Related Experiment Video
Updated: Feb 13, 2026

Author Spotlight: Establishment and Confirmation of a Postnatal Right Ventricular Volume Overload Mouse Model
Published on: June 9, 2023
Predicting the Time Course of Ventricular Dilation and Thickening Using a Rapid Compartmental Model
Colleen M Witzenburg1, Jeffrey W Holmes2
1Biomedical Engineering, University of Virginia, Charlottesville, VA, USA.
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.
Related Concept Videos
Eukaryotic Compartmentalization
For example, lysosomes in the animal...
Eukaryotic Compartmentalizations
For example, lysosomes in the animal cells...
Cardiomyopathy II: Dilated Cardiomyopathy
Predicting Molecular Geometry
Prediction Intervals
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.
Sensitivity, Specificity, and Predicted Value
Sensitivity is the...

