Abstract
In this paper an existing in vivo parameter identification method for arteries is extended to account for smooth muscle activity. Within this method a continuum-mechanical model, whose parameters relate to the mechanical properties of the artery, is fit to clinical data by solving a minimization problem. Including smooth muscle activity in the model increases the number of parameters. This may lead to overparameterization, implying that several parameter combinations solve the minimization problem equally well and it is therefore not possible to determine which set of parameters represents the mechanical properties of the artery best. To prevent overparameterization the model is fit to clinical data measured at different levels of smooth muscle activity. Three conditions are considered for the human abdominal aorta: basal during rest; constricted, induced by lower-body negative pressure; and dilated, induced by physical exercise. By fitting the model to these three arterial conditions simultaneously a unique set of model parameters is identified and the model prediction agrees well with the clinical data.
Highlights
Cardiovascular diseases are the leading cause of death in the western world (Mozaffarian et al 2016; Wilkins et al 2017)
An exception is the method proposed in Masson et al (2008). Their model requires 14 parameters to be identified, making it very questionable whether a unique solution has been obtained (Spronck et al 2015). It was hypothesized in Reesink and Spronck (2019) that smooth muscle activity can be included without causing overparameterization if the arterial model is fit to multiple in vivo data sets collected at different levels of vascular tone
The artery is exposed to the blood pressure P and an axial force, where the latter cannot be measured in vivo
Summary
Cardiovascular diseases are the leading cause of death in the western world (Mozaffarian et al 2016; Wilkins et al 2017). Introducing too many model parameters leads to overparameterization, meaning that a (nonlinear) parameter combination can be continuously changed without affecting the objective function value This makes it impossible to determine which set of parameters represents the mechanical properties of the artery. Their model requires 14 parameters to be identified, making it very questionable whether a unique solution has been obtained (Spronck et al 2015) It was hypothesized in Reesink and Spronck (2019) that smooth muscle activity can be included without causing overparameterization if the arterial model is fit to multiple in vivo data sets collected at different levels of vascular tone. The paper is concluded with a discussion and a final conclusion
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