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Updated: Sep 9, 2026
A 3D Quantification Technique for Liver Fat Fraction Distribution Analysis Using Dixon Magnetic Resonance Imaging
Published on: October 20, 2023
Robust Liver Steatosis Quantification Using Photon-Counting CT in Comparison to PDFF: Validation across Protocols and
Xinxin Xu1, Jie Yuan2, Xinxin Cai3
1Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China (X.X., J.Y., X.C., R.D., J.L., X.W., H.C., H.D., R.C., W.L., R.L., F.Y., H.L.); Faculty of Medical Imaging Technology, College of Health Science and Technology, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China (X.X., J.L., R.L., F.Y., H.L.).
Rationale And Objectives:
To evaluate the robustness and grading performance of Photon-counting CT (PCCT)-derived fat fraction (CTFF) in liver fat quantification across different protocols and cohorts with varying liver conditions, using proton density fat fraction (PDFF) as the reference.
Materials And Methods:
The prospective study enrolled 297 participants in the Volunteer cohort. Participants were randomly assigned to 120-kVp or 140-kVp groups and subdivided into high- and low-dose subgroups for technical validation. Clinical validation was performed in two cohorts: participants with metabolic dysfunction-associated steatotic liver disease (MASLD, n = 86) and heterogeneous liver diseases (HLD, n = 61). PCCT and PDFF (reference standard for grading) were performed within 1 month. Statistical analyses included intraclass correlation coefficients, Bland-Altman analysis, Mann-Whitney U and Kruskal-Wallis tests, and areas under the receiver operating characteristic (AUC-ROC) and precision-recall curves (AUC-PR).
Results:
Overall, 444 participants were included (age 44.9 ± 14.3 years; 264 men). In the Volunteer cohort, CTFF showed excellent agreement with PDFF (all ICCs = 0.98; R2 ≥0.96) with a maximum bias of 0.80% (95% CI: 0.70-0.89%), across the whole-cohort and subgroups. No significant differences in the absolute error between PDFF and CTFF were observed across all subgroups (all p > 0.05). CTFF achieved high diagnostic accuracy for both the detection and grading of steatosis with all AUC-ROC and AUC-PR exceeding 0.99. The diagnostic accuracy of CTFF was verified in the MASLD and HLD cohorts.
Conclusion:
CTFF demonstrated excellent agreement with PDFF and consistent diagnostic performance across diverse scan settings and liver conditions.
