RESUMEN
OBJECTIVE: To summary radiating blood flow signals and evaluate their diagnostic value in differentiating benign and malignant thyroid nodules. MATERIALS AND METHODS: We retrospectively recruited consecutive patients undergoing US at 4 hospitals from 2018 to 2022. In a training dataset, the correlations of US features with malignant thyroid nodules were assessed by multivariate logistic analysis. Multivariate logistic regression models involving the ACR TI-RADS score, radiating blood flow signals and their combination were built and validated internally and externally. The AUC with 95% asymptotic normal confidence interval as well as sensitivity, specificity, negative predictive value (NPV), and positive predictive value (PPV) with 95% exact binomial confidence intervals were calculated. RESULTS: Among 2475 patients (1818 women, age: 42.47 ± 11.57; 657 men, age: 42.16 ± 11.69), there were 3187 nodules (2342 malignant nodules and 845 benign nodules). Radiating blood flow signals were an independent risk factor for diagnosing thyroid carcinoma. In the training set, the AUC of the model using the combination of radiating blood flow signals and the ACR TI-RADS score (0.95 95 % CI: [0.94, 0.97]; P < 0.001) was significantly higher than that of the ACR TI-RADS model (0.91 [0.89, 0.93]). In the two internal validation sets and the external validation set, the AUCs of the combination model were 0.97 [0.96, 0.98], 0.92 [0.88, 0.96], and 0.91 [0.86, 0.95], respectively, and were all significantly higher than that of the ACR TI-RADS score (0.92 [0.90, 0.95], 0.86 [0.81, 0.91], 0.84 [0.79, 0.89]; P < 0.001). CONCLUSION: Radiating blood flow is a new US feature of thyroid carcinomas that can significantly improve the diagnostic performance vs. the ACR TI-RADS score.