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Biomechanics and Modeling in Mechanobiology

, Volume 13, Issue 4, pp 897–914 | Cite as

Dimensional reductions of a cardiac model for effective validation and calibration

  • M. Caruel
  • R. Chabiniok
  • P. Moireau
  • Y. Lecarpentier
  • D. Chapelle
Original Paper

Abstract

Complex 3D beating heart models are now available, but their complexity makes calibration and validation very difficult tasks. We thus propose a systematic approach of deriving simplified reduced-dimensional models, in “0D”—typically, to represent a cardiac cavity, or several coupled cavities—and in “1D”—to model elongated structures such as muscle samples or myocytes. We apply this approach with an earlier-proposed 3D cardiac model designed to capture length-dependence effects in contraction, which we here complement by an additional modeling component devised to represent length-dependent relaxation. We then present experimental data produced with rat papillary muscle samples when varying preload and afterload conditions, and we achieve some detailed validations of the 1D model with these data, including for the length-dependence effects that are accurately captured. Finally, when running simulations of the 0D model pre-calibrated with the 1D model parameters, we obtain pressure–volume indicators of the left ventricle in good agreement with some important features of cardiac physiology, including the so-called Frank–Starling mechanism, the End-Systolic Pressure–Volume Relationship, as well as varying elastance properties. This integrated multi-dimensional modeling approach thus sheds new light on the relations between the phenomena observed at different scales and at the local versus organ levels.

Keywords

Cardiac modeling Experimental validation Hierarchical modeling Length-dependence effects Frank–Starling mechanism 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • M. Caruel
    • 1
  • R. Chabiniok
    • 2
  • P. Moireau
    • 1
  • Y. Lecarpentier
    • 3
    • 4
  • D. Chapelle
    • 1
  1. 1.Inria Saclay Ile-de-France, MΞDISIM teamPalaiseauFrance
  2. 2.Division of Imaging Sciences and Biomedical Engineering, St Thomas’ HospitalKing’s College LondonLondonUK
  3. 3.Institut du CoeurHôpital de la Pitié-SalpêtriéreParisFrance
  4. 4.Centre de Recherche CliniqueHôpital de MeauxParisFrance

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