AUTHOR=Zhang Laizhu , Cheng Chunxiao , Li Binghua , Chen Jun , Peng Jin , Cao Yajuan , Yue Yang , Mai Xiaoli , Yu Decai 

TITLE=Combined clinical features and MRI parameters for the prediction of VEGFR2 in hepatocellular carcinoma patients

JOURNAL=Frontiers in Oncology

VOLUME=Volume 12 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2022.961530

DOI=10.3389/fonc.2022.961530

ISSN=2234-943X

ABSTRACT=Abstract
Purpose To develop a prediction model for estimating the expression of vascular endothelial growth factor receptor 2 (VEGFR2) in hepatocellular carcinoma (HCC) patients using clinical features and the contrast-enhanced MRI Liver Imaging Reporting and Data System (LI-RADS).

Methods A total of 206 HCC patients were subjected to preoperative contrast-enhanced MRI, radical resection, and VEGFR2 immunohistochemistry labeling. The intensity of VEGFR2 expression was used to split patients into either the positive or negative group. For continuous data, the Mann Whitney U test was employed, and for categorical variables, the χ2 test was utilized.

Results VEGFR2 positivity was identified in 41.7% (86/206) of patients. VEGFR2-positive HCCs were confirmed by higher serum alpha-fetoprotein (AFP) levels, larger tumor dimensions on either MRI or upon final pathology, and a higher LI-RADS score (all p < 0.001). The LI-RADS score and AFP were independent predictors for high VEGFR2 expression. These two parameters were used to establish a VEGFR2-positive risk nomogram which was validated as possessing both good discrimination and calibration. The area under the curve was 0.830 (sensitivity 83.6%, specificity 72.5%) and the mean absolute error was 0.021. While the threshold probabilities ranged between 0.07 and 0.95, the model harbored net benefits.

Conclusion A nomogram including clinical features and contrast-enhanced MRI parameters was developed and was demonstrably effective at predicting VEGFR2 expression in HCC patients.