What question did this study set out to answer?

This study aims to assess the diagnostic accuracy of quantitative ultrasound fat fraction against MRI-PDFF for hepatic steatosis grading.

February 26, 2026Open Access

Quantitative Ultrasound As an Alternative Method for Assessment and Grading of Hepatic Steatosis: A Comparison Study with Quantitative MRI-Proton Density Fat Fraction

Key Points

This study aims to assess the diagnostic accuracy of quantitative ultrasound fat fraction against MRI-PDFF for hepatic steatosis grading.
Conducted a single-center prospective study from January 2024 to July 2025.
Included 40 adults undergoing both quantitative ultrasound and MRI within 24 hours.
Utilized tissue attenuation imaging and tissue scatter-distribution imaging to calculate USFF.
MRI-PDFF classified steatosis grades with a distribution of S0 (37.5%), S1 (47.5%), S2 (7.5%), and S3 (7.5%).
USFF showed the following distribution: S0 (20%), S1 (47.5%), S2 (20%), and S3 (12.5%).
USFF demonstrated a strong correlation with MRI-PDFF (r = 0.912; p < 0.001).

Abstract

Abstract Although liver biopsy remains the gold standard for diagnosis of hepatic steatosis, non-invasive imaging is essential for population screening, risk assessment, and monitoring treatment. New ultrasonic techniques enable quantitative assessment of steatosis in individuals with hepatic metabolic disorders, offering an alternative noninvasive screening method. This study aims to evaluate the diagnostic accuracy of quantitative ultrasound fat fraction (USFF) in detecting and grading hepatic steatosis, using quantitative magnetic resonance imaging-proton density fat fraction (MRI-PDFF) as the reference standard. In this single-center prospective study (January 2024–July 2025), 40 consecutive adults (average age 57.83 ± 15.7 years; 14 men) referred for liver fat measurement underwent multivariable quantitative ultrasound (Samsung V7, convex probe CA 1–7 MHz) and 1.5-T MRI within 24 hours. After fasting for at least 4 hours, five reliable ultrasound acquisitions (reliability index R 2 ≥ 0.60) of tissue attenuation imaging (TAI) and tissue scatter-distribution imaging (TSI) were obtained through a right intercostal window, and their means were automatically converted to USFF (%). MRI-PDFF maps were created using a six-echo spoiled gradient-echo sequence with multi-peak fat modeling and T2* correction. Steatosis grades were classified on USFF and PDFF as S0 (0–5%), S1 ( ≥ 5%), S2 ( ≥ 15%), and S3 (>25%). Pearson correlation and weighted κ statistics were used for analysis (SPSS v20). MRI-PDFF classified 15/40 (37.5%) of the livers as S0, 19/40 (47.5%) as S1, 3/40 (7.5%) as S2, and 3/40 (7.5%) as S3. The corresponding USFF distribution was S0 for 8/40 (20%), S1 for 19/40 (47.5%), S2 for 8/40 (20%), and S3 for 5/40 (12.5%). USFF showed a strong correlation with MRI-PDFF (r = 0.912; 99% CI 0.805–0.961; p < 0.001). Quantitative ultrasound shows excellent correlation and strong agreement with MRI-PDFF for both detection and grading of hepatic steatosis. Given its low cost, real-time capability, and wide availability, USFF is a practical alternative for routine assessment and ongoing monitoring of hepatic fat.

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