652 research outputs found

    The amplitude-normalised area of a bipolar electrograms as a measure of local conduction delay in the heart

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    Background: Re-entrant ventricular tachycardia may be non-inducible or haemodynamically compromising, requiring assessment of the electrophysiological properties of the myocardium during sinus rhythm (i.e., substrate mapping). Areas of heart tissue with slow conduction can act as a critical isthmus for re-entrant electrical excitation and are a potential target for ablation therapy. Aim: To develop and validate a novel metric of local conduction delay in the heart, the amplitude-normalized electrogram area (norm_EA). Methods: A computational model of a propagating mouse action potential was used to establish the impact of altering sodium channel conductance, intracellular conductivity, fibrosis density, and electrode size/orientation on bipolar electrogram morphology. Findings were then validated in experimental studies in mouse and guinea pig hearts instrumented for the recording of bipolar electrograms from a multipolar linear mapping catheter. norm_EA was calculated by integrating the absolute area of a bipolar electrogram divided by the electrogram amplitude. Electrogram metrics were correlated with the local conduction delay during sodium channel block, gap junction inhibition, and acute ischemia. Results: In computational simulations, reducing sodium channel conductance and intracellular conductivity resulted in a decrease in signal amplitude and increase in norm_EA (reflecting a broadening of electrogram morphology). For larger electrodes (3 mm diameter/7.1 mm2 area), the change in norm_EA was essentially linear with the change in local conduction delay. Experimental studies supported this finding, showing that the magnitude of change in norm_EA induced by flecainide (1–4 μM), carbenoxolone (10–50 μM), and low-flow ischemia (25% of initial flow rate) was linearly correlated with the local conduction delay in each condition (r2 = 0.92). Qualitatively similar effects were observed in guinea pig hearts perfused with flecainide. Increasing fibrosis density in the computational model also resulted in a decrease in signal amplitude and increase in norm_EA. However, this remains to be validated using experimental/clinical data of chronic infarct. Conclusion: norm_EA is a quantitative measure of local conduction delay between the electrode pair that generates a bipolar electrogram, which may have utility in electrophysiological substrate mapping of non-inducible or haemodynamically compromising tachyarrhythmia

    Endocardial activation mapping of human atrial fibrillation

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    Successful ablation of arrhythmias depends upon interpretation of the mechanism. However, in persistent atrial fibrillation (AF) ablation is currently directed towards the mechanism that initiates paroxysmal AF. We sought to address the hypothesis that atrial activation patterns during persistent AF may help determine the underlying mechanism. Activation mapping of AF wavefronts is labor intensive and often restricted to short time segments in limited atrial locations. RETRO-Mapping was developed to identify uniform wavefronts that occur during AF, and summate all wavefront vectors on to an orbital plot. Uniform wavefronts were mapped using RETRO-Mapping during sinus rhythm, atrial tachycardia, and atrial fibrillation, and validated against detailed manual analysis of the same wavefronts with conventional isochronal mapping. RETRO-Mapping was found to have comparable accuracy to isochronal mapping. RETRO-Mapping was then used to investigate atrial activation patterns during persistent AF. Atrial activation patterns demonstrated evidence of spatiotemporal stability over long time periods. Orbital plots created at different time points in the same location remained unchanged. Together with this important discovery, both fractionation and bipolar voltage were also demonstrated to express stability over time. Spatiotemporal stability during persistent AF enables sequential mapping as an acceptable technique. This property also allowed the development of a method for displaying sequentially mapped locations on a single map – RETRO-Choropleth Map. These findings go against the multiple wavelet hypothesis with random activation. Having gained insights in to these stable activation patterns, extensive analysis was undertaken to identify the presence of focal activation. Focal activations were identified during persistent AF. RETRO-Mapping was used to show that adjacent activation patterns were not related to focal activations. Lastly, the effect of pulmonary vein isolation (PVI) was studied by mapping atrial activation patterns before and after PVI. RETRO-Mapping showed that PVI leads to increased organisation of AF in most patients, supporting a mechanistic role of the pulmonary veins in persistent AF. In conclusion, a new technique has been developed and validated for automated activation mapping of persistent AF. These techniques could be used to guide additional ablation strategies beyond PVI for patients with persistent AF.Open Acces

    The contact electrogram and its architectural determinants in atrial fibrillation

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    The electrogram is the sine qua non of excitable tissues, yet classification in atrial fibrillation (AF) remains poorly related to substrate factors. The objective of this thesis was to establish the relationship between electrograms and two commonly implicated substrate factors, connexin 43 and fibrosis in AF. The substrates and methods chosen to achieve this ranged from human acutely induced AF using open chest surgical mapping (Chapter 6), ex vivo whole heart Langendorff (Chapter 7) with in vivo telemetry confirming spontaneous AF in a new species of rat, the Brown Norway and finally isolated atrial preparations from an older cohort of rats using orthogonal pacing and novel co-localisation methods at sub-millimetre resolution and in some atria, optical mapping (Chapter 8). In rodents, electrode size and spacing was varied (Chapters 5, 10) to study its effects on structure function correlations (Chapter 9). Novel indices of AF organisation and automated electrogram morphology were used to quantify function (Chapter 4). Key results include the discoveries that humans without any history of prior AF have sinus rhythm electrograms with high spectral frequency content, that wavefront propagation velocities correlated with fibrosis and connexin phosphorylation ratios, that AF heterogeneity of conduction correlates to fibrosis and that orthogonal pacing in heavily fibrosed atria causes anisotropy in electrogram-fibrosis correlations. Furthermore, fibrosis and connexin 43 have differing and distinct spatial resolutions in their relationship with AF organisational indices. In conclusion a new model of AF has been found, and structure function correlations shown on an unprecedented scale, but with caveats of electrode size and direction dependence. These findings impact structure function methods and prove the effect of substrate on AF organisation.Open Acces

    Modeling the Heart as a Communication System

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    Electrical communication between cardiomyocytes can be perturbed during arrhythmia, but these perturbations are not captured by conventional electrocardiographic metrics. We developed a theoretical framework to quantify electrical communication using information theory metrics in 2-dimensional cell lattice models of cardiac excitation propagation. The time series generated by each cell was coarse-grained to 1 when excited or 0 when resting. The Shannon entropy for each cell was calculated from the time series during four clinically important heart rhythms: normal heartbeat, anatomical reentry, spiral reentry, and multiple reentry. We also used mutual information to perform spatial profiling of communication during these cardiac arrhythmias. We found that information sharing between cells was spatially heterogeneous. In addition, cardiac arrhythmia significantly impacted information sharing within the heart. Entropy localized the path of the drifting core of spiral reentry, which could be an optimal target of therapeutic ablation. We conclude that information theory metrics can quantitatively assess electrical communication among cardiomyocytes. The traditional concept of the heart as a functional syncytium sharing electrical information cannot predict altered entropy and information sharing during complex arrhythmia. Information theory metrics may find clinical application in the identification of rhythm-specific treatments which are currently unmet by traditional electrocardiographic techniques.Comment: 26 pages (including Appendix), 6 figures, 8 videos (not uploaded due to size limitation

    Complexity of Atrial Fibrillation Electrograms Through Nonlinear Signal Analysis: In Silico Approach

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    Identification of atrial fibrillation (AF) mechanisms could improve the rate of ablation success. However, the incomplete understanding of those mechanisms makes difficult the decision of targeting sites for ablation. This work is focused on the importance of EGM analysis for detecting and modulating rotors to guide ablation procedures and improve its outcomes. Virtual atrial models are used to show how nonlinear measures can be used to generate electroanatomical maps to detect critical sites in AF. A description of the atrial cell mathematical models, and the procedure of coupling them within two‐dimensional and three‐dimensional virtual atrial models in order to simulate arrhythmogenic mechanisms, is given. Mathematical modeling of unipolar and bipolar electrogramas (EGM) is introduced. It follows a discussion of EGM signal processing. Nonlinear descriptors, such as approximate entropy and multifractal analysis, are used to study the dynamical behavior of EGM signals, which are not well described by a linear law. Our results evince that nonlinear analysis of EGM can provide information about the dynamics of rotors and other mechanisms of AF. Furthermore, these fibrillatory patterns can be simulated using virtual models. The combination of features using machine learning tools can be used for identifying arrhythmogenic sources of AF

    Uncovering Atrial Fibrillation Complexity: From signals to (bio)markers

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    Signal processing of intracardiac electrograms : optimization of mapping and ablation in tachyarrhythmias

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    Examining Left Axis Deviation

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    Axis deviation indicates possible presence of various conditions. It also affects the QRS and T morphologies. The limits of axis deviations are as such arbitrary and the approximate degree of axis itself can be easily determined. Various conditions often shift the QRS axis without fulfilling the defined limits of deviations in the initial stage. The associations with various conditions may be missed if such partial shift of the axis is disregarded. Isolated left axis deviation is relatively common in the general population and left anterior fascicular conduction delay is the most common cause of such isolated leftward shift of axis. Vulnerability of left anterior fascicle to interruption makes it likely to be affected by both atherosclerosis and fibrodegeneration. Glucose intolerance may increase the risk of both atherosclerosis and fibrodegeneration. The association of glucose intolerance with leftward shift of axis has been increasingly noticed. Research studies to get further evidences are required; however, utilizing the already available evidences to protect the susceptible population is equally essential. Documenting the approximate degree itself of the axis is the bottom line to study the association with the levels of various possible risk factors like glycated hemoglobin

    Doctor of Philosophy

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    dissertationFibrillation is defined as turbulent cardiac electrical activity and results in the inability of the myocardium to contract. When fibrillation occurs in the ventricles, it is known as ventricular fibrillation (VF). The consequence of VF is sudden death unless treated immediately. Fibrillation can also occur in the atria and is known as atrial fibrillation (AF). The consequences of atrial fibrillation (AF) are less immediate; however, it leads to increased risk of stroke. Despite the impact of fibrillatory arrhythmias, there are many gaps in our mechanistic knowledge of these arrhythmias. The purpose of this dissertation is to study through several projects how different cardiac substrates help initiate and/or sustain fibrillation. The first project examined several properties of the ventricular conduction system during VF. The conduction system coordinates excitation and consequently coordinates the contraction of the ventricles. Despite the conduction system's unique structure, its role in VF remains unclear. We examined the proximal conduction system and found that it develops a more rapid activation rate than the ventricular myocardium during prolonged VF, and may be driving the arrhythmia. The second and third projects examined the effects of fibrosis on electrical conduction to initiate and/or sustain AF. Despite fibrosis being associated with AF, it is still unknown whether it is a byproduct of an underlying heart disease and does not in itself promote AF, or if it affects the organization of conduction during fibrillation to promote AF. In the second project we studied the effect of fibrosis on conduction following different types of triggers. We found that fibrosis causes transverse conduction slowing following premature stimulation, which makes AF more likely to initiate. As AF persists, single episodes of AF last longer before the patient transitions into normal sinus rhythm, and in some cases AF can become permanent. The third project examined why some patients may never transition from AF to normal sinus rhythm. Specifically, this project found that regions of dense fibrosis anchor high-frequency activation that may be driving the arrhythmia. These studies showed that fibrosis causes conduction changes that make AF more likely to initiate and to be sustained
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