Literature DB >> 31400870

Noninvasive Mapping and Electrocardiographic Imaging in Atrial and Ventricular Arrhythmias (CardioInsight).

Ghassen Cheniti1, Stephane Puyo2, Claire A Martin3, Antonio Frontera3, Konstantinos Vlachos3, Masateru Takigawa3, Felix Bourier3, Takeshi Kitamura3, Anna Lam3, Carole Dumas-Pommier4, Xavier Pillois4, Thomas Pambrun3, Josselin Duchateau3, Nicolas Klotz3, Arnaud Denis3, Nicolas Derval3, Hubert Cochet5, Frederic Sacher3, Remi Dubois2, Pierre Jais3, Meleze Hocini3, Michel Haissaguerre3.   

Abstract

Electrocardiographic imaging is a mapping technique aiming to noninvasively characterize cardiac electrical activity using signals collected from the torso to reconstruct epicardial potentials. Its efficacy has been demonstrated clinically, from mapping premature ventricular complexes and accessory pathways to of complex arrhythmias. Electrocardiographic imaging uses a standardized workflow. Signals should be checked manually to avoid automatic processing errors. Reentry is confirmed in the presence of local activation covering the arrhythmia cycle length. Focal breakthroughs demonstrate a QS pattern associated with centrifugal activation. Electrocardiographic imaging offers a unique opportunity to better understand the mechanism of cardiac arrhythmias and guide ablation.
Copyright © 2019 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Ablation; Arrhythmias; ECGI; Electrocardiographic imaging; Noninvasive mapping

Mesh:

Year:  2019        PMID: 31400870     DOI: 10.1016/j.ccep.2019.05.004

Source DB:  PubMed          Journal:  Card Electrophysiol Clin        ISSN: 1877-9182


  5 in total

Review 1.  How personalized heart modeling can help treatment of lethal arrhythmias: A focus on ventricular tachycardia ablation strategies in post-infarction patients.

Authors:  Natalia A Trayanova; Ashish N Doshi; Adityo Prakosa
Journal:  Wiley Interdiscip Rev Syst Biol Med       Date:  2020-01-09

2.  Body Surface Potential Mapping: Contemporary Applications and Future Perspectives.

Authors:  Jake Bergquist; Lindsay Rupp; Brian Zenger; James Brundage; Anna Busatto; Rob S MacLeod
Journal:  Hearts (Basel)       Date:  2021-11-05

Review 3.  Artificial intelligence in the diagnosis and management of arrhythmias.

Authors:  Venkat D Nagarajan; Su-Lin Lee; Jan-Lukas Robertus; Christoph A Nienaber; Natalia A Trayanova; Sabine Ernst
Journal:  Eur Heart J       Date:  2021-10-07       Impact factor: 29.983

4.  Spatial-Temporal Signals and Clinical Indices in Electrocardiographic Imaging (II): Electrogram Clustering and T-wave Alternans.

Authors:  Raúl Caulier-Cisterna; Manuel Blanco-Velasco; Rebeca Goya-Esteban; Sergio Muñoz-Romero; Margarita Sanromán-Junquera; Arcadi García-Alberola; José Luis Rojo-Álvarez
Journal:  Sensors (Basel)       Date:  2020-05-29       Impact factor: 3.576

5.  Solving Inverse Electrocardiographic Mapping Using Machine Learning and Deep Learning Frameworks.

Authors:  Ke-Wei Chen; Laura Bear; Che-Wei Lin
Journal:  Sensors (Basel)       Date:  2022-03-17       Impact factor: 3.576

  5 in total

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