Tumor heterogeneity in oral and oropharyngeal squamous cell carcinoma assessed by texture analysis of CT and conventional MRI: a potential marker of overall survival

Abstract

Background

The combined prognostic value of texture analysis on computed tomography (CT) and conventional magnetic resonance imaging (MRI) in oral and oropharyngeal squamous cell carcinoma (OOSCC) has rarely been reported.

Purpose

To evaluate the ability of texture-based heterogeneity indices extracted from CT and conventional MRI to predict the overall survival (OS) of OOSCC patients.

Material and Methods

Eighty-eight patients with OOSCC underwent contrast-enhanced CT, and T2-weighted (T2W) and contrast-enhanced T1-weighted (T1W) imaging. For each imaging protocol, four histogram (HISTO) and six gray-level co-occurrence matrix (GLCM) parameters were extracted. Intraclass correlation coefficients (ICCs) were used to evaluate variation in inter-observer delineation. The association of clinicopathologic factors and texture parameters with OS was analyzed using log-rank testing and Cox regression. The Harrell Concordance Index (C-index) was used to evaluate the prognostic performance of the predictors and Cox model.

Results

Higher inter-observer delineation agreement of texture analysis on contrast-enhanced T1W imaging was observed relative to that on CT and T2W imaging. T stage (P = 0.026, hazard ratio [HR] = 2.35), GLCM_Entropy on CT (P = 0.003, HR = 3.15), and HISTO_Energy (P = 0.036, HR = 0.27) and HISTO_Skewness (P = 0.026, HR = 0.41) on contrast-enhanced T1W imaging were independent predictors for the OS of OOSCC patients. The multivariate Cox model performed strongly in predicting OS, with a significantly higher C-index than the independent predictors separately (C-index: 0.751 vs. 0.600–0.627, P < 0.005 for all).

Conclusion

Texture analysis using CT and conventional MRI could provide a valuable method for survival stratification of OOSCC patients.

Keywords

Head and neck cancer heterogeneity computed tomography magnetic resonance imaging prognosis texture analysis

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