Abstract
BACKGROUND: To determine the feasibility of diffusion-relaxation correlation spectroscopic imaging in identifying tumoral differentiation profile and predicting cervical lymph node metastasis (CLNM) in oral tongue squamous cell carcinoma (OTSCC). MATERIALS AND METHODS: This prospective study enrolled fifty-seven OTSCC patients who underwent preoperative head and neck magnetic resonance imaging (MRI). Scans with multi b-values (0-1500 s/mm(2)) and multi-echo times (7-150 ms) were performed to generate normalized diffusion-T2 spectra. Tumor maximal diameter and depth of invasion were measured. Tumors were segmented into five compartments (V(A) to V(E)) with metrics compared across normal controls, CLNM-, and CLNM+ groups. Pathological parameters such as tumor-stroma ratio (TSR), perineural invasion, Ki-67, tumor p53 protein, and cyclin-dependent kinase inhibitor p16 were evaluated. Correlations between MRI metrics and pathological parameters were assessed. Predictors of CLNM+ were identified using logistic regression analysis, and the predictive performance was evaluated using receiver operating characteristic analysis. RESULTS: Thirty-four patients were assigned to the CLNM+ group and 23 to the CLNM- group. CLNM+ patients showed larger tumor maximal diameters, deeper invasion, increased V(B) and V(D), and decreased V(A) compared to CLNM- patients. V(B) exhibited strong positive correlations with perineural invasion and depth of invasion, while V(D) correlated positively with TSR. Moreover, V(B) and depth of invasion were independent prognostic factors for CLNM+, and their combined model achieved the highest predictive performance. CONCLUSION: Diffusion-relaxation correlation spectroscopic imaging marked a significant advancement in the diagnostic and prognostic assessment of OTSCC, offering detailed tumor characterization and improving CLNM+ prediction, with great potential for accurate and non-invasive evaluation. RELEVANCE STATEMENT: Diffusion-relaxation correlation spectroscopic imaging metrics (V(B) and V(D)) characterized tumor heterogeneity and correlated with pathological biomarkers, making it a promising non-invasive tool for enhancing preoperative decisions and reducing unnecessary lymph node dissections in clinical workflows. KEY POINTS: Tumoral components and heterogeneity of oral tongue cancer were investigated on MRI. Advanced diffusion-relaxation imaging delineated the tumoral differential profile and predicted metastasis. We provided a non-invasive tool for preoperative decision-making in clinical workflows.