Evaluation of Artificial Intelligence-Calculated Hepatorenal Index for Diagnosing Mild and Moderate Hepatic Steatosis in Non-Alcoholic Fatty Liver Disease

Abstract

<i>Background and Objectives</i>: This study aims to evaluate artificial intelligence-calculated hepatorenal index (AI-HRI) as a diagnostic method for hepatic steatosis. <i>Materials and Methods</i>: We prospectively enrolled 102 patients with clinically suspected non-alcoholic fatty liver disease (NAFLD). All patients had a quantitative ultrasound (QUS), including AI-HRI, ultrasound attenuation coefficient (AC,) and ultrasound backscatter-distribution coefficient (SC) measurements. The ultrasonographic fatty liver indicator (US-FLI) score was also calculated. The magnetic resonance imaging fat fraction (MRI-PDFF) was the reference to classify patients into four grades of steatosis: none < 5%, mild 5-10%, moderate 10-20%, and severe ≥ 20%. We compared AI-HRI between steatosis grades and calculated Spearman's correlation (r_s) between the methods. We determined the agreement between AI-HRI by two examiners using the intraclass correlation coefficient (ICC) of 68 cases. We performed a receiver operating characteristics (ROC) analysis to estimate the area under the curve (AUC) for AI-HRI. <i>Results</i>: The mean AI-HRI was 2.27 (standard deviation, ±0.96) in the patient cohort. The AI-HRI was significantly different between groups without (1.480 ± 0.607, <i>p</i> < 0.003) and with mild steatosis (2.155 ± 0.776), as well as between mild and moderate steatosis (2.777 ± 0.923, <i>p</i> < 0.018). AI-HRI showed moderate correlation with AC (r_s = 0.597), SC (r_s = 0.473), US-FLI (r_s = 0.5), and MRI-PDFF (r_s = 0.528). The agreement in AI-HRI was good between the two examiners (ICC = 0.635, 95% confidence interval (CI) = 0.411-0.774, <i>p</i> < 0.001). The AI-HRI could detect mild steatosis (AUC = 0.758, 95% CI = 0.621-0.894) with fair and moderate/severe steatosis (AUC = 0.803, 95% CI = 0.721-0.885) with good accuracy. However, the performance of AI-HRI was not significantly different (<i>p</i> < 0.578) between the two diagnostic tasks. <i>Conclusions</i>: AI-HRI is an easy-to-use, reproducible, and accurate QUS method for diagnosing mild and moderate hepatic steatosis.