Shah Haritya, Guddati Murthy N
North Carolina State University, Raleigh, NC 27695-7908, United States of America.
Phys Med Biol. 2025 Feb 4;70(4). doi: 10.1088/1361-6560/adaad3.
Motivated by elastography that utilizes tissue mechanical properties as biomarkers for liver disease, with the eventual objective of quantitatively linking histopathology and bulk mechanical properties, we develop a micromechanical modeling approach to capture the effects of fat and collagen deposition in the liver. Specifically, we utilize computational homogenization to convert the microstructural changes in hepatic lobule to the effective viscoelastic modulus of the liver tissue, i.e. predict the bulk material properties by analyzing the deformation of repeating unit cell. The lipid and collagen deposition is simulated with the help of ad hoc algorithms informed by histological observations. Collagen deposition is directly included in the computational model, while composite material theory is used to convert fat content to the microscopic mechanical properties, which in turn is included in the computational model. The results illustrate the model's ability to capture the effect of both fat and collagen deposition on the viscoelastic moduli and represents a step towards linking histopathological changes in the liver to its bulk mechanical properties, which can eventually provide insights for accurate diagnosis with elastography.
受弹性成像技术的启发，该技术利用组织力学特性作为肝病的生物标志物，最终目标是将组织病理学与整体力学特性进行定量关联，我们开发了一种微观力学建模方法来捕捉肝脏中脂肪和胶原蛋白沉积的影响。具体而言，我们利用计算均匀化方法将肝小叶的微观结构变化转化为肝组织的有效粘弹性模量，即通过分析重复单元胞的变形来预测整体材料特性。借助基于组织学观察的特殊算法模拟脂质和胶原蛋白沉积。胶原蛋白沉积直接包含在计算模型中，而复合材料理论用于将脂肪含量转化为微观力学特性，进而包含在计算模型中。结果表明该模型能够捕捉脂肪和胶原蛋白沉积对粘弹性模量的影响，代表了朝着将肝脏组织病理学变化与其整体力学特性相联系迈出的一步，最终可为弹性成像的准确诊断提供见解。
