Predicting the Time Course of Ventricular Dilation and Thickening Using a Rapid Compartmental Model

Abstract

The ability to predict long-term growth and remodeling of the heart in individual patients could have important clinical implications, but the time to customize and run current models makes them impractical for routine clinical use. Therefore, we adapted a published growth relation for use in a compartmental model of the left ventricle (LV). The model was coupled to a circuit model of the circulation to simulate hemodynamic overload in dogs. We automatically tuned control and acute model parameters based on experimentally reported hemodynamic data and fit growth parameters to changes in LV dimensions from two experimental overload studies (one pressure, one volume). The fitted model successfully predicted the reported time course of LV dilation and thickening not only in independent studies of pressure and volume overload but also following myocardial infarction. Implemented in MATLAB on a desktop PC, the model required just 6 min to simulate 3 months of growth.

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

“…Consequently, changes in cavity and wall volume, as induced by growth, result in a change in LV function without a need to change tissue properties. This is an advantage in comparison with an even simpler LV mechanics model, the time-varying elastance model, in which a change in size has to be converted into a change in elastance, as demonstrated in a similar growth study by Witzenburg and Holmes (2018). In addition, the one-fiber model offers the possibility to use tissue level load, i.e., fiber stress and strain, as an input for growth.…”

“…Consequently, comparison between model results and the literature data can only be done qualitatively. In a similar study, Witzenburg and Holmes (2018) show how a better match between clinical and numerical data can be obtained by considering a customization of the hemodynamic parameters for each case. They not only tuned the valve pathology, but also adapted the systemic resistance and the stressed blood volume.…”

“…Tuning our model to the individual patient as well would allow for a more strict test of the model. In particular, it would be interesting to see whether we could still use one homeostatic set point, derived from a generic healthy state, or whether the homeostatic set point should be set differently for different types of disease, as done by Witzenburg and Holmes (2018).…”

Multiscale model of heart growth during pregnancy: Integrating mechanical and hormonal signaling

“…We conclude that additional experimental data -including simultaneous measurements of LV mass, EDD or EDV, and end-diastolic pressure (EDP) -would be needed in order to determine which of these two variants of our model is most consistent with experiments. In particular, while SBV is extremely difficult to measure directly, we have found in prior work that fitting EDP allows good estimation of SBV changes during multiple different types of overload [40]. One advantage of the modeling framework presented here is the ability to validate our predictions across multiple length scales, from intracellular signaling to organ-level growth.…”

“…AngII, AngII+E2 data are from [44][45][46]. More details are available in Supplemental Table 2. 2.2 Compartmental model of organ-level growth Our group previously published a rapid, compartmental growth model of the heart coupled to a lumped-parameter circuit model based on a canine anatomy, and demonstrated its ability to predict heart growth in multiple settings where changes in mechanical loading of the heart occur, including volume overload (VO), pressure overload (PO), and myocardial infarction [40,47]. Briefly, this model uses a time-varying elastance model to simulate the ventricles.…”