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Purpose The objective of this research was to develop and validate an ultrasound‐based radiomics nomogram for the pre‐operative assessment of Ki‐67 in breast cancer (BC). Materials and Methods From December 2016 to December 2018, 515 patients with invasive ductal breast cancer who received two‐dimensional (2D) ultrasound and Ki‐67 examination were studied and analyzed retrospectively. The dataset was distributed at random into a training cohort (n = 360) and a test cohort (n = 155) in the ratio of 7:3. Each tumor region of interest was defined based on 2D ultrasound images and radiomics features were extracted. ANOVA, maximum correlation minimum redundancy (mRMR) algorithm, and minimum absolute shrinkage and selection operator (LASSO) were performed to pick features, and independent clinical predictors were integrated with radscore to construct the nomogram for predicting Ki‐67 index by univariate and multivariate logistic regression analysis. The performance and utility of the models were evaluated by plotting receiver operating characteristic (ROC) curves, decision curve analysis (DCA), and calibration curves. Results In the testing cohort, the area under the receiver characteristic curve (AUC) of the nomogram was 0.770 (95% confidence interval, 0.690–0.860). In both cohorts, the nomogram outperformed both the clinical model and the radiomics model (P < .05 according to the DeLong test). The analysis of DCA proved that the model has clinical utility. Conclusions The nomogram based on 2D ultrasound images offered an approach for predicting Ki‐67 in BC.

Background: In recent years, the incidence rate of thyroid cancer is increasing. Meanwhile, with the development of medical technology, the detection rate of thyroid cancer by ultrasound has been greatly improved. Normally doctors can initially distinguish pathology of malignant thyroid diseases by their abundant experience. And it will bring assistance to follow-up treatment. However, the results of these studies have been contradictory. Therefore, this meta-analysis tested the hypothesis that ultrasound is accurate in distinguishing pathology of malignant thyroid diseases. Methods: We will search PubMed, Web of Science, Cochrane Library, and Chinese biomedical databases from their inceptions to the December 14, 2021, without language restrictions. Two authors will independently carry out searching literature records, scanning titles and abstracts, full texts, collecting data, and assessing risk of bias. Review Manager 5.2 and Stata14.0 software will be used for data analysis. Results: This systematic review will determine the accuracy of ultrasound in distinguishing pathology of malignant thyroid diseases. Conclusion: It is findings will provide helpful evidence for the accuracy of ultrasound in distinguishing pathology of malignant thyroid diseases. Systematic review registration: INPLASY2021120072.