Modeling Cardiac Growth: An Alternative Approach

Osta, N Van; Donk, Loes van der; Rondanina, Emanuele; Bovendeerd, P.H.M.

doi:10.1007/978-3-030-21949-9_28

Cited by 3 publications

(3 citation statements)

References 11 publications

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“…In a FE model, it would also be possible to evaluate growth in response to spatially distributed changes in stimuli, as induced for example by localized infarctions or electrical conduction disorders. As a drawback, stability of model outcome would not only depend on the growth law, but also on the choice of boundary conditions and possible deterioration of element quality during growth (van Osta et al 2019).…”

Section: Figmentioning

confidence: 99%

Evaluation of stimulus-effect relations in left ventricular growth using a simple multiscale model

Rondanina

Bovendeerd

2019

Biomech Model Mechanobiol

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Cardiac growth is the natural capability of the heart to change size in response to changes in blood flow demand of the growing body. Cardiac diseases can trigger the same process leading to an abnormal type of growth. Prediction of cardiac growth would be clinically valuable, but so far published models on cardiac growth differ with respect to the stimulus-effect relation and constraints used for maximum growth. In this study, we use a zero-dimensional, multiscale model of the left ventricle to evaluate cardiac growth in response to three valve diseases, aortic and mitral regurgitation along with aortic stenosis. We investigate how different combinations of stress-and strain-based stimuli affect growth in terms of cavity volume and wall volume and hemodynamic performance. All of our simulations are able to reach a converged state without any growth constraint, with the most promising results obtained while considering at least one stress-based stimulus. With this study, we demonstrate how a simple model of left ventricular mechanics can be used to have a first evaluation on a designed growth law.

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Section: Figmentioning

confidence: 99%

Evaluation of stimulus-effect relations in left ventricular growth using a simple multiscale model

Rondanina

Bovendeerd

2019

Biomech Model Mechanobiol

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“…In comparison with finite element (FE) models, our model lacks the ability to describe spatially varying growth in response to spatially varying changes in myocardial load, as induced for example by myocardial infarction or conduction disorders. As an advantage, we avoid the numerical problems that may arise in FE models, typically related to distortion of elements during growth or uncertainty on boundary conditions (van Osta et al 2019). Thus we are better able to test the intrinsic stability of a potential growth law.…”

Section: Considerations On the Methodsmentioning

confidence: 99%

Stimulus–effect relations for left ventricular growth obtained with a simple multi-scale model: the influence of hemodynamic feedback

Rondanina

Bovendeerd

2020

Biomech Model Mechanobiol

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Cardiac growth is an important mechanism for the human body to respond to changes in blood flow demand. Being able to predict the development of chronic growth is clinically relevant, but so far models to predict growth have not reached consensus on the stimulus–effect relation. In a previously published study, we modeled cardiac and hemodynamic function through a lumped parameter approach. We evaluated cardiac growth in response to valve disease using various stimulus–effect relations and observed an unphysiological decline pump function. Here we extend that model with a model of hemodynamic feedback that maintains mean arterial pressure and cardiac output through adaptation of peripheral resistance and circulatory unstressed volume. With the combined model, we obtain stable growth and restoration of pump function for most growth laws. We conclude that a mixed combination of stress and strain stimuli to drive cardiac growth is most promising since it (1) reproduces clinical observations on cardiac growth well, (2) requires only a small, clinically realistic adaptation of the properties of the circulatory system and (3) is robust in the sense that results were fairly insensitive to the exact choice of the chosen mechanics loading measure. This finding may be used to guide the choice of growth laws in more complex finite element models of cardiac growth, suitable for predicting the response to spatially varying changes in tissue load. Eventually, the current model may form a basis for a tool to predict patient-specific growth in response to spatially homogeneous changes in tissue load, since it is computationally inexpensive.

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“…Such computational models usually combine a growth law based on a growth evolution model, mostly adopting the approaches by Skalak et al [18] and Rodriguez et al [19], where growth was modeled by adding volume in prescribed directions. While conceptually simple, these models suffer from several disadvantages, such as, e.g., the need of defining a priori the direction in which growth will take place or the limit at which growth will stop [20]. Therefore, microstructurally motivated models in a framework such as constrained mixture theory (see section 2.2) could provide deeper insight into the actual events leading to physiological and pathological G&R. To our knowledge, G&R of the heart has not been modelled this way yet.…”

Section: Introductionmentioning

confidence: 99%

Computational modeling of cardiac growth and remodeling in pressure overloaded hearts—Linking microstructure to organ phenotype

2020

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Cardiac growth and remodeling (G&R) refers to structural changes in myocardial tissue in response to chronic alterations in loading conditions. One such condition is pressure overload where elevated wall stresses stimulate the growth in cardiomyocyte thickness, associated with a phenotype of concentric hypertrophy at the organ scale, and promote fibrosis. The initial hypertrophic response can be considered adaptive and beneficial by favoring myocyte survival, but over time if pressure overload conditions persist, maladaptive mechanisms favoring cell death and fibrosis start to dominate, ultimately mediating the transition towards an overt heart failure phenotype. The underlying mechanisms linking biological factors at the myocyte level to biomechanical factors at the systemic and organ level remain poorly understood. Computational models of G&R show high promise as a unique framework for providing a quantitative link between myocardial stresses and strains at the organ scale to biological regulatory processes at the cellular level which govern the hypertrophic response. However, microstructurally motivated, rigorously validated computational models of G&R are still in their infancy.This article provides an overview of the current state-of-the-art of computational models to study cardiac G&R. The microstructure and mechanosensing/mechanotransduction within cells of the myocardium is discussed and quantitative data from previous experimental and clinical studies is summarized. We conclude with a discussion of major challenges and possible directions of future research that can advance the current state of cardiac G&R computational modeling. Statement of SignificanceThe mechanistic links between organ-scale biomechanics and biological factors at the cellular size scale remain poorly understood as these are largely elusive to investigations using experimental methodology alone. Computational G&R models show high promise to establish quantitative links which allow more mechanistic insight into adaptation mechanisms and may be used as a tool for stratifying the state and predict the progression of disease in the clinic. This review provides a comprehensive overview of research in this domain including a summary of experimental data. Thus, this study may serve as a basis for the further development of more advanced G&R models which are suitable for making clinical predictions on disease progression or for testing hypotheses on pathogenic mechanisms using in-silico models.

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Modeling Cardiac Growth: An Alternative Approach

Cited by 3 publications

References 11 publications

Evaluation of stimulus-effect relations in left ventricular growth using a simple multiscale model

Evaluation of stimulus-effect relations in left ventricular growth using a simple multiscale model

Stimulus–effect relations for left ventricular growth obtained with a simple multi-scale model: the influence of hemodynamic feedback

Computational modeling of cardiac growth and remodeling in pressure overloaded hearts—Linking microstructure to organ phenotype

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