ArticleBMC medical imaging2025
MRI proton density fat fraction for estimation of biological characteristics in hepatocellular carcinoma.
Article in BMC medical imaging, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Preoperative MRI-derived fat fraction is linked to survival after liver transplantation for hepatocellular carcinoma.iLIVER · 2026Article
- Qualitative and quantitative assessment of intratumoral fat using chemical-shift MRI for predicting histological grade of hepatocellular carcinoma.BMC medical imaging · 2026Article
- Noninvasive Prediction of High Ki-67 Expression in Hepatocellular Carcinoma Using Multiparametric MRI and Clinical Biomarkers.Journal of hepatocellular carcinoma · 2026Article
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8 authors.
Funding
Abstract
purposeTo evaluate whether the magnetic resonance imaging (MRI) proton density fat fraction (PDFF) can predict the biological characteristics of hepatocellular carcinoma (HCC) preoperatively.
methodsA total of 131 HCCs were included. The MRI features and PDFF values were evaluated by two independent radiologists. The intraclass correlation coefficient (ICC) was calculated in terms of inter- and intra-observer agreements. The macrotrabecular-massive (MTM) subtype, microvascular invasion (MVI) status, histological grade, and proliferative status of Ki-67 and p53 were identified in HCCs. The diagnostic performance of the PDFF was evaluated using receiver operating characteristic (ROC) curve analysis based on the area under the receiver operating characteristic curve (AUC).
resultsPDFF values showed significant differences between: MTM vs. non-MTM HCCs (p=0.048), MVI-positive vs. negative tumors (p=0.041), high- vs. low-grade lesions (p<0.001), and p53-positive vs. negative cases (p=0.015), but not for Ki-67 expression (p=0.075). The AUC values of the PDFF for predicting the MTM subtype, MVI status, histological grade, and proliferative status of p53 were 0.606, 0.588, 0.683, and 0.671, respectively. Only infiltrative appearance had significant difference between MVI-positive and MVI-negative groups. Combining PDFF with infiltrative appearance significantly improved MVI prediction (AUC = 0.681, p = 0.02).
conclusionsMRI-PDFF demonstrates potential as a quantitative biomarker for preoperative assessment of HCC aggressiveness, particularly for the MTM subtype, histological grade and p53 status, though its standalone performance for MVI prediction remains limited. Integration with morphological features enhances diagnostic accuracy, supporting its complementary role in multiparametric HCC characterization. CLINICAL TRIAL NUMBER: Not applicable.
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