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.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6613709PMC
http://dx.doi.org/10.1371/journal.pcbi.1007157DOI Listing

Publication Analysis

Top Keywords

liver function
12
mechanisms liver
8
magnetic resonance
8
resonance imaging
8
validated model
8
liver
6
model
5
model-inferred mechanisms
4
function magnetic
4
imaging data
4

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!