MRI features predict microvascular invasion in intrahepatic cholangiocarcinoma

Abstract Background The presence of microvascular invasion (MVI) in intrahepatic cholangiocarcinoma (ICC) is a significant adverse prognostic factor. This study sought to investigate the correlation between preoperative imaging parameters and MVI in ICC. Methods A total of 108 patients with surgically resected single ICC tumors (34 MVI-positive and 74 MVI-negative lesions) who underwent MRI examination, including T1WI, T2WI, DWI, and dynamic enhancement imaging, were enrolled in this retrospective study. The following qualitative and quantitative characteristics were evaluated: tumor morphology, signal features on T1WI and T2WI, intrahepatic duct dilatation, hepatic capsule retraction, target sign on DWI, dynamic enhancement pattern, arterial phase enhancement pattern, dot−/band-like enhancement inside the tumor, visible vessel penetration inside the tumor (hepatic artery, portal vein, or hepatic vein), integrity of the enhancement edge of the arterial phase, peripheral hepatic enhancement, tumor size, maximum enhancement edge thickness, arterial edge enhancement ratio, and delayed phase enhancement ratio. Other clinicopathological features were also used to predict and evaluate MVI in ICC. Chi-square test, Fisher’s exact test, and independent t-test were used for univariate analysis to determine the relationships among the presence of MVI and these MR parameters. Logistic regression analysis was used to identify predictors of MVI among these MR parameters. Results Among MRI characteristics, tumor morphology, intrahepatic duct dilatation, arterial phase enhancement pattern, visible hepatic artery penetration sign, maximum diameter of the tumor and the arterial phase edge enhancement ratio were correlated with MVI (P = 0.007, 0.003, 0.008, 0.000, 0.003, and 0.002, respectively). Furthermore, higher CA19–9 levels (≥37 U/ml) and pathological tumor grade III were also related to MVI (P = 0.014 and 0.004, respectively). However, multivariate logistic regression analysis demonstrated that none of the parameters were independent risk factors for the diagnosis of MVI in ICCs. Conclusion For the preoperative prediction of MVI in ICC, six qualitative and quantitative data obtained on preoperative MRI, as well as one tumorigenic marker and the pathological tumor grade, were statistically significant. More research is needed to identify MR characteristics that can be used as independent risk factors.