Predictions of hypertrophy and its regression in response to pressure overload

Kyoko Yoshida, Andrew D. McCulloch, Jeffrey H. Omens, Jeffrey W. Holmes

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

Mechanics-based cardiac growth models can now predict changes in mass, chamber size, and wall thickness in response to perturbations such as pressure overload (PO), volume overload, and myocardial infarction with a single set of growth parameters. As these models move toward clinical applications, many of the most interesting applications involve predictions of whether or how a patient’s heart will reverse its growth after an intervention. In the case of PO, significant regression in wall thickness is observed both experimentally and clinically following relief of overload, for example following replacement of a stenotic aortic valve. Therefore, the objective of this work was to evaluate the ability of a published cardiac growth model that captures forward growth in multiple situations to predict growth reversal following relief of PO. Using a finite element model of a beating canine heart coupled to a circuit model of the circulation, we quantitatively matched hemodynamic data from a canine study of aortic banding followed by unbanding. Surprisingly, although the growth model correctly predicted the time course of PO-induced hypertrophy, it predicted only limited growth reversal given the measured unbanding hemodynamics, contradicting experimental and clinical observations. We were able to resolve this discrepancy only by incorporating an evolving homeostatic setpoint for the governing growth equations. Furthermore, our analysis suggests that many strain- and stress-based growth laws using the traditional volumetric growth framework will have similar difficulties capturing regression following the relief of PO unless growth setpoints are allowed to evolve.

Original languageEnglish (US)
Pages (from-to)1079-1089
Number of pages11
JournalBiomechanics and Modeling in Mechanobiology
Volume19
Issue number3
DOIs
StatePublished - Jun 1 2020
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2019, Springer-Verlag GmbH Germany, part of Springer Nature.

Keywords

  • Finite element model
  • Growth
  • Hypertrophy
  • Pressure overload
  • Reverse growth

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