Abstract:
Introduction: An ultrasound (US) scoring system was developed by combining seven ultrasonographic descriptors for predicting metastatic lymph nodes (LNs). The aims of this study were (1) to validate the Ultrasound Neck Node Reporting and Data System (UNN-RADS) for suspicious ultrasonographic features of LN metastasis in patients undergoing thyroid cancer follow-up and (2) to evaluate the interobserver agreement. Materials and Methods: Patients undergoing thyroid cancer follow-up were evaluated with US and US-guided fine-needle aspiration biopsy (FNAB) of the LNs. The weighted UNN-RADS score of seven ultrasonographic descriptors, namely, shape, margin, echogenicity, echogenic hilum, cystic degeneration, calcification, and intranodal vascular pattern for suspicious malignant LN was evaluated. UNN-RADS categories were assigned according to the total score. The optimal cut-off value and diagnostic performance of the weighted score for predicting malignant LN were determined using a receiver operating characteristic (ROC) curve. Cohen’s kappa was used to calculate the interobserver agreement. Results: We included 99 LNs from 99 patients who underwent thyroid cancer follow-up, of which 46 (46.5%) had metastatic LNs and 53 (53.5%) LNs were benign. Metastatic LNs were UNN-RADS categories 3 (22/46), 4 (15/46), and 5 (9/46), while LNs in UNN-RADS categories 1 and 2 were benign. A cut-off of 6 points, corresponding to UNN-RADS category 3, had a sensitivity of 100% for predicting malignant LNs. The ROC curve showed an AUC of 0.893 (95% CI, 81.5–94.6). The interobserver agreement between the two radiologists was good (κ = 0.71, 95% CI 0.573–0.798). Conclusion: UNN-RADS is a reliable tool for predicting LN metastases in thyroid cancer patients during follow-up. The multiple features in this scoring system, which weighs US findings suspicious of malignancy, may be more accurate than a single feature.