Background: Three-dimensional (3D) MR elastography (MRE) derives viscoelastic parameters that may reflect inflammation, but their frequency dependence and the influence of steatosis on inflammation grading and fibrosis staging remain unclear.

Purpose: To investigate 3D multifrequency MRE for assessing hepatic inflammation, fibrosis stage across frequencies, and the influence of steatosis.

Study Type: Prospective.

Population: Sixty-four (40 men, median age: 58 years) participants with chronic liver disease (CLD); 21 (8 men, median age:28 years) healthy volunteers.

Field Strength/Sequence: 3-T; gradient-echo sequence with mechanical vibrations at low (16.7 and 18 Hz), medium (33.4 and 36 Hz), and high (50.1 and 54 Hz) frequencies.

Assessment: In CLD participants, MRE-derived viscoelastic parameters, shear stiffness, storage modulus, loss modulus, and damping ratio were compared with histologically assessed fibrosis, inflammation, and steatosis. MRE test–retest repeatability over 10 min was evaluated in healthy volunteers.

Statistical Tests: Wilcoxon rank sum test, Spearman's correlation, multivariable regression analysis, and area under the receiver operating curve (AUROC). A p value of < 0.05 was considered statistically significant.

Results: Inflammation was significantly independently associated with damping ratio at medium frequency, which showed moderate performance for grading inflammation (AUROC = 0.76–0.83, sensitivity = 0.83–0.84, specificity = 0.70–0.79). Fibrosis staging using shear stiffness and moduli showed high diagnostic performance (AUROC = 0.82–0.95), with comparable accuracy between medium and high frequencies (p = 0.327–0.896). Steatosis was not significantly correlated with MRE overall (p = 0.212–0.459), but was significantly associated with 19% higher stiffness and 20% higher loss modulus at medium frequency in CLD participants without fibrosis or inflammation.

Data Conclusion: Medium frequency 3D MRE demonstrated an independent association with inflammation while preserving accurate fibrosis assessment. Steatosis seemed not to confound MRE-based evaluation.

Level of Evidence: 1.

Technical Efficacy: Stage 2.

Plain Language Summary: Chronic liver disease can cause both inflammation and scarring (fibrosis). Accurate assessment usually requires a biopsy, which is invasive. This study evaluated a noninvasive imaging method called three-dimensional magnetic resonance elastography (3D MRE) in patients who underwent same-day liver biopsy. The researchers tested whether different vibration frequencies could detect inflammation and fibrosis. They found that medium frequency measurements were associated with liver inflammation while still accurately identifying fibrosis. Fat accumulation in the liver did not significantly affect the results. These findings suggest that 3D MRE may help medical doctors assess liver inflammation and fibrosis noninvasively in a single examination.

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.

Unhealthy dieting and a sedentary lifestyle are causing an increased prevalence of obesity related complications. One such complication is metabolic dysfunction-associated steatotic liver disease (MASLD) the manifestation of metabolic dysregulation and insulin resistance in the liver. Today, MASLD effect a third of the world’s population. One of the main characteristics of MASLD is accumulation of ectopic lipids in the liver, also denoted steatosis. Steatosis is not inherently dangerous but is an indication of metabolic dysregulation, and long-term MASLD can progress into severe conditions such as chronic hepatic inflammation denoted metabolic dysfunction-associated steatohepatitis (MASH), liver scarring (cirrhosis), and primary liver cancer (hepatocellular carcinoma, HCC). Moreover, these conditions can be further aggravated by alcohol consumption. The increase in potential patients with MASLD will have an enormous burden on future healthcare. Thus, future healthcare has a need for innovative solutions to lessen this burden. Such solutions should be capable of personalized and preventive measures, cost-effective high throughput screening methods, and frameworks integrating all available patient data, for all stages of MASLD. Today, some of these methodologies already exist, however there is still a need for ways to integrate different liver biomarkers into a user-friendly framework, with strong personalization and predictive capabilities. For this purpose, data-driven mathematical modelling is of use. Data-driven mathematical models has proven useful for such integration in other disease areas such as stroke. In this thesis, I have created and explored several mathematical models aimed at exploring different aspects of MASLD, as well as developed several models using data from example: our own collected magnetic resonance imaging (MRI) data from patients suffering from chronic liver disease or HCC, and pre-clinical mouse data of insulin resistance progression. The studies presented in this thesis investigate diet-driven insulin resistance development, steatosis development and screening, as well as lifestyle interventions for alcohol and dietary habits, and liver function evaluation at late-stage liver disease. Thus, this thesis presents a possible fundament to create a so-called digital twin of MASLD – a highly personalized model capable of making predictions based on lifestyle. 

BACKGROUND: Drug induced liver injury (DILI) is a major concern when developing new drugs. A promising biomarker for DILI is the hepatic uptake rate of the contrast agent gadoxetate. This rate can be estimated using a novel approach combining magnetic resonance imaging and mathematical modeling. However, previous work has used different mathematical models to describe liver function in humans or rats, and no comparative study has assessed which model is most optimal to use, or focused on possible translatability between the two species.

AIMS: Our aim was therefore to do a comparison and assessment of models for DILI biomarker assessment, and to develop a conceptual basis for a translational framework between the species.

METHODS AND RESULTS: We first established which of the available pharmacokinetic models to use by identifying the most simple and identifiable model that can describe data from both human and rats. We then developed an extension of this model for how to estimate the effects of a hepatotoxic drug in rats. Finally, we illustrated how such a framework could be useful for drug dosage selection, and how it potentially can be applied in personalized treatments designed to avoid DILI.

CONCLUSION: Our analysis provides clear guidelines of which mathematical model to use for model-based assessment of biomarkers for liver function, and it also suggests a hypothetical path to a translational framework for DILI.

Non-alcoholic fatty liver disease (NAFLD) is considered to be the hepatic manifestation of the metabolic syndrome and is characterized by ectopic accumulation of triglycerides in the cytoplasm of hepatocytes, i.e., steatosis. NAFLD has become the most common chronic liver disease, with an estimated global prevalence of 25%. Although the majority of NAFLD patients will never experience liver-related complications, the progressive potential of NAFLD is indisputable, with 5-10% of subjects progressing to cirrhosis, end-stage liver disease, or hepatocellular carcinoma. NAFLD patients with advanced fibrosis are at the highest risk of developing cardiovascular and cirrhosis-related complications. Liver biopsy has hitherto been considered the reference method for evaluation of hepatic steatosis and fibrosis stage. Given the limitations of biopsy for widescale screening, non-invasive tests (NITs) for assessment of steatosis and fibrosis stage, including serum-based algorithms and ultrasound- and magnetic resonance-based methods, will play an increasing role in the management of NAFLD patients. This comprehensive review presents the advantages and limitations of NITs for identification of steatosis and advanced fibrosis in NAFLD. The clinical implications of using NITs to identify and manage NAFLD patients are also discussed.