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A biomechanics-based parametrized cardiac end-diastolic pressure–volume relationship for accurate patient-specific calibration and estimation

Authors :
Chapelle, Dominique
Le Gall, Arthur
Mathematical and Mechanical Modeling with Data Interaction in Simulations for Medicine (M3DISIM)
Laboratoire de mécanique des solides (LMS)
École polytechnique (X)-Mines Paris - PSL (École nationale supérieure des mines de Paris)
Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-École polytechnique (X)-Mines Paris - PSL (École nationale supérieure des mines de Paris)
Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-Inria Saclay - Ile de France
Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)
Service d'ophthalmologie [CHU Lariboisière]
Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Lariboisière-Fernand-Widal [APHP]
Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Université Paris Cité (UPCité)
Source :
Scientific Reports, Scientific Reports, 2023, 13, pp.9. ⟨10.1038/s41598-023-38196-5⟩
Publication Year :
2023
Publisher :
HAL CCSD, 2023.

Abstract

International audience; A simple power law has been proposed in the pioneering work of Klotz et al. (Am J Physiol Heart Circ Physiol 291(1):H403–H412, 2006) to approximate the end-diastolic pressure–volume relationship of the left cardiac ventricle, with limited inter-individual variability provided the volume is adequately normalized. Nevertheless, we use here a biomechanical model to investigate the sources of the remaining data dispersion observed in the normalized space, and we show that variations of the parameters of the biomechanical model realistically account for a substantial part of this dispersion. We therefore propose an alternative law based on the biomechanical model that embeds some intrinsic physical parameters, which directly enables personalization capabilities, and paves the way for related estimation approaches.

Details

Language :
English
ISSN :
20452322
Database :
OpenAIRE
Journal :
Scientific Reports, Scientific Reports, 2023, 13, pp.9. ⟨10.1038/s41598-023-38196-5⟩
Accession number :
edsair.od.......165..ee848a6ff223cfebe468f54b3ff6ae97
Full Text :
https://doi.org/10.1038/s41598-023-38196-5⟩