Frontiers in Oncology (Oct 2022)

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

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

DOI
https://doi.org/10.3389/fonc.2022.961530
Journal volume & issue
Vol. 12

Abstract

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PurposeTo 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).MethodsA 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 group or the negative group. For continuous data, the Mann-Whitney U test was employed, and for categorical variables, the χ2 test was utilized.ResultsVEGFR2-positivity was identified in 41.7% (86/206) of the patients. VEGFR2-positive HCCs were confirmed by higher serum alpha-fetoprotein (AFP) levels, larger tumor dimensions (either on MRI or upon final pathology), and a higher LI-RADS score (all p < 0.001). LI-RADS scores and AFP levels were independent predictors for high VEGFR2 expression. These two parameters were used to establish a VEGFR2-positive risk nomogram, which was validated to possess 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. The threshold probabilities ranged between 0.07 and 0.95, and usage of the model contributed net benefits.ConclusionA nomogram including clinical features and contrast-enhanced MRI parameters was developed and was demonstrably effective at predicting VEGFR2 expression in HCC patients.

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