FIG 2.

Statistically significant associations between radiomic features and (A) transcriptional activity of cancer-related genetic pathways, (B) gene copy number variations (CNVs) of cancer-related genetic pathways, and (C) gene promoter region DNA methylation changes of cancer-related genetic pathways. In each heat map, only genetic pathways and radiomic features with statistically significant associations are shown. Each of the gray-level cooccurrence matrix features can be calculated using different offset parameter values (ie, 1, 2, 3, 4, and 5), which results in five different instances of a feature. Because the five instances of a feature were usually correlated, the directions (ie, positive or negative) of the associations between a cancer-related pathway and the different instances of a radiomic feature were always the same. Thus, in the heat maps, associations between different instances of a radiomic feature and a pathway could be collapsed into one association. If a pathway had an association with at least one instance of a radiomic feature, the association between the pathway and the radiomic feature was included in the heat map. Percentile and quantile radiomic features from the intensity direct category were not included in the heat maps for simplicity, because they had many instances with different percentile or quantile values. 3D, three dimensional; ECM, extracellular matrix; JAK-STAT, Janus kinase–signal transducers and activators of transcription; MAPK, mitogen-activated protein kinase; mTOR, mammalian target of rapamycin; TGF-β, transforming growth factor β; VEGF, vascular endothelial growth factor.