MRI calculated liver fat mass as a new biomarker for steatosis grade evaluation in middle age population

Abstract

ABSTRACT

Purpose:

Steatosis, the condition where intracellular excess fat accumulates in the liver, is a growing health concern worldwide.                   

This is a meta-analysis from MRI data, that was initially produced to investigate the relation of Hepatic Steatosis with abdominal obesity and PNPLA3 molecular variability in Metabolic dysfunction–associated steatotic liver disease patients. It aims to investigate and statistically confirm any correlation of fat mass in liver with steatosis grade by using MRI-PDFF as a diagnostic tool and introduce liver fat mass as a new biomarker for steatosis grade assessment.

Material and Methods:

A sample of 162 Metabolic dysfunction–associated steatotic liver disease patients and healthy volunteers (average age 60.3y) participated and had abdomen MRI scan with a 3D-GE IQ-IDEAL and a 3D-LAVA sequencies. Fat fraction, liver fat mass and liver volume were calculated. Statistical analysis was performed to evaluate data, including Shapiro-Wilk test, Kruskal-Wallis test, Dunn’s post-hoc test with Bonferroni correction and Ordinal Logistic Regression. 

Results:

Statistical analysis proves that there is a strong positive correlation between liver fat mass and steatosis grade; higher fat mass is associated with higher grades of steatosis.  From the Predicted Probabilities diagram, we calculated, as a sum of probabilities, the steatosis grade from a given liver fat mass, in a non-discrete steatosis scale.

Conclusions:

MRI fat mass estimation could serve as a reliable and clinically meaningful biomarker for Metabolic dysfunction–associated steatotic liver disease (MASLD). The ability to calculate steatosis grade in a more precise non-discrete form may help to better evaluate and monitor a patient’s condition through time.