Abstract
Management of thyroid nodules with atypia of undetermined significance/follicular lesion of undetermined significance (AUS/FLUS) cytology is challenging because of uncertain malignancy risk. Intraoperative frozen section pathology provides real-time diagnosis for AUS/FLUS nodules undergoing surgery, but its accuracy is limited. This study aimed to develop an integrated predictive model combining clinical, ultrasound and IOFS features to improve intraoperative malignancy risk assessment. A retrospective cohort study was conducted on patients with AUS/FLUS cytology and negative BRAF(V600E) mutation who underwent thyroid surgery. The cohort was randomly divided into training and validation sets. Clinical, ultrasound, and pathological features were extracted for analysis. Three models were developed: an IOFS model with IOFS results as sole predictor, a clinical model integrating clinical and ultrasound features, and an integrated model combining all features. Model performance was evaluated using comprehensive metrics in both sets. The superior model was visualized as a nomogram. Among 531 included patients, the integrated model demonstrated superior diagnostic ability, predictive performance, calibration, and clinical utility compared to other models. It exhibited AUC values of 0.92 in the training set and 0.95 in the validation set. The nomogram provides a practical tool for estimating malignancy probability intraoperatively. This study developed an innovative integrated predictive model for intraoperative malignancy risk assessment of AUS/FLUS nodules. By combining clinical, ultrasound, and IOFS features, the model enhances IOFS diagnostic sensitivity, providing a reliable decision-support tool for optimizing surgical strategies.