MRI proton density fat fraction for estimation of biological characteristics in hepatocellular carcinoma

利用磁共振质子密度脂肪分数评估肝细胞癌的生物学特征

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Abstract

PURPOSE: To evaluate whether the magnetic resonance imaging (MRI) proton density fat fraction (PDFF) can predict the biological characteristics of hepatocellular carcinoma (HCC) preoperatively. METHODS: A 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). RESULTS: PDFF 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). CONCLUSIONS: MRI-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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