AUTHOR=Zhang Linqi , Kuang Sichi , Chen Jingbiao , Zhang Yao , Zhao Binliang , Peng Hao , Xiao Yuanqiang , Fowler Kathryn , Wang Jin , Sirlin Claude B.
TITLE=The Role of Preoperative Dynamic Contrast-enhanced 3.0-T MR Imaging in Predicting Early Recurrence in Patients With Early-Stage Hepatocellular Carcinomas After Curative Resection
JOURNAL=Frontiers in Oncology
VOLUME=9
YEAR=2019
URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2019.01336
DOI=10.3389/fonc.2019.01336
ISSN=2234-943X
ABSTRACT=Objectives: Liver resection is potentially curative for early-stage hepatocellular carcinoma (eHCC) in patients with well-preserved liver function. The prognosis of these patients after resection is still unsatisfactory because of frequent early recurrence (ER). Therefore, we investigated the role of preoperative dynamic contrast-enhanced 3.0-T MR imaging in predicting ER of eHCC after curative resection.
Methods From May 2014 to October 2017, we retrospectively analyzed 82 patients with eHCC who underwent dynamic MR imaging and subsequently underwent curative resection. Liver Imaging Reporting and Data System (LI-RADS) v2018 major and ancillary imaging features, as well as two non-LI-RADS MR imaging features (irregular tumor margin and tumor number), were evaluated. A multivariate Cox regression analysis was used to identify independent predictors, and two models (preoperative and postoperative prediction models) were developed.
Results ER was observed in 25 patients (25/82, 30.5%). In the univariate analyses, preoperative alpha-fetoprotein (AFP) level >200 ng/ml, three MR imaging features (multifocal tumors, corona enhancement, and irregular tumor margin), and microvascular invasion (MVI) were associated with ER. In the multivariate analysis, corona enhancement (hazard ratio [HR]: 2.970; p = 0.013) and irregular tumor margin (HR: 2.377; p = 0.048) were independent predictors in the preoperative prediction model, and preoperative AFP level >200 ng/ml (HR: 2.493; p = 0.044) plus corona enhancement (HR: 3.046; p = 0.014) were independent predictors in the postoperative prediction model (microvascular invasion [MVI] was not; p = 0.061). When combined with both predictors, the specificity for ER in the preoperative prediction model was 98.2% (56/57), which was comparable to that of the postoperative prediction model [96.7% (55/57)].
Conclusions Our results demonstrated that preoperative MR imaging features (corona enhancement and irregular tumor margin) have the potential to preoperatively identify high-risk ER patients with eHCC, with a specificity >90%.