Children with non-alcoholic fatty liver disease (NAFLD) who had undergone MRI with proton density fat fraction (MRI-PDFF) for Liver Steatosis quantification and magnetic resonance elastography (MRE) for liver stiffness measurement were included in the study. To construct a predictive model for fat percentage and stiffness, researchers analyzed data from patients who were scanned between April 2009 and July 2018. In addition, researchers used data from a second cohort, which was observed between 2018 and 2019, to validate the models’ performance. The first cohort (n=344) consisted primarily of non-Hispanic (80%) and male (67%) adolescents. For 343 children, MRE data was available, while for 130 children, PDFF data was available. Ethnicity, insulin levels, platelet count, and aspartate aminotransferase all predicted liver stiffness independently in multivariable regression, and these factors were used to create the predictive model. Similarly, the PDFF model employed sex, ethnicity, alanine aminotransferase, and triglycerides levels as independent predictors of hepatic PDFF. For the model that predicted a stiffness of more than 2.71 kPa, the AUC of the best cutoff was 0.70, while for the model that projected PDFF of more than 5%, it was 0.78. Similar characteristics were found in the validation group (n=110). The model had a correlation coefficient of 0.30 with measured liver stiffness and 0.26 with liver PDFF. Pediatric-specific models perform poorly at predicting exact liver stiffness and steatosis; nonetheless, they can be used to indicate the presence of severe steatosis (>5%) and significant stiffness (>2.71) in the absence of magnetic resonance imaging. As a result, imaging remains a crucial supplement to laboratory tests in evaluating the severity of the disease.

 

Source:journals.lww.com/jpgn/Abstract/2022/04000/Non_Invasive_Approaches_to_Estimate_Liver.14.aspx