Predicting Perineural Invasion and Prognosis in Intrahepatic Mass-Forming Cholangiocarcinoma Using DKI and Gadoxetic...

Perineural invasion (PNI) is a critical pathological feature predictive of early recurrence and poor survival in intrahepatic mass-forming cholangiocarcinoma (IMCC), yet it remains undetectable preoperatively. This study aimed to develop a multiparametric MRI-based texture model incorporating diffusion kurtosis imaging (DKI) and gadoxetic acid-enhanced sequences for noninvasive prediction of PNI and stratification of disease-free survival (DFS).

A prospective study was conducted including 99 pathologically confirmed IMCC patients (31 PNI-positive, 68 PNI-negative). All patients underwent 1.5 T MRI with T1-weighted, gadoxetic acid-enhanced (arterial, portal, transitional, hepatobiliary phases), DWI, and DKI sequences. Texture and histogram features were extracted from enhanced phases and parametric maps. A radiomics signature and a clinical-radiomics model were developed using logistic regression. A prognostic index for DFS was constructed using Cox regression.

The radiomics signature combining AP_Contrast and DKI_K_Mean predicted PNI with an AUC of 0.766 (optimism-corrected AUC: 0.757). The clinical-radiomics model incorporating the target sign further improved the AUC to 0.837 (optimism-corrected AUC: 0.819), and decision curve analysis confirmed its clinical net benefit. A prognostic index based on microvascular invasion, TP_E.Kurtosis, and DKI_D_Std stratified DFS with an AUC of 0.742, distinguishing high- and low-risk groups with mean DFS of 10.7 vs 21.6 months (log-rank P = .001).

A multiparametric MRI-based model integrating DKI and gadoxetic acid-enhanced texture features provides a noninvasive tool for preoperative prediction of PNI and DFS stratification in IMCC patients, potentially guiding individualized treatment strategies.