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• Clinical Article •
The study of enhanced MR radiomics combining clinical factors in predicting early recurrence of hepatocellular carcinoma after resection
YANG Haoran  ZHANG Juntao  MA Mimi  ZOU Linxuan  CAO Xinshan 

Cite this article as: Yang HR, Zhang JT, Ma MM, et al. The study of enhanced MR radiomics combining clinical factors in predicting early recurrence of hepatocellular carcinoma after resection[J]. Chin J Magn Reson Imaging, 2022, 13(4): 49-55. DOI:10.12015/issn.1674-8034.2022.04.009.


[Abstract] Objective To develop and validate a preoperative MRI radiomics model combining clinical factors in predicting early recurrence of hepatocellular carcinoma after surgical resection.Materials and Methods One hundred and sixteen patients (82 in the training set and 34 in the test set), who had been pathologically diagnosed as hepatocellular carcinoma (HCC) with preoperative abdominal dynamic contrast-enhancement magnetic resonance imaging (DCE-MRI) and relevant clinical factors, were recruited in this retrospective study. The 3D slicer software was used to delineate the ROI of lesions and extract the radiomics features. The radiomics score model was established by utilizing the maximum correlation-minimum redundancy algorithm (mRMR), minimum absolute contraction and selection operator (LASSO) feature selection procedure, Similarly, the clinical factors were introduced to build the Logistic regression model. The area under the receiver operating characteristic curve (AUC), Delong test and decision curve analysis (DCA) were performed to evaluate and compare the accuracy and difference of each radiomics model.Results In all,nine radiomics features were selected to construct the radiomics score model. The clinical factors model, including TNM stage, alpha-fetoprotein level, γ-glutamylaminotransferase, Child-Pugh grade. The radiomics nomogram of integrated the radiomics score and clinical factors demonstrated better discriminative performance (AUC=0.79, 95% CI: 0.63-0.96) than the Clinical factors models (AUC=0.71, 95% CI: 0.52-0.90),Delong test Z=2.363,P=0.018. The decision curve analysis presented the improved clinical net benefit.Conclusion The combined model based on preoperative MR radiomics and clinical factors can be served as effective imaging biomarker to predict early recurrence of hepatocellular carcinoma after surgical resection.
[Keywords] radiomics；magnetic resonance imaging；hepatocellular carcinoma；prognosis prediction

YANG Haoran1   ZHANG Juntao2   MA Mimi1   ZOU Linxuan1   CAO Xinshan1*  

1 Department of Radiology, Affiliated Hospital of Binzhou Medical College, Binzhou 256603, China

2 GE Healthcare Precision Health Institution, Shanghai 210000, China

Cao XS, E-mail: byfycxs@126.com

Conflicts of interest   None.

ACKNOWLEDGMENTS Science and Technology Development Plan Project of Shandong Province (No. 2010GSF10265).
Received  2021-12-21
Accepted  2022-03-25
DOI: 10.12015/issn.1674-8034.2022.04.009
Cite this article as: Yang HR, Zhang JT, Ma MM, et al. The study of enhanced MR radiomics combining clinical factors in predicting early recurrence of hepatocellular carcinoma after resection[J]. Chin J Magn Reson Imaging, 2022, 13(4): 49-55. DOI:10.12015/issn.1674-8034.2022.04.009.

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