CT Texture Analysis-Correlations With Histopathology Parameters in Head and Neck Squamous Cell Carcinomas

Area of Science:

• Radiology
• Oncology
• Medical Imaging Analysis

Background:

• Texture analysis is an emerging imaging technique for quantifying heterogeneity in radiological images.
• Its capability to reflect tumor microstructure, particularly in head and neck squamous cell carcinomas (HNSCC), remains unclear.
• Understanding tumor microstructure is crucial for accurate diagnosis and treatment planning.

Purpose of the Study:

• To correlate histopathology parameters with texture features derived from contrast-enhanced CT images in HNSCC.
• To investigate the potential of CT texture analysis in reflecting tumor microstructure and hypoxia.

Main Methods:

• Retrospective analysis of 28 patients with histopathologically proven HNSCC.
• Semiautomatic calculation of EGFR, VEGF, Hif1-alpha, Ki67, and p53 expression from immunohistochemical specimens.
• Texture analysis performed on contrast-enhanced CT images; Spearman's correlation with Benjamini-Hochberg correction.

Main Results:

• Several texture features showed correlation with histopathological parameters.
• After correction, CT texture joint entropy and CT entropy demonstrated a statistically significant correlation with Hif1-alpha expression (ρ = -0.60 and ρ = -0.50, respectively).
• These findings suggest a link between CT texture features and tumor hypoxia.

Conclusions:

• CT texture joint entropy and CT entropy are associated with Hif1-alpha expression in HNSCC.
• These texture features may serve as non-invasive biomarkers to reflect hypoxic areas within HNSCC.
• Further research is warranted to validate these findings and explore their clinical utility.