Assessment of atrioventricular valve regurgitation using biomechanical cardiac modeling

R. Chabiniok, P. Moireau, C. Kiesewetter, T. Hussain, Reza Razavi, D. Chapelle

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

In this work we introduce the modeling of atrioventricular valve regurgitation in a spatially reduced order biomechanical heart model. The model can be fast calibrated using non-invasive data of cardiac magnetic resonance imaging and provides an objective measure of contractile properties of the myocardium in the volume overloaded ventricle, for which the real systolic function may be masked by the significant level of the atrioventricular valve regurgitation. After demonstrating such diagnostic capabilities, we show the potential of modeling to address some clinical questions concerning possible therapeutic interventions for specific patients. The fast running of the model allows targeting specific questions of referring clinicians in a clinically acceptable time.

Original languageEnglish (US)
Title of host publicationFunctional Imaging and Modelling of the Heart - 9th International Conference, FIMH 2017, Proceedings
PublisherSpringer Verlag
Pages401-411
Number of pages11
Volume10263 LNCS
ISBN (Print)9783319594477
DOIs
Publication statusPublished - Jan 1 2017
Event9th International Conference on Functional Imaging and Modelling of the Heart, FIMH 2017 - Toronto, Canada
Duration: Jun 11 2017Jun 13 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10263 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other9th International Conference on Functional Imaging and Modelling of the Heart, FIMH 2017
CountryCanada
CityToronto
Period6/11/176/13/17

    Fingerprint

Keywords

  • Atrioventricular regurgitation
  • Cardiac modeling
  • Model-based diagnosis assistance
  • Reduced-order model
  • Therapy planning

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Chabiniok, R., Moireau, P., Kiesewetter, C., Hussain, T., Razavi, R., & Chapelle, D. (2017). Assessment of atrioventricular valve regurgitation using biomechanical cardiac modeling. In Functional Imaging and Modelling of the Heart - 9th International Conference, FIMH 2017, Proceedings (Vol. 10263 LNCS, pp. 401-411). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10263 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-59448-4_38