Ultrasound-Based Radiomic Nomogram for Predicting Lateral Cervical Lymph Node Metastasis in Papillary Thyroid Carcinoma

Rationale and Objectives Accurate preoperative identification of lateral cervical lymph node metastasis (LNM) is important for decision-making and clinical management of patients with papillary thyroid carcinoma (PTC). The aim of this study was to develop an ultrasound (US)-based radiomic nomogram to preoperatively predict the lateral LNM in PTC patients. Methods In this retrospective study, a total of 886 patients were enrolled and randomly divided into 2 groups. Radiomic features were extracted from the preoperative US images. A radiomic signature was constructed using the least absolute shrinkage and selection operator algorithm in the training set. Multivariate logistic regression was performed to develop the radiomic nomogram, which incorporating the radiomic signature and the selected clinical characteristics. The performance of the nomogram was assessed by its discrimination, calibration, and clinical usefulness in both the training and validation sets. Results The radiomic signature was significantly associated with the lateral LNM in both cohorts (p Conclusion The radiomic nomogram proposed here has good performance for noninvasively predicting the lateral LNM and might be used to facilitate clinical decision-making and potentially improve the survival outcome in selected patients.