Non-Invasive Approaches to Estimate Liver Steatosis and Stiffness in Children With Non-Alcoholic Fatty Liver Disease

Abstract

Objectives: To develop pediatric-specific models that predict liver stiffness and hepatic steatosis in non-alcoholic fatty liver disease (NAFLD), based on clinical and laboratory data.

Methods: Children with NAFLD, who had undergone magnetic resonance imaging with proton density fat fraction (MRI-PDFF) for steatosis quantification and/or magnetic resonance elastography (MRE) for liver stiffness assessment were included. We used data from patients imaged between April 2009 to July 2018 to develop a predictive model for fat fraction and stiffness. We validated the performance of the models using data from a second cohort, imaged between 2018 and 2019.

Results: The first cohort (n = 344) consisted of predominantly non-Hispanic (80%), male (67%) adolescents. MRE data were available for 343 children, while PDFF data were available for 130. In multivariable regression, ethnicity, insulin levels, platelet count, and aspartate aminotransferase independently predicted liver stiffness and these variables were used to develop the predictive model. Similarly, sex, ethnicity, alanine aminotransferase, and triglycerides levels independently predicted liver PDFF and were used in the PDFF model. The AUC of the optimal cutoff for the model that predicted a stiffness of >2.71 kPa was 0.70 and for the model that predicted PDFF >5% was 0.78. The validation group (n = 110) had similar characteristics. The correlation coefficient of the model with the measured liver stiffness was 0.30 and with the measured liver PDFF was 0.26.

Conclusions: Pediatric-specific models perform poorly at predicting exact liver stiffness and steatosis; however, in the absence of magnetic resonance imaging can be used to predict the presence of significant steatosis (>5%) and/or significant stiffness (>2.71). Thus, imaging remains an invaluable adjunct to laboratory investigations in determining disease severity.

FIGURE 1.

ROC curve showing the performance of the calculated liver stiffness value in predicting the presence of increased liver stiffness (>2.71 kPa). The black dot is the optimal cutoff point (2.445) that maximizes the distance to the diagonal line (Youden’s method). The two red dots are the cutoff points can predict the presence of MRI-measured liver stiffness >2.71 kPa with a minimum sensitivity and specificity of 95%, respectively. MRI = magnetic resonance imaging; ROC = receiver operating characteristic.

FIGURE 2.

ROC curve showing the performance of the calculated liver PDFF (MRI-measured fat fraction) value in predicting the presence of increased liver PDFF (>5%). The black dot is the best cutoff point (18.3%) that maximize the distance to the diagonal line (Youden’s method). The two red dots are the cutoff points can predict the presence of PDFF with at least 95% of sensitivity and with at least 95% of specificity respectively. MRI=magnetic resonance imaging; PDFF = proton density fat fraction; ROC = receiver operating characteristic.