ObjectiveTo evaluate the laparoscopic procedure and therapeutic efficacy of retroperitoneal laparoscopic surgery for the treatment of adrenal ganglioneuroma.Methods6 patients [4 male and 2 female,32 to 59 (mean 41.3) years old],underwent retroperitoneal laparoscopic resection of adrenal ganglioneuroma. In this group, 2 patients with left adrenal ganglioneuroma, 4 patients with right adrenal ganglioneuroma. ResultsAll of the 6 cases was successfully performed uneventfully with retroperitoneal laparoscopic adrenalectomy. Pathologic studies confirmed there were 6 cases of adrenal ganglioneuroma. No case was transferred to open operation.The blood pressure remained stable during operation.Mean tumor size was (5.9±2.1) cm (tumor diameter 3.6-11.2 cm) Mean operative time was 120(90-210) min.Mean estimated blood loss was 160 (50-700) ml.Postoperative hospital stay ranged from 7 to 9 days.All the patients were cured without relapse during 4-32 month, follow-up. ConclusionsRetroperitoneal laparoscopic procedures for adrenal ganglioneuroma causes less traumatic;less operative blood loss;distinct image during operation;less postoperative discomfort;faster postoperative recovery and earlier return to daily activities and diet.Retroperitoneal laparoscopic procedure should be considered as the first choice for adrenal ganglioneuroma.

Objective To quantitatively study right ventricular function in the normal second and third trimester fetuses by M-mode tricuspid annular displacement(TAD).Methods TAD was measured using conventional M-mode echocardiography on 161 normal second and third trimester fetuses with gestation age (GA) between 19-38 weeks,meanwhile multiple parameters for evaluating right ventricular function were obtained using pulsed Doppler echocardiography (PW) and myocardial Dopple tissue imaging (DTI).The correlation between TAD and other parameters were analyzed using SPSS 17.0.Results In normal second and third trimester fetuses,the TAD was (9.38 ± 1.71)mm with a range of 5.79-13.90 mm,and was increased with the growth of GA.TAD was correlated with GA,E,A,Em,Am and Sm significantly (r =0.759,0.547,0.320,0.497,0.483 and 0.598 respectively,all P ＜0.001).TAD was not correlated with HR(P ＞0.05).TAD showed differences between the second trimester fetuses and the third trimester fetuses (P ＜ 0.05).Conclusions In normal second and third trimester fetuses,the TAD is increased with the growth of GA,and has good correlation with GA,E,A,Em,Am and Sm respectively,and may become a new promising modality to evaluate function of RV simply and accurately.The technique will be propitious to use in hospitals (without DTI) because of simplicity of operator and lower requirement on the technology and equipment precision.

Objective To observe the effect of atropine in the treatment of bromiderosis with anhydrous alcohol injection. Methods Patients were randomly divided into two groups (A and B): the patients in Group A was injected with both anhydrous alcohol and atropine, and that in Group B was only injected with anhydrous alcohol. The effect of the operation was evaluated at 1, 3 and 6 months after the treatment. Results From August 2004 to January 2008, 72 patients were involved in this study. 37 cases were included in Group A, and 35 patients were included in Group B. The effective rate in the Group A was 83.78 %, and that in the Group B was 82.86 %. There was no statistical difference between these two groups. Conclusion Atropine has no effect on the treatment of axillary bromidrosis with anhydrous alcohol injection and it is, therefore, not necessarily included in the treatment.

Objective To review the clinical diagnosis and treatment of acute focal renal infarction. Methods Three cases of focal renal infarction were reported and the literature was reviewed.The patients aged from 45 to 63 years with mean age of 54. Two cases had low back pain, 1 case with abdominal pain. Based on clinical history, B-ultrasonography and CT scan, focal renal infarction was diagnosed in 3 patients. There were 2 cases on left kidney and 1 case right. All cases were applied digital subtraction angiography (DSA) and thrombolytic anticoagulant therapy. Results Two cases received DSA and thrombolytic therapy. The other one case received pethidine 50 mg, progesterone 20 mg treatment, the salvia infusion and low molecular heparin 6000 U anticoagulant therapy. All patients had symtoms relieved after 1 d. A week later CT scan, 3 cases of renal infarction were apparently disappeared. Serum creatinine and urea nitrogen were normal. Three patients were followed, mean follow-up time was 1. 5 (0. 5-2) years. Conclusions The diagnosis of acute focal renal infarction mainly depends on B-ultrasound and CT. Early diagnosis and treatment is important for achieving recovery of the compromised renal function. Renal infarction should be suspected in the presence of abdominal pain of sudden onset.

Objective:To explore and analyze the online Q&A texts for hyperglycemia in pregnancy (HIP) users in online health communities, and to provide references for health information services for HIP patients.Methods:A total of 108 590 Q&A texts were collected from "Diabetes Forum" and "Mom Forum". Social network analysis was used to construct the co-occurrence network of feature words in text content and carry out visual analysis and display. On the basis of identifying content themes, the relationship between themes and the nodes within themes were further analyzed, and the attributes of content themes were differentiated with Wilson's information behavior model.Results:In this study, a question and answer text feature word network for pregnant hyperglycemia users with 321 nodes was constructed, among which the largest sub-net included 177 nodes. A total of 12 content themes were identified to seek motivation around two major categories of information, including blood sugar control and coping with disease stress. Among them, the themes with physiological, cognitive, and emotional attributes were 4, 7 and 6, respectively. The number of feature words contained in drug treatment, diet and nutrition was the most prominent, and there were feature words with high degree of centrality in each theme.Conclusions:The content that hyperglycemia in pregnancy (HIP) users pay attention to has multiple attributes and dimensions. Clinical and community healthcare workers and other health information providers can continuously improve the information service content for HIP patients to meet their health information needs.

Objective: The study aimed to investigate the diurnal variation in cervical disc hydration and its relationship with cervical degeneration. Materials and Methods: C3–C7 discs of 86 prospectively enrolled participants (37 males, 49 females; mean age ± standard deviation, 23.5 ± 2.5 years) were assessed using T2 mapping in the morning and evening. All discs were stratified by Miyazaki grade or C2–C7 Cobb angle and T2 values (T2). The degree of diurnal T2 variation (T2-DDV), defined as (morning T2 – evening T2)/morning T2 x 100%, was measured for the entire disc, annulus fibrosus (AF), nucleus pulposus (NP), and endplate zones. Results: T2 of the entire disc decreased significantly after the daytime load (p < 0.001), with a T2-DDV of 13.3% for all discs and 16.0%, 12.2%, and 13.0% for healthy (grade I), mild degenerative (grade II), and advanced degenerative (grade III/IV) discs, respectively. T2 of regional NPs and AFs decreased significantly from morning to evening (p ≤ 0.049) except in the healthy anterior inner AF (p = 0.092). Compared with healthy discs, mild degenerative discs displayed lower T2 and T2-DDV in regional NPs (p < 0.001). Advanced degenerative discs showed higher T2-DDV in the anterior inner AF compared with healthy discs (p = 0.050). Significant diurnal T2 changes in the endplate zones were observed only in healthy discs (p = 0.013). Cervical discs in the low Cobb angle group showed higher T2-DDV in the anterior AFs and anterior NP and lower T2-DDV in the posterior AF than those in the high Cobb angle group (p ≤ 0.041). Conclusion This study characterized the diurnal variation in hydration of the cervical discs as assessed using T2 mapping and revealed early chemo-mechanical coupling dysfunction in degenerating discs. Cervical sagittal alignment on MRI can affect the diurnal stress patterns of the cervical discs. T2 mapping is sensitive to disc biomechanical dysfunction and offers translational potential from biomechanical research to clinical application.

Objective:To investigate the value of net water uptake (NWU) in predicting malignant edema (ME) in large hemispheric infarction (LHI).Methods:Fifty-six patients suffering from LHI in the General Hospital of Northern Theater Command from September 2017 to July 2018 were retrospectively analyzed, and their NWU was calculated separately. Patients were divided into two groups according to the occurrence of ME, which was defined as space-occupying infarct requiring decompressive craniectomy or death resulting from cerebral hernia in seven days from onset. The clinical characteristics were analyzed, and receiver operating characteristic (ROC) curve and respective area under curve (AUC) were used to assess the value of NWU and other factors.Results:After adjusting for atrial fibrillation, National Institutes of Health Stroke Scale scores at admission, and time from onset to imaging, multivariable analysis showed that NWU was an independent predictor of ME ( OR=1.226，95% CI 1.040-1.446, P=0.015). According to the ROC curve, NWU≥13.08% identified ME with great predictive power (AUC=0.813;sensitivity 0.64, specificity 0.94). Conclusions:NWU is an important predictor of ME in patients with LHI. It can help identify patients at risk of ME.

Background Diagnosis of pneumoconiosis by radiologist reading chest X-ray images is affected by many factors and is prone to misdiagnosis/missed diagnosis. With the rapid development of artificial intelligence in the field of medical imaging, whether artificial intelligence can be used to read images of pneumoconiosis deserves consideration. Objective Three deep learning models for identifying presence of pneumoconiosis were constructed based on deep convolutional neural network. An optimal model was selected by comparing diagnostic efficiency of the three models. Methods Digital radiography (DR) chest images were collected between June 2017 and December 2020 from 7 hospitals and standard radiograph quality control protocol was also followed. The DR chest images with positive results were classified into the positive group, while those without pneumoconiosis were classified into the negative group. The collected chest radiographs were labeled by experts who had passed the assessment of reading radiographs,and the experts were constantly assessed for consistency in the labeling process based on an expectation-maximization algorithm. The labeled data were cleaned, archived, and preprocessed, and then were grouped into a training set and a verification set. Three deep convolutional neural network models TMNet, ResNet-50, and ResNeXt-50 were constructed and trained by ten-fold cross-validation method to obtain an optimal model. Five hundred cases of DR chest radiographs that were not included in the training set and the validation set were collected, and identified by five senior experts as the gold standard, named the test set. The accuracy rate, sensitivity, specificity, area under curve (AUC), and other indexes of the three models were derived after testing, and the efficiency of the three models was evaluated and compared. Results A total of 24867 DR chest radiographs of the training set and the validation set were collected in this study, including 6978 images in the positive group and 17889 images in the negative group. There were 312 cases of pulmonary abnormalities such as pneumothorax and pulmonary tuberculosis. A total of nine experts labeled the chest radiographs, the labeling consistency rate of pneumoconiosis (non-staging) was above 88%, and the labeling consistency rate of pneumoconiosis staging ranged from 84.68% to 93.66%. The diagnostic accuracy, sensitivity, specificity, and AUC of TMNet were 95.20%, 99.66%, 88.61%, and 0.987, respectively. The indicators of ResNeXt were 87.00%, 89.93%, 82.67%, and 0.911, respectively. Those of ResNet were 84.00%, 85.91%, 81.19%, and 0.912, respectively. All these indexes of TMNet were higher than those of ResNeXt-50 and ResNet-50 models. The AUC differences between TMNet and the other two models were both statistically significant (P<0.001). Conclusion All the three convolutional neural network models can effectively diagnose the presence of pneumoconiosis, among which TMNet provides the best efficiency.

The Republic of China period （1912—1949） was an important stage of transition from traditional herbalism to clinical Chinese materia medica. The clinical application of Chinese materia medica became the focus of academic attention. During the Republic of China period， the research objectives， methods， and content of clinical Chinese materia medica were clarified， and the basic framework of Chinese materia medica was established through efficacy classification and item description. Based on the historical background at that time， striving for survival in adversity were the internal factors driving the construction of clinical Chinese materia medica， and the rise of academic education and the popularity of traditional Chinese medicine journals provided favorable conditions for the development of clinical Chinese materia medica. The clinical Chinese materia medica during the Republic of China period gradually formed a theoretical structure and core content that was distinctly different from that of traditional herbal medicine， which was integrated with the scientific research of Chinese materia medica and promoted the continuous development of Chinese materia medica together with other subdisciplines， presenting distinctive characteristics of the times and important academic significance.

Objective:To evaluate the image quality of prostate T 2WI reconstructed based on deep learning (deep learning T 2WI) and the diagnostic performance for prostate cancer (PCa) in the transition zone. Methods:Totally 79 patients who underwent prostate MRI for elevated prostate specific antigen from December 2020 to September 2022 were prospectively consecutively collected from Beijing Hospital. Scan sequences included axial standard T 2WI, deep learning T 2WI, and diffusion-weighted imaging. The scan time was recorded. The image quality was scored subjectively including image quality, diagnostic confidence, noise level, artifacts, clarity and lesion detectability. For objective evaluation of image quality, signal-to-noise ratio (SNR) and contrast signal-to-noise ratio (CNR) were calculated. Two-parameter MRI prostate imaging reporting and data system version 2.1 (PI-RADS v2.1) scoring was performed for transition zone lesions using deep learning T 2WI and standard T 2WI, respectively. The subjective and objective image quality evaluation metrics for deep learning T 2WI and standard T 2WI were compared using the Wilcoxon signed-rank test. For transition zone lesions, the diagnostic performance of PI-RADS scores with deep learning T 2WI and standard T 2WI for PCa was evaluated by the receiver operating characteristic curve based on the lesion (all lesions in the transition zone) and the patient (the most malignant lesions in the transition zone), respectively, using the pathologic results as the gold standard. The area under the curve (AUC) was compared using the DeLong test. Results:Deep learning T 2WI significantly reduced the examination time by 64.6.%, from 4 min 37 s to 1 min 38 s. The scores of subjective image quality of deep learning T 2WI and standard T 2WI all were 5 (4, 5). The differences in image quality and lesion detectability were statistically significant ( Z=-2.32, -2.36, P=0.020, 0.018), and the differences of all other image quality evaluation metrics were not statistically significant ( P>0.05). The SNR of deep learning T 2WI and standard T 2WI were 17.11 (14.09, 21.92) and 9.15 (7.16, 11.17), with a statistically significant difference ( Z=-7.72, P<0.001). The CNR of deep learning T 2WI and standard T 2WI were 20.78 (13.42, 31.42) and 11.05 (7.82, 16.25), with a statistically significant difference ( Z=-7.54, P<0.001). Based on the lesion (40 PCa and 48 benign lesions), the AUC of the two-parameter PI-RADS score with deep learning T 2WI and standard T 2WI for diagnosing PCa in the transition zone were 0.915 (95%CI 0.856-0.975) and 0.916 (95%CI 0.857-0.976), without statistically significant difference ( Z=0.03, P=0.973). Based on the patient (33 PCa and 46 benign patients), the AUC of the two-parameter PI-RADS score with deep learning T 2WI and standard T 2WI were 0.921 (95%CI 0.857-0.984) and 0.939 (95%CI 0.886-0.992), without statistically significant difference ( Z=0.59, P=0.558). Conclusions:Compared with standard T 2WI, deep learning T 2WI of the prostate reduces scanning time while maintaining image quality and has comparable diagnostic performance for PCa in the transition zone.