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Updated: Jul 2, 2026
Mapping Hepatic Stellate Cell Morphology in Mouse Models of Liver Fibrosis
Published on: February 13, 2026
A non-invasive algorithm accurately predicts advanced fibrosis in hepatitis C: a comparison using histology with
Silvia Paggi1, Agostino Colli, Mirella Fraquelli
1Second Division of Gastroenterology, Fondazione IRCCS Policlinico, Mangiagalli e Regina Elena, University of Milan, Milan, Italy.
Background/Aims:
Biochemical tests and ultrasonography (US) are useful in the non-invasive assessment of liver fibrosis in patients with chronic hepatitis C (CH-C); however histology remains the reference standard. This multicenter, cross-sectional cohort study evaluated the accuracy of APRI (AST-to-platelet-ratio-index) and liver surface ultrasound nodularity (LSN), singularly and sequentially combined in an algorithm, in diagnosing advanced fibrosis (i.e. METAVIR F3,F4), to derive a prediction rule to confirm or exclude F3,F4.
Methods:
Four hundred and thirty consecutive CH-C patients with elevated ALT, grouped into a first cohort (training set), and an internal and an external validation cohort, were studied. APRI and LSN were compared to liver biopsy and sequentially combined in order to obtain a predictive rule for advanced fibrosis METAVIR F3,F4.
Results:
LSN was negative and APRI < or = 1 in 185/430 patients, whereas LSN was positive and APRI>2 in 46/430 cases, with a 94% diagnostic accuracy for presence/absence of F3, F4, respectively. In a further 60/430 patients, F3,F4 was detected with an accuracy of 83%. In the remaining cases no classification was possible.
Conclusions:
An algorithm based on APRI and LSN confirms or excludes F3,F4 in 54% of CH-C patients with elevated ALT and suggests a highly probable diagnosis in a further one-sixth of patients, thus rendering liver biopsy unnecessary in these patients.
