Why the study?
Including smooth muscle activity in arterial mechanical models increases parameters and may cause overparameterization, making it difficult to identify unique arterial properties.
Fitting a continuum-mechanical model to multiple levels of smooth muscle activity prevents overparameterization and accurately identifies in vivo arterial mechanical properties.
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Potential overparameterization limits clinical translation of smooth muscle-inclusive arterial models; leaves open regularization strategies for robust in vivo identification.
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.
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Gade et al. (2021) studied this question.
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