Understanding AF Mechanisms Through Computational Modelling and Simulations

Aronis, Konstantinos N.; Ali, Rheeda L.; Liang, Jialiu A.; Zhou, Shijie; Trayanova, Natalia A.

doi:10.15420/aer.2019.28.2

Cited by 21 publications

(14 citation statements)

References 116 publications

(149 reference statements)

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“…We have reached a new era in minimising X-ray radiation exposure, with new ideas and novel technologies still to be developed in the future. 46,47…”

Section: Our Perspectivesmentioning

confidence: 99%

A New Era in Zero X-ray Ablation

Mascia

Giaccardi

2020

Arrhythm Electrophysiol Rev

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In this article, the authors focus on the importance of the zero X-ray ablation approach in electrophysiology. Radiation exposure related to conventional transcatheter ablation carries small but non-negligible stochastic and deterministic effects on health. Non-fluoroscopic mapping systems can significantly reduce, or even completely avoid, radiological exposure. The zero X-ray approach determines potential clinical benefits in terms of reduction of ionising radiation exposure, as well as safe technical advantages. The use of this method can result in similar outcomes when compared to the conventional fluoroscopic technique. These results are achieved without altering the duration, or compromising the effectiveness and safety, of the procedure. The zero X-ray ablation approach is a feasible and safe alternative to fluoroscopy, which is often only used in selected cases for troubleshooting. The non-fluoroscopic approach is considered a milestone for cancer prevention in ablation procedures.

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“…We have reached a new era in minimising X-ray radiation exposure, with new ideas and novel technologies still to be developed in the future. 46,47…”

Section: Our Perspectivesmentioning

confidence: 99%

A New Era in Zero X-ray Ablation

Mascia

Giaccardi

2020

Arrhythm Electrophysiol Rev

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“…Computational modeling has advanced in its ability to shed light on the knowledge of AF. This topic, however, lies beyond the scope of this review and is well reviewed elsewhere 57–60 . Since the first discovered mutation related to AF, S140G, advancements in genetic (mutations related to ion channels, cardiogenesis, and fibrosis) and epigenetic (microRNAs, long non‐coding RNAs) modifications have shed light on the relationship between DNA and AF 23 .…”

Section: Pathophysiological Mechanisms Of Af Related To Eatmentioning

confidence: 99%

Updates on epicardial adipose tissue mechanisms on atrial fibrillation

et al. 2021

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Summary Obesity is a well‐known risk factor for atrial fibrillation (AF). Local epi‐myocardial or intra‐myocardial adiposity caused by aging, obesity, or cardiovascular disease (CVD) is considered to be a better predictor of the risk of AF than general adiposity. Some of the described mechanisms suggest that epicardial adipose tissue (EAT) participates in structural remodeling owing to its endocrine activity or its infiltration between cardiomyocytes. Epicardial fat also wraps up the ganglionated plexi that reach the myocardium. Although the increment of volume/thickness and activity of EAT might modify autonomic activity, autonomic system dysfunction might also change the endocrine activity of epicardial fat in a feedback response. As a result, new preventive therapeutic strategies are focused on reducing adiposity and weight loss before AF ablation or inhibiting autonomic neurotransmitter secretion on fat pads during open‐heart surgery to reduce the recurrence or postoperative risk of AF. In this manuscript, we review some of the novel findings regarding the pathophysiology and associated risk factors of AF, with special emphasis on the role of EAT in the electrical, structural, and molecular mechanisms of AF initiation and maintenance. In addition, we have included a brief note provided on epicardial fat preclinical models that could be useful for identifying new therapeutic targets.

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“… 24 In silico studies also demonstrated that AF-promoting atrial repolarization alternans might occur due to decreased RyR inactivation, and that calcium-driven repolarization alternans due to AF-associated electrical remodelling increased the vulnerability to ectopy-induced arrhythmia. 12 , 68 , 69 Finally, in silico models of human atrial cardiomyocytes 75 , 118 , 120 have been used to study the impact of AF-related ion-channel remodelling 70–74 and remodelling associated with AF risk factors. 59 Until recently, most computational studies employed a single deterministic model, reflecting a representative atrial cardiomyocyte, thereby disregarding experimentally observed variability.…”

Section: The Role Of Mechanistic Models To Improve Understanding and Management Of Afmentioning

confidence: 99%

Computational models of atrial fibrillation: achievements, challenges, and perspectives for improving clinical care

Heijman

Sutanto

Crijns

et al. 2021

Cardiovascular Research

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Despite significant advances in its detection, understanding and management, atrial fibrillation (AF) remains a highly prevalent cardiac arrhythmia with major impact on morbidity and mortality of millions of patients. AF results from complex, dynamic interactions between risk factors and comorbidities that induce diverse atrial remodeling processes. Atrial remodeling increases AF vulnerability and persistence, while promoting disease progression. The variability in presentation and wide range of mechanisms involved in initiation, maintenance and progression of AF, as well as its associated adverse outcomes, make the early identification of causal factors modifiable with therapeutic interventions challenging, likely contributing to suboptimal efficacy of current AF management. Computational modeling facilitates the multilevel integration of multiple datasets and offers new opportunities for mechanistic understanding, risk prediction and personalized therapy. Mathematical simulations of cardiac electrophysiology have been around for 60 years and are being increasingly used to improve our understanding of AF mechanisms and guide AF therapy. This narrative review focuses on the emerging and future applications of computational modeling in AF management. We summarize clinical challenges that may benefit from computational modeling, provide an overview of the different in silico approaches that are available together with their notable achievements, and discuss the major limitations that hinder the routine clinical application of these approaches. Finally, future perspectives are addressed. With the rapid progress in electronic technologies including computing, clinical applications of computational modeling are advancing rapidly. We expect that their application will progressively increase in prominence, especially if their added value can be demonstrated in clinical trials.

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Understanding AF Mechanisms Through Computational Modelling and Simulations

Cited by 21 publications

References 116 publications

A New Era in Zero X-ray Ablation

A New Era in Zero X-ray Ablation

Updates on epicardial adipose tissue mechanisms on atrial fibrillation

Computational models of atrial fibrillation: achievements, challenges, and perspectives for improving clinical care

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