This study explores the efficacy of texture analysis by using preoperative multi-slice spiral computed tomography (MSCT) to non-invasively determine the grade of cellular differentiation in head and neck squamous cell carcinoma (HNSCC). In a retrospective study, MSCT scans of patients with HNSCC were analyzed and classified based on its histological grade as moderately differentiated, well-differentiated, or poorly differentiated. The location of the tumor was categorized as either in the bone or in soft tissues. Segmentation of the lesion areas was conducted, followed by texture analysis. Eleven GLCM parameters across five different distances were calculated. Median values and correlations of texture parameters were examined in relation to tumor differentiation grade by using Spearman’s correlation coefficient and Kruskal–Wallis and Dunn tests. Forty-six patients were included, predominantly female (87%), with a mean age of 66.7 years. Texture analysis revealed significant parameter correlations with histopathological grades of tumor differentiation. The study identified no significant age correlation with tumor differentiation, which underscores the potential of texture analysis as an age-independent biomarker. The strong correlations between texture parameters and histopathological grades support the integration of this technique into the clinical decision-making process.

Background: Texture analysis (TA) has shown promise in characterizing intratumoral heterogeneity from imaging data. We add to the literature that shows its capability to differentiate oropharyngeal cancers based on HPV status. Methods: Multislice CT analysis was done in 120 patients with confirmed OP SCC: a single 5 mm region of interest was placed on three consecutive homogeneous CT slices per patient. Texture features were extracted by using gray-level co-occurrence matrices averaged per patient. HPV status (via p16 IHC and molecular confirmation) and differentiation grade (i.e., good, moderate, and poor) were recorded. Non-parametric statistical tests assessed differences between subgroups. Results: Seven texture parameters (i.e., angular second moment, contrast, sum of squares, sum entropy, entropy, inverse difference moment, and difference variance) differed significantly between HPV+ and HPV− tumors (all p < 0.05). HPV+ tumors exhibited increased heterogeneity and complexity on CT imaging. No texture feature correlated with histological grade. Conclusions: This study adds to the growing evidence that CT-based TA can assess HPV status in OP SCC. TA may be promising, though it requires further validation as an adjunctive method integrating into radiomics workflows to develop predictive models for diagnosis, prognosis, and treatment planning.