A Comparison of Phenomenologic Growth Laws for Myocardial Hypertrophy

Colleen M Witzenburg1, Jeffrey W Holmes1,2,3

  • 1Department of Biomedical Engineering, University of Virginia, Charlottesville, VA, USA.

Journal of Elasticity
|April 11, 2018
PubMed

Insights

Predictive cardiac growth models are crucial for understanding heart diseases. Three of eight tested "growth laws" accurately simulated heart growth under pressure and volume overload conditions.

Area of Science:

  • Cardiovascular Physiology
  • Biomedical Engineering
  • Computational Biology

Background:

  • Cardiac growth is a complex response to hemodynamic loading, crucial for development and disease states like valve disease and hypertension.
  • Left ventricular pressure overload typically causes concentric growth (wall thickening), while volume overload leads to eccentric growth (cavity dilation).
  • Predictive models of cardiac growth are vital for treatment evaluation, clinical decision-making, and developing new therapies.

Purpose of the Study:

  • To compare and evaluate eight published cardiac growth laws.
  • To assess the ability of these laws to predict experimentally observed myocardial growth patterns under simulated pressure and volume overload conditions.

Main Methods:

  • Eight different cardiac growth laws were analyzed.
  • A comparative test-bed was used, applying stretches measured during in vivo pressure and volume overload.
  • Growth predictions were compared against experimentally measured myocardial fiber and radial growth, and their ratio.

Main Results:

  • Three of the eight growth laws successfully reproduced key aspects of cardiac growth observed in both pressure and volume overload scenarios.
  • These successful models, despite using different approaches, incorporated multiple, weakly correlated inputs providing independent mechanical information.

Conclusions:

  • Certain cardiac growth laws demonstrate significant predictive power for simulating heart growth in response to distinct hemodynamic loads.
  • The efficacy of these models highlights the importance of integrating diverse, independent mechanical inputs for accurate hypertrophy prediction.

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