Preoperative MRI prediction and molecular pathway study of perineural invasion in intrahepatic cholangiocarcinoma: Insights from bioinformatics approach.

INTRODUCTION

Perineural invasion (PNI) is a significant factor associated with tumor recurrence and metastasis in intrahepatic cholangiocarcinoma (ICC). This study aims to develop predictive model for PNI in ICC using preoperative MRI features and explore its molecular basis.

MATERIALS AND

METHODS

We analyzed 165 ICC patients from two centers, dividing them into training (n = 120), internal validation (n = 24), and external validation (n = 21) cohorts. Clinical and MRI features associated with PNI were used to construct predictive models. The molecular mechanisms underlying PNI were analyzed using data from The Cancer Genome Atlas (TCGA) and were further validated with a subset of the training cohort.

RESULTS

The study identified high CEA level, tumor morphology, location, intrahepatic bile duct dilatation, and tumor invasion into the portal vein as independent predictors of PNI. The clinical-radiological model showed an AUC of 0.839 in the training set, with AUCs of 0.754 and 0.872 in the internal and external validation cohorts, respectively. The COL1A1 gene was found to exhibit up-regulation in the PNI-positive group and was closely linked to poorer overall survival (OS). The arterial-phase enhancement pattern, tumor location, and tumor invasion into portal vein were significantly correlated with COL1A1 expression.

CONCLUSIONS

This preoperative clinical-radiological model effectively predicts PNI in ICC, thereby aiding in the clinical management and prognosis stratification for patients. COL1A1 may serve as a significant biomarker for the development of PNI in ICC, which was significantly correlated with MRI features.