Emerging applications of radiomics in rectal cancer: State of the art and future perspectives

Table 1 Commonly-used radiomics feature categories according to “order”

“Order”	Paraphrase	Categories	Description
First-order	Based on an intensity histogram of pixel values, providing no information on neighboring interactions or the spatial distribution	Mean	Average intensity of the pixels
		Skewness	Asymmetry of histogram
		Kurtosis	Magnitude of pixel distribution
		Entropy	Irregularity of the structure
Second-order	Considers the spatial relationship between 2 pixels	Grey level co-occurrence matrix (GLCM)	Frequency of specific gray values along a distance or direction
		Grey level run Length Matrix (GLRLM)	Length of consecutive pixels or voxels with the same grey values in a specific direction
		Grey level size zone matrix (GLSZM)	Length of consecutive pixels or voxels with the same grey values in all directions
Superior-order	Describes the neighborhood gray difference matrices and the relationship between 3 or more pixels	Neighboring gray tone difference matrix (NGTDM)	Describes the sum and average grey levels of discretized voxels in planes
		Gray level dependence matrix (GLDM)	Describes the coarseness of overall texture by evaluating the grey levels between a voxel and the neighborhood in 3 dimensions

In reference to “order”, it is defined as the number of stages required to obtain the quantitative information in a model.