Department of Management and Engineering, Division of Solid Mechanics, Linköping University, Linköping, Sweden.
Department of Cardiothoracic and Vascular Surgery, Skåne University Hospital, Malmö, Sweden.
Biomech Model Mechanobiol. 2021 Aug;20(4):1547-1559. doi: 10.1007/s10237-021-01462-4. Epub 2021 May 2.
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.
本文将一种现有的动脉体内参数识别方法进行扩展，以考虑平滑肌活动。在该方法中，通过求解最小化问题，将与动脉机械特性相关的参数的连续力学模型拟合到临床数据。在模型中纳入平滑肌活动会增加参数的数量。这可能导致过参数化，意味着有几个参数组合可以同样很好地解决最小化问题，因此无法确定哪一组参数最能代表动脉的机械特性。为了防止过参数化，将模型拟合到在不同平滑肌活动水平下测量的临床数据。本文考虑了人体腹主动脉的三种情况：休息时的基础状态；通过下体负压引起的收缩状态；通过体育锻炼引起的扩张状态。通过同时将模型拟合到这三种动脉情况，确定了一组独特的模型参数，并且模型预测与临床数据吻合良好。
