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

Jinyang Wang; Xiaoben Li; Mengyuan Ma; Changqing Wang; Claude B Sirlin; Scott B Reeder; Diego Hernando

doi:10.1016/j.cmpb.2023.107494

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

Comput Methods Programs Biomed. 2023 May:233:107494. doi: 10.1016/j.cmpb.2023.107494. Epub 2023 Mar 17.

Authors

Jinyang Wang¹, Xiaoben Li¹, Mengyuan Ma¹, Changqing Wang², Claude B Sirlin³, Scott B Reeder⁴, Diego Hernando⁵

Affiliations

¹ School of Biomedical Engineering, Anhui Medical University, Hefei, China.
² School of Biomedical Engineering, Anhui Medical University, Hefei, China. Electronic address: wangchangqing@ahmu.edu.cn.
³ Department of Radiology, University of California San Diego, San Diego, CA, USA.
⁴ Department of Radiology, University of Wisconsin, Madison, WI, USA; Department of Medical Physics, University of Wisconsin, Madison, WI, USA; Department of Biomedical Engineering, University of Wisconsin, Madison, WI, USA; Department of Medicine, University of Wisconsin, Madison, WI, USA; Department of Emergency Medicine, University of Wisconsin, Madison, WI, USA.
⁵ Department of Radiology, University of Wisconsin, Madison, WI, USA; Department of Medical Physics, University of Wisconsin, Madison, WI, USA.

Abstract

Background and objective: To 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.

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 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.

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 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.

Keywords: Fat droplet; Hepatic steatosis; Simulation; Spatial distribution; Stereology.

MeSH terms

Adult
Humans
Liver* / diagnostic imaging
Magnetic Resonance Imaging / methods
Monte Carlo Method
Non-alcoholic Fatty Liver Disease* / diagnostic imaging
Non-alcoholic Fatty Liver Disease* / pathology
Severity of Illness Index

Abstract

MeSH terms

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