Outcome prediction in metabolic dysfunction‐associated steatotic liver disease using stain‐free digital pathological assessment

Computational quantification reduces observer-related variability in histological assessment of metabolic dysfunction-associated steatotic liver disease (MASLD). We undertook stain-free imaging using the SteatoSITE resource to generate tools directly predictive of clinical outcomes. Unstained liver biopsy sections (n = 452) were imaged using second-harmonic generation/two-photon excitation fluorescence (TPEF) microscopy, and all-cause mortality and hepatic decompensation indices constructed. The mortality index had greater predictive power for all-cause mortality (index >.14 vs. .31 vs. </=.31, HR 5.96, p < .001) than the NASH-CRN (HR 3.65, 95% CI 1.81-7.35, p < .001) or qFibrosis stage (HR 3.59, 95% CI 1.79-7.20, p < .001). These tools directly predict hard endpoints in MASLD, without relying on ordinal fibrosis scores as a surrogate, and demonstrate predictive value at least equivalent to traditional or computational ordinal fibrosis scores.