PurposeTo explore the characteristics of C-TIRADS by comparing it with ACR-TIRADS, Kwak-TIRADS, KSThR-TIRADS and EU-TIRADS.MethodsA total of 1096 nodules were collected from 884 patients undergoing thyroidectomy in our center between May 2018 and December 2020. Divided the nodules into two groups: “>10mm” and “≤10mm”. Ultrasound characteristics of each nodule were observed and recorded by 2 doctors, then classified based on ACR-TIRADS, Kwak-TIRADS, KSThR-TIRADS, EU-TIRADS, and C-TIRADS.ResultsA total of 682 benign nodules cases (62.23%) and 414 malignant nodules cases (37.77%) were identified. The ICC value of each guideline was:0.937(ACR-TIRADS), 0.858(EU-IRADS), 0.811(Kwak-TIRADS), 0.835(KTA/KSThR-TIRADS) and 0.854(C-TIRADS). The nodule malignancy rates in the groups(Kwak-TIRADS 4B, C-TIRADS 4B、4C) of two sizes were significantly different (all p<0.05). There was no statistical difference in the other grades of two sizes (all p>0.05). Unnecessary biopsy rates were the lowest in C-TIRADS (49.02% p<0.001). Furthermore, Kwak-TIRADS had the highest sensitivity and NPV (89.9%, 91.0%, all p<0.05), while C-TIRADS had the highest specificity and PPV (82.3%, 69.2%, all p<0.05). C-TIRADS and Kwak-TIRADS had the highest accuracy (76.0%, 72.5%, P=0.071). The AUCs of the 5 guidelines were C-TIRADS(0.816, P<0.05), Kwak-TIRADS(0.789, P<0.05) KTA/KSThR-TIRADS and ACR-TIRADS(0.773, 0.763, P=0.305), EU-TIRADS(0.734, P<0.05). The AUCs of the five guidelines were not statistically different between “nodules>10mm” and “nodules ≤ 10mm” (all P>0.05).ConclusionsAll five guides showed excellent interobserver agreement. C-TIRADS was slightly efficient than Kwak-IRADS, KTA/KSThR-TIRADS and ACR-TIRADS, and had greater advantages than EU-TIRADS. The diagnostic abilities of the five guidelines for “nodules ≤ 10mm” were not inferior to that of “nodules> 10mm”. C-TIRADS is simple and easy to implement and can provide effective thyroid tumor risk stratification for thyroid nodule diagnosis, especially in China.

The objective of this study is to evaluate the diagnostic value of combination of artificial neural networks (ANN) and support vector machine (SVM)-based CAD systems in differentiating malignant from benign thyroid nodes with gray-scale ultrasound images. Two morphological and 65 texture features extracted from regions of interest in 610 2D-ultrasound thyroid node images from 543 patients (207 malignant, 403 benign) were used to develop the ANN and SVM models. Tenfold cross validation evaluated their performance; the best models showed accuracy of 99% for ANN and 100% for SVM. From 50 thyroid node ultrasound images from 45 prospectively enrolled patients, the ANN model showed sensitivity, specificity, positive and negative predictive values, Youden index, and accuracy of 88.24, 90.91, 83.33, 93.75, 79.14, and 90.00%, respectively, the SVM model 76.47, 90.91, 81.25, 88.24, 67.38, and 86.00%, respectively, and in combination 100.00, 87.88, 80.95, 100.00, 87.88, and 92.00%, respectively. Both ANN and SVM had high value in classifying thyroid nodes. In combination, the sensitivity increased but specificity decreased. This combination might provide a second opinion for radiologists dealing with difficult to diagnose thyroid node ultrasound images.

Contrast-enhanced ultrasound can be used to differentiate low from high-grade bladder urothelial carcinoma. The TIC parameters of CEUS reflect the MVD of bladder urothelial tumors and may be helpful for evaluating tumor angiogenesis, with implications for clinical diagnosis, treatment, and prognosis.

RT-3DE is a simple and fast imaging technique, and the detailed 3D images obtained can be used to confirm the diagnosis of MVC. RT-3DE is considered to be an important preoperative test that provides more comprehensive information for selecting a subsequent procedure for treatment.

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