study, we propose a method for classification of spatiotemporal characteristics of simulated atrial activation patterns in terms of distinct spiral wave behaviors during Afib using two different techniques: normalized compressed distance (NCD) and normalized FFT (NFFTD). We use a phenomenological model for cardiac electrical propagation to produce various simulated spiral wave behaviors on a 2D grid and labeled them as stable, meandering, or breakup. By mimicking commonly used catheter types, a star shaped and a circular shaped both of which do the local readings from atrial wall, monopolar and bipolar intracardiac electrograms are simulated. Virtual catheters are positioned at different locations on the grid. The classification performance for different catheter locations, types and for monopolar or bipolar readings were also compared. We observed that the performance for each case differed slightly. However, we found that NCD performance is superior to NFFTD. Through the simulation study, we showed the theoretical validation of the proposed method. Our findings suggest that a qualitative wavefront activation pattern can be assessed during Afib without the need for highly invasive mapping techniques such as multisite simultaneous electrogram recordings.

Resolving Myocardial Activation With Novel Omnipolar Electrograms

BACKGROUND

With its inherent limitations, determining local activation times has been the basis of cardiac mapping for over a century. Here, we introduce omnipolar electrograms that originate from the natural direction of a travelling wave and from which instantaneous conduction velocity amplitude and direction can be computed at any single location without first determining activation times. We sought to validate omnipole-derived conduction velocities and explore potential application for localization of sources of arrhythmias.

METHODS AND RESULTS

Electrograms from omnipolar mapping were derived and validated using 4 separate models and 2 independent signal acquisition methodologies. We used both electric signals and optical signals collected from monolayer cell preparations, 3-dimensional constructs built with cardiomyocytes derived from human embryonic stem cells, simultaneous optical and electric mapping of rabbit hearts, and in vivo pig electrophysiology studies. Conduction velocities calculated from omnipolar electrograms were compared with wavefront propagation from optical and electric-mapping studies with a traditional local activation time-based method. Bland-Altman analysis revealed that omnipolar measurements on optical data were in agreement with local activation time methods for wavefront direction and velocity within 25 cm/s and 30°, respectively. Similar agreement was also found on electric data. Furthermore, mathematical operations, such as curl and divergence, were applied to omnipole-derived velocity vector fields to locate rotational and focal sources, respectively.

CONCLUSIONS

Electrode orientation-independent cardiac wavefront trajectory and speed at a single location for each cardiac activation can be determined accurately with omnipolar electrograms. Omnipole-derived vector fields, when combined with mathematical transforms may aid in real-time detection of cardiac activation sources.

Atrial Conduction Velocity Correlates with Frequency Content of Bipolar Signal

BACKGROUND

Anisotropy in conduction velocity (CV) is a key substrate abnormality influencing atrial arrhythmias. In skeletal muscle fibers, CV and frequency content of the surface electromyogram signal are directly related. We hypothesized that in human atria the frequency content of the bipolar signal, recorded on the endocardial surface, is directly related to the local CV.

METHODS

In 15 patients submitted to ablation of supraventricular arrhythmias, incremental pacing was performed through an octapolar catheter inserted into the coronary sinus (CS), alternatively from both extremities in two different sequences: CS bipole 1-2 as the pacing site and CS bipole 7-8 as the detection site in the first, and vice versa in the second. The pacing cycle length (PCL) was stepwise decreased from 600 ms to 500 ms, 400 ms, 300 ms, until 250 ms. Estimation of the CV was performed as the ratio between the distance traveled by the propagating pulse and the propagation time. The frequency distribution of the signal energy was estimated using the fast Fourier transform, and the characteristic frequency (CF) was estimated as the barycenter of the frequency spectrum.

RESULTS

A total of 2,496 bipolar signals were analyzed; CV and CF were estimated and compared. The single patient and group data analysis showed a significant direct correlation between CV and CF of the local bipolar signal.

CONCLUSIONS

Comparing the degree of spectral compression among signals registered in different points of the endocardial cardiac surface in response to decreasing PCL enables to map local differences in CV, a useful arrhythmogenic substrate index.

Time-Delay Mapping of High-Resolution Gastric Slow-Wave Activity

GOAL

Analytic monitoring of electrophysiological data has become an essential component of efficient and accurate clinical care. In the gastrointestinal (GI) field, recent advances in high-resolution (HR) mapping are now providing critical information about spatiotemporal profiles of slow-wave activity in normal and disease (dysrhythmic) states. The current approach to analyze GI HR electrophysiology data involves the identification of individual slow-wave events in the electrode array, followed by tracking and clustering of events to create a spatiotemporal map. This method is labor and computationally intensive and is not well suited for real-time clinical use or chronic monitoring.

METHODS

In this study, an automated novel technique to assess propagation patterns was developed. The method utilized time delays of the slow-wave signals which was computed through cross correlations to calculate velocity. Validation was performed with both synthetic and human and porcine experimental data.

RESULTS

The slow-wave profiles computed via the time-delay method compared closely with those computed using the traditional method (speed difference: 7.2% ± 2.6%; amplitude difference: 8.6% ± 3.5%, and negligible angle difference).

CONCLUSION

This novel method provides rapid and intuitive analysis and visualization of slow-wave activity.

SIGNIFICANCE

This techniques will find major applications in the clinical translation of acute and chronic HR electrical mapping for motility disorders, and act as a screening tool for detailed detection and tracking of individual propagating wavefronts, without the need for comprehensive standard event-detection analysis.

Techniques for automated local activation time annotation and conduction velocity estimation in cardiac mapping

Measurements of cardiac conduction velocity provide valuable functional and structural insight into the initiation and perpetuation of cardiac arrhythmias, in both a clinical and laboratory context. The interpretation of activation wavefronts and their propagation can identify mechanistic properties of a broad range of electrophysiological pathologies. However, the sparsity, distribution and uncertainty of recorded data make accurate conduction velocity calculation difficult. A wide range of mathematical approaches have been proposed for addressing this challenge, often targeted towards specific data modalities, species or recording environments. Many of these algorithms require identification of activation times from electrogram recordings which themselves may have complex morphology or low signal-to-noise ratio. This paper surveys algorithms designed for identifying local activation times and computing conduction direction and speed. Their suitability for use in different recording contexts and applications is assessed.

Automated classification and identification of slow wave propagation patterns in gastric dysrhythmia

The advent of high-resolution (HR) electrical mapping of slow wave activity has significantly improved the understanding of gastric slow wave activity in normal and dysrhythmic states. One of the current limitations of this technique is it generates a vast amount of data, making manual analysis a tedious task for research and clinical development. In this study we present new automated methods to classify, identify, and locate patterns of interest in gastric slow wave propagation. The classification method uses a similarity metric to classify slow wave propagations, while the identification algorithm uses the divergence and mean curvature of the slow wave propagation to identify and regionalize patterns of interest. The methods were applied to synthetic and experimental datasets and were also compared to manual analysis. The methods classified and identified patterns of slow wave propagation in less than 1 s, compared to manual analysis which took up to 40 min. The automated methods achieved 96% accuracy in classifying AT maps, and 95% accuracy in identifying the propagation pattern with a mean spatial error of 1.5 mm in comparison to manual methods. These new methods will facilitate the efficient translation of gastrointestinal HR mapping techniques to clinical practice.

Computational modeling of the human atrial anatomy and electrophysiology

This review article gives a comprehensive survey of the progress made in computational modeling of the human atria during the last 10 years. Modeling the anatomy has emerged from simple "peanut"-like structures to very detailed models including atrial wall and fiber direction. Electrophysiological models started with just two cellular models in 1998. Today, five models exist considering e.g. details of intracellular compartments and atrial heterogeneity. On the pathological side, modeling atrial remodeling and fibrotic tissue are the other important aspects. The bridge to data that are measured in the catheter laboratory and on the body surface (ECG) is under construction. Every measurement can be used either for model personalization or for validation. Potential clinical applications are briefly outlined and future research perspectives are suggested.

An improved method for the estimation and visualization of velocity fields from gastric high-resolution electrical mapping

High-resolution (HR) electrical mapping is an important clinical research tool for understanding normal and abnormal gastric electrophysiology. Analyzing velocities of gastric electrical activity in a reliable and accurate manner can provide additional valuable information for quantitatively and qualitatively comparing features across and within subjects, particularly during gastric dysrhythmias. In this study, we compared three methods of estimating velocities from HR recordings to determine which method was the most reliable for use with gastric HR electrical mapping. The three methods were 1) simple finite difference (FD) 2) smoothed finite difference (FDSM), and 3) a polynomial-based method. With synthetic data, the accuracy of the simple FD method resulted in velocity errors almost twice that of the FDSM and the polynomial-based method, in the presence of activation time error up to 0.5 s. With three synthetic cases under various noise types and levels, the FDSM resulted in average speed error of 3.2% and an average angle error of 2.0° and the polynomial-based method had an average speed error of 3.3% and an average angle error of 1.7°. With experimental gastric slow wave recordings performed in pigs, the three methods estimated similar velocities (6.3-7.3 mm/s), but the FDSM method had a lower standard deviation in its velocity estimate than the simple FD and the polynomial-based method, leading it to be the method of choice for velocity estimation in gastric slow wave propagation. An improved method for visualizing velocity fields is also presented.

Conduction velocity restitution of the human atrium--an efficient measurement protocol for clinical electrophysiological studies

Conduction velocity (CV) and CV restitution are important substrate parameters for understanding atrial arrhythmias. The aim of this work is to (i) present a simple but feasible method to measure CV restitution in-vivo using standard circular catheters, and (ii) validate its feasibility with data measured during incremental pacing. From five patients undergoing catheter ablation, we analyzed eight datasets from sinus rhythm and incremental pacing sequences. Every wavefront was measured with a circular catheter and the electrograms were analyzed with a cosine-fit method that calculated the local CV. For each pacing cycle length, the mean local CV was determined. Furthermore, changes in global CV were estimated from the time delay between pacing stimulus and wavefront arrival. Comparing local and global CV between pacing at 500 and 300 ms, we found significant changes in seven of eight pacing sequences. On average, local CV decreased by 20 ± 15% and global CV by 17 ± 13%. The method allows for in-vivo measurements of absolute CV and CV restitution during standard clinical procedures. Such data may provide valuable insights into mechanisms of atrial arrhythmias. This is important both for improving cardiac models and also for clinical applications, such as characterizing arrhythmogenic substrates during sinus rhythm.

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.