Objective: To compare the visualization ability for thyroid nodular vascularity among superb micro-vascular imaging (SMI), power Doppler flow imaging (PDFI), and color Doppler flow imaging(CDFI), and determine optimal vascular findings for the diagnosis of thyroid nodules. Methods: A total of 58 thyroid nodules from 50 patients were enrolled, including 27 benign nodules (benign group) and 31 malignant nodules (malignant group). Vascular patterns of these nodules were detected by SMI, PDFI and CDFI, respectively. Results: Thyroid cancer was characterized by type III vascular pattern. "Only central vascularity" performed best in detecting thyroid cancers. When using the criterion, SMI performed a better specificity (96.3%) and sensitivity (77.4%) than PDFI (92.5%, 41.9%) and CDFI (88.9%, 48.3%); and the specificity of SMI was significantly higher than the others (all P<0.01). Conclusions The sign of only central vascularity is of value in distinguishing malignant thyroid nodules. SMI is better on presenting thyroid nodular vascularity than CDFI and PDFI, and it could be used to differentiate thyroid nodules.

Objective: To explore the roles of self efficacy and smoking rationalization tendency in the relationship between college students physical activity and smoking cessation beliefs, in order to provide a basis for the positive effects of college students physical activity on smoking cessation beliefs. Methods: From May 6 to 23 in 2023, 3 048 students from 10 colleges in Jiangxi Province were recruited and surveyed using the Physical Activity Participation Scale, the Smoking Cessation Self efficacy Scale, the Smoking Rationalization Tendency Scale and the Smoking Cessation Belief Scale. The Harman one way test was adopted for common method bias test. Bias correction was unfolded by Bootstrap method, and 95% confidence intervals of parameter estimates were analyzed using repeated sampling 5 000 times. Results: The results of the sequential mediation model analysis showed that physical activity was positively associated with college students beliefs about smoking cessation ( β =0.17), and physical activity, self efficacy and smoking rationalization tendency were positively associated with each other ( β =0.41, 0.08, 0.19) ( P <0.05). Both self efficacy and smoking rationalization tendency positively predicted smoking cessation beliefs ( β =0.19, 0.17, P <0.01). Self efficacy and smoking rationalization tendency mediated the relationship between physical activity and smoking cessation beliefs, with a mediating effect value of 0.09, accounting for 62.82% of the total effect value (0.15). Conclusions Self efficacy and smoking rationalization tendency have a serial mediating effect between physical activity and smoking cessation beliefs among college students. Interventions should be actively used to enhance college students beliefs about smoking cessation, promote smoking cessation behaviors.

Objective Explore the diagnostic value of color Doppler ultrasonography in renal vein embolism compared with contrast-enhanced CT.Analyze and summarize the sonographic features and reasons of misdiagnosis of renal vein embolism.Methods Reports of color Doppler ultrasonography and contrast-enhanced CT in 15 patients with 20 renal vein thrombosis and 25 patients with 25 renal vein tumor thrombosis were retrospectively analyzed.We summarized the sonographic features including the location of emboli,the lumen and wall of the involved veins,the information of collateral circulation and the color Doppler sonographic features.Results The diagnostic accuracy of renal vein thrombosis and tumor thrombosis were 85%and 84%for ultrasound,100%and 96%for contrast-enhanced CT,the difference was not statistically significant(all P＞0.05).The typical sonographic features include(1)Expansion of the renal vein and full of solid echogenicity;(2)No flow signals or flow filling defect in renal veins;(3)No or sparse venous flow signal in the involved kidney.Conclusions Color Doppler ultrasonography and contrast-enhanced CT have a good consistency in the diagnosis of renal vein embolism.Color Doppler ultrasonography can be used as an important imaging method to evaluate the renal vein embolism,which can combine medical history and provide a more reliable basis for the diagnosis of renal vein embolism.

Entropy model is widely used in epileptic electroencephalogram (EEG) analysis, but there are few reports on how to objectively select the parameters to compute the entropy model in the analysis of resting-state functional magnetic resonance imaging (rfMRI). Therefore, an optimization algorithm to confirm the parameters in multi-scale entropy (MSE) model was proposed, and the location of epileptogenic hemisphere was taken as an example to test the optimization effect by supervised machine learning. The rfMRI data of 20 temporal lobe epilepsy (TLE) patients with hippocampal sclerosis, positive on structural magnetic resonance imaging, were divided into left and right groups. Then, the parameters in MSE model were optimized by the receiver operating characteristic curves (ROC) and area under ROC curve (AUC) values in sensitivity analysis, and the entropy value of the brain regions with statistically significant difference between the groups were taken as sensitive features to epileptogenic hemisphere lateral. The optimized entropy values of these bio-marker brain areas were considered as feature vectors input into the support vector machine (SVM). Finally, combining optimized MSE model with SVM could accurately distinguish epileptogenic hemisphere in TLE at an average accuracy rate of 95%, which was higher than the current level. The results show that the MSE model parameter optimization algorithm can accurately extract the functional imaging markers sensitive to the epileptogenic hemisphere, and achieve the purpose of objectively selecting the parameters for MSE in rfMRI, which provides the basis for the application of entropy in advanced technology detection.
Brain/diagnostic imaging* ; Brain Mapping ; Entropy ; Epilepsy, Temporal Lobe/diagnostic imaging* ; Humans ; Magnetic Resonance Imaging