Information theory to tachycardia therapy: electrogram entropy predicts diastolic microstructure of reentrant ventricular tachycardia.

There is no known strategy to differentiate which multicomponent electrograms in sinus rhythm maintain reentrant ventricular tachycardia (VT). Low entropy in the voltage breakdown of a multicomponent electrogram can localize conditions suitable for reentry but has not been validated against the classic VT activation mapping. We examined whether low entropy in a late and diversely activated ventricular scar region characterizes and differentiates the diastolic path of VT and represents protected tissue channels devoid of side branches. Intraoperative bipolar electrogram (BiEGM) activation and entropy maps were obtained during sinus rhythm in 17 patients with ischemic cardiomyopathy and compared with diastolic activation paths of VT (total of 39 VTs). Mathematical modeling of a zigzag main channel with side branches was also used to further validate structural representation of low entropy in the ventricular scar. A median of one region per patient (range: 1-2 regions) was identified in sinus rhythm, in which BiEGM with the latest mean activation time and adjacent minimum entropy were assembled together in a high-activation dispersion region. These regions accurately recognized diastolic paths of 34 VTs, often to multiple inducible VTs within a single individual arrhythmogenic region. In mathematical modeling, side branching from the main channel had a strong influence on the BiEGM composition along the main channel. The BiEGM obtained from a long unbranched channel had the lowest entropy compared with those with multiple side branches. In conclusion, among a population of multicomponent sinus electrograms, those that demonstrate low entropy and are delayed colocalize to critical long-protected channels of VT. This information is pertinent for planning VT ablation in sinus rhythm. NEW & NOTEWORTHY Entropy is a measure to quantify breakdown in information. Electrograms from a protected tissue channel can only possess a few states in their voltage and thus less information. In contrast, current-load interactions from side branches in unprotected channels introduce a number of dissimilar voltage deflections and thus high information. We compare here a mapping approach based on entropy against a rigorous reference standard of activation mapping during VT and entropy was assessed in sinus rhythm.

Determinants of atrial bipolar voltage: Inter electrode distance and wavefront angle.

BACKGROUND: Local bipolar electrogram (EGM) peak-to-peak voltage (Vpp) is currently used to characterise mapped myocardial substrate. However, how interelectrode distance and angle of wavefront incidence affect bipolar, Vpp values, in the current era of multi-electrode mapping is unknown. OBJECTIVES: To elucidate the effects of tissue and electrode geometry on bipolar Vpp measurements, when mapping healthy versus diseased atrial regions. METHODS: A bidomain model of human atrial tissue was used to quantify the influence on Vpp values of various electrode configurations in healthy tissue, and tissue containing an unexcitable region. The orientation angle and interelectrode spacing of a surface bipole, and thickness and depth of the unexcitable core were serially varied. Results were validated with data obtained from isolated porcine hearts. RESULTS: In healthy tissue, bipolar Vpp values increased with increasing interelectrode spacing and plateaued beyond a spacing of approximately 4 mm. The bipolar Vpp values in healthy tissue were relatively less sensitive to wavefront orientation angle with large interelectrode spacing. In diseased tissue, on the contrary, with increasing interelectrode spacing, bipolar Vpp values increased linearly without a plateau and were more sensitive to orientation angle. The bipolar Vpp values decreased with increasing thickness of the scar, with larger relative decrease in small bipoles than larger ones. Bipolar Vpp values increased with a progressively intramural location of fixed-size scar and became less distinguishable from healthy tissue especially for smaller interelectrode spacings. CONCLUSIONS: The scalable relationship established for interelectrode distances favour an electric-field-based assessment as opposed to traditional Vpp values as a tool for physiologically relevant measurement for mapping catheters with interelectrode spacing up to 4 mm. This will allow for universal assessment of myocardial health across catheters with varied spacing.

Quantifying the determinants of decremental response in critical ventricular tachycardia substrate.

BACKGROUND: Decremental response evoked with extrastimulation (DEEP) is a useful tool for determining diastolic return path of ventricular tachycardia (VT). Though a targeted VT ablation is feasible with this approach, determinants of DEEP response have not been studied OBJECTIVES: To elucidate the effects of clinically relevant factors, specifically, the proximity of the stimulation site to the arrhythmogenic scar, stimulation wave direction, number of channels open in the scar, size of the scar and number of extra stimuli on decrement and entropy of DEEP potentials. METHODS: In a 3-dimensional bi-domain simulation of human ventricular tissue (TNNP cell model), an irregular subendocardial myopathic region was generated. An irregular channel of healthy tissue with five potential entry branches was shaped into the myopathic region. A bipolar electrogram was derived from two electrodes positioned in the centre of the myopathic region. Evoked delays between far-field and local Electrogram (EGM) following an extrastimulus (S1-S2, 500-350 ms) were measured as the stimulation site, channel branches, and inexcitable tissue size were altered. RESULTS: Stimulation adjacent to the inexcitable tissue from the side opposite to the point-of-entry produces longest DEEP delay. The DEEP delay shortens when the stimulation point is farther away from the scar, and it decreases maximally when stimulation is done from a site beside a conduction barrier. Entropy increases with S2 when stimulation site is from farther away. An unprotected channel structure with multiple side-branch openings had shorter DEEP delay compared to a protected channel structure with a paucity of additional side-branch openings and a point-of-entry on the side opposite to the pacing source. Addition of a second shorter extrastimulus did not universally lead to higher DEEP delay CONCLUSIONS: Location and direction of the wavefront in relation to scar entry and size of scar determine the degree of evoked response while the number of extrastimuli has a small additional decremental effect.

Electrophysiological Cardiac Modeling: A Review.

Cardiac electrophysiological modeling in conjunction with experimental and clinical findings has contributed to better understanding of electrophysiological phenomena in various species. As our knowledge on underlying electrical, mechanical, and chemical processes has improved over time, mathematical models of the cardiac electrophysiology have become more realistic and detailed. These models have provided a testbed for various hypotheses and conditions that may not be easy to implement experimentally. In addition to the limitations in experimentally validating various scenarios implemented by the models, one of the major obstacles for these models is computational complexity. However, the ever-increasing computational power of supercomputers facilitates the clinical application of cardiac electrophysiological models. The potential clinical applications include testing and predicting effects of pharmaceutical agents and performing patient-specific ablation and defibrillation. A review of studies involving these models and their major findings are provided.

Feature-based MRI data fusion for cardiac arrhythmia studies.

Current practices in studying cardiac arrhythmias primarily use electrical or optical surface recordings of a heart, spatially limited transmural recordings, and mathematical models. However, given that such arrhythmias occur on a 3D myocardial tissue, information obtained from such practices lack in dimension, completeness, and are sometimes prone to oversimplification. The combination of complementary Magnetic-Resonance Imaging (MRI)-based techniques such as Current Density Imaging (CDI) and Diffusion Tensor Imaging (DTI) could provide more depth to current practices in assessing the cardiac arrhythmia dynamics in entire cross sections of myocardium. In this work, we present an approach utilizing feature-based data fusion methods to demonstrate that complimentary information obtained from electrical current distribution and structural properties within a heart could be quantified and enhanced. Twelve (12) pairs of CDI and DTI image data sets were gathered from porcine hearts perfused through a Langendorff setup. Images were fused together using feature-based data fusion techniques such as Joint Independent Component Analysis (jICA), Canonical Correlation Analysis (CCA), and their combination (CCA+jICA). The results suggest that the complimentary information of cardiac states from CDI and DTI are enhanced and are better classified with the use of data fusion methods. For each data set, an increase in mean correlations of fused images were observed with 38% increase from CCA+jICA compared to the original images while mean mutual information of the fused images from jICA and CCA+jICA increased by approximately three-fold. We conclude that MRI-based techniques present potential viable tools in furthering studies for cardiac arrhythmias especially Ventricular Fibrillation.

Noise distribution and denoising of current density images.

Current density imaging (CDI) is a magnetic resonance (MR) imaging technique that could be used to study current pathways inside the tissue. The current distribution is measured indirectly as phase changes. The inherent noise in the MR imaging technique degrades the accuracy of phase measurements leading to imprecise current variations. The outcome can be affected significantly, especially at a low signal-to-noise ratio (SNR). We have shown the residual noise distribution of the phase to be Gaussian-like and the noise in CDI images approximated as a Gaussian. This finding matches experimental results. We further investigated this finding by performing comparative analysis with denoising techniques, using two CDI datasets with two different currents (20 and 45 mA). We found that the block-matching and three-dimensional (BM3D) technique outperforms other techniques when applied on current density ([Formula: see text]). The minimum gain in noise power by BM3D applied to [Formula: see text] compared with the next best technique in the analysis was found to be around 2 dB per pixel. We characterize the noise profile in CDI images and provide insights on the performance of different denoising techniques when applied at two different stages of current density reconstruction.