Automated Segmentation and Morphological Characterization of Hepatic Steatosis and Correlation with Histopathology

J Clin Exp Hepatol. 2023 May-Jun;13(3):468-478. doi: 10.1016/j.jceh.2022.12.003. Epub 2022 Dec 7.

Abstract

Background/objectives: Prevalence of nonalcoholic fatty liver disease (NAFLD) has increased to 25% of the world population. Hepatic steatosis is a hallmark feature of NAFLD and is assessed histologically using visual and ordinal fat grading criteria (0-3) from the Nonalcoholic Steatohepatitis (NASH) Clinical Research Network (CRN) scoring system. The purpose of this study is to automatically segment and extract morphological characteristics and distributions of fat droplets (FDs) on liver histology images and find associations with severity of steatosis.

Methods: A previously published human cohort of 68 NASH candidates was graded for steatosis by an experienced pathologist using the Fat CRN grading system. The automated segmentation algorithm quantified fat fraction (FF) and fat-affected hepatocyte ratio (FHR), extracted fat morphology by calculating radius and circularity of FDs, and examined FDs distribution and heterogeneity using nearest neighbor distance and regional isotropy.

Results: Regression analysis and Spearman correlation (ρ) yielded high correlations for radius (R2 = 0.86, ρ = 0.72), nearest neighbor distance (R2 = 0.82, ρ = -0.82), regional isotropy (R2 = 0.84, ρ = 0.74), and FHR (R2 = 0.90, ρ = 0.85), and low correlation for circularity (R2 = 0.48, ρ = -0.32) with FF and pathologist grades, respectively. FHR showed a better distinction between pathologist Fat CRN grades compared to conventional FF measurements, making it a potential surrogate measure for Fat CRN scores. Our results showed variation in distribution of morphological features and steatosis heterogeneity within the same patient's biopsy sample as well as between patients of similar FF.

Conclusions: The fat percentage measurements, specific morphological characteristics, and patterns of distribution quantified with the automated segmentation algorithm showed associations with steatosis severity; however, future studies are warranted to evaluate the clinical significance of these steatosis features in progression of NAFLD and NASH.

Keywords: fat fraction; liver; morphometry; segmentation; steatosis.