Abstract
PURPOSE: To investigate the application of imaging biomarkers, including R2*, Fat Fraction (FF) and apparent diffusion coefficient (ADC) values, obtained through Iterative Decomposition of water and fat with Echo Asymmetry and Least-squares estimation for Imaging Quantification (IDEAL-IQ) and DWI techniques, in differentiating P53-mutated and non-mutated HCC. PATIENTS AND METHODS: This retrospective study included patients with pathologically confirmed HCC between January 2019 and July 2024. HCC were divided into P53-mutated group and non-mutated group by immunostaining. Preoperative R2*, FF, and ADC values derived from IDEAL-IQ and DWI were compared between the two groups, as well as different histological grades. Receiver operating characteristic (ROC) analysis was used to evaluate the diagnostic performance of each MRI parameter for detecting P53 mutations in HCC, with area under the curve (AUC) compared by Delong's test. RESULTS: Compared to the non-mutated group, the P53-mutated group (n = 31) showed significantly higher R2* values (34.821 ± 9.980 vs 23.713 ± 5.586, P < 0.001) and lower ADC values (0.760 ± 0.142 vs 0.855 ± 0.130, P = 0.002), while FF values showed no significant difference (P = 0.646). R2*, ADC, and the combined model (R2* + ADC) revealed AUCs of 0.849, 0.726, and 0.856, respectively, with the combined model demonstrating the highest sensitivity and specificity. Additionally, high-grade HCC showed significantly lower ADC values compared to lower-grade tumors (P < 0.001). CONCLUSION: R2* and ADC exhibited significant features in P53-mutated HCC, suggesting their potential as non-invasive biomarkers for predicting P53 mutation status and guiding clinical management. The combined use of R2* and ADC may further enhance diagnostic accuracy.