CT Texture Analysis Potentially Predicts Local Failure in Head and Neck Squamous Cell Carcinoma Treated with Chemoradiotherapy
Fellows’ Journal Club
This was a retrospective study including 62 patients diagnosed with primary head and neck squamous cellcarcinoma who underwent contrast-enhanced CT examinations for staging, followed by chemoradiotherapy. CT texture features of thewhole primary tumor were measured using an in-house developed Matlab-based texture analysis program. Histogram, gray-level co-occurrence matrix, gray-level run-length, gray-level gradient matrix, and Laws features were used for texture feature extraction. Three histogram features (geometric mean, harmonic, and fourth moment) and 4 gray-level run-length features (short-run emphasis, gray-level nonuniformity, run-length nonuniformity, and short-run low gray-level emphasis) were significant predictors of outcome.