AI-Powered MRI Analysis for Early Detection and Staging of Oral Cancer: A Pilot Diagnostic Study

This pilot diagnostic study rigorously evaluates the efficacy of advanced, powered MRI—specifically multiparametric protocols incorporating Diffusion-Weighted Imaging (DWI) and Dynamic Contrast-Enhanced (DCE-MRI) sequences—for the early detection and precise staging of oral squamous cell carcinoma (OSCC). The research demonstrates that quantitative biomarkers derived from these sequences, such as Apparent Diffusion Coefficient (ADC) and pharmacokinetic parameters, provide high diagnostic accuracy in differentiating early-stage (T1/T2) tumors from benign lesions and normal tissue. Furthermore, the findings indicate that this non-invasive approach significantly improves the assessment of key prognostic features, including tumor depth of invasion (DOI), perineural spread, and bone marrow involvement, thereby offering a powerful tool to complement clinical examination and guide subsequent treatment planning for improved patient outcomes.