Figure 2.

Workflow of the necessary steps in this study. Regions of interest (ROIs) in the portal venous phase (PVP). CT images were segmented with a three-dimensional, semi-automatic segmentation method by two radiologists. Radiomics features were extracted from the defined ROI to quantify tumor intensity, shape and texture. Two semantic features (“micro-satellite” and the presence of metastatic lesions other than the liver and regional lymph nodes) were assessed by two radiologists. We constructed the semantic, radiomics and combined scores using seven machine learning algorithms. Three scores using the artificial neural network (ANN) method showed the best predictive performance based on semantic, radiomics and combined features. The performances of the three constructed scores were evaluated by the area under a receiver operating characteristic (ROC) curves followed by decision curve analysis.