Contrast-enhanced MRI could predict response of systemic therapy in advanced intrahepatic cholangiocarcinoma

To investigate whether pre-treatment contrast-enhanced MRI could predict the therapeutic response of systemic treatment in advanced intrahepatic cholangiocarcinoma (ICC). This retrospective study enrolled 61 ICC participants with contrast-enhanced MRI before combined systemic therapy. Clinical characteristics and MRI features were compared between patients with and without therapeutic response by univariate and multivariate logistic regression analyses. Then, a combined MRI-based model and the nomogram were established based on the results of the multivariate analysis. The diagnostic performances of significant findings and the combined model were evaluated and compared. The progression-free survival (PFS) rates between patients with high and low combined index values were compared. Thirty (49.18%) patients showed overall response after therapy. In multivariate analysis, tumor margin (odds ratio (OR) = 5.004, p = 0.014), T2 homogeneity (OR = 14.93, p = 0.019), and arterial peritumoral enhancement (OR = 5.076, p = 0.042) were independent predictive factors associated with therapeutic response. The C-index with the formulated nomogram incorporating the three independent imaging features was 0.828 (95% CI 0.710-0.913). Diagnostic characteristics of the combined index were superior to any single feature alone (p = 0.0007-0.0141). ICCs with high combined index values showed higher PFS rates than those with low values (χ${}^2$ = 13.306, p < 0.0001). Pre-treatment contrast-enhanced MRI can be used to predict therapeutic response in advanced ICC with systemic therapy. The combination model incorporating significant MRI features achieved an improved predictive value, which may play an important role in identifying appropriate therapeutic candidates. Contrast-enhanced MRI can predict response of systemic therapy in advanced ICC. MRI features of tumor margin, T2 homogeneity, and arterial peritumoral enhancement are related to therapeutic response. The combined MRI-based model may help to identify appropriate therapeutic candidates.