Mri-based Ki-67 prediction for intrahepatic cholangiocarcinoma: Risk stratification and treatment efficacy prediction
Beixuan Zheng1, Lingsong Zhou2, Kai Liu1
1Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai 200032, China; Shanghai Institute of Medical Imaging, Shanghai 200032, China.
Purpose:
Ki-67 is a marker of tumor aggressiveness and poor prognosis in intrahepatic cholangiocarcinoma (iCCA). This study aimed to develop an MRI-based model to predict Ki-67 expression in iCCA and evaluate its therapeutic benefit from systemic treatment.
Methods:
255 pathologically confirmed iCCA patients who underwent curative surgery (179 training, 76 validation) and 51 advanced iCCA patients receiving combined systemic targeted-immunotherapy were retrospectively included. Clinical and MRI features were compared between Ki-67 status. Univariate and multivariate regression analyses identified independent predictors. Survival analysis was conducted and compared between MRI-predicted high and low Ki-67 groups in patients receiving combined targeted-immunotherapy.
Results:
Patients with high histologic Ki-67 had shorter postoperative recurrence-free survival (median RFS 9.0 vs 16.8 months; P = 0.018). Multivariate analysis revealed that patient gender (odds ratio = 2.31, P = 0.032), T2-weighted central brightness (odds ratio = 3.247, P = 0.003) and tumor apparent diffusion coefficient (ADC) values (odds ratio = 0.996, P < 0.001) were independent predictors of Ki-67 status. The combined predictive model yielded AUCs of 0.789 [95%CI 0.719, 0.859] in the training cohort and 0.753 [95%CI 0.641, 0.845] in the validation cohort. In advanced iCCA patients receiving combined targeted-immunotherapy, MRI-predicted high Ki-67 group had a lower objective response rate (31.8% vs. 62.1%, P = 0.032) and shorter progression-free survival (median 8.0 vs. 16.0 months; P < 0.001) compared to predicted low Ki-67 group.
Conclusions:
The MRI-based model incorporating patient gender, T2-weighted central brightness and tumor ADC values effectively predicts Ki-67 expression in iCCA. This non-invasive biomarker may aid in treatment efficacy prediction and risk stratification for systemic targeted-immunotherapy.
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