Objective:To establish the prediction model of postoperative Gleason score (GS) risk of prostatic cancer (PCa), and to compare the diagnostic efficacy of the model and each independent risk factor for PCa medium-high risk group.Methods:The clinical data of 362 patients who accepted transrectal prostate biopsy in the Run Run Shaw Hospital Affiliated to Zhejiang University School of Medicine from January 2018 to December 2019 were analyzed retrospectively, and a total of 343 patients with prostate cancer who met the enrollment criteria were selected. According to the GS grading system, these patients were divided into low risk group, moderate risk group and high risk group. At first, the single factor analysis and Spearman rank correlation were used to find out the effective indicators with good correlation with GS risk. Then, multiple linear regression equation was applied for multi-factor analysis to obtain the independent risk factors and the prediction model for predicting GS risk, and then the ROC curve was used to compare the diagnostic efficacy of each independent risk factor and prediction model for PCa medium-high risk group.Results:In the single factor analysis, the differences of all indicators in GS risk were statistically significant (all P<0.05). In the correlation analysis with GS risk, except for the indicators of prostate volume (all P>0.05), the other indexes had linear correlations with the different risks of GS (all P<0.05). Among them, the total prostate specific antigen and two-dimensional ultrasound (2D-US) score showed moderate positive correlations( rs=0.402, 0.579, all P<0.001), contrast enhanced ultrasound (CEUS) score showed a high positive correlation ( rs=0.709, P<0.001), and the rest indexes showed low positive correlations. Multiple linear regression was used to obtain two independent risk factors of 2D-US score ( X1) and CEUS score ( X2) for the prediction of GS risk, then, a prediction model was established: Y=0.863+ 0.066 X1+ 0.27 X2, the corresponding linear coefficient differences were statistically significant(all P<0.05). By the ROC analysis, the areas under the curves of 2D-US score, CEUS score and the prediction model were 0.838, 0.906 and 0.907, respectively. Conclusions:2D-US score and CEUS score are independent risk factors for predicting postoperative GS risk, and the diagnostic efficacy of the prediction model is higher than those of the 2D-US score and CEUS score for the medium-high risk group.

Objective To investigate the sonographic features and diagnosis values of struma ovarii. Methods The sonographic features of 20 struma ovarii patients diagnosed by pathology from June 2015 to March 2018 were retrospectively analyzed. Results The age of the patients was 29 to 82 (41.5 ± 24.0) years old, and 5 cases were postmenopausal. Ultrasonography showed that ovarian goiter was mainly unilateral and solid-cystic, and most of them were thick partitions. The solid echo was similar to the thyroid gland, and more specific papillary protrusions and honeycomb structures could be found. Some of them could show crystallization speckle echo (high probability of cystic part), and blood flow signal could be seen in most of solid part. The pathological results showed that all cases were ovarian goiter except 1 case of ovarian goiter with local papillary thyroid carcinoma. Conclusions Struma ovarii is characteristic to a certain extent, and ultrasonography is helpful for the diagnosis of the disease.

Objective:To establish a predictive model of lateral lymph node metastasis in patients with papillary thyroid carcinoma(PTC), and further to compare the diagnostic efficiency of this model with the suspected abnormal lymph node thyroglobulin in fine-needle aspirate fluid (FNA-Tg) for lateral lymph node metastasis.Methods:The preoperative clinical and ultrasonographic data of 110 patients (257 lymph nodes) who underwent PTC cervical lymph node dissection were retrospectively analyzed. According to the postoperative pathological results, they were divided into lateral lymph node metastasis and non-metastasis group. Regression analysis was used to screen out independent risk factors affecting lateral lymph node metastasis and establish a predictive model. The ROC curve was used to evaluate the diagnostic efficacy and the best diagnostic cut-off point.Results:Prediction model: Logit( P)=-2.987+ 2.189(S/L ratio of lymph nodes)+ 1.748(hilum absent)+ 2.030(hyperechoic)+ 1.849(vascular abnormalities). The sensitivity, specificity, accuracy and AUC of the prediction model in the diagnosis of lateral lymph node metastasis were 92.1%, 83.9%, 87.9% and 0.929, respectively. The Homser-Lemeshow goodness of fit test showed that the Logistic model has a good fitting effect. The sensitivity, specificity, accuracy, and AUC of FNA-Tg in the diagnosis of lateral lymph node metastasis were 87.4%, 95.4%, 90.3% and 0.968, respectively. The sensitivity, specificity, accuracy, and AUC of the combined diagnosis of the predictive model and FNA-Tg were 92.9%, 96.9%, 94.2% and 0.989, respectively. Conclusions:The model has a good predictive value for PTC cervical lymph node metastasis. Combined with FNA-Tg, it can improve its diagnostic efficiency and provide more valuable information for the decision-making of clinical surgical procedures.

Objective: To evaluate the correlation between ultrasound features of papillary thyroid carcinoma (PTC) and lymph node metastasis by preoperative ultrasound elemental observation of thyroid nodules. Methods: Three hundred and seventy-six patients who underwent primary thyroid surgery and confirmed by ultrasound and pathological data as single-focal PTC from Jannary to December 2017 in Sir Run Run Shaw Hospital of Zhejiang Univbersity College of Medicine were retrospectively analyzed. According to the presence or absence of lymph node metastasis, they were divided into central and lateral lymph node metastasis group and non-metastasis group. Independent risk factors for central lymph node metastasis (CLNM) and lateral lymph node metastasis (LLNM) were analyzed by χ² test and multivariate Logistic regression. Results: Multivariate analysis showed that the posterior margin of the cancer was <0.25 cm from the posterior wall of the thyroid gland as an independent risk factor for CLNM (P=0.025). Compared with the tumor volume ≤0.38 cm³, the cancer volume >0.38 cm³ (P=0.000), was more prone to CLNM. And multivariate analysis showed that the anterior margin of the cancer was <0.17 cm (P=0.006) from the anterior thyroid capsule and the inner wall of the foci was <0.26 cm (P=0.014) as independent risk factors for LLNM. Compared with the maximum diameter of the tumor lesion ≤1 cm, the maximum diameter >2 cm (P=0.001) group was more prone to LLNM. Compared with the tumor volume ≤0.38 cm³, the tumor volume >0.38 cm³ (P=0.000) was more prone to LLNM. Conclusions The larger volume of single focal PTC carcinoma and the closer to the posterior thyroid capsule are independent risk factors for CLNM. The larger volume and diameter of single focal PTC, and the closer to the anterior and medial wall capsule are independent risk factors for LLNM.