Department of Mechanical and Aerospace Engineering, University of California, Los Angeles CA 90095, USA.
Department of Electrical and Computer Engineering, University of California, Los Angeles CA 90095, USA; Center for Advanced Surgical and Interventional Technology (CASIT), Los Angeles CA 90095, USA.
J Mech Behav Biomed Mater. 2019 Feb;90:591-603. doi: 10.1016/j.jmbbm.2018.11.006. Epub 2018 Nov 6.
Realistic modeling of biologic material is required for optimizing fidelity in computer-aided surgical training and assistance systems. The modeling of liver tissue has remained challenging due to its nonlinear viscoelastic properties and high hysteresis of the stress-strain relation. While prior studies have described the behavior of liver tissue during the loading status (in elongation, compression, or indentation tests) or unloading status (in stress relaxation or creep tests), a hysteresis curve with both loading and unloading processes was incompletely defined. We seek to use a single material model to characterize the mechanical properties of liver tissue in a full indentation cycle ex vivo perfused and then sectioned. Based on measurements taken from ex-vivo perfused porcine livers, we converted force-displacement curves to stress-strain curves and developed a visco-hyperelastic constitutive model to characterize the liver's mechanical behavior at different locations under various rates of indentation (1, 2, 5, 10, and 20 mm/s). The proposed model is a mixed visco-hyperelastic model with up to 6 coefficients. The normalized root mean square standard deviations of fitted curves are less than 5% and 10% in low (<0.05) and high strain (>0.3) conditions respectively.
为了优化计算机辅助手术培训和辅助系统的逼真度,需要对生物材料进行真实建模。由于肝脏组织的非线性黏弹性特性和应力-应变关系的高度滞后性,其建模一直具有挑战性。虽然先前的研究已经描述了肝脏组织在加载状态(在拉伸、压缩或压痕试验中)或卸载状态(在应力松弛或蠕变试验中)下的行为,但加载和卸载过程的滞后曲线并未完全定义。我们试图使用单个材料模型来描述在体外灌注和切片后完整压痕循环中肝脏组织的力学特性。基于从体外灌注的猪肝脏中获得的测量结果,我们将力-位移曲线转换为应力-应变曲线,并开发了一个黏超弹性本构模型来描述肝脏在不同位置下以不同的压入速度(1、2、5、10 和 20mm/s)的机械行为。所提出的模型是一个具有多达 6 个系数的混合黏超弹性模型。在低应变(<0.05)和高应变(>0.3)条件下,拟合曲线的归一化均方根标准偏差分别小于 5%和 10%。