Objectives-To investigate the independent risk factors for cervical lymph node metastasis (CLNM) in patients with papillary thyroid carcinoma (PTC) and establish a prediction model via conventional ultrasound (US) and contrastenhanced ultrasound (CEUS). Methods-A total of 275 patients with single PTC, who were admitted to our hospital from January 2016 to December 2018, were enrolled in this study. The clinical characteristics and features of the tumor on conventional US and CEUS were retrospectively analyzed. A binary logistic regression model was established, and the diagnostic efficacy of conventional US and CEUS was compared. Results-The binary logistic regression analysis showed that age younger than 38 years, size of 10.0 mm or greater, solid composition, peak of the nodule interior of 28.3750 or greater, and area under the curve (AUC) of the peripheral ring of less than 3.2500 were independent risk factors of CLNM (P < .05, for all). Prediction model: Logit (p) = −4.135 + 1.040 (age) + 1.920 (size) + 1.769 (composition) + 1.230 (peak of nodule interior) + 0.812 (AUC of peripheral ring). The model positively predicted CLNM at a value of L > −0.199. The AUC, sensitivity, and negative predictive value of the receiver operating characteristic curve for the model were 0.727, 71.7%, and 75.2%, respectively, which were significantly higher than those of conventional US (Z = −2.403; P = .016; Z = −5.330; P < .001; and Z = −2.390; P = .017). The specificity of the model was 73.7%, which was lower than that of conventional US (Z = 3.508; P < .001). Conclusions-The preoperative prediction model established via conventional US and CEUS may be helpful to evaluate CLNM in patients with PTC and determine the appropriate treatment options.

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Objectives-To explore the characteristics of breast ductal carcinoma in situ (DCIS) on real-time grayscale contrast-enhanced ultrasound (CEUS) imaging and the diagnostic value of CEUS in DCIS.Methods-A total of 127 histopathologically confirmed DCIS lesions and 124 fibroadenomas (FAs; controls) were subjected to conventional ultrasound and CEUS. Next, the CEUS findings of DCIS and FA lesions, including morphologic features and quantitative parameters, were analyzed.Results-Binary logistic regression was used to identify the independent risk factors from DCIS and FA lesions detected by CEUS. Contrast-enhanced ultrasound revealed significant differences between DCIS and FA. The wash-in time, enhancement mode, enhancement intensity, blood perfusion defects, peripheral high enhancement, enhancement scope, intratumoral vessels and their courses and dilatation degree, and penetrating vessels on CEUS were identified as features correlated with DCIS (P < .05). Moreover, a multivariate logistic regression analysis was developed, and the area under receiver operating characteristic curve of each index was generated, including the wash-in time, enhancement intensity, blood perfusion defects, enhancement scope, penetrating vessels, arrival time, and peak intensity (P < .05; area under the curve, >0.6). Conclusions-The contrast-enhancement patterns and DCIS parameters appeared different from FA lesions, thus suggesting that CEUS can be very useful in distinguishing DCIS from FA lesions.