Impact of radiogenomics in esophageal cancer on clinical outcomes: A pilot study

Figure 1 Flowchart reporting the organization of data and analyses in the study. BMI: Body mass index; CT: Computed tomography; TCGA: The Cancer Genome Atlas; TCIA: The Cancer Imaging Archive.

Figure 2 Workflow of radiogenomic analysis implemented in the study. On the first row the radiomic analysis steps. On the second row the radiogenomic analysis for each clinical outcome. BMI: Body mass index; miRNA: MicroRNA; mRNA: Messenger RNA.

Figure 3 Radiogenomic analysis using stage as clinical outcome. Heatmap depicting the correlation matrix between transcriptomic features and radiomic features significantly associated with stage. GLCM: Gray level co-occurrence matrix; GLDM: Gray level dependence matrix; GLRLM: Gray level run length matrix; GLSZM: Gray level size zone matrix; H: High-pass filter; L: Low-pass filter; NGTDM: Neighboring gray tone difference matrix.

Figure 4 Radiogenomic analysis using alcohol history as clinical outcome. Heatmap depicting the correlation matrix between transcriptomic features and radiomic features significantly associated with alcohol history. H: High-pass filter; L: Low-pass filter; miRNA: MicroRNA.

Figure 5 Radiogenomic analysis using body mass index as clinical outcome. Heatmap depicting the correlation matrix between transcriptomic features and radiomic features significantly associated with body mass index. GLCM: Gray level co-occurrence matrix; GLDM: Gray level dependence matrix; GLRLM: Gray level run length matrix; GLSZM: Gray level size zone matrix; H: High-pass filter; L: Low-pass filter; miRNA: MicroRNA; mRNA: Messenger RNA; NGTDM: Neighboring gray tone difference matrix.