Objective To look for more serum biomarkers supporting the diagnosis of multiple system atrophy ( MSA) and providing more evidence for early treatment.Methods All patients and healthy controls were enrolled from January 2011 to March 2015 in the First Affiliated Hospital of Zhengzhou University.Demographic features and biochemical examination results were collected.The t test was used to compare the lipid levels between MSA patients and controls.LSD-t test was used to compare the lipid levels among subtypes of MSA patients.Multivariate Logistic regression analysis was conducted to analyze the influencing factors.The relevance between lipid levels and onset age, disease duration and Hoehn & Yahr stage was calculated by Spearman correlation coefficients.Results Participants included 195 MSA patients and 195 age-and gender-matched controls with no neurological diseases.The levels of total cholesterol ((4.33 ±0.90) mmol/L), triglyceride ((1.27 ±0.71) mmol/L), low-density lipoprotein (LDL;(2.70 ±0.76) mmol/L) were significantly lower in patients than in controls ((4.52 ±0.85), (1.47 ± 0.86), (2.85 ±0.71) mmol/L ,t=2.056,2.528 and 2.149 respectively, all P<0.05).The levels of total cholesterol ((4.28 ±0.96) mmol/L) and triglyceride ((1.20 ±0.64) mmol/L) were significantly lower in MSA-P patients than in control group ((4.52 ±0.85), (1.47 ±0.86) mmol/L;LSD-t=1.983, 2.566, both P<0.05).After adjusting for age, gender and histories, the odds ratio ( OR) was 0.31 (95%CI 0.15-0.65, P =0.002 ) for MSA patients in the highest quartile of triglyceride and 0.38 (95%CI 0.17 -0.83,P=0.016) for those in the highest quartile of high-density lipoprotein (HDL), compared with the lowest quartiles.And HDL level was in a significantly positive correlation with onset age (r=0.15, P=0.039).Conclusion Our data suggest that triglyceride and HDL may be associated with the prevalence of MSA, and the lower levels of HDL, the earlier onset of MSA.

Objective:To explore the application value of artificial intelligence-assisted diagnosis model based on convolutional neural network (CNN) in the differential diagnosis of benign and malignant breast masses.Methods:A total of 10 490 images of 2 098 patients with breast lumps (including 1 132 cases of benign tumor, 779 cases of malignant tumor, 32 cases of inflammation, 155 cases of adenosis) were collected from January 2016 to January 2018 in Beijing Tiantan Hospital Affiliated to the Capital University of Medical Sciences. They were divided into training set and test set and the auxiliary artificial intelligence diagnosis model was used for training and testing. Two sets of data training models were compared by two-dimensional imaging (2D) and two-dimensional and color Doppler flow imaging (2D-CDFI). The ROC curves of benign breast tumors, malignant tumors, inflammation and adenopathy were analyzed, and the area under the ROC curve (AUC) were calculated.Results:The accuracies of 2D-CDFI ultrasonic model for training group and testing group were significantly improved. ①For benign tumors, the result from training set with 2D image was: sensitivity 92%, specificity 95%, AUC 0.93; the result from training set with 2D-CDFI images was: sensitivity 93%, specificity 95%, AUC 0.93; the result for test set with 2D images was: sensitivity 91%, specificity 96%, AUC 0.94; the result for test set with 2D-CDFI images was: sensitivity 93%, specificity: 94%, AUC 0.94. ② For malignancies, the result for training set with 2D images was: sensitivity 93%, specificity 97%, AUC 0.94; the result for training set with 2D-CDFI images was: sensitivity 93%, specificity 96%, AUC 0.94; the result for test set with 2D images was: sensitivity 93%, specificity 96%, AUC 0.94; the result for test set with 2D-CDFI images was: sensitivity 93%, specificity 96%, AUC 0.94. ③For inflammation, the result for training set with 2D images was: sensitivity 81%, specificity 99%, AUC 0.91; the result for training set with 2D-CDFI images was: sensitivity 86%, specificity 99%, AUC 0.89; the result for test set with 2D images was: sensitivity 100%, specificity 98%, AUC 0.98; the result for test set with 2D-CDFI images was: sensitivity 100%, specificity 99%, AUC 0.96. ④For adenopathy, the result for training set with 2D images was: sensitivity 88%, specificity 97%, AUC 0.94; the result for training set with 2D-CDFI images was: sensitivity 93%, specificity 98%, AUC 0.94; the result for test set with 2D images was: sensitivity 94%, specificity 98%, AUC 0.93; the result for test set with 2D-CDFI images was: sensitivity 88%, specificity 99%, AUC 0.90. Its diastolic accuracy was not affected even if the maximum diameter of the tumor was less than 1 cm.Conclusions:Through the deep learning of artificial intelligence based on CNN for breast masses, it can be more finely classified and the diagnosis rate can be improved. It has potential guiding value for the treatment of breast cancer patients.

Objective:To investigate the value of contrast-enhanced ultrasound (CEUS) in the diagnosis of malignant endometrial lesions.Methods:A total of 142 patients with endometrial lesions who underwent contrast-enhanced ultrasound examination in Beijing Tiantan Hospital, Capital Medical University from January 2019 to September 2021 were selected. The endometrial lesions were divided into benign group (including endometrial hyperplasia and endometrial polyps) and malignant group (endometrial cancer) according to the pathological results of surgery, and the differences of contrast enhancement patterns between benign group and malignant group were compared. The sensitivity, specificity of CEUS in the diagnosis of endometrial cancer were calculated, and the Kappa value was calculated with the initial enhancement time earlier than or equal to the muscularity or the peak time earlier than the muscularity as the diagnostic index for the diagnosis of endometrial malignant lesions. The sensitivity, specificity, and Kappa value of CEUS in the diagnosis of endometrial cancer and endometrial cancer with thickness ≥10 mm were calculated.Results:A total of 108 patients underwent surgery with clear pathological results, including 66 patients in the benign lesion group and 42 patients in the malignant lesion group. The thickness of malignant lesions was significantly larger than that of benign lesions, and the difference was statistically significant( t=4.039, P<0.05), but there was no significant difference of hemodynamic parameters between the two groups ( P>0.05). The initial enhancement time, peak time and peak intensity of benign lesions were significantly different from those of malignant lesions(all P<0.05). The sensitivity, specificity, and Kappa value of CEUS in the diagnosis of endometrial cancer were 64.3%, 100% and 0.668, respectively. The sensitivity, specificity and Kappa value of CEUS in the diagnosis of endometrial carcinoma with lesion thickness ≥10 mm were 75.0%, 100% and 0.795, respectively. Conclusions:For the diagnosis of endometrial lesions, especially the malignant endometrial lesions with thickness and diameter greater than or equal to 10mm, there is a high diagnostic coincidence rate between CEUS and pathological diagnosis, and endometrial malignant lesions have more specific CEUS manifestations.

Objective:To explore the value of different levels of sonographers and International Ovarian Tumor Analysis (IOTA) simple rules in judging benign and malignant ovarian tumors.Methods:The ultrasound images of 182 patients treated in Beijing Tiantan Hospital, Capital Medical University from January 2017 to November 2020 with ovarian tumors were retrospectively analyzed. The ovarian tumors were diagnosed by two senior sonographers and two junior sonographers without knowing the pathological diagnosis. Another junior sonographer trained in IOTA terminology and simple rules applied IOTA simple rules to diagnose 182 ovarian tumors. The sensitivity, specificity, positive predictive value and negative predictive value of the diagnosis of ovarian tumors by senior sonographers, junior sonographers and IOTA simple rules were calculated using the postoperative pathological diagnosis as the gold standard. The Kappa value was calculated for the consistency between different levels of sonographers and the IOTA simple rules and pathological diagnosis.Results:Of the 182 cases, 61 cases were pathologically benign and 121 cases were pathologically malignant. The diagnostic sensitivity, specificity and accuracy of senior sonographers were 93.4%, 99.2%, 97.2%, respectively, Kappa value was 0.938. The diagnostic sensitivity, specificity, and accuracy of junior sonographers were 80.3%, 90.0%, 86.8%, respectively, Kappa value was 0.704. The diagnostic sensitivity, specificity and accuracy of IOTA simple rules(When an uncertain tumor was classified as malignant) were 95.0%, 73.5%, 80.7%, respectively, Kappa value was 0.614. The diagnostic sensitivity, specificity and accuracy of IOTA simple rules(when an uncertain tumor was excluded) were 94.2%, 90.9%, 92.0%, respectively, Kappa value was 0.834.Conclusions:IOTA simple rules is a very useful diagnostic tool for junior sonographers to judge benign and malignant ovarian tumors. When IOTA simple principle is judged as an uncertain case, it is recommended to refer to experienced senior sonographers for further diagnosis.

Objective:To investigate the ultrasound characteristics of benign and malignant endometrial lesions in postmenopausal women terminology.Methods:Patients with endometrial lesions who underwent transvaginal ultrasound examination in Beijing Tiantan Hospital affiliated to Capital Medical University from January 2019 to November 2021 were selected.Pathological diagnosis after surgery was used as the gold standard, and endometrial lesions were divided into a benign group(including endometrial hyperplasia and endometrial polyps)and a malignant group(endometrial cancer)according to surgical pathology results.Endometrial thickness and Doppler flow parameters were compared between the benign group and the malignant group.The chi-square test was used to compare the echogenicity, the presence or absence of cystic areas, the integrity of the endometrial-myometrial junction, the blood flow score, and the blood supply vessels between the benign and malignant groups.A prediction model was established according to the ultrasonic characteristics.Results:A total of 136 participants received surgery at our hospital with definitive pathological diagnoses, including 72 patients in the benign group and 64 patients in the malignant group.Peak systolic velocity(PSV) and end diastolic velocity(EDV) in malignant lesions were higher than those in benign lesions[(28.75±14.66)cm/s vs.(22.94±13.62)cm/s, (14.75±8.10)cm/s vs.(11.56±6.21)cm/s]. The thickness of malignant lesions was significantly greater than that of benign lesions[(19.31±8.97)mm vs.10.14±4.31)mm], and the blood flow resistance index was lower than that of benign lesions(14.75±8.10 vs.11.56±6.21). The differences were statistically significant( t=2.393, 2.597, 7.452, 2.028, all P<0.05). The prediction model was established based on the above ultrasonic characteristics.The area under the ROC curve for ultrasound physicians to diagnose benign and malignant endometrial lesions was 0.905( P<0.001), indicating that the prediction model had high diagnostic value. Conclusions:Both benign and malignant endometrial lesions in postmenopausal women have different ultrasonic characteristics.Malignant lesions tend to have a larger lesion thickness, an interrupted or irregular endometrial-myometrial junction, higher blood flow signal scores, and multiple blood supply patterns.The ultrasonic prediction model has high diagnostic value for benign and malignant endometrial lesions.

Objective: To analyze the ultrasound examination and computed tomography angiography (CTA) features of carotid web(CAW), and compare with the pathology after carotid endarterectomy, and then compare diagnostic efficacies of the two methods. Methods: From June 2018 to July 2019, 159 patients underwent carotid endarterectomy(CEA) in Beijing Tian Tan Hospital were collected, ultrasound examination and CTA were performed preoperatively. The presence or absence of CAW and whether there were thrombosis or atherosclerotic plaques associated with it were identified. The location length, thickness, direction in the lumen, echo characteristics of CAW, and complicated with or without thrombosis or atherosclerotic plaques were recorded. The postoperative specimens were observed, and the pathological analysis was performed. Results: Among the 159 cases of CEA, 22 cases were confirmed to have CAW structure by pathology, and HE staining showed extensive intimal fibrohyperplasia and mucoid degeneration, among which 18 cases had plaque formation at the bottom of the carotid web, and 4 cases associated with thrombosis. There were 17 cases of CAW structure diagnosed by ultrasound, 5 cases were misdiagnosed or missed, the sensitivity and specificity of ultrasound in the diagnosis of CAW were 77% (17/22) and 98% (135/137), and the accuracy was 75%. Eleven cases of CAW were diagnosed by preoperative CTA, and 11 cases were misdiagnosed and missed diagnosis, the sensitivity and specificity of CTA in the diagnosis of CAW were 50%(11/22) and 97%(134/137), and the accuracy was 47%. Conclusions The sensitivity of ultrasound in the diagnosis of CAW is higher than that of CTA, which can better display the structure of CAW and whether it is associated with plaque or thrombosis.