Skip to Main content Skip to Navigation
Conference papers

Model assessment through data assimilation of realistic data in cardiac electrophysiology

Antoine Gérard 1 Annabelle Collin 2 Gautier Bureau 3 Philippe Moireau 4 Yves Coudière 5
2 MONC - Modélisation Mathématique pour l'Oncologie
IMB - Institut de Mathématiques de Bordeaux, Institut Bergonié [Bordeaux], Inria Bordeaux - Sud-Ouest
4 M3DISIM - Mathematical and Mechanical Modeling with Data Interaction in Simulations for Medicine
LMS - Laboratoire de mécanique des solides, Inria Saclay - Ile de France
5 CARMEN - Modélisation et calculs pour l'électrophysiologie cardiaque
IMB - Institut de Mathématiques de Bordeaux, Inria Bordeaux - Sud-Ouest, IHU-LIRYC
Abstract : We consider a model-based estimation procedure-namely a data assimilation algorithm-of the atrial depolarization state of a subject using data corresponding to electro-anatomical maps. Our objective is to evaluate the sensitivity of such a model-based reconstruction with respect to model choices. The followed data assimilation approach is capable of using electrical activation times to adapt a monodomain model simulation, thanks to an ingenious model-data fitting term inspired from image processing. The resulting simulation smoothes and completes the activation maps when they are spatially incomplete. Moreover, conductivity parameters can also be inferred. The model sensitivity assessment is performed based on synthetic data generated with a validated realistic atria model and then inverted using simpler modeling ingredients. In particular, the impact of the muscle fibers definition and corresponding anisotropic conductivity parameters is studied. Finally, an application of the method to real data is presented, showing promising results.
Complete list of metadata

Cited literature [13 references]  Display  Hide  Download

https://hal.inria.fr/hal-02172102
Contributor : Antoine Gérard <>
Submitted on : Wednesday, July 3, 2019 - 2:34:38 PM
Last modification on : Thursday, September 24, 2020 - 4:00:37 PM

File

sequentialDA_FIMH2019.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : hal-02172102, version 1

Citation

Antoine Gérard, Annabelle Collin, Gautier Bureau, Philippe Moireau, Yves Coudière. Model assessment through data assimilation of realistic data in cardiac electrophysiology. FIMH 2019 - 10th Functional Imaging and Modeling of the Heart, Jun 2019, Bordeaux, France. ⟨hal-02172102⟩

Share

Metrics

Record views

267

Files downloads

977