Can MR textural analysis improve the prediction of extracapsular nodal spread in patients with oral cavity cancer?

Objective: To explore the utility of MR texture analysis (MRTA) for detection of nodal extracapsular spread (ECS) in oral cavity squamous cell carcinoma (SCC).

Methods: 115 patients with oral cavity SCC treated with surgery and adjuvant (chemo)radiotherapy were identified retrospectively. First-order texture parameters (entropy, skewness and kurtosis) were extracted from tumour and nodal regions of interest (ROIs) using proprietary software (TexRAD). Nodal MR features associated with ECS (flare sign, irregular capsular contour; local infiltration; nodal necrosis) were reviewed and agreed in consensus by two experienced radiologists. Diagnostic performance characteristics of MR features of ECS were compared with primary tumour and nodal MRTA prediction using histology as the gold standard. Receiver operating characteristic (ROC) and regression analyses were also performed.

Results: Nodal entropy derived from contrast-enhanced T1-weighted images was significant in predicting ECS (p = 0.018). MR features had varying accuracy: flare sign (70%); irregular contour (71%); local infiltration (66%); and nodal necrosis (64%). Nodal entropy combined with irregular contour was the best predictor of ECS (p = 0.004, accuracy 79%).

Conclusion: First-order nodal MRTA combined with imaging features may improve ECS prediction in oral cavity SCC.

Key Points: • Nodal MR textural analysis can aid in predicting extracapsular spread (ECS). • Medium filter contrast-enhanced T1 nodal entropy was strongly significant in predicting ECS. • Combining nodal entropy with irregular nodal contour improves predictive accuracy.