431 research outputs found

    Catheter ablation in patients with atrial fibrillation : mapping refinements, outcome prediction and effect on quality of life

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    PhD ThesisChapter 1 presents a literature review, focused primarily on the pathophysiology and management of atrial fibrillation (AF). Chapter 2 examines correlations between the dominant frequency of AF - calculated using principal component analysis from a modified surface 12-lead ECG (which included posterior leads), a standard 12-lead ECG and intracardiac recordings from both atria. The inclusion of posterior leads did not improve correlation with left atrial activity because of the dominance of lead V1 in both ECG configurations. Chapter 3 explores whether acute and 12-month outcome following catheter ablation for AF can be predicted beforehand from clinical and surface AF waveform parameters. Multivariate risk scores combining these parameters can predict arrhythmia outcome following ablation, and could therefore be used to identify those most likely to benefit from this therapy. Chapter 4 examines the effect of catheter ablation on AF symptoms and quality of life (QoL). AF symptom and QoL scores improved significantly in patients who maintained sinus rhythm after ablation but did not change in those with recurrent AF. AF-specific QoL scales are more responsive to change and correlate better with ablation outcome. Chapter 5 examines inter-atrial frequency gradients in patients with persistent AF using multipolar contact mapping. A right-to-left atrial frequency gradient was found in a quarter of the patients studied, implying that their arrhythmia was being maintained by high frequency sources in the right rather than the left atrium. Chapter 6 examines whether targeting high frequency and highly repetitive complex fractionated atrial electrogram sites, identified using multipolar contact mapping during persistent AF, resulted in arrhythmia termination and maintenance of sinus rhythm long-term. The utility of administering flecainide to distinguish critical from bystander AF sites was also investigated. Flecainide did not help refine ablation targets and 12-month outcome after targeting these sites was not superior to other ablation strategies

    Atrial Heterogeneity Generates Re-entrant Substrate during Atrial Fibrillation and Anti-arrhythmic Drug Action: Mechanistic Insights from Canine Atrial Models

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    Anti-arrhythmic drug therapy is a frontline treatment for atrial fibrillation (AF), but its success rates are highly variable. This is due to incomplete understanding of the mechanisms of action of specific drugs on the atrial substrate at different stages of AF progression. We aimed to elucidate the role of cellular, tissue and organ level atrial heterogeneities in the generation of a re-entrant substrate during AF progression, and their modulation by the acute action of selected anti-arrhythmic drugs. To explore the complex cell-to-organ mechanisms, a detailed biophysical models of the entire 3D canine atria was developed. The model incorporated atrial geometry and fibre orientation from high-resolution micro-computed tomography, region-specific atrial cell electrophysiology and the effects of progressive AF-induced remodelling. The actions of multi-channel class III anti-arrhythmic agents vernakalant and amiodarone were introduced in the model by inhibiting appropriate ionic channel currents according to experimentally reported concentration-response relationships. AF was initiated by applied ectopic pacing in the pulmonary veins, which led to the generation of localized sustained re-entrant waves (rotors), followed by progressive wave breakdown and rotor multiplication in both atria. The simulated AF scenarios were in agreement with observations in canine models and patients. The 3D atrial simulations revealed that a re-entrant substrate was typically provided by tissue regions of high heterogeneity of action potential duration (APD). Amiodarone increased atrial APD and reduced APD heterogeneity and was more effective in terminating AF than vernakalant, which increased both APD and APD dispersion. In summary, the initiation and sustenance of rotors in AF is linked to atrial APD heterogeneity and APD reduction due to progressive remodelling. Our results suggest that anti-arrhythmic strategies that increase atrial APD without increasing its dispersion are effective in terminating AF

    A multi-variate predictability framework to assess invasive cardiac activity and interactions during atrial fibrillation

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    Objective: This study introduces a predictability framework based on the concept of Granger causality (GC), in order to analyze the activity and interactions between different intracardiac sites during atrial fibrillation (AF). Methods: GC-based interactions were studied using a three-electrode analysis scheme with multi-variate autoregressive models of the involved preprocessed intracardiac signals. The method was evaluated in different scenarios covering simulations of complex atrial activity as well as endocardial signals acquired from patients. Results: The results illustrate the ability of the method to determine atrial rhythm complexity and to track and map propagation during AF. Conclusion: The proposed framework provides information on the underlying activation and regularity, does not require activation detection or postprocessing algorithms and is applicable for the analysis of any multielectrode catheter. Significance: The proposed framework can potentially help to guide catheter ablation interventions of AF

    A Mechanistically Guided Approach to Treatment of Multi-Wavelet Reentry: Experiments in a Computational Model of Cardiac Propagation

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    Atrial fibrillation (AF) is the most common cardiac arrhythmia in the United States today. However, treatment options remain limited despite the enormous magnitude of both AF prevalence and the associated economic cost. Of those treatment options that are available, ablation-based interventional methods have demonstrated the highest rates of long-term cure. Unfortunately, these methods have substantially lower efficacy in patients with heavier burdens of disease, thus leaving the most affected individuals with the least hope for successful treatment. The focus of this research is to develop a mechanistically guided approach towards the treatment of multi-wavelet reentry (MWR), one of the primary drivers of AF. For this purpose, we use a computational model of electrical propagation in cardiac tissue to simulate both episodes of fibrillatory activity and the ablative treatment thereof. We demonstrate that the probability of forming the reentrant circuits necessary for continuous electrical activity is a function of the shape and size of a tissue as well as its underlying cellular properties. Ablation at tissue sites with high probability of circuit formation more efficiently reduces the overall duration of fibrillatory episodes than ablation at sites with low probability. We then propose and validate in silico a parameter-based metric for predicting the propensity of an individual tissue to support fibrillation, which we term the fibrillogenicity index. Using this metric, we develop an algorithm for prospectively determining optimized, tissue-specific ablation patterns. Finally, we examine the relationship between multi-wavelet reentry and focal drivers, and demonstrate that MWR and fibrillatory conduction exist along a continuum. We examine the complex interplay between functional and structural substrates within fibrillating tissue and define the mechanisms by which they promote the perpetuation of AF. These findings present a novel theoretical framework for understanding treatment of multi-wavelet reentry driven AF and provide a set of testable predictions that can serve to guide the design of future experimental studies aimed at advancing the rational design of patient-specific ablation sets for treating AF

    Mapping Technologies for Catheter Ablation of Atrial Fibrillation Beyond Pulmonary Vein Isolation

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    Catheter ablation remains the most effective and relatively minimally invasive therapy for rhythm control in patients with AF. Ablation has consistently shown a reduction of arrhythmia-related symptoms and significant improvement in patients’ quality of life compared with medical treatment. The ablation strategy relies on a well-established anatomical approach of effective pulmonary vein isolation. Additional anatomical targets have been reported with the aim of increasing procedure success in complex substrates. However, larger ablated areas with uncertainty of targeting relevant regions for AF initiation or maintenance are not exempt from the potential risk of complications and pro-arrhythmia. Recent developments in mapping tools and computational methods for advanced signal processing during AF have reported novel strategies to identify atrial regions associated with AF maintenance. These novel tools – although mainly limited to research series – represent a significant step forward towards the understanding of complex patterns of propagation during AF and the potential achievement of patient-tailored AF ablation strategies for the near future

    Automated algorithm-driven methods of localising drivers of persistent atrial fibrillation using atrial fibrillation cycle length and atrial fibrillation voltage

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    The assessment of atrial fibrillation cycle length has played a role in the development of atrial fibrillation ablation by pulmonary vein isolation (PVI) and has also been used to assess response to ablation. Areas of rapid rotational activity in the left atrium have been implied to act as drivers of persistent atrial fibrillation and several methods have been developed to identify these potential drivers. Unprocessed atrial fibrillation electrograms show large variation in cycle length and signal amplitude. Current methods of localising driver regions rely on complex pattern recognition and subjective assessment of operators. The main hypotheses of this thesis were as follows: 1) a technique can be developed to ascertain a clinically relevant, dominant cycle length for any AF segment, 2) the automated technique, can be used to map rapid and regular activity in the left atrium, 3) a patient-tailored definition of rapid activity and low AF voltage, calculated based on patient-specific parameters is feasible; 4) paired with automated low voltage substrate analysis, dominant cycle length analysis is able to provide a framework for localising drivers of AF that is objective, transparent and requires no complex pattern recognition of subjective judgement. To test the hypotheses, a technique was developed based on manual annotation of real-world AF electrograms that was able to ascertain cycle length independent of missing segments or variable cycle length or signal amplitude. Following this, an automated algorithm was validated to determine dominant cycle length. In the following chapter, the nature of AF cycle length was investigated by investigating the patterns of rapid activity with extended AF segments and the concept of patient-tailored definitions of rapid activity was introduced. In the subsequent analysis, the effect of PVI was examined on AF voltage and the AF cycle length, focusing on rapid and regular areas and low voltage zones, and their changes. The last chapter utilised the accumulated information to test the sensitivity and specificity of a percentile-based, patient-tailored approach to low AF voltage and to present an objective, automated method of localising rapid and regular areas within low voltage zones within the left atrium. In summary, it is feasible to assess and locate rapid and regular areas, and localise low voltage zones in persistent AF with a completely automated algorithm, and patient-tailored definitions of low voltage rapid AF activity are a preferable alternative to absolute cut offs.Open Acces

    Critical appraisal of technologies to assess electrical activity during atrial fibrillation: a position paper from the European Heart Rhythm Association and European Society of Cardiology Working Group on eCardiology in collaboration with the Heart Rhythm Society, Asia Pacific Heart Rhythm Society, Latin American Heart Rhythm Society and Computing in Cardiology

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    We aim to provide a critical appraisal of basic concepts underlying signal recording and processing technologies applied for (i) atrial fibrillation (AF) mapping to unravel AF mechanisms and/or identifying target sites for AF therapy and (ii) AF detection, to optimize usage of technologies, stimulate research aimed at closing knowledge gaps, and developing ideal AF recording and processing technologies. Recording and processing techniques for assessment of electrical activity during AF essential for diagnosis and guiding ablative therapy including body surface electrocardiograms (ECG) and endo- or epicardial electrograms (EGM) are evaluated. Discussion of (i) differences in uni-, bi-, and multi-polar (omnipolar/Laplacian) recording modes, (ii) impact of recording technologies on EGM morphology, (iii) global or local mapping using various types of EGM involving signal processing techniques including isochronal-, voltage- fractionation-, dipole density-, and rotor mapping, enabling derivation of parameters like atrial rate, entropy, conduction velocity/direction, (iv) value of epicardial and optical mapping, (v) AF detection by cardiac implantable electronic devices containing various detection algorithms applicable to stored EGMs, (vi) contribution of machine learning (ML) to further improvement of signals processing technologies. Recording and processing of EGM (or ECG) are the cornerstones of (body surface) mapping of AF. Currently available AF recording and processing technologies are mainly restricted to specific applications or have technological limitations. Improvements in AF mapping by obtaining highest fidelity source signals (e.g. catheter–electrode combinations) for signal processing (e.g. filtering, digitization, and noise elimination) is of utmost importance. Novel acquisition instruments (multi-polar catheters combined with improved physical modelling and ML techniques) will enable enhanced and automated interpretation of EGM recordings in the near future

    The Impact of Filter Settings on Morphology of Unipolar Fibrillation Potentials

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    Using unipolar atrial electrogram morphology as guidance for ablative therapy is regaining interest. Although standardly used in clinical practice during ablative therapy, the impact of filter settings on morphology of unipolar AF potentials is unknown. Thirty different filters were applied to 2,557,045 high-resolution epicardial AF potentials recorded from ten patients. Deflections with slope ≤ − 0.05 mV/ms and amplitude ≥ 0.3 mV were marked. High-pass filtering decreased the number of detected potentials, deflection amplitude, and percentage of fractionated potentials (≥ 2 deflections) as well as fractionation delay time (FDT) and increased percentage of single potentials. Low-pass filtering decreased the number of potentials, percentage of fractionated potentials, whereas deflection amplitude, percentage of single potentials, and FDT increased. Notch filtering (50 Hz) decreased the number of potentials and deflection amplitude, whereas the percentage of complex fractionated potentials (≥ 3 deflections) increased. Filtering significantly impacted morphology of unipolar fibrillation potentials, becoming a potential source of error in identification of ablative targets.

    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
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