Abstract
BACKGROUND: This study aimed to evaluate the diagnostic performance of ultrasound-derived fat fraction (UDFF) for metabolic dysfunction-associated steatotic liver disease (MASLD), by directly comparing it with the non-invasive gold standard MRI-PDFF and the established ultrasound method CAP. METHODS: The diagnostic criteria for MASLD were used, we included 103 individuals with 53 MASLD patients and 49 healthy controls. All participants underwent liver MRI for MRI-PDFF quantification; ultrasound elastography for UDFF measurement; and vibration-controlled transient elastography for CAP assessment. Receiver operating characteristic (ROC) curves were generated to evaluate the performance of UDFF and CAP for predicting MRI-PDFF ≥ 5%, the imaging threshold defining hepatic steatosis in MASLD diagnosis. Finally, we analyzed the correlation between UDFF and serological indicators and the consistency between UDFF and MRI-PDFF. RESULTS: Across all 103 participants, the median UDFF value was 6.0%, median CAP was 246 dB/m, and median MRI-PDFF was 5.44%. Overall, UDFF was positively correlated with MRI-PDFF (R = 0.876; P < 0.001), and CAP was positively correlated with MRI-PDFF (R = 0.792, P < 0.001). For diagnosing 5% and above MRI-PDFF, UDFF was noted to have a mean AUC of 0.981. Additionally, CAP was noted to have an AUC of 0.932 in diagnosing MASLD. In addition, the Bland-Altman difference plots showed overall UDFF and MRI-PDFF, with a mean deviation of -0.2%. A linear regression model between the difference and the mean suggested proportional error. CONCLUSIONS: Ultrasound testing for UDFF provides a simple and noninvasive clinical tool to quantify the extent of hepatic steatosis. The diagnostic efficacy of UDFF is superior to CAP. Notably, while UDFF shows strong agreement with MRI-PDFF overall, Bland-Altman analysis revealed a proportional bias, with UDFF tending to underestimate MRI-PDFF at higher fat content levels. Despite this limitation, UDFF demonstrates potential as a noninvasive alternative to MRI-PDFF for MASLD diagnosis.