Multiscale simulations of left ventricular growth and remodeling

Hossein Sharifi, Charles K. Mann, Alexus L. Rockward, Mohammad Mehri, Joy Mojumder, Lik Chuan Lee, Kenneth S. Campbell, Jonathan F. Wenk

Research output: Contribution to journalReview articlepeer-review

5 Scopus citations

Abstract

Cardiomyocytes can adapt their size, shape, and orientation in response to altered biomechanical or biochemical stimuli. The process by which the heart undergoes structural changes—affecting both geometry and material properties—in response to altered ventricular loading, altered hormonal levels, or mutant sarcomeric proteins is broadly known as cardiac growth and remodeling (G&R). Although it is likely that cardiac G&R initially occurs as an adaptive response of the heart to the underlying stimuli, prolonged pathological changes can lead to increased risk of atrial fibrillation, heart failure, and sudden death. During the past few decades, computational models have been extensively used to investigate the mechanisms of cardiac G&R, as a complement to experimental measurements. These models have provided an opportunity to quantitatively study the relationships between the underlying stimuli (primarily mechanical) and the adverse outcomes of cardiac G&R, i.e., alterations in ventricular size and function. State-of-the-art computational models have shown promise in predicting the progression of cardiac G&R. However, there are still limitations that need to be addressed in future works to advance the field. In this review, we first outline the current state of computational models of cardiac growth and myofiber remodeling. Then, we discuss the potential limitations of current models of cardiac G&R that need to be addressed before they can be utilized in clinical care. Finally, we briefly discuss the next feasible steps and future directions that could advance the field of cardiac G&R.

Original languageEnglish
Pages (from-to)729-746
Number of pages18
JournalBiophysical Reviews
Volume13
Issue number5
DOIs
StatePublished - Oct 2021

Bibliographical note

Funding Information:
This study was supported by the National Institutes of Health grant U01HL133359.

Publisher Copyright:
© 2021, International Union for Pure and Applied Biophysics (IUPAB) and Springer-Verlag GmbH Germany, part of Springer Nature.

Keywords

  • Cardiac growth
  • Cardiomyopathy
  • Machine learning
  • Multiscale modeling
  • Myofiber remodeling
  • Sarcomeres

ASJC Scopus subject areas

  • Biophysics
  • Structural Biology
  • Molecular Biology

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