Objective: Primary sclerosing cholangitis (PSC) is a rare broin ammatory hepatobiliary disease with a highly variable clinical course. Identifying patients at risk for poor outcomes remains challenging. Magnetic resonance imaging (MRI)-based approaches such as DiStrict, Anali score, and relative enhancement (RE) show promise but are limited by operator dependency or static measurements. This study explored pharmacokinetic modelling of liver function as a quantitative imaging biomarker for risk assessment in PSC.

Materials and methods: A prospective cohort of 26 PSC patients underwent up to ve annual MRI examinations with follow-up up to 7.5 years. Clinical endpoints included liver transplantation, decompensated cirrhosis, and cholangiocarcinoma. Correlation and receiver operating characteristics (ROC) analyses compared the pharmacokinetic model with Anali scores, RE, model for end-stage liver disease (MELD), and the Amsterdam–Oxford Model (AOM).

Results: The pharmacokinetic model (ksingle) correlated signi cantly with MELD (r = -0.429, p= 0.029), AOM (r = -0.557, p= 0.003), and endpoint events (r = -0.605, p= 0.001). ROC analysis showed excellent discrimination for ki,single (area under the curve [AUC]= 0.943) outperformed Anali scores (AUC= 0.800–0.829) and comparable to MELD (AUC= 0.857) and AOM (AUC= 0.900).

Conclusion: Pharmacokinetic liver function modelling correlated strongly with MELD and AOM, effectively identifying high-risk PSC patients.

Relevance statement: Pharmacokinetic liver function modelling detects functional impairment in PSC, correlating well with established tools such as the AOM. As an objective, quantitative imaging biomarker, this method may complement established risk scores and aid in the identi cation of patients at risk of adverse outcomes.

Key Points:

● Pharmacokinetic modelling estimates changes in liver function based on MRI.

● These estimates can be used as a prognostic tool in PSC.

● The model’s prognostic performance was comparable to established clinical tests.