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Maintenance of Atrial Fibrillation

Brian J. Hansen, Thomas A. Csepe, Jichao Zhao, Anthony J. Ignozzi, John D. Hummel, Vadim V. Fedorov
2016 Circulation: Arrhythmia and Electrophysiology  
Keywords atrial fibrillation; optical mapping; intramural microanatomic reentry; reentrant driver; human atria Presented in the following review are the insights on atrial fibrillation (AF) gained from  ...  by localized AF drivers 1 .  ...  The utilization of non-toxic near-infrared voltage-sensitive dye 20, 21 allowed us to record optical action potentials up to 4mm deep simultaneously from sub-endocardial and sub-epicardial layers ( Figure  ... 
doi:10.1161/circep.116.004398 pmid:27729340 pmcid:PMC5066578 fatcat:eycex6gimjggfnjpsot55ek7nm

Artificial intelligence in the diagnosis and management of arrhythmias

Venkat D Nagarajan, Su-Lin Lee, Jan-Lukas Robertus, Christoph A Nienaber, Natalia A Trayanova, Sabine Ernst
2021 European Heart Journal  
Recent renewed interest in deep learning techniques has opened new frontiers in electrocardiography analysis including signature identification of diseased states.  ...  Changing lifestyles with an expansion of the concept of internet of things and advancements in telecommunication technology have opened doors to population-based detection of atrial fibrillation in ways  ...  ADAS, Automatic Detection of Arrhythmic Substrate; AF, atrial fibrillation; BSM, body surface mapping; CIE, computerized interpretation of electrocardiography; DL, deep learning; EAM, electro anatomical  ... 
doi:10.1093/eurheartj/ehab544 pmid:34392353 pmcid:PMC8497074 fatcat:n23f4f5x2fhivcccw5cqkejhbi

Non-invasive Estimation of Atrial Fibrillation Driver Position With Convolutional Neural Networks and Body Surface Potentials

Miguel Ángel Cámara-Vázquez, Ismael Hernández-Romero, Eduardo Morgado-Reyes, Maria S. Guillem, Andreu M. Climent, Oscar Barquero-Pérez
2021 Frontiers in Physiology  
a non-invasive recording of body surface potentials (BSP).  ...  Therefore, CNN could be a robust method that could help to non-invasively identify target regions for ablation in AF by using body surface potential mapping, avoiding the use of ECGI.  ...  024346B-750), Consejería de Ciencia, Universidades e Innovación of the Comunidad de Madrid through the program RIS3 (S-2020/L2-622), EIT Health (Activity code 19600, EIT Health is supported by EIT, a body  ... 
doi:10.3389/fphys.2021.733449 pmid:34721065 pmcid:PMC8552066 fatcat:f7hqlsqhqbcbvb5sqcl4tf22d4

Editorial: Recent Advances in Understanding the Basic Mechanisms of Atrial Fibrillation Using Novel Computational Approaches

Jichao Zhao, Oleg Aslanidi, Pawel Kuklik, Geoffrey Lee, Gary Tse, Steven Niederer, Edward J. Vigmond
2019 Frontiers in Physiology  
Atrial fibrillation (AF) is the most common sustained heart rhythm disturbance, associated with substantial morbidity and mortality (Andrade et al., 2014) .  ...  Multi-scale computer models of the human atria have been used to investigate the important role of fibrosis in AF and consistently demonstrated that AF is perpetuated by the re-entrant circuits persisting  ...  For example, deep convolutional neural networks have been used to classify AF from single-lead ECGs (Hannun et al., 2019) and to reconstruct 3D left atrial chambers from gadolinium-enhanced MRIs (Xiong  ... 
doi:10.3389/fphys.2019.01065 pmid:31551796 pmcid:PMC6736575 fatcat:6qoucnypynhynnip45kh3dlsly

Patient-derived models link re-entrant driver localization in atrial fibrillation to fibrosis spatial pattern

Sohail Zahid, Hubert Cochet, Patrick M. Boyle, Erica L. Schwarz, Kaitlyn N. Whyte, Edward J. Vigmond, Rémi Dubois, Mélèze Hocini, Michel Haïssaguerre, Pierre Jaïs, Natalia A. Trayanova
2016 Cardiovascular Research  
The goal of this study was to use patient-derived atrial models to test the hypothesis that AF re-entrant drivers (RDs) persist only in regions with specific fibrosis patterns.  ...  Aims The mechanisms underlying persistent atrial fibrillation (AF) in patients with atrial fibrosis are poorly understood.  ...  Unipolar electrograms were reconstructed from body surface potentials, as previously described. 38 Re-entrant drivers and fibrosis in AF models From unipolar electrograms, local phase was computed to  ... 
doi:10.1093/cvr/cvw073 pmid:27056895 pmcid:PMC4872878 fatcat:e475tsdaafckbjyll2doiugcuy

The Electrophysiology of Atrial Fibrillation: From Basic Mechanisms to Catheter Ablation

Panagiotis Ioannidis, Theodoros Zografos, Evangelia Christoforatou, Konstantinos Kouvelas, Andreas Tsoumeleas, Charalambos Vassilopoulos, Robert Chen
2021 Cardiology Research and Practice  
The electrophysiology of atrial fibrillation (AF) has always been a deep mystery in understanding this complex arrhythmia.  ...  If this really happens, then the targeted ablation may be the solution; otherwise, more rough techniques such as atrial compartmentalization may prove to be more effective.  ...  In the study of Ammar-Busch et al., CFAEs were indeed correlated with AF drivers as highlighted by noninvasive body surface mapping.  ... 
doi:10.1155/2021/4109269 fatcat:bt37os2fojhl3aaoxu654uxwbq

Convolutional Neural Networks for Mechanistic Driver Detection in Atrial Fibrillation

Gonzalo Ricardo Ríos-Muñoz, Francisco Fernández-Avilés, Ángel Arenal
2022 International Journal of Molecular Sciences  
The maintaining and initiating mechanisms of atrial fibrillation (AF) remain controversial.  ...  Deep learning is emerging as a powerful tool to better understand AF and improve its treatment, which remains suboptimal.  ...  AF, atrial fibrillation; BSA, body surface area; COPD, chronic obstructive pulmonary disease; SHD, structural heart disease. Table 2 . 2 Performance results.  ... 
doi:10.3390/ijms23084216 pmid:35457044 pmcid:PMC9032062 fatcat:l6qci54ianbyjdrihwuvyarhta

Atrial Fibrosis Hampers Non-invasive Localization of Atrial Ectopic Foci From Multi-Electrode Signals: A 3D Simulation Study

Eduardo Jorge Godoy, Miguel Lozano, Ignacio García-Fernández, Ana Ferrer-Albero, Rob MacLeod, Javier Saiz, Rafael Sebastian
2018 Frontiers in Physiology  
BSPM were obtained for all simulations, and the body surface potential integral maps (BSPiM) were calculated to describe atrial activations.  ...  Multi-electrode surface ECG systems allow acquiring dense body surface potential maps (BSPM) for non-invasive therapy planning of cardiac arrhythmia.  ...  The use of multi-electrode surface ECG systems allows for dense body surface potential maps (BSPM) with the aim of improving diagnosis of cardiac arrhythmia.  ... 
doi:10.3389/fphys.2018.00404 pmid:29867517 pmcid:PMC5968126 fatcat:mphxzpz4vfdijmex3xuos65qjm

Body Surface Potential Mapping: Contemporary Applications and Future Perspectives

Jake Bergquist, Lindsay Rupp, Brian Zenger, James Brundage, Anna Busatto, Rob S. MacLeod
2021 Hearts  
Body surface potential mapping (BSPM) is a noninvasive modality to assess cardiac bioelectric activity with a rich history of practical applications for both research and clinical investigation.  ...  In this report, we examine contemporary uses of BSPM, and provide an assessment of its future prospects in both clinical and research environments.  ...  Recent studies in this domain have explored the use of ECGI to identify atrial fibrillation drivers using both simulated data and real-world clinical data [159, [184] [185] [186] .  ... 
doi:10.3390/hearts2040040 fatcat:sgzzoo76b5f3fgewfklu6wzdei

16th Atrial Fibrillation Symposium

Stephanie Wasek
2017 Arrhythmia & Electrophysiology Review  
International expert faculty shared experiences from their practice, as well as tips and tricks.  ...  The next two days comprised the Atrial Fibrillation Symposium, where international faculties presented the newest developments and research results, some prior to publication.  ...  Bruges, Belgium, closed the 16th Atrial Fibrillation Symposium by thanking the presenters and attendees for the fruitful discussions, and interactive and insightful learning.  ... 
doi:10.15420/aer.2017.6.4.sup1 fatcat:vzzuhwje6jbyhkxahc3rw6fpea

Post Ablation Left Atrial Tachycardia: Understanding Mechanism, Prevention and Treatment

Carlo Pappone, Vincenzo Santinelli
2012 Journal of Atrial Fibrillation  
Understanding mechanisms and location of potentially widely located arrhythmogenic substrates in the left atrium is crucial for successful ablation.  ...  Currently, post-ablation Atrial Tachycardias (ATs) represent a growing clinical problem particularly in patients with persistent AF undergoing a more extensive substrate ablation.  ...  The local activation time, recorded from the catheter tip at each mapping site, is measured relative to the timing of the reference atrial potential.  ... 
doi:10.4022/jafib.525 pmid:28496760 pmcid:PMC5153123 fatcat:b5bmu63wwbbenprlwhowxfxiom

2021 ISHNE/HRS/EHRA/APHRS collaborative statement on mHealth in Arrhythmia Management: Digital Medical Tools for Heart Rhythm Professionals

Niraj Varma, Iwona Cygankiewicz, Mintu Turakhia, Hein Heidbuchel, Yufeng Hu, Lin Yee Chen, Jean‐Philippe Couderc, Edmond M. Cronin, Jerry D. Estep, Lars Grieten, Deirdre A. Lane, Reena Mehra (+12 others)
2021 Journal of Arrhythmia  
This collaborative statement from the International Society for Holter and Noninvasive Electrocardiology/Heart Rhythm Society/European Heart Rhythm Association/Asia Pacific Heart Rhythm Society describes  ...  High-throughput, contact-free detection of atrial fibrillation from video with deep learning.  ...  Most commonly, AI is implemented using analytical methods of machine learning or deep learning. These methods are well suited for pattern classifications, such as images, including ECG.  ... 
doi:10.1002/joa3.12461 pmid:33850572 pmcid:PMC8022003 fatcat:exfxdxrszzbovgyw37cwiheohu

Deep Learning in the Biomedical Applications: Recent and Future Status

Ryad Zemouri, Noureddine Zerhouni, Daniel Racoceanu
2019 Applied Sciences  
Deep neural networks represent, nowadays, the most effective machine learning technology in biomedical domain.  ...  This paper reviews the major deep learning concepts pertinent to such biomedical applications. Concise overviews are provided for the Omics and the BBMI.  ...  fibrillation ECG CNN [265] Detection sleep apnea ECG DNN [266] Detecting atrial fibrillation ECG CNN [267] Fetal electrocardiogram (FECG) monitoring ECG DNN [268] Drowsiness detection  ... 
doi:10.3390/app9081526 fatcat:srjvngtufbhstfcvn4mvhmrdve

2019 APHRS expert consensus statement on three‐dimensional mapping systems for tachycardia developed in collaboration with HRS, EHRA, and LAHRS

Young‐Hoon Kim, Shih‐Ann Chen, Sabine Ernst, Carlos E. Guzman, Seongwook Han, Zbigniew Kalarus, Carlos Labadet, Yenn‐Jian Lin, Li‐Wei Lo, Akihiko Nogami, Eduardo B. Saad, John Sapp (+5 others)
2020 Journal of Arrhythmia  
cited, the use is non-commercial and no modifications or adaptations are made.  ...  This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly  ...  using CT reconstruction for paroxysmal atrial fibrillation catheter ablation.  ... 
doi:10.1002/joa3.12308 pmid:32256872 pmcid:PMC7132207 fatcat:dsdnhfi3rnfydcmzzs4tywmvdu

The efficacy of intraoperative atrial radiofrequency ablation for atrial fibrillation during concomitant cardiac surgery—the Surgical Atrial Fibrillation Suppression (SAFS) Study

Rick A. Veasey, Oliver R. Segal, Janet K. Large, Michael E. Lewis, Uday H. Trivedi, Andrew S. Cohen, Jonathan A. J. Hyde, A. Neil Sulke
2011 Journal of interventional cardiac electrophysiology  
Four patients had episodes of asymptomatic paroxysmal atrial fibrillation, with a mean AF burden of 12.6% for these individuals.  ...  However, prolonged cardiac monitoring demonstrates a significant number of patients to have asymptomatic episodes of atrial fibrillation.  ...  To localize the arrhyth- mogenic focuses and areas of VRH by body surface potential map- ping (BSPM).  ... 
doi:10.1007/s10840-011-9576-y pmid:21687970 fatcat:cggib4oiarci7c7s54f4c444ga
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