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• Clinical Article •
Predicting microvascular invasion of hepatocellular carcinoma based on non-contrast-enhanced MRI radiomics signature
DUAN Yayang  ZHOU Kunpeng  BIAN Jie  LI Siyao 

Cite this article as: Duan YY, Zhou KP, Bian J, et al. Predicting microvascular invasion of hepatocellular carcinoma based on non-contrast-enhanced MRI radiomics signature. Chin J Magn Reson Imaging, 2020, 11(3): 195-200. DOI:10.12015/issn.1674-8034.2020.03.007.


[Abstract] Objective: Magnetic resonance imaging (MRI)-based radiomics signatures was conducted to predict microvascular invasion (MVI) of hepatocellular carcinoma (HCC) preoperatively.Materials and Methods: One hundred and twenty-nine HCC patients who had undergone MRI examination on 3.0 T MRI were recruited. Radiomics features were extracted from fat-suppressed T2-weighted (T2WI-FS) imaging and apparent diffusion coefficient (ADC) map. We used the Variance Threshold, SelectKBest, and least absolute shrinkage and selection operator (LASSO) algorithms in order to perform dimensionality reduction. Then random forests (RF), k-nearest neighbor (KNN), extreme gradient boosting (XGBoost), logistic regression (LR), decision tree (DT) and support vector machine (SVM) algorithm were trained to separate the HCC with MVI positive and with MVI negative. The performance of each model built by the classifier was evaluated by AUC and accuracy.Results: Quantitative imaging features (n=1409) were extracted from T2WI-FS and ADC map respectively. Finally, 12 features of T2WI-FS and 8 features of ADC were selected to construct the radiomics model separately. The model that used SVM classification method achieved the best performance among the six methods, with AUC values of 0.87, accuracy of 0.78 based on T2WI-FS, and AUC values of 0.75, accuracy of 0.71 based on ADC.Conclusions: Good accuracy and AUC could be obtained using only 12 radiomic features of T2WI-FS. Therefore, we proposed radiomics features from T2WI-FS could be used as candidate biomarkers for preoperative prediction of MVI of HCC noninvasively.
[Keywords] radiomics；microvascular invasion；hepatocellular carcinoma；magnetic resonance imaging

DUAN Yayang Department of Radiology, The Second Hospital of Dalian Medical University, Dalian 116027, China

ZHOU Kunpeng Department of Radiology, The Second Hospital of Dalian Medical University, Dalian 116027, China

BIAN Jie* Department of Radiology, The Second Hospital of Dalian Medical University, Dalian 116027, China

LI Siyao Dalian Medical University, Dalian 116027, China

*Correspondence to: Bian J, E-mail: drbianjie@163.com

Conflicts of interest   None.

Received  2019-11-19
Accepted  2019-02-14
DOI: 10.12015/issn.1674-8034.2020.03.007
Cite this article as: Duan YY, Zhou KP, Bian J, et al. Predicting microvascular invasion of hepatocellular carcinoma based on non-contrast-enhanced MRI radiomics signature. Chin J Magn Reson Imaging, 2020, 11(3): 195-200. DOI:10.12015/issn.1674-8034.2020.03.007.

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