Baseline Computed Tomography Radiomic and Genomic Assessment of Head and Neck Squamous Cell Carcinoma.

Abstract

To determine the relationship between computed tomography (CT) radiomic features and gene expression levels in head and neck squamous cell carcinoma (HNSCC). This retrospective study included 66 patients with HNSCC primary lesions (36 oropharyngeal, 6 hypopharyngeal, 10 laryngeal, 14 oral cavity). Gene expression information for 6 targetable genes (fibroblast growth factor receptor [FGFR]1, epidermal growth factor receptor [EGFR], FGFR2, FGFR3, EPHA2, PIK3CA) was obtained via Agilent microarrays from samples collected between 1997 and 2010. Pretreatment contrast-enhanced soft tissue neck CT scans were reviewed, and 142 radiomics features were derived. R was used to calculate Pearson correlation coefficients were calculated between gene expression levels and each radiomic feature. P values were adjusted using the false discovery rate (FDR) method. There were significant correlations between FGFR1 and 5 gray level cooccurrence matrix (GLCM) features with FDR-adjusted P values less than 0.05: inertia (r = 0.366, FDR-adjusted P = 0.006), absolute value (r = 0.31, FDR-adjusted P = 0.024), contrast (r = 0.366, FDR-adjusted P = 0.006), difference average (r = 0.31, FDR-adjusted P = 0.024), and difference variance (r = 0.37, FDR-adjusted P = 0.005). There was 1 correlated feature for FGFR2 with an FDR-adjusted P value less than 0.05: fractal dimension box-coarse (r = 0.33, FDR-adjusted P = 0.018). There was 1 correlated feature for EPHA2 with an FDR-adjusted P value less than 0.05: GLCM entropy (r = -0.28, FDR-adjusted P = 0.049). Six of the 7 features that showed significant correlation belonged to the GLCM class of features. The CT radiomic features demonstrate correlations with FGFR1 status in HNSCC and should be further investigated for their potential to predict FGFR1 status.