软体生物材料中剪切波传播的有限元分析模型

Jianing Wang, Runze Li, Qifa Zhou, Linxia Gu, Pengfei Dong
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引用次数: 0

摘要

基于剪切波速的弹性学方法已被广泛应用于生物材料的刚度估计。生物材料表面单个凹痕所激发的波传播并不总是理想的横波。感兴趣区域到压痕的距离或不同的弹性学算法都会影响刚度的计算。本文在明胶体外实验的基础上,建立了剪切波在软性生物材料中的传播有限元模型,分析了剪切波在软性生物材料中的传播特性。单次压痕在1kHz下诱导横波传播。为了分析剪切波的传播,提取了三个深度沿路径线的位移。用我们的数据研究了阻尼特性和三种不同的弹性成像算法的影响。结果表明,有限元模拟与体外实验结果吻合较好。当深度从1mm增加到7mm时,刚度增加了10%以上,对于具有较大阻尼行为(粘弹性)的材料,刚度增加更大。对于具有较大阻尼特性的材料,其精确估计与感兴趣区域与压痕之间的距离有关。研究了波前斜率法、相互关联法和有限差分法(FDM)三种算法的可行性。FDM可以根据局部时空数据确定横波速度,但需要高频数据。这项工作为优化弹性成像的性能提供了有价值的信息。
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A Finite Element Model for Analyzing the Shear Wave Propagation in Soft Biomaterials
Abstract The elastography method has been widely used to estimate the stiffness of biomaterials based on the shear wave speed. The wave propagation excited by a single indent on the surface of the biomaterials is not always an ideal shear wave. The distance from the interested region to the indent, or different algorithms for elastography may affect the calculation of stiffness. This paper aims to analyze the shear wave propagation in soft biomaterials with a finite element model that was constructed based on the setup of our previous in-vitro experiments on gelatin. A shear wave propagation was induced by a single indent at 1kHz. The displacements along a path line, at three depths, were extracted for analyzing the shear wave propagation. The influence of the damping behavior and three different elastography algorithms were also investigated with our data. Results have shown that the finite element simulation agreed well with the previous in-vitro experiments. The stiffness increased by more than 10% as the depth increased from 1mm to 7mm, which is larger for materials with larger damping behavior (viscoelasticity). The precise estimation was related to the distance between the interested region and the indent for the material with a larger damping behavior. The feasibility of three algorithms: wavefront slope, cross-correlation algorithm, and finite differencing method (FDM), were investigated. The FDM can determine the shear wave speed based on local spatial and temporal data, while high-frequency data are required. This work provides valuable information for optimizing performance of elastography.
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