Author(s) :

Cinty Lin.

Volume/Issue :

Abstract :

Nonalcoholic fatty liver disease (NAFLD; recently redefined as metabolic dysfunction-associated steatotic liver disease, MASLD) is one of the most common chronic liver diseases worldwide and is strongly associated with obesity, type 2 diabetes, metabolic syndrome, and insulin resistance. NAFLD is defined by the accumulation of fat in more than five percent of hepatocytes without excess alcohol use. Current staging systems categorize liver histology into discrete groups based on visual assessment, but subtle differences in fat droplet morphology are difficult for pathologists to detect. Precise histological staging is important for understanding disease severity. This study applies the Linearized Compressed Polar Coordinates (LCPC) Transform, a spatial algorithm, to quantify the pure shape of macrovesicular steatosis in NAFLD liver histology with the goal of identifying objective morphological subtypes of fat droplets. Shape analysis followed by Principal Component Analysis (PCA) and density-based clustering revealed at least three droplet groups that may represent previously uncharacterized morphological subtypes. These findings suggest that quantitative shape analysis could provide additional information that supports future efforts to refine NAFLD staging and improve diagnostic precision.