Characterization of fibrillatory rhythms by ensemble vector directional analysis

OpenEP: A Cross-Platform Electroanatomic Mapping Data Format and Analysis Platform for Electrophysiology Research

BACKGROUND

Electroanatomic mapping systems are used to support electrophysiology research. Data exported from these systems is stored in proprietary formats which are challenging to access and storage-space inefficient. No previous work has made available an open-source platform for parsing and interrogating this data in a standardized format. We therefore sought to develop a standardized, open-source data structure and associated computer code to store electroanatomic mapping data in a space-efficient and easily accessible manner.

METHODS

A data structure was defined capturing the available anatomic and electrical data. OpenEP, implemented in MATLAB, was developed to parse and interrogate this data. Functions are provided for analysis of chamber geometry, activation mapping, conduction velocity mapping, voltage mapping, ablation sites, and electrograms as well as visualization and input/output functions. Performance benchmarking for data import and storage was performed. Data import and analysis validation was performed for chamber geometry, activation mapping, voltage mapping and ablation representation. Finally, systematic analysis of electrophysiology literature was performed to determine the suitability of OpenEP for contemporary electrophysiology research.

RESULTS

The average time to parse clinical datasets was 400 ± 162 s per patient. OpenEP data was two orders of magnitude smaller than compressed clinical data (OpenEP: 20.5 ± 8.7 Mb, vs clinical: 1.46 ± 0.77 Gb). OpenEP-derived geometry metrics were correlated with the same clinical metrics (Area: R 2 = 0.7726, P < 0.0001; Volume: R 2 = 0.5179, P < 0.0001). Investigating the cause of systematic bias in these correlations revealed OpenEP to outperform the clinical platform in recovering accurate values. Both activation and voltage mapping data created with OpenEP were correlated with clinical values (mean voltage R 2 = 0.8708, P < 0.001; local activation time R 2 = 0.8892, P < 0.0001). OpenEP provides the processing necessary for 87 of 92 qualitatively assessed analysis techniques (95%) and 119 of 136 quantitatively assessed analysis techniques (88%) in a contemporary cohort of mapping studies.

CONCLUSIONS

We present the OpenEP framework for evaluating electroanatomic mapping data. OpenEP provides the core functionality necessary to conduct electroanatomic mapping research. We demonstrate that OpenEP is both space-efficient and accurately representative of the original data. We show that OpenEP captures the majority of data required for contemporary electroanatomic mapping-based electrophysiology research and propose a roadmap for future development.

An automated algorithm for determining conduction velocity, wavefront direction and origin of focal cardiac arrhythmias using a multipolar catheter

Determining locations of focal arrhythmia sources and quantifying myocardial conduction velocity (CV) are two major challenges in clinical catheter ablation cases. CV, wave-front direction and focal source location can be estimated from multipolar catheter data, but currently available methods are time-consuming, limited to specific electrode configurations, and can be inaccurate. We developed automated algorithms to rapidly identify CV from multipolar catheter data with any arrangement of electrodes, whilst providing estimates of wavefront direction and focal source position, which can guide the catheter towards a focal arrhythmic source. We validated our methods using simulations on realistic human left atrial geometry. We subsequently applied them to clinically-acquired intracardiac electrogram data, where CV and wavefront direction were accurately determined in all cases, whilst focal source locations were correctly identified in 2/3 cases. Our novel automated algorithms can potentially be used to guide ablation of focal arrhythmias in real-time in cardiac catheter laboratories.

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.

Differences in the characteristics of induced and spontaneous episodes of ventricular fibrillation

AIMS

The degree of organization of ventricular fibrillation (VF) can be examined in terms of the regularity of the electrical activity within the ventricle. Using electrograms (EGMs) stored within implanted cardioverter defibrillators (ICDs), we examined the hypothesis that the degree of organization, or regularity, was different if the VF was induced by electrical stimulation as opposed to occurring clinically due to ischemia or scar.

METHODS AND RESULTS

We compared the statistical characteristics of EGMs recorded by ICDs during spontaneous episodes with those induced during device testing in the laboratory in nine subjects. Regularity of the VF EGM signals was quantified using autocorrelation, Shannon entropy (derived from cycle to cycle activation complexes), and Kolmogorov entropy (derived from eight second long episodes of VF). All three measurements showed a statistically greater degree of regularity for induced VF than in spontaneous episodes.

CONCLUSION

Analysis of VF EGMs using these techniques is novel and robust, providing a new way for assessing electrical organization during VF. The clinical significance and utility of differences in VF waveform regularity is unclear at this stage.

Wave similarity of human ventricular fibrillation from bipolar electrograms

AIMS

The aim of this report was to review existing techniques for assessment of directionality in fibrillation and to describe the concept of wave similarity analysis in human VF.

METHODS

We applied a technique called wave similarity analysis to bipolar electrograms to study directionality during various rhythms (sinus rhythm, ventricular tachycardia and ventricular fibrillation) in humans. This technique uses the barycentre to determine the activation time and a similarity index is calculated using a technique described previously for AF studies.

RESULTS

We show here that using the wave similarity concept it is possible to recognize myocardial regions that are activated from multiple directions and differentiate those areas from regions that are activated by wave fronts in similar direction or at the exact mirror angle in ventricular fibrillation.

CONCLUSIONS

Wave similarity analysis provides a tool for assessing directional organization in human VF. This analysis of directional organization may have implications for the study of mechanisms of VF in the clinical arena.