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Traditional histological evaluation for grading liver disease severity is based on subjective and semi-quantitative scores. We examined the relationship between digital pathology analysis and corresponding scoring systems for the assessment of hepatic necroinflammatory activity. A prospective, multicenter study including 156 patients with chronic liver disease (74% nonalcoholic fatty liver disease-NAFLD, 26% chronic hepatitis-CH etiologies) was performed. Inflammation was graded according to the Nonalcoholic Steatohepatitis (NASH) Clinical Research Network system and METAVIR score. Whole-slide digital image analysis based on quantitative (I-score: inflammation ratio) and morphometric (C-score: proportionate area of staining intensities clusters) measurements were independently performed. Our data show that I-scores and C-scores increase with inflammation grades (p < 0.001). High correlation was seen for CH (ρ = 0.85–0.88), but only moderate for NAFLD (ρ = 0.5–0.53). I-score (p = 0.008) and C-score (p = 0.002) were higher for CH than NAFLD. Our MATLAB algorithm performed better than QuPath software for the diagnosis of low-moderate inflammation (p < 0.05). C-score AUC for classifying NASH was 0.75 (95%CI, 0.65–0.84) and for moderate/severe CH was 0.99 (95%CI, 0.97–1.00). Digital pathology measurements increased with fibrosis stages (p < 0.001). In conclusion, quantitative and morphometric metrics of inflammatory burden obtained by digital pathology correlate well with pathologists’ scores, showing a higher accuracy for the evaluation of CH than NAFLD.

Background and Aims: Diagnosis of metabolic dysfunction‐associated steatohepatitis (MASH) requires histology. In this study, a magnetic resonance imaging (MRI) score was developed and validated to identify MASH in patients with metabolic dysfunction‐associated steatotic liver disease (MASLD). Secondarily, a screening strategy for MASH diagnosis was investigated. Methods: This prospective multicentre study included 317 patients with biopsy‐proven MASLD and contemporaneous MRI. The discovery cohort (Spain, Portugal) included 194 patients. NAFLD activity score (NAS) and fibrosis were assessed with the NASH‐CRN histologic system. MASH was defined by the presence of steatosis, lobular inflammation, and ballooning, with NAS ≥4 with or without fibrosis. An MRI‐based composite biomarker of Proton Density Fat Fraction and waist circumference (MR–MASH score) was developed. Findings were afterwards validated in an independent cohort (United States, Spain) with different MRI protocols. Results: In the derivation cohort, 51% (n = 99) had MASH. The MR–MASH score identified MASH with an AUC =.88 (95% CI.83–.93) and strongly correlated with NAS (r =.69). The MRI score lower cut‐off corresponded to 88% sensitivity with 86% NPV, while the upper cut‐off corresponded to 92% specificity with 87% PPV. MR–MASH was validated with an AUC =.86 (95% CI.77–.92), 91% sensitivity (lower cut‐off) and 87% specificity (upper cut‐off). A two‐step screening strategy with sequential MR–MASH examination performed in patients with indeterminate‐high FIB‐4 or transient elastography showed an 83–84% PPV to identify MASH. The AUC of MR–MASH was significantly higher than that of the FAST score (p <.001). Conclusions: The MR–MASH score has clinical utility in the identification and management of patients with MASH at risk of progression. [ABSTRACT FROM AUTHOR]