Model Assessment Through Data Assimilation of Realistic Data in Cardiac Electrophysiology

Antoine Gérard; Annabelle Collin; Gautier Bureau; Philippe Moireau; Yves Coudière

doi:10.1007/978-3-030-21949-9_14

Model Assessment Through Data Assimilation of Realistic Data in Cardiac Electrophysiology

Antoine Gérard
, Annabelle Collin
, Gautier Bureau
, Philippe Moireau
, Yves Coudière

Electrophysiology and Heart Modeling Institute
IMB UMR 5251
INRIA Institut National de Recherche en Informatique et en Automatique
Univ. Bordeaux
Université Paris-Saclay
Department of Mechanics École Polytechnique

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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.

Original language	English
Title of host publication	Functional Imaging and Modeling of the Heart - 10th International Conference, FIMH 2019, Proceedings
Editors	Nejib Zemzemi, Valéry Ozenne, Edward Vigmond, Yves Coudière
Publisher	Springer Verlag
Pages	121-130
Number of pages	10
ISBN (Print)	9783030219482
DOIs	https://doi.org/10.1007/978-3-030-21949-9_14
Publication status	Published - 1 Jan 2019
Externally published	Yes
Event	10th International Conference on Functional Imaging and Modeling of the Heart, FIMH 2019 - Bordeaux, France Duration: 6 Jun 2019 → 8 Jun 2019

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	11504 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	10th International Conference on Functional Imaging and Modeling of the Heart, FIMH 2019
Country/Territory	France
City	Bordeaux
Period	6/06/19 → 8/06/19

Keywords

Cardiac modeling
Data assimilation
Electrophysiology

Access to Document

10.1007/978-3-030-21949-9_14

Cite this

Gérard, A., Collin, A., Bureau, G., Moireau, P., & Coudière, Y. (2019). Model Assessment Through Data Assimilation of Realistic Data in Cardiac Electrophysiology. In N. Zemzemi, V. Ozenne, E. Vigmond, & Y. Coudière (Eds.), Functional Imaging and Modeling of the Heart - 10th International Conference, FIMH 2019, Proceedings (pp. 121-130). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11504 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-030-21949-9_14

Gérard, Antoine ; Collin, Annabelle ; Bureau, Gautier et al. / Model Assessment Through Data Assimilation of Realistic Data in Cardiac Electrophysiology. Functional Imaging and Modeling of the Heart - 10th International Conference, FIMH 2019, Proceedings. editor / Nejib Zemzemi ; Valéry Ozenne ; Edward Vigmond ; Yves Coudière. Springer Verlag, 2019. pp. 121-130 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{b948c2d007b94e2fa10e3e52ba07eacb,

title = "Model Assessment Through Data Assimilation of Realistic Data in Cardiac Electrophysiology",

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.",

keywords = "Cardiac modeling, Data assimilation, Electrophysiology",

author = "Antoine G{\'e}rard and Annabelle Collin and Gautier Bureau and Philippe Moireau and Yves Coudi{\`e}re",

note = "Publisher Copyright: {\textcopyright} 2019, Springer Nature Switzerland AG.; 10th International Conference on Functional Imaging and Modeling of the Heart, FIMH 2019 ; Conference date: 06-06-2019 Through 08-06-2019",

year = "2019",

month = jan,

day = "1",

doi = "10.1007/978-3-030-21949-9\_14",

language = "English",

isbn = "9783030219482",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

pages = "121--130",

editor = "Nejib Zemzemi and Val{\'e}ry Ozenne and Edward Vigmond and Yves Coudi{\`e}re",

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}

Gérard, A, Collin, A, Bureau, G, Moireau, P & Coudière, Y 2019, Model Assessment Through Data Assimilation of Realistic Data in Cardiac Electrophysiology. in N Zemzemi, V Ozenne, E Vigmond & Y Coudière (eds), Functional Imaging and Modeling of the Heart - 10th International Conference, FIMH 2019, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11504 LNCS, Springer Verlag, pp. 121-130, 10th International Conference on Functional Imaging and Modeling of the Heart, FIMH 2019, Bordeaux, France, 6/06/19. https://doi.org/10.1007/978-3-030-21949-9_14

Model Assessment Through Data Assimilation of Realistic Data in Cardiac Electrophysiology. / Gérard, Antoine; Collin, Annabelle; Bureau, Gautier et al.
Functional Imaging and Modeling of the Heart - 10th International Conference, FIMH 2019, Proceedings. ed. / Nejib Zemzemi; Valéry Ozenne; Edward Vigmond; Yves Coudière. Springer Verlag, 2019. p. 121-130 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11504 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Model Assessment Through Data Assimilation of Realistic Data in Cardiac Electrophysiology

AU - Gérard, Antoine

AU - Collin, Annabelle

AU - Bureau, Gautier

AU - Moireau, Philippe

AU - Coudière, Yves

PY - 2019/1/1

Y1 - 2019/1/1

N2 - 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.

AB - 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.

KW - Cardiac modeling

KW - Data assimilation

KW - Electrophysiology

U2 - 10.1007/978-3-030-21949-9_14

DO - 10.1007/978-3-030-21949-9_14

M3 - Conference contribution

AN - SCOPUS:85067195842

SN - 9783030219482

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 121

EP - 130

BT - Functional Imaging and Modeling of the Heart - 10th International Conference, FIMH 2019, Proceedings

A2 - Zemzemi, Nejib

A2 - Ozenne, Valéry

A2 - Vigmond, Edward

A2 - Coudière, Yves

PB - Springer Verlag

T2 - 10th International Conference on Functional Imaging and Modeling of the Heart, FIMH 2019

Y2 - 6 June 2019 through 8 June 2019

ER -

Gérard A, Collin A, Bureau G, Moireau P, Coudière Y. Model Assessment Through Data Assimilation of Realistic Data in Cardiac Electrophysiology. In Zemzemi N, Ozenne V, Vigmond E, Coudière Y, editors, Functional Imaging and Modeling of the Heart - 10th International Conference, FIMH 2019, Proceedings. Springer Verlag. 2019. p. 121-130. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-21949-9_14

Model Assessment Through Data Assimilation of Realistic Data in Cardiac Electrophysiology

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