Towards linking histological changes to liver viscoelasticity: a hybrid analytical-computational micromechanics approach.

IF 3.3 3区 医学 Q2 ENGINEERING, BIOMEDICAL
Haritya Shah, Murthy N Guddati
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引用次数: 0

Abstract

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.

将组织学变化与肝脏粘弹性联系起来:一种混合分析-计算微观力学方法。
弹性成像利用组织力学特性作为肝脏疾病的生物标志物,最终目标是定量联系组织病理学和整体力学特性,我们开发了一种微力学建模方法来捕捉肝脏中脂肪和胶原沉积的影响。具体而言,我们利用计算均质化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细胞的变形来预测整体材料的特性。脂质和胶原沉积是模拟的帮助下,特设算法通知的组织学观察。胶原沉积直接包含在计算模型中,而复合材料理论将脂肪含量转化为微观力学性能,再将其包含在计算模型中。结果表明,该模型能够捕捉脂肪和胶原沉积对粘弹性模量的影响,并代表了将肝脏组织病理变化与其整体力学特性联系起来的一步,这最终可以为弹性成像的准确诊断提供见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Physics in medicine and biology
Physics in medicine and biology 医学-工程:生物医学
CiteScore
6.50
自引率
14.30%
发文量
409
审稿时长
2 months
期刊介绍: The development and application of theoretical, computational and experimental physics to medicine, physiology and biology. Topics covered are: therapy physics (including ionizing and non-ionizing radiation); biomedical imaging (e.g. x-ray, magnetic resonance, ultrasound, optical and nuclear imaging); image-guided interventions; image reconstruction and analysis (including kinetic modelling); artificial intelligence in biomedical physics and analysis; nanoparticles in imaging and therapy; radiobiology; radiation protection and patient dose monitoring; radiation dosimetry
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