Histopathological Scoring Systems for Experimental Liver Injury Models

Histopathological evaluation is a fundamental component of experimental liver injury studies because it allows direct assessment of structural alterations occurring at the tissue level. However, purely descriptive microscopic examination may be limited by observer-dependent interpretation and reduced comparability between experimental groups. For this reason, semi-quantitative scoring systems are widely used to convert morphological findings into numerical data and to improve the objectivity, reproducibility, and interpretability of histological assessment. In experimental liver injury models, commonly evaluated parameters include hepatocellular necrosis, inflammatory cell infiltration, hepatocyte degeneration or vacuolization, sinusoidal congestion or dilatation, steatosis, cholestasis, bile duct proliferation, fibrosis, and collagen deposition. The selection of scoring parameters should be guided by the type of experimental model, the expected pattern of injury, and the main objective of the study. In addition to conventional scoring, morphometric and digital image analysis methods may support histopathological evaluation by providing more objective measurements of specific tissue changes, particularly fibrosis, collagen accumulation, necrotic areas, steatosis, and immunohistochemical staining. Standardization of magnification, field selection, number of evaluated areas, staining conditions, scoring criteria, and blinded assessment is essential for obtaining reliable and comparable results. This review summarizes the main histopathological scoring approaches used in experimental liver injury models and emphasizes the importance of selecting appropriate, standardized, and reproducible scoring methods according to the specific characteristics of each model. Although this review focused on experimental liver damage models, standardized histopathological scoring can also support the interpretation of liver pathology in broader research contexts.