Monte Carlo modeling of hepatic steatosis based on stereology and spatial distribution of fat droplets.
Monte Carlo modeling of hepatic steatosis based on stereology and spatial distribution of fat droplets.
复制标题
基于体视学和脂肪滴空间分布的肝脂肪变性蒙特卡罗建模。
DOI：
10.1016/j.cmpb.2023.107494
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发表时间：
2023
影响因子：
6.1
通讯作者：
Hernando,Diego
中科院分区：
文献类型：
--
作者：
Wang,Jinyang;Li,Xiaoben;Ma,Mengyuan;Wang,Changqing;Sirlin,ClaudeB;Reeder,ScottB;Hernando,Diego
背景和目的模型肝脂肪变性在成人非酒精性脂肪性肝病的基础上体视学和空间分布的脂肪滴从liver biopsy samples.MethodsHistological分析进行了30成人肝活检标本不同程度的脂肪变性。脂肪滴的形态特征在二维（2D）和三维（3D）空间中由伽马分布函数（GDF）从三个方面表征：1）指示脂肪滴在半径上的不均匀性的尺寸分布; 2）指示不均匀积累的最近邻距离分布（即，聚类）; 3）区域各向异性，指示脂肪分数（FF）的区域间变异性。为了将肝脂肪变性的形态学描述推广到不同的FF，对所有标本的估计GDF参数和FF之间进行相关性分析。最后，Monte Carlo模拟肝脏脂肪变性的脂肪滴在tissue.ResultsMorphological功能，包括大小和最近邻距离在2D和3D空间以及区域各向异性，统计捕获的分布脂肪滴的GDF拟合（R2> 0.54）。估计的GDF参数（即，尺度和形状参数）与FFS呈良好的相关性，R2> 0.55。此外，模拟的三维肝脏形态模型表现出类似的部分真实的组织学样品在视觉上和quantitatively.ConclusionsThe肝脂肪变性的形态学特征在于体视学和空间分布的脂肪滴。模拟模型表现出与真实的组织学样本相似的外观。此外，该模型可以帮助理解在肝脏脂肪变性存在下的MRI信号行为。
Background and ObjectiveTo model hepatic steatosis in adult humans with non-alcoholic fatty liver disease based on stereology and spatial distribution of fat droplets from liver biopsy specimens.MethodsHistological analysis was performed on 30 adult human liver biopsy specimens with varying degrees of steatosis. Morphological features of fat droplets were characterized by gamma distribution function (GDF) in both two-dimensional (2D) and three-dimensional (3D) spaces from three aspects: 1) size distribution indicating non-uniformity of fat droplets in radius; 2) nearest neighbor distance distribution indicating heterogeneous accumulation (i.e., clustering) of fat droplets; 3) regional anisotropy indicating inter-regional variability in fat fraction (FF). To generalize the morphological description of hepatic steatosis to different FFs, correlation analysis was performed among the estimated GDF parameters and FFs for all specimens. Finally, Monte Carlo modeling of hepatic steatosis was developed to simulate fat droplet distribution in tissue.ResultsMorphological features, including size and nearest neighbor distance in 2D and 3D spaces as well as regional anisotropy, statistically captured the distribution of fat droplets by the GDF fit (R2> 0.54). The estimated GDF parameters (i.e., scale and shape parameters) and FFs were well correlated, withR2> 0.55. In addition, simulated 3D liver morphological models demonstrated similar sections to real histological samples both visually and quantitatively.ConclusionsThe morphology of hepatic steatosis is well characterized by stereology and spatial distribution of fat droplets. Simulated models demonstrate similar appearances to real histological samples. Furthermore, the model may help understand MRI signal behavior in the presence of liver steatosis.