Radiomics features extraction

In this study, we used Python language (version 3.7.4) program to call the Pyrometric package (version 2.2.0)^14,15. In the process of program running, seven filters are used to process the original VOI. Seven categories (each category including: 18 features of first-order statistics (FOS), 24 features of gray level co-occurrence matrix (GLCM), 16 features of gray level run matrix (GLRLM), 16 features of gray level size region matrix (GLSZM) and 5 of neighbouring gray tone difference matrix (NGTDM) are extracted from each filtered image There are 1674 texture features. Together with 14 shape features of the original image, 1688 features were extracted for this study. For more information on the methods and parameters of feature extraction in radiomics¹⁶, see Table ​Table22.

The number of Radiomics features of CT images extracted with Pyradiomics2.2.0.

Note: #Category” Shape” features were only extracted from the original image, were not included in the group analysis because of the obvious difference between the study group and the control group;

*Filter “Wavelet” uses 8 levels of LLL, LLH, LHL, LHH, HLL, HHL, HLH, HHH to process images;

*Filter “LocalBinaryPattern3D” uses 3 levels of m1, m2, and k to process images.