Diagnostic value of CT-quantified abdominal fat parameters for metabolic dysfunction-associated fatty liver disease

To analyze the diagnostic value of CT-derived abdominal fat indices in predicting MAFLD and establish an integrated diagnostic system. A retrospective study on 174 patients with a previous history of abdominal CT examination in our institute between January 2022 and June 2024 was conducted, comprising 120 diagnosed with MAFLD, and 54 controls without it. CT-derived measures including SAT, visceral adipose tissue volume(VAT), total liver volume, and average hepatic. The average value and CT attenuation value of the left and right lobe of liver and the VAT/SAT were compared using Mann-Whitney U test. were compared between both groups. Then, we used Spearman’s rank correlation analysis to study whether there existed correlations between CT metrics and metabolic indicators. Logistic regression and receiver operating characteristic(ROC)curve analysis were utilized to evaluate the diagnostic accuracy of individual parameters.Calibration of a composite prediction model was evaluated by using calibration plots. In MAFLD groups, SAT, VAT, liver volume, and the VAT / SAT ratio were higher than those of the control group, while the mean hepatic CT attenuation value, as well as the mean attenuation value of the left lobe and right lobe, were all lower than those of the control group (all P < 0.05). The mean hepatic CT attenuation correlated negatively with BMI ( r = -0.607) and TG ( r = -0.418), while the sign was positive for VAT. In univariate logistic regression, we found that the mean hepatic CT attenuation is the best diagnostic indicator of MAFLD, with an AUC of 0.923, then were left and right hepatic attenuation (AUC = 0.886), liver volume (AUC = 0.814), and VAT’s mean CT attenuation (AUC = 0.796). BMI ( r = 0.554) and UA ( r = 0.362) were also considered. Combining SAT, VAT, and mean hepatic CT attenuation together in one model resulted in an AUC of 0.928 (sensitivity: 91.7%, specificity: 85.2%). The calibration curves demonstrated an acceptable fit of the model. When multiple variables were combined, the sensitivity improved from 85.8% to 91.7% and specificity changed from 87.0% to 85.2%, yielding an AUC of 0.928 (ΔAUC = 0.005 compared with mean hepatic CT attenuation alone, P = 0.62). CT-measured abdominal fat may represent a reliable and noninvasive approach for the diagnosis of MAFLD.The greatest individual diagnostic utility was exhibited by mean liver CT attenuation alone; however, with multiple variables merged into a combined model, the sensitivity and specificity were also further increased, which could be an effective method to image MAFLD in clinical diagnosis.