Time-dependent diffusion-weighted MRI discriminates hepatocellular carcinoma from intrahepatic cholangiocarcinoma: A prospective animal model study.

[OBJECTIVE] To evaluate the diagnostic potential of microstructural parameters derived from time-dependent diffusion magnetic resonance imaging (Td-dMRI) for distinguishing hepatocellular carcinoma (HCC) from intrahepatic cholangiocarcinoma (ICC).

[METHODS] We established nude mouse models bearing subcutaneous xenografts of HCC (MHCC97H, HepG2 cell lines) and ICC (QBC939 cell line) (n = 30). All models underwent Td-dMRI scanning. Microstructural parameters, including cell diameter (d), extracellular diffusion coefficient (D), intracellular volume fraction (V), and cellularity, were calculated based on the IMPULSED model. Intergroup differences were assessed using independent samples t-test or Mann-Whitney U test (significance threshold: P < 0.05). The diagnostic performance of each parameter was evaluated by receiver operating characteristic (ROC) curve analysis. Post-operative liver tissue specimens were subjected to β-catenin immunohistochemical staining to validate the correlation between imaging parameters and pathological findings.

[RESULTS] The ICC group exhibited significantly higher D values compared to the HCC group (P < 0.05), whereas d, V, and cellularity were significantly lower in the ICC group (P < 0.05). The areas under the ROC curve (AUCs) for differentiating HCC from ICC were 0.838 for D, 0.779 for d, 0.833 for V, and 0.733 for cellularity. The d value measured by Td-dMRI showed a significant positive correlation with pathological results (r = 0.634, P < 0.05). Notably, combining V and cellularity parameters enhanced the AUC to 0.95, outperforming any single parameter. The ICC group exhibited a significantly higher extracellular diffusivity (D) compared to the HCC group, whereas the cell diameter (d), intracellular volume fraction (V), and cellularity were significantly lower (all P < 0.05). The area under the.

[CONCLUSION] Td-dMRI enables non-invasive differentiation between HCC and ICC by quantifying distinct tumor microstructural environments. The parameters derived from this technique show promise as potential imaging biomarkers for subtyping liver cancers.