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

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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.

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Notes

  1. In this paper, we used the words “growth” and “remodeling” interchangeably although other authors have used “growth” and “remodeling” to specifically describe a change in mass and properties, respectively.

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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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Authors and Affiliations

  1. Department of Surgery, School of Medicine, University of California at San Francisco, San Francisco, CA, 94143, USA

    L. C. Lee, M. Genet & J. M. Guccione

  2. Department of Radiology and Biomedical Imaging, School of Medicine, University of California at San Francisco, San Francisco, CA, 94143, USA

    G. Acevedo-Bolton & K. Ordovas

  3. Departments of Mechanical Engineering, Bioengineering, and Cardiothoracic Surgery, Stanford University, Stanford, CA, 94305-4040, USA

    E. Kuhl

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  1. L. C. Lee
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  2. M. Genet
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  3. G. Acevedo-Bolton
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  4. K. Ordovas
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  5. J. M. Guccione
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  6. E. Kuhl
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Correspondence to L. C. Lee.

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Lee, L.C., Genet, M., Acevedo-Bolton, G. et al. A computational model that predicts reverse growth in response to mechanical unloading. Biomech Model Mechanobiol 14, 217–229 (2015). https://doi.org/10.1007/s10237-014-0598-0

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  • DOI: https://doi.org/10.1007/s10237-014-0598-0

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