Ablating atrial fibrillation: A translational science perspective for clinicians

Weiss, James N.; Qu, Zhilin; Shivkumar, Kalyanam

doi:10.1016/j.hrthm.2016.05.026

Cited by 20 publications

(19 citation statements)

References 54 publications

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“…AF is often referred to as the most common arrhythmia in clinical practice with an estimated prevalence of 2% and is associated with a five-fold and two-fold higher risk of stroke and death, respectively (43). Catheter ablation of AF yields moderate success rates (44)(45)(46), which is related to the lack of understanding of AF mechanisms. Different mechanisms for AF have been described such as focal activation, dissociated activity or stable rotors (47)(48)(49)(50)(51)(52).…”

Section: Discussionmentioning

confidence: 99%

Directed networks as a novel way to describe and analyze cardiac excitation: Directed Graph mapping

Vandersickel

Nieuwenhuyse

Cleemput

et al. 2019

Preprint

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Networks provide a powerful methodology with applications in a variety of biological, technological and social systems such as analysis of brain data, social networks, internet search engine algorithms, etc. To date, directed networks have not yet been applied to characterize the excitation of the human heart. In clinical practice, cardiac excitation is recorded by multiple discrete electrodes. During (normal) sinus rhythm or during cardiac arrhythmias, successive excitation connects neighboring electrodes, resulting in their own unique directed network. This in theory makes it a perfect fit for directed network analysis. In this study, we applied directed networks to the heart in order to describe and characterize cardiac arrhythmias. Proofof-principle was established using in-silico and clinical data. We demonstrated that tools used in network theory analysis allow to determine the mechanism and location of certain cardiac arrhythmias. We show that the robustness of this approach can potentially exceed the existing state-of-the art methodology used in clinics. Furthermore, implementation of these techniques in daily practice can improve accuracy and speed of cardiac arrhythmia analysis. It may also provide novel insights in arrhythmias that are still incompletely understood. network theory| cardiac arrhythmia Correspondence: nele.vandersickel@ugent.be

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Section: Discussionmentioning

confidence: 99%

Directed networks as a novel way to describe and analyze cardiac excitation: Directed Graph mapping

Vandersickel

Nieuwenhuyse

Cleemput

et al. 2019

Preprint

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“…We focused exclusively on these two properties because they are known to affect multiple emergent phenomena relevant to arrhythmia dynamics, including refractoriness periods, wavebreak incidence, and RD stability. [34][35][36] For simulations with APD variability, specific ionic currents were modified to achieve Since we were concerned about variability in intrinsic APD, these experiments were conducted in isolated cell-scale models. For simulations with CV variability, the longitudinal and transverse components of the conductivity tensor were modified to achieve 610% CV.…”

Section: B Modeling Cell-and Tissue-scale Variability Of Atrial Elecmentioning

confidence: 99%

Sensitivity of reentrant driver localization to electrophysiological parameter variability in image-based computational models of persistent atrial fibrillation sustained by a fibrotic substrate

Deng

Murphy

Hakim

et al. 2017

Chaos: An Interdisciplinary Journal of Nonlinear Science

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Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia, causing morbidity and mortality in millions worldwide. The atria of patients with persistent AF (PsAF) are characterized by the presence of extensive and distributed atrial fibrosis, which facilitates the formation of persistent reentrant drivers (RDs, i.e., spiral waves), which promote fibrillatory activity. Targeted catheter ablation of RD-harboring tissues has shown promise as a clinical treatment for PsAF, but the outcomes remain sub-par. Personalized computational modeling has been proposed as a means of non-invasively predicting optimal ablation targets in individual PsAF patients, but it remains unclear how RD localization dynamics are influenced by inter-patient variability in the spatial distribution of atrial fibrosis, action potential duration (APD), and conduction velocity (CV). Here, we conduct simulations in computational models of fibrotic atria derived from the clinical imaging of PsAF patients to characterize the sensitivity of RD locations to these three factors. We show that RDs consistently anchor to boundaries between fibrotic and non-fibrotic tissues, as delineated by late gadolinium-enhanced magnetic resonance imaging, but those changes in APD/CV can enhance or attenuate the likelihood that an RD will anchor to a specific site. These findings show that the level of uncertainty present in patient-specific atrial models reconstructed without any invasive measurements (i.e., incorporating each individual's unique distribution of fibrotic tissue from medical imaging alongside an average representation of AF-remodeled electrophysiology) is sufficiently high that a personalized ablation strategy based on targeting simulation-predicted RD trajectories alone may not produce the desired result.

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“…Success rates for catheter ablation of persistent atrial fibrillation (AF) patients are currently low; however, there is a subset of patients for whom pulmonary vein isolation (PVI) alone is a successful treatment strategy [ 1 ]. PVI ablation may work by preventing triggered beats from entering the left atrial body, or by converting rotors or functional reentry around the left atrial/pulmonary vein (LA/PV) junction to anatomical reentry around a larger circuit, potentially converting AF to a simpler tachycardia [ 2 ]. It is difficult to predict whether PVI represents a sufficient treatment strategy for a given patient with persistent AF [ 1 ], and it is unclear what to do for the majority of patients for whom it is not effective.…”

Section: Introductionmentioning

confidence: 99%

Variability in pulmonary vein electrophysiology and fibrosis determines arrhythmia susceptibility and dynamics

et al. 2018

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Success rates for catheter ablation of persistent atrial fibrillation patients are currently low; however, there is a subset of patients for whom electrical isolation of the pulmonary veins alone is a successful treatment strategy. It is difficult to identify these patients because there are a multitude of factors affecting arrhythmia susceptibility and maintenance, and the individual contributions of these factors are difficult to determine clinically. We hypothesised that the combination of pulmonary vein (PV) electrophysiology and atrial body fibrosis determine driver location and effectiveness of pulmonary vein isolation (PVI). We used bilayer biatrial computer models based on patient geometries to investigate the effects of PV properties and atrial fibrosis on arrhythmia inducibility, maintenance mechanisms, and the outcome of PVI. Short PV action potential duration (APD) increased arrhythmia susceptibility, while longer PV APD was found to be protective. Arrhythmia inducibility increased with slower conduction velocity (CV) at the LA/PV junction, but not for cases with homogeneous CV changes or slower CV at the distal PV. Phase singularity (PS) density in the PV region for cases with PV fibrosis was increased. Arrhythmia dynamics depend on both PV properties and fibrosis distribution, varying from meandering rotors to PV reentry (in cases with baseline or long APD), to stable rotors at regions of high fibrosis density. Measurement of fibrosis and PV properties may indicate patient specific susceptibility to AF initiation and maintenance. PV PS density before PVI was higher for cases in which AF terminated or converted to a macroreentry; thus, high PV PS density may indicate likelihood of PVI success.

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Ablating atrial fibrillation: A translational science perspective for clinicians

Cited by 20 publications

References 54 publications

Directed networks as a novel way to describe and analyze cardiac excitation: Directed Graph mapping

Directed networks as a novel way to describe and analyze cardiac excitation: Directed Graph mapping

Sensitivity of reentrant driver localization to electrophysiological parameter variability in image-based computational models of persistent atrial fibrillation sustained by a fibrotic substrate

Variability in pulmonary vein electrophysiology and fibrosis determines arrhythmia susceptibility and dynamics

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