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ECSTATIC SIGNED

Electrostructural Tomography – Towards Multiparametric Imaging of Cardiac Electrical Disorders

Total Cost €

0

EC-Contrib. €

0

Partnership

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 ECSTATIC project word cloud

Explore the words cloud of the ECSTATIC project. It provides you a very rough idea of what is the project "ECSTATIC" about.

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Project "ECSTATIC" data sheet

The following table provides information about the project.

Coordinator
UNIVERSITE DE BORDEAUX 

Organization address
address: PLACE PEY BERLAND 35
city: BORDEAUX
postcode: 33000
website: www.nouvelle-univ-bordeaux.fr

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country France [FR]
 Total cost 1˙475˙000 €
 EC max contribution 1˙475˙000 € (100%)
 Programme 1. H2020-EU.1.1. (EXCELLENT SCIENCE - European Research Council (ERC))
 Code Call ERC-2016-STG
 Funding Scheme ERC-STG
 Starting year 2017
 Duration (year-month-day) from 2017-02-01   to  2022-01-31

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    UNIVERSITE DE BORDEAUX FR (BORDEAUX) coordinator 1˙186˙250.00
2    INSTITUT NATIONAL DE RECHERCHE ENINFORMATIQUE ET AUTOMATIQUE FR (LE CHESNAY CEDEX) participant 288˙750.00

Map

 Project objective

Cardiac electrical diseases are directly responsible for sudden cardiac death, heart failure and stroke. They result from a complex interplay between myocardial electrical activation and structural heterogeneity. Current diagnostic strategy based on separate electrocardiographic and imaging assessment is unable to grasp both these aspects. Improvements in personalised diagnostics are urgently needed as existing curative or preventive therapies (catheter ablation, multisite pacing, and implantable defibrillators) cannot be offered until patients are correctly recognised. My aim is to achieve a major advance in the way cardiac electrical diseases are characterised and thus diagnosed and treated, through the development of a novel non-invasive modality (Electrostructural Tomography), combining magnetic resonance imaging (MRI) and non-invasive cardiac mapping (NIM) technologies. The approach will consist of: (1) hybridising NIM and MRI technologies to enable the joint acquisition of magnetic resonance images of the heart and torso and of a large array of body surface potentials within a single environment; (2) personalising the inverse problem of electrocardiography based on MRI characteristics within the heart and torso, to enable accurate reconstruction of cardiac electrophysiological maps from body surface potentials within the 3D cardiac tissue; and (3) developing a novel disease characterisation framework based on registered non-invasive imaging and electrophysiological data, and propose novel diagnostic and prognostic markers. This project will dramatically impact the tailored management of cardiac electrical disorders, with applications for diagnosis, risk stratification/patient selection and guidance of pacing and catheter ablation therapies. It will bridge two medical fields (cardiac electrophysiology and imaging), thereby creating a new research area and a novel semiology with the potential to modify the existing classification of cardiac electrical diseases.

 Publications

year authors and title journal last update
List of publications.
2018 Patrick M. Boyle, Joe B. Hakim, Sohail Zahid, William H. Franceschi, Michael J. Murphy, Edward J. Vigmond, Rémi Dubois, Michel Haïssaguerre, Mélèze Hocini, Pierre Jaïs, Natalia A. Trayanova, Hubert Cochet
Comparing Reentrant Drivers Predicted by Image-Based Computational Modeling and Mapped by Electrocardiographic Imaging in Persistent Atrial Fibrillation
published pages: article 414, ISSN: 1664-042X, DOI: 10.3389/fphys.2018.00414
Frontiers in Physiology 9 2019-09-20
2017 Alexia Hennig, Marjorie Salel, Frederic Sacher, Claudia Camaioni, Soumaya Sridi, Arnaud Denis, Michel Montaudon, François Laurent, Pierre Jais, Hubert Cochet
High-resolution three-dimensional late gadolinium-enhanced cardiac magnetic resonance imaging to identify the underlying substrate of ventricular arrhythmia
published pages: , ISSN: 1099-5129, DOI: 10.1093/Europace/eux278
EP Europace 2019-09-20
2018 Sophie Giffard-Roisin, Hervé Delingette, Thomas Jackson, Jessica Webb, Lauren Fovargue, Jack Lee, Christopher Rinaldi, Reza Razavi, Nicholas Ayache, Maxime Sermesant
Transfer Learning from Simulations on a Reference Anatomy for ECGI in Personalised Cardiac Resynchronization Therapy
published pages: 1-1, ISSN: 0018-9294, DOI: 10.1109/TBME.2018.2839713
IEEE Transactions on Biomedical Engineering 2019-09-20

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The information about "ECSTATIC" are provided by the European Opendata Portal: CORDIS opendata.

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