Imaging Biomarkers of CT Textural Analysis Correlate to Genomic Expression in Oral Cavity Squamous Cell Carcinoma
D Fried*, C Pickering, A Rao, L Hunter, K Shah, S Ahmed, M Frederick, J Zhang, A Unruh, J Wang, L Ginsberg, A Kumar, J Myers, L Court, J Hamilton, UT MD Anderson Cancer Center, Houston, TXSU-E-CAMPUS-I-6 Sunday 3:00PM - 6:00PM Room: Exhibit Hall
Purpose: To determine whether correlations exist between CT-generated texture features and genetic biomarkers in oral cavity squamous cell carcinoma (OCSCC).
Methods: We retrospectively analyzed 27 OCSCC patients with surplus frozen tissue and preoperative CT for genetic expression of vascular endothelial growth factor (VEGF) ligands A B, and C, VEGF receptors 1, 2, and 3, Cyclin D1 protein, and epidermal growth factor receptor (EGFR). Each tumor was segmented, blinded to the results of the gene expression analysis, on their preoperative CT and was modified into a 6-bit grayscale image prior to texture feature extraction. Seven calculated texture features were computed based on intensity histograms (IHIST) and co-occurrence matrices (COM). Pearson correlation coefficients (PC) were calculated between texture features and genetic expression. A sub-group analysis (n = 17) was performed excluding patients that had a CT slice thickness greater than 1mm.
Results: Correlations were found between IHIST-kurtosis and VEGF-receptor1 (PC = 0.42,
p = 0.03) as well as between IHIST-mean and COM-correlation with VEGF-receptor 1 (PC = 0.40, p = 0.04 and -0.39, p = 0.04, respectively). In the subset analysis with more controlled preoperative CT scans, the correlation between IHIST-kurtosis and VEGF-receptor1 remained (PC = 0.54, p = 0.03) while the correlations with VEGF-receptor 1 did not. Additionally, IHIST-entropy was found to correlate with VEGF ligand A (PC = -0.51, p = 0.04). This correlation is arguably the most useful as an established chemotherapy agent exists for VEGFA (bevacizumab). However, no correlations survived a Bonferroni correction for multiple hypothesis testing in the initial or subset analyses.
Conclusion: This study provides some preliminary data indicating that CT-based texture features may be correlated with genetic expression in OCSCC. In future studies, a larger sample size and more focused hypothesis of texture correlations with specific genetic targets should be implemented.