Journal of Hepatocellular Carcinoma (Jul 2021)

Preoperative Prediction of Cytokeratin 19 Expression for Hepatocellular Carcinoma with Deep Learning Radiomics Based on Gadoxetic Acid-Enhanced Magnetic Resonance Imaging

  • Chen Y,
  • Chen J,
  • Zhang Y,
  • Lin Z,
  • Wang M,
  • Huang L,
  • Huang M,
  • Tang M,
  • Zhou X,
  • Peng Z,
  • Huang B,
  • Feng ST

Journal volume & issue
Vol. Volume 8
pp. 795 – 808

Abstract

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Yuying Chen,1,* Jia Chen,2,* Yu Zhang,3,* Zhi Lin,1 Meng Wang,1 Lifei Huang,2 Mengqi Huang,1 Mimi Tang,1 Xiaoqi Zhou,1 Zhenpeng Peng,1 Bingsheng Huang,2 Shi-Ting Feng1 1Department of Radiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, People’s Republic of China; 2Medical AI Lab, School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, Guangdong, People’s Republic of China; 3Department of Pathology, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, People’s Republic of China*These authors contributed equally to this workCorrespondence: Bingsheng HuangMedical AI Lab, School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, Guangdong, People’s Republic of ChinaTel +86 755-86172208Fax +86 755-86171820Email [email protected] FengDepartment of Radiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, People’s Republic of ChinaTel +86 20-87755766 Ext 8471Fax +86 20-87615805Email [email protected]: Cytokeratin 19 (CK19) expression is a proven independent prognostic predictor of hepatocellular carcinoma (HCC). This study aimed to develop and validate the performance of a deep learning radiomics (DLR) model for CK19 identification in HCC based on preoperative gadoxetic acid-enhanced magnetic resonance imaging (MRI).Patients and Methods: A total of 141 surgically confirmed HCCs with preoperative gadoxetic acid-enhanced MRI from two institutions were included. Prediction models were established based on hepatobiliary phase (HBP) images using a training set (n=102) and validated using time-independent (n=19) and external (n=20) test sets. A receiver operating characteristic curve was used to evaluate the performance for CK19 prediction. Recurrence-free survival (RFS) was also analyzed by incorporating the CK19 expression and other factors.Results: For predicting CK19 expression, the area under the curve (AUC) of the DLR model was 0.820 (95% confidence interval [CI]: 0.732– 0.907, P< 0.001) with sensitivity, specificity, accuracy of 0.800, 0.766, and 0.775, respectively, and reached 0.781 in the external test set. Combined with alpha fetoprotein, the AUC increased to 0.833 (95% CI: 0.753– 0.912, P

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