Preoperative Prediction of Neck Lymph Node Metastasis in Oral Squamous Cell Carcinoma Using 18 F-FDG PET/CT-based Radiomics Analysis

Background Preoperative knowledge of neck lymph node metastasis (LNM) of oral squamous cell carcinoma (OSCC) can provide valuable information for determining the necessity of adjuvant treatment and the adequacy of surgical resection, thereby facilitating pretreatment decision-making. Therefore, this study aimed to create and evaluate an ¹⁸ F-FDG PET/CT radiomics model for the preoperative prediction of neck LNM in patients with OSCC. Results This retrospective study enrolled 174 OSCC patients who underwent 18F-FDG PET/CT scans before surgery and were randomly allocated to training and test sets. The research process involved lesion segmentation, feature extraction, model construction and evaluation. The radiomics signature, comprising five selected features, significantly correlated with LNM (p < 0.001 for both training and test sets). The radiomics model outperformed the clinical model in distinguishing LNM, with AUCs (area under the receiver operating characteristic (ROC) curves) of 0.928 and 0.890 in the training and test sets, respectively, compared to 0.863 and 0.853 for the clinical model. The integrated model based on clinical factors and the radiomics signature improved AUCs to 0.937 (95%CI: 0.902, 0.966) in the training set and 0.903 (95%CI: 0.825, 0.966) in the test set, showing superior LNM prediction. The nomogram exhibited satisfactory discrimination and good calibration, and decision curve analysis confirmed its clinical value. Conclusion ¹⁸ F-FDG PET/CT-based radiomics demonstrated significant preoperative predictive power of neck LNM in OSCC patients, providing valuable insights for pretreatment management.