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Biomechanics and Modeling in Mechanobiology

, Volume 14, Issue 2, pp 217–229 | Cite as

A computational model that predicts reverse growth in response to mechanical unloading

  • L. C. Lee
  • M. Genet
  • G. Acevedo-Bolton
  • K. Ordovas
  • J. M. Guccione
  • E. Kuhl
Original Paper

Abstract

Ventricular growth is widely considered to be an important feature in the adverse progression of heart diseases, whereas reverse ventricular growth (or reverse remodeling) is often considered to be a favorable response to clinical intervention. In recent years, a number of theoretical models have been proposed to model the process of ventricular growth while little has been done to model its reverse. Based on the framework of volumetric strain-driven finite growth with a homeostatic equilibrium range for the elastic myofiber stretch, we propose here a reversible growth model capable of describing both ventricular growth and its reversal. We used this model to construct a semi-analytical solution based on an idealized cylindrical tube model, as well as numerical solutions based on a truncated ellipsoidal model and a human left ventricular model that was reconstructed from magnetic resonance images. We show that our model is able to predict key features in the end-diastolic pressure–volume relationship that were observed experimentally and clinically during ventricular growth and reverse growth. We also show that the residual stress fields generated as a result of differential growth in the cylindrical tube model are similar to those in other nonidentical models utilizing the same geometry.

Keywords

Remodeling Reverse remodeling Growth End-diastolic pressure–volume relationship Finite element method Magnetic resonance imaging 

Notes

Acknowledgments

This work was supported by NIH Grants R01-HL-077921 and R01-HL-118627 (J.M. Guccione); K25-NS058573-05 (G. Acevedo-Bolton); NSF Grants 0952021 and 1233054 (E. Kuhl); and Marie Curie international outgoing fellowship within the 7th European Community Framework Program (M. Genet). We thank the reviewers for their valuable comments, which have helped us improve the presentation.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • L. C. Lee
    • 1
  • M. Genet
    • 1
  • G. Acevedo-Bolton
    • 2
  • K. Ordovas
    • 2
  • J. M. Guccione
    • 1
  • E. Kuhl
    • 3
  1. 1.Department of Surgery, School of MedicineUniversity of California at San FranciscoSan FranciscoUSA
  2. 2.Department of Radiology and Biomedical Imaging, School of MedicineUniversity of California at San FranciscoSan FranciscoUSA
  3. 3.Departments of Mechanical Engineering, Bioengineering, and Cardiothoracic SurgeryStanford UniversityStanfordUSA

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