Strain-dependent shear properties of human adipose tissue in vivo.

Journal of the mechanical behavior of biomedical materials(2023)

引用 1|浏览1
暂无评分
摘要
INTRODUCTION:Human adipose tissue (fat) deforms substantially under normal physiological loading and during impact. Thus, accurate data on strain-dependent stiffness of fat is essential for the creation of accurate biomechanical models. Previous studies on ex vivo samples reported human fat to be nonlinear and viscoelastic. When static compression is combined with magnetic resonance (MR) elastography (an imaging technique used to measure viscoelasticity in vivo), the large deformation properties of tissues can be determined. Here, we use magnetic resonance elastography to quantify fat shear modulus in vivo under increasing compressive strain and compare it to the underlying passive gluteal muscle. METHODS:The right buttocks of ten female participants were incrementally compressed at four levels while MR elastography (50 Hz) and mDixon images were acquired. Maps of tissue shear modulus (G*) were reconstructed from the MR elastography phase images. Tissue strain was estimated from registration of deformed and undeformed mDixon images. Linear mixed models were fit to the natural logarithm of the compressive strain and shear modulus data for each tissue. RESULTS:Shear modulus increased in an exponential relationship with compressive strain in fat: Gfat*=748.5*Cyy-1.18Pa, and to a lesser extent in muscle: Gmuscle*=956.4*Cyy-0.36Pa. The baseline (undeformed) stiffness of fat was significantly lower than that of muscle (mean G*fat = 752 Pa, mean G*muscle = 1000 Pa, paired samples t-test, t = -4.24, p = 0.001). However, fat exhibited a significantly higher degree of strain dependence (characterised by the exponent of the curve, t = -6.47, p = 0.0001). CONCLUSION:Static compression of human adipose tissue results in an increase in apparent viscoelastic shear modulus (stiffness), in an exponentially increasing relationship. The relationships defined here can be used in the development of physiologically realistic computational models for impact, injury and biomechanical modelling.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要