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Updated: Jan 23, 2026

Acquisition of Resting-State Functional Magnetic Resonance Imaging Data in the Rat
Published on: August 28, 2021
Model-inferred mechanisms of liver function from magnetic resonance imaging data: Validation and variation across a
Mikael F Forsgren1,2, Markus Karlsson2,3, Olof Dahlqvist Leinhard2,3
1Wolfram MathCore AB and Department of Medical and Health Sciences, Linköping University, Linköping, Sweden.
Abstract:
Estimation of liver function is important to monitor progression of chronic liver disease (CLD). A promising method is magnetic resonance imaging (MRI) combined with gadoxetate, a liver-specific contrast agent. For this method, we have previously developed a model for an average healthy human. Herein, we extended this model, by combining it with a patient-specific non-linear mixed-effects modeling framework. We validated the model by recruiting 100 patients with CLD of varying severity and etiologies. The model explained all MRI data and adequately predicted both timepoints saved for validation and gadoxetate concentrations in both plasma and biopsies. The validated model provides a new and deeper look into how the mechanisms of liver function vary across a wide variety of liver diseases. The basic mechanisms remain the same, but increasing fibrosis reduces uptake and increases excretion of gadoxetate. These mechanisms are shared across many liver functions and can now be estimated from standard clinical images.
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