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Enhanced Diagnostic Precision: Assessing Tumor Differentiation in Head and Neck Squamous Cell Carcinoma Using
Lays Assolini Pinheiro de Oliveira1,2, Diana Lorena Garcia Lopes2, João Pedro Perez Gomes3
1Department of Anesthesiology, Oncology and Radiology, Faculty of Medical Sciences, University of Campinas (UNICAMP), Campinas 13084-971, SP, Brazil.
Texture analysis of multi-slice spiral computed tomography (MSCT) scans can non-invasively determine head and neck squamous cell carcinoma (HNSCC) differentiation. This age-independent imaging biomarker shows strong correlations with histopathological grades, aiding clinical decisions.
Area of Science:
- Oncology
- Radiology
- Medical Imaging
Background:
- Head and neck squamous cell carcinoma (HNSCC) grading is crucial for treatment planning.
- Accurate non-invasive grading of HNSCC remains a clinical challenge.
Purpose of the Study:
- To evaluate the efficacy of preoperative multi-slice spiral computed tomography (MSCT) texture analysis for determining HNSCC differentiation grade.
- To assess texture analysis as a potential age-independent biomarker for HNSCC.
Main Methods:
- Retrospective analysis of MSCT scans from 46 HNSCC patients.
- Segmentation of tumor areas and calculation of eleven GLCM texture parameters across five distances.
- Statistical analysis using Spearman's correlation, Kruskal-Wallis, and Dunn tests to correlate texture parameters with histopathological grades.
Main Results:
- Texture analysis demonstrated significant correlations between parameters and HNSCC histopathological differentiation grades.
- No significant correlation was found between patient age and tumor differentiation grade.
- Identified texture parameters as potential non-invasive biomarkers for HNSCC grading.
Conclusions:
- Preoperative MSCT texture analysis is a promising non-invasive method for assessing HNSCC cellular differentiation.
- Texture analysis can serve as an age-independent biomarker, supporting clinical decision-making in HNSCC management.
