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Updated: Aug 22, 2026
A 3D Quantification Technique for Liver Fat Fraction Distribution Analysis Using Dixon Magnetic Resonance Imaging
Published on: October 20, 2023
Quantitative ultrasound-derived fat fraction for hepatic steatosis in MASLD using liver biopsy as the reference
Yuting Shen1, Dong Jiang2, Anqi Zhu1
1Department of Ultrasound, Institute of Ultrasound in Medicine and Engineering, Zhongshan Hospital, Fudan University, Shanghai, China.
Objectives:
Non-invasive steatosis grading tools are critical for the assessment of Metabolic dysfunction-associated steatotic liver disease (MASLD). This study evaluated the performance of ultrasound-derived fat fraction (UDFF) against histopathology for the grading of hepatic steatosis.
Materials And Methods:
From August 2022 to September 2024, this prospective dual-center study enrolled 418 participants (376 from Center 1, 42 from Center 2) with confirmed or suspected MASLD, all of whom underwent UDFF and liver biopsy. Diagnostic performance was evaluated using Spearman correlation, Bland-Altman plots, and receiver operating characteristic (ROC) curve analyses. Optimal UDFF cut-offs for steatosis grades (S0-S3) were derived from the training cohort and refined to clinically practical integers with reference to validation cohort performance. A dual-threshold strategy defining an indeterminate zone (sensitivity ≥ 90% for rule-out; specificity ≥ 90% for rule-in) was implemented.
Results:
UDFF showed excellent reproducibility and strong correlations with histopathology (Spearman's ρ = 0.724-0.767, p < 0.001). Bland-Altman analyses revealed minimal bias between UDFF and histopathology (Center 1/2: 1.432%/1.921%). In our biopsy-selected MASLD cohort, the optimal UDFF cut-offs were ≥ 6%, ≥ 15%, and ≥ 21% for mild (S ≥ 1), moderate (S ≥ 2), and severe (S3) steatosis, respectively. In the training cohort, area under the ROC curves (AUROCs) were 0.966, 0.805, and 0.929 for S ≥ 1, S ≥ 2, and S3. These established cut-offs were robustly validated internally and externally (AUROCs: 0.972/0.922 for S ≥ 1; 0.948/0.934 for S ≥ 2; 0.911/0.936 for S3) and reduced indeterminate cases by 2.8-24.6% compared to initial dual thresholds.
Conclusion:
UDFF demonstrated promising performance for steatosis grading in patients with clinically indicated biopsy and might serve as a useful non-invasive tool.
Key Points:
QuestionCan UDFF provide a reproducible, accurate, and clinically reliable imaging-based assessment of hepatic steatosis grading in MASLD? FindingsUDFF accurately grades hepatic steatosis against histopathology. Optimized cut-offs (≥ 6%/≥ 15%/≥ 21%) reduce indeterminate classifications by up to 24.6%, and high reproducibility enables robust multicenter application. Clinical relevanceUDFF demonstrates promising diagnostic performance for hepatic steatosis with robust reproducibility and optimized thresholds (≥ 6%/15%/21%). However, its utility is limited by the small number of severe cases and lack of inter-observer data, further validation is needed.
