Monte Carlo modeling of hepatic steatosis based on stereology and spatial distribution of fat droplets

Background and Objective: To model hepatic steatosis in adult humans with non-alcoholic fatty liver dis-ease based on stereology and spatial distribution of fat droplets from liver biopsy specimens. Methods: Histological 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 distri-bution indicating heterogeneous accumulation (i.e., clustering) of fat droplets; 3) regional anisotropy indi-cating 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.Results: Morphological 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, with R2 > 0.55. In addition, simulated 3D liver morphological models demonstrated similar sections to real histological samples both visually and quantitatively. Conclusions: The morphology of hepatic steatosis is well characterized by stereology and spatial distri-bution 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.(c) 2023 Elsevier B.V. All rights reserved.

Automated summary

This study aimed to model hepatic steatosis in adult humans with non-alcoholic fatty liver disease based on the stereology and spatial distribution of fat droplets. Histological analysis of liver biopsy specimens was performed, and the morphological features of fat droplets were characterized using the gamma distribution function in 2D and 3D spaces. Correlation analysis showed a strong relationship between the morphological features and fat fraction. Monte Carlo modeling was used to simulate the distribution of fat droplets in tissue. This study provides insights into the MRI signal behavior in the presence of liver steatosis.