ArticleFrontiers in physiology2021
Characterization of Exercise-Induced Myocardium Growth Using Finite Element Modeling and Bayesian Optimization.
Article in Frontiers in physiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Developing cardiac biomechanical models beyond the clinic: modeling stressors of daily life.Biomechanics and modeling in mechanobiology · 2025Review
- A homogenized constrained mixture model of cardiac growth and remodeling: analyzing mechanobiological stability and reversal.Biomechanics and modeling in mechanobiology · 2023Article
- Bayesian optimisation for efficient parameter inference in a cardiac mechanics model of the left ventricle.International journal for numerical methods in biomedical engineering · 2022Article
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8 authors.
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Abstract
Cardiomyocyte growth can occur in both physiological (exercised-induced) and pathological (e.g., volume overload and pressure overload) conditions leading to left ventricular (LV) hypertrophy. Studies using animal models and histology have demonstrated the growth and remodeling process at the organ level and tissue-cellular level, respectively. However, the driving factors of growth and the mechanistic link between organ, tissue, and cellular growth remains poorly understood. Computational models have the potential to bridge this gap by using constitutive models that describe the growth and remodeling process of the myocardium coupled with finite element (FE) analysis to model the biomechanics of the heart at the organ level. Using subject-specific imaging data of the LV geometry at two different time points, an FE model can be created with the inverse method to characterize the growth parameters of each subject. In this study, we developed a framework that takes
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