Correlation between Liver fat Content Determined by Ultrasonic Attenuation Imaging and Lipid Metabolism in Patients with Non-Alcoholic Fatty Liver Disease - Hao, Yanhong; Zhang, Yanjing; Yin, Guolin; Zhang, Lei; Liu, Liping (Current Medical Imaging, 2025)
Objective: This study aimed to investigate the utility of ultrasonic attenuation imaging (ATI) in assessing the relationship between hepatic fat content and lipid metabolism in patients with type 2 diabetes mellitus (T2DM).Methods: 239 patients diagnosed with T2DM were included, with liver fat quantified using proton density fat fraction (PDFF). We analyzed the variance in ATI across various grades of fatty liver and its correlation with clinical parameters. Additionally, a receiver operating characteristic curve (ROC) was employed to evaluate the diagnostic accuracy of ATI for different degrees of fatty liver, determining optimal diagnostic thresholds while calculating sensitivity and specificity. Furthermore, we assessed the reliability of ATI and SWE in measuring liver acoustic attenuation and elastic stiffness using the intraclass correlation coefficient (ICC).Results: We observed significant variations in ATI across different grades of fatty liver (p<0.001). ATI exhibited positive correlations with SWE, BMI, GLU (OH), steatosis grade, ALT, TG, and UA, while demonstrating a negative correlation with HDL-c. Notably, the correlation coefficient with steatosis grade was 0.784, indicating a strong association. The equation for the stepwise multiple linear regression model used is as follows: ATI=0.338+0.014×TG+0.052×BMI+0.001×ALT+0.113×SWE. AUROCs indicated the best cutoffs for ATI in different degrees of steatosis to be as follows: ≥ S1 = 0.665 dB·cm-1·MHz-1 (AUC = 0.899); ≥ S2 = 0.695 dB·cm-1·MHz-1 (AUC = 0.939); ≥ S3 = 0.745 dB·cm-1·MHz-1 (AUC = 0.937). The ICC values for ATI and SWE in liver-mimicking measurements exceeded 0.75 (p<0.001), signifying excellent repeatability.Conclusion: The ATI could quantitatively assess the severity of fatty liver, enabling effective identification of patients suitable for liver biopsy referral.
Keywords: Type 2 diabetes