Nima Zamiri

Effects of Renal Artery Denervation on Ventricular Arrhythmias in a Postinfarct Model

Background— The therapeutic potential of renal denervation (RDN) for arrhythmias has not been fully explored. Detailed mechanistic evaluation is in order. The objective of the present study was to determine the antiarrhythmic potential of RDN in a postinfarct animal model and to determine whether any benefits relate to RDN-induced reduction of sympathetic effectors on the myocardium. Methods and Results— Pigs implanted with single-chamber implantable cardioverter defibrillators to record ventricular arrhythmias (VAs) were subjected to percutaneous coronary occlusion to induce myocardial infarction. Two weeks later, a sham or real RDN treatment was performed bilaterally using the St Jude EnligHTN basket catheter. Parameters of ventricular remodeling and modulation of cardio–renal sympathetic axis were monitored for 3 weeks after myocardial infarction. Histological analysis of renal arteries yielded a mean neurofilament score of healthy nerves that was significantly lower in the real RDN group than in sham controls; damaged nerves were found only in the real RDN group. There was a 100% reduction in the rate of spontaneous VAs after real RDN and a 75% increase in the rate of spontaneous VAs after sham RDN (P=0.03). In the infarcted myocardium, presence of sympathetic nerves and tissue abundance of neuropeptide-Y, an indicator of sympathetic nerve activities, were significantly lower in the RDN group. Peak and mean sinus tachycardia rates were significantly reduced after RDN. Conclusions— RDN in the infarcted pig model leads to reduction of postinfarction VAs and myocardial sympathetic effectors. This may form the basis for a potential therapeutic role of RDN in postinfarct VAs.

Fusion of structural and functional cardiac magnetic resonance imaging data for studying Ventricular Fibrillation

Magnetic Resonance Imaging (MRI) techniques such as Current Density Imaging (CDI) and Diffusion Tensor Imaging (DTI) provide a complementing set of imaging data that can describe both the functional and structural states of biological tissues. This paper presents a Joint Independent Component Analysis (jICA) based fusion approach which can be utilized to fuse CDI and DTI data to quantify the differences between two cardiac states: Ventricular Fibrillation (VF) and Asystolic/Normal (AS/NM). Such an approach could lead to a better insight on the mechanism of VF. Fusing CDI and DTI data from 8 data sets from 6 beating porcine hearts, in effect, detects the differences between two cardiac states, qualitatively and quantitatively. This initial study demonstrates the applicability of MRI-based imaging techniques and jICA-based fusion approach in studying cardiac arrhythmias.

Effect of spatial resolution and filtering on mapping cardiac fibrillation

BACKGROUND Endocardial mapping tools use variable interelectrode resolution, whereas body surface mapping tools use narrow bandpass filtering (BPF) to map fibrillatory mechanisms established by high-resolution optical imaging. OBJECTIVE The purpose of this study was to study the effect of resolution and BPF on the underlying mechanism being mapped. METHODS Hearts from 14 healthy New Zealand white rabbits were Langendorff perfused. We studied the effect of spatial resolution and BPF on the location and characterization of rotors by comparing phase singularities detected by high-resolution unfiltered optical maps and of fibrillating myocardium with decimated and filtered maps with simulated electrode spacing of 2, 5, and 8 mm. RESULTS As we decimated the maps with 2-mm, 5-mm, and 8-mm interelectrode spacing, the mean ( ± SD) number of rotors detected decreased from 10.2 ± 9.6, 1.6 ± 3.2, and 0.2 ± 0.5, respectively. Lowering the resolution led to synthesized pseudo-rotors that may be inappropriately identified. Applying a BPF led to fewer mean phase singularities detected (248 ± 207 vs 333 ± 130; P<.01), giving the appearance of pseudo-spatial stability measured as translation index (with BPF 3.6 ± 0.4 mm vs 4.0 ± 0.5 mm without BPF; P<.01) and pseudo-temporal stability with longer duration (70.0 ± 17.6 ms in BPF maps vs 44.1 ± 6.6 ms in unfiltered maps; P<.001) than true underlying fibrillating myocardium mapped. CONCLUSION Electrode resolution and BPF of electrograms can result in distortion of the underlying electrophysiology of fibrillation. Newer mapping techniques need to demonstrate sensitivity analysis to quantify the degree of distortion before clinical use to avoid inaccurate electrophysiologic interpretation.

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.

Effects of Late Sodium Current Blockade on Ventricular Refibrillation in a Rabbit Model

Background— After defibrillation of initial ventricular fibrillation (VF), it is crucial to prevent refibrillation to ensure successful resuscitation outcomes. Inability of the late Na+ current to inactivate leads to intracellular Ca2+ dysregulation and arrhythmias. Our aim was to determine the effects of ranolazine and GS-967, inhibitors of the late Na+ current, on ventricular refibrillation. Methods and Results— Long-duration VF was induced electrically in Langendorff-perfused rabbit hearts (n=22) and terminated with a defibrillator after 6 minutes. Fibrillating hearts were randomized into 3 groups: treatment with ranolazine, GS-967, or nontreated controls. In the treated groups, hearts were perfused with ranolazine or GS-967 at 2 minutes of VF. In control experiments, perfusion solution was supplemented with isotonic saline in lieu of a drug. Inducibility of refibrillation was assessed after initial long-duration VF by attempting to reinduce VF. Sustained refibrillation was successful in fewer ranolazine-treated (29.17%; P=0.005) or GS-967–treated (45.83%, P=0.035) hearts compared with that in nontreated control hearts (84.85%). In GS-967–treated hearts, significantly more spontaneous termination of initial long-duration VF was observed (66.67%; P=0.01). Ca2+ transient duration was reduced in ranolazine-treated hearts compared with that in controls (P=0.05) and also Ca2+ alternans (P=0.03). Conclusions— Late Na+ current inhibition during long-duration VF reduces the susceptibility to subsequent refibrillation, partially by mitigating dysregulation of intracellular Ca2+. These results suggest the potential therapeutic use of ranolazine and GS-967 and call for further testing in cardiac arrest models.

A novel approach to quantification of real and artifactual components of current density imaging for phantom and live heart.

Spatial distribution of injected current in a subject could be calculated and visualized through current density imaging (CDI). Calculated CDI paths however have a limited degree of accuracy due to both avoidable methodological errors and inevitable limitations dictated by MR imaging constraints. The source and impact of these limitations are scrutinized in this paper. Quantification of such limitations is an essential step prior to passing any judgment about the results especially in biomedical applications. An innovative technique along with metrics for evaluation of range of errors using baseline and phase cycle MR images is proposed in this work. The presented approach is helpful in pinpointing the local artifacts (areas for which CDI results are suspect), evaluation of global noises and artifacts and assessment of the effect of approximation algorithms on real and artifactual components. We will demonstrate how this error/reliability evaluation is applicable to interpretation of CDI results and in this framework, report the CDI results for an artificial phantom and a live pig heart in Langendorff setup. It is contended here that using this method, the inevitable trade-off between details and approximations of CDI components could be monitored which provides a great opportunity for robust interpretation of results. The proposed approach could be extended, adapted and used for statistical analysis of similar methods which aim at mapping current and impedance based on magnetic flux images obtained through MRI.

Blind source separation in characterizing ECG pre-shock waveforms during ventricular fibrillation

Ventricular Fibrillation (VF) is a cardiac arrhythmia for which the only available treatment option is defibrillation by electrical shock. Existing literature indicates that VF could be the manifestation of different sources controlling the heart with different degrees of organization. In this work we test the hypothesis that the pre-shock waveforms of successful and unsuccessful shock outcomes could be related to the number of independent sources present in these waveforms. The proposed method uses Blind Source Separation (BSS) to extract independent components in frequency direction from a pig database consisting of 20 pre-shock waveforms. The slope of the energy capture curve was used as an indicator to demonstrate the number of independent sources required to model the pre-shock waveforms. The results were also quantified by performing a linear discriminant analysis based classification achieving an overall classification accuracy of 75%. The results indicate that successful cases can be modeled with less number of independent sources compared to unsuccessful cases.

Essential Role of RyR2 Phosphorylation in the Effect of Azumolene on Ventricular Arrhythmia Vulnerability in a Rabbit Heart Model: SI et al.

Following long‐duration ventricular fibrillation (LDVF), reinitiation of ventricular fibrillation (VF) poses a major challenge during resuscitation. Ryanodine receptor 2 (RyR2) becomes dysfunctional following VF. The relationship between LDVF, RyR2 modulation, and ventricular refibrillation, as well as the role of RyR2 phosphorylation, remains unknown.