Comparing Reentrant Drivers Predicted by Image-Based Computational Modeling and Mapped by Electrocardiographic Imaging in Persistent Atrial Fibrillation-Reference-Cited by-同舟云学术

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Comparing Reentrant Drivers Predicted by Image-Based Computational Modeling and Mapped by Electrocardiographic Imaging in Persistent Atrial Fibrillation

Published:2018-04-19 Issue: Volume:9 Page:
ISSN:1664-042X
Container-title:Frontiers in Physiology
language:
Short-container-title:Front. Physiol.

Author:

Boyle Patrick M.,Hakim Joe B.,Zahid Sohail,Franceschi William H.,Murphy Michael J.,Vigmond Edward J.,Dubois Rémi,Haïssaguerre Michel,Hocini Mélèze,Jaïs Pierre,Trayanova Natalia A.,Cochet Hubert

Funder

National Institutes of Health

American Heart Association

European Research Council

Agence Nationale de la Recherche

Achievement Rewards for College Scientists Foundation

Fondation Leducq

Publisher

Frontiers Media SA

Subject

Physiology (medical),Physiology

Reference32 articles.

1. The clinical profile and pathophysiology of atrial fibrillation: relationships among clinical features, epidemiology, and mechanisms;Andrade;Circ. Res.,2014

2. Arrhythmogenic substrate of the pulmonary veins assessed by high-resolution optical mapping;Arora;Circulation,2003

3. Towards personalized computational modelling of the fibrotic substrate for atrial arrhythmia;Boyle;Europace,2016

4. Atrial fibrosis: mechanisms and clinical relevance in atrial fibrillation;Burstein;J. Am. Coll. Cardiol.,2008

5. 2017 HRS/EHRA/ECAS/APHRS/SOLAECE expert consensus statement on catheter and surgical ablation of atrial fibrillation;Calkins;Heart Rhythm,2017

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