Background: It is difficult to accurately assess the risk of Thyroid Imaging Reporting and Data System (TI-RADS) 4 thyroid nodules due to the overlap of benign and malignant conventional ultrasound (US) features of nodules. To reduce unnecessary needle biopsies and assist clinical decision-making, this study established a dynamic nomogram incorporating superb microvascular imaging (SMI) and shear wave elastography (SWE) for the risk evaluation of TI-RADS 4 thyroid nodules. Methods: A total of 248 patients who underwent US, SMI, and SWE with cytological or histopathological results were included in this retrospective study, and were randomly divided into training (174 patients) and verification (74 patients) cohorts. The clinical characteristics and US, SMI, and SWE features of patients were analyzed in the training cohort. The least absolute shrinkage and selection operator (LASSO) regression and multivariate logistic regression were used to screen parameters and construct dynamic nomogram. The receiver operating characteristic (ROC) curves, calibration curve, and decision curve were used to evaluate the performance of the nomogram. Results: A dynamic nomogram was constructed based on age [odds ratio (OR) =0.954; P=0.005] , shape (OR =0.345; P=0.041), SMI (OR =9.511; P<0.001), and SWE (OR =3.670; P=0.001). The nomogram showed excellent discrimination both in the training [area under the curve (AUC): 0.848; 95% confidence interval (CI): 0.784-0.911] and validation (AUC: 0.862; 95% CI: 0.780-0.944) cohorts, and better than US, SMI, and SWE alone in all cohorts (P<0.05). The Nomo-score of each patient was calculated and the cut-off value was 0.607 which can be used to distinguish high-risk and low-risk patients. Conclusions: The SMI and SWE show added predictive value on risk stratification in patients with TIRADS 4 thyroid nodules and a dynamic nomogram was constructed to screen high-risk individuals and assist the clinical decision-making.