Hollander Yaniv, Durban David, Lu Xiao, Kassab Ghassan S, Lanir Yoram
Faculty of Aerospace Engineering, Technion-Israel Institute of Technology, Haifa 3200, Israel.
J Biomech Eng. 2011 Jun;133(6):061008. doi: 10.1115/1.4004249.
Accurate modeling of arterial elasticity is imperative for predicting pulsatile blood flow and transport to the periphery, and for evaluating the mechanical microenvironment of the vessel wall. The goal of the present study is to compare a recently developed structural model of porcine left anterior descending artery media to two commonly used typical representatives of phenomenological and structure-motivated invariant-based models, in terms of the number of model parameters, model descriptive and predictive powers, and requisite different test protocols for reliable parameter estimation. The three models were compared against 3D data of radial inflation, axial extension, and twist tests. Also checked are the models predictive capabilities to response data not used for estimation, including both tests outside the range of estimation database, as well as protocols of a different nature. The results show that the descriptive estimation error (model fit to estimation database), measured by the sum of squared residuals (SSE) between full 3D data and model predictions, was about twice as low for the structural (4.58%) model compared to the other two (9.71 and 8.99% for the phenomenological and structure-motivated models, respectively). Similar SSE ratios were obtained for the predictive capabilities. Prediction SSE at high stretch based on estimation of two low stretches yielded an SSE value of 2.81% for the structural model, and 10.54% and 7.87% for the phenomenological and structure-motivated models, respectively. For the prediction of twist from inflation-extension data, SSE values for the torsional stiffness was 1.76% for the structural model and 39.62 and 2.77% for the phenomenological and structure-motivated models. The required number of model parameters for the structural model is four, whereas the phenomenological model requires six to nine and the structure-motivated has four parameters. These results suggest that modeling based on the tissue structural features improves model reliability in describing given data and in predicting the tissue general response.
准确模拟动脉弹性对于预测脉动血流及其向周围组织的输送，以及评估血管壁的力学微环境至关重要。本研究的目的是将最近开发的猪左前降支动脉中膜结构模型与两种常用的基于唯象学和基于结构不变量的典型模型进行比较，比较内容包括模型参数数量、模型描述和预测能力，以及可靠参数估计所需的不同测试方案。将这三种模型与径向膨胀、轴向拉伸和扭转试验的三维数据进行比较。还检查了模型对未用于估计的响应数据的预测能力，包括估计数据库范围之外的试验以及不同性质的试验方案。结果表明，通过全三维数据与模型预测之间的残差平方和（SSE）测量的描述性估计误差（模型与估计数据库的拟合度），结构模型（4.58%）约为其他两种模型（唯象学模型和基于结构的模型分别为9.71%和8.99%）的一半。预测能力也获得了类似的SSE比率。基于两个低拉伸量估计的高拉伸量下的预测SSE，结构模型的值为2.81%，唯象学模型和基于结构的模型分别为10.54%和7.87%。对于根据膨胀-拉伸数据预测扭转，结构模型的扭转刚度SSE值为1.76%，唯象学模型和基于结构的模型分别为39.62%和2.77%。结构模型所需的模型参数数量为四个，而唯象学模型需要六到九个，基于结构的模型有四个参数。这些结果表明，基于组织结构特征的建模提高了模型在描述给定数据和预测组织一般响应方面的可靠性。
