Objective To evaluate the application value of artificial intelligence (AI) in the quality control of mammographic images and explore its feasibility for improving image quality. Methods A retrospective analysis was conducted on 500 mammographic images from 125 female patients. These images were acquired in December 2024 at the Department of Radiology, Obstetrics and Gynecology Hospital of Tongji University by two junior technologists with qualification certificate for junior radiologic technologists and ≤ 2 months of independent operation. The reference standard was the evaluation by a panel of senior experts comprising one associate chief radiologist and two intermediate radiologic technologists with over 10 years of experience in mammography. The evaluation was based on nine criteria within an AI quality control system. The correlation and consistency (Kappa test) of the assessment outcomes were compared among the junior technologist group, the AI quality control group, and the panel group. Additionally, the differences in the proportions of high-, medium-, and low-quality images rated by the three groups were analyzed. After one month of AI assistance, 200 images from 50 additional patients acquired by the same two junior technologists in January 2025 were collected. The area under the receiver operating characteristic curve and 95% confidence interval (95%CI) were calculated for the assessment performance of the junior technologist group before and after AI assistance. Differences were compared using the DeLong test. Changes in the disqualification rates for the nine criteria were analyzed. Results In consistency analysis, the AI quality control group showed high consistency with the panel group across multiple key criteria, with Kappa values ranging from 0.41 to 1.00. In contrast, the consistency between the junior technologist group and the panel group was generally low, with Kappa values ranging from 0.13 to 0.49. In comparison of image quality classification, no significant differences were observed in image quality classification between the AI group and the panel group (P>0.05). However, the proportion of images rated as high quality by the junior technologist group was significantly higher, while the proportions rated as medium and low quality were significantly lower, compared to those rated by the panel group (P<0.05). After AI assistance, the area under the receiver operating characteristic curve for the assessment performance of junior technologist group increased significantly from 0.56 (95%CI: 0.51-0.61) to 0.91 (95%CI: 0.87-0.94) (P<0.001). The disqualification rates for skin folds, incomplete inclusion of the pectoralis major muscle, and nipple not in profile decreased significantly. Conclusion AI demonstrates assessment capability comparable to the panel group in mammographic quality control. AI effectively enhances the quality of images acquired by junior technologists through real-time, objective feedback.

AIM: To evaluate clinical efficacy of recombinant human epidermal growth factor(rhEGF)combined with adjuvant amniotic membrane transplantation in corneal alkaline burns. METHODS:In the prospective, randomized controlled study, patients with corneal alkaline burns treated in the hospital were enrolled between November 2022 and November 2024. After emergency treatment, patients were divided into combined treatment group and routine treatment group by random number table method. The routine treatment group was given basic treatment(rhEGF), while combined treatment group additionally underwent adjuvant amniotic membrane transplantation. The clinical efficacy, healing time of corneal epithelium, best corrected visual acuity, VAS scores, corneal neovascularization area, break-up time, score of corneal opacity, and levels of inflammatory factors(IL-6, hs-CRP, TNF-α)in the two groups were observed and compared. RESULTS:There were 110 patients(110 eyes)in this study, including 55 cases(55 eyes)in each group. The combination group had a mean age of 46.82±10.38 y, including 26 males and 29 females. The routine treatment group had a mean age of 45.13±11.57 y, with 31 males and 24 females. The total response rate of combined treatment group [94.5%(52/55)] was significantly higher than that of routine treatment group [81.8%(45/55), P<0.05]. The healing time of corneal epithelium in combined treatment group was significantly shorter than that in routine treatment group(P<0.001), and VAS score for pain severity after treatment was significantly lower than that in routine treatment group(P<0.001). The corneal neovascularization area in combined treatment group was significantly smaller than that in routine treatment group(P<0.001), break-up time was significantly longer than that in routine treatment group(P<0.001),and score of corneal opacity was significantly lower than that in routine treatment group(P<0.001). After treatment, levels of inflammatory factors in combined treatment group were significantly lower than those in routine treatment group(all P<0.05). CONCLUSION:Adjuvant amniotic membrane transplantation combined with rhEGF presents prominent clinical advantages in the treatment of alkaline corneal burns. It can enhance therapeutic efficacy, accelerate wound healing, relieve pain, reduce corneal neovascularization, prolong tear film break-up time, alleviate corneal opacification, and reduce the levels of inflammatory factors.

Objective To provide a reference for the establishment, development and application of the adverse drug reaction （ADR） automated monitoring system, through verifying and quantifying the research hotspots and advantages of the system by CiteSpace software and systematic review. Methods Literature on ADR automated monitoring up to December 2023 were retrieved and screened from CNKI and web of science databases. CiteSpace 6.4.R1 software was used to conduct co-occurrence, clustering and emergence analysis, and to visualize and comparatively analyze the research hotspots, rules and distribution in the field of automated monitoring of ADR at home and abroad. In compliance with the preferred reporting items for systematic reviews and Meta-analyses （PRISMA）, literature covering publications in English and Chinese including detection rates of ADR collected using Incident Reporting Systems （IRSs） and/or automated monitoring systems were retrieved and screened. The advantages and disadvantages of automated monitoring systems were analyzed by comparing the differences between these two systems in terms of the number of ADR reports and the types of positive signals. Results A total of 56 articles in English and 80 articles in Chinese were indexed by CiteSpace. The research hotspots in recent years included data mining, deep learning, text classification techniques, machine learning and so on. A total of seven studies compiled with the inclusion criteria for the systematic evaluation, all of which were completed between 1991 and 2021 in hospitals in four countries. 150 526 medical records were reviewed from 15 institutions. A total of 194 ADR reports were collected by IRSs. A total of 2 090 ADR reports were collected by the automated monitoring system over the same period, indicating a 977% increase in the number of ADR reports （P=0.0156） compared with the IRSs. Conclusion The ADR automatic monitoring system had significantly improved the level of drug risk identification and reduced costs, but it was necessary to optimize the algorithm, expand the data source and carry out standardization construction to overcome the current limitations.

Objective To evaluate the application value of artificial intelligence (AI) in the quality control of mammographic images and explore its feasibility for improving image quality. Methods A retrospective analysis was conducted on 500 mammographic images from 125 female patients. These images were acquired in December 2024 at the Department of Radiology, Obstetrics and Gynecology Hospital of Tongji University by two junior technologists with qualification certificate for junior radiologic technologists and ≤ 2 months of independent operation. The reference standard was the evaluation by a panel of senior experts comprising one associate chief radiologist and two intermediate radiologic technologists with over 10 years of experience in mammography. The evaluation was based on nine criteria within an AI quality control system. The correlation and consistency (Kappa test) of the assessment outcomes were compared among the junior technologist group, the AI quality control group, and the panel group. Additionally, the differences in the proportions of high-, medium-, and low-quality images rated by the three groups were analyzed. After one month of AI assistance, 200 images from 50 additional patients acquired by the same two junior technologists in January 2025 were collected. The area under the receiver operating characteristic curve and 95% confidence interval (95%CI) were calculated for the assessment performance of the junior technologist group before and after AI assistance. Differences were compared using the DeLong test. Changes in the disqualification rates for the nine criteria were analyzed. Results In consistency analysis, the AI quality control group showed high consistency with the panel group across multiple key criteria, with Kappa values ranging from 0.41 to 1.00. In contrast, the consistency between the junior technologist group and the panel group was generally low, with Kappa values ranging from 0.13 to 0.49. In comparison of image quality classification, no significant differences were observed in image quality classification between the AI group and the panel group (P>0.05). However, the proportion of images rated as high quality by the junior technologist group was significantly higher, while the proportions rated as medium and low quality were significantly lower, compared to those rated by the panel group (P<0.05). After AI assistance, the area under the receiver operating characteristic curve for the assessment performance of junior technologist group increased significantly from 0.56 (95%CI: 0.51-0.61) to 0.91 (95%CI: 0.87-0.94) (P<0.001). The disqualification rates for skin folds, incomplete inclusion of the pectoralis major muscle, and nipple not in profile decreased significantly. Conclusion AI demonstrates assessment capability comparable to the panel group in mammographic quality control. AI effectively enhances the quality of images acquired by junior technologists through real-time, objective feedback.

Objective To evaluate the application value of artificial intelligence (AI) in the quality control of mammographic images and explore its feasibility for improving image quality. Methods A retrospective analysis was conducted on 500 mammographic images from 125 female patients. These images were acquired in December 2024 at the Department of Radiology, Obstetrics and Gynecology Hospital of Tongji University by two junior technologists with qualification certificate for junior radiologic technologists and ≤ 2 months of independent operation. The reference standard was the evaluation by a panel of senior experts comprising one associate chief radiologist and two intermediate radiologic technologists with over 10 years of experience in mammography. The evaluation was based on nine criteria within an AI quality control system. The correlation and consistency (Kappa test) of the assessment outcomes were compared among the junior technologist group, the AI quality control group, and the panel group. Additionally, the differences in the proportions of high-, medium-, and low-quality images rated by the three groups were analyzed. After one month of AI assistance, 200 images from 50 additional patients acquired by the same two junior technologists in January 2025 were collected. The area under the receiver operating characteristic curve and 95% confidence interval (95%CI) were calculated for the assessment performance of the junior technologist group before and after AI assistance. Differences were compared using the DeLong test. Changes in the disqualification rates for the nine criteria were analyzed. Results In consistency analysis, the AI quality control group showed high consistency with the panel group across multiple key criteria, with Kappa values ranging from 0.41 to 1.00. In contrast, the consistency between the junior technologist group and the panel group was generally low, with Kappa values ranging from 0.13 to 0.49. In comparison of image quality classification, no significant differences were observed in image quality classification between the AI group and the panel group (P>0.05). However, the proportion of images rated as high quality by the junior technologist group was significantly higher, while the proportions rated as medium and low quality were significantly lower, compared to those rated by the panel group (P<0.05). After AI assistance, the area under the receiver operating characteristic curve for the assessment performance of junior technologist group increased significantly from 0.56 (95%CI: 0.51-0.61) to 0.91 (95%CI: 0.87-0.94) (P<0.001). The disqualification rates for skin folds, incomplete inclusion of the pectoralis major muscle, and nipple not in profile decreased significantly. Conclusion AI demonstrates assessment capability comparable to the panel group in mammographic quality control. AI effectively enhances the quality of images acquired by junior technologists through real-time, objective feedback.

Objective To explore the teaching effect of a"one-day"training model for basic application of periop-erative echocardiography for refresher anesthesiologists based on AR glasses and simulators.Methods The cardiac ultrasound teaching team of the Department of Anesthesiology at Peking Union Medical College Hospital designed a"one-day"teaching course for 60 trainees with no prior experience,based on AR glasses and simulators,covering basic applications of transthoracic echocardiography(TTE)and transesophageal echocardiography(TEE).We col-lected the scores of theoretical and practical assessments before and after the training and conducted a survey on trainee satisfaction and changes in clinical behavior post-training.Statistical analysis was performed using SPSS 23.0 software.Results The theoretical knowledge scores before and after the training were 52.35±12.33 and 81.20±22.78,respectively(P＜0.05);the practical assessment scores were 30.33±10.65 and 73.96±23.15,respectively(P＜0.05).Overall satisfaction rate was 96.66%(58/60).Conclusions The"one-day"teaching model for basic application of perioperative cardiac ultrasound based on AR glasses and simulators,as an introductory training model,can help beginners quickly master the core content at the entry level and lay a solid foundation for subsequent clinical application.

Objective To discuss the perioperative anesthesia management strategy for the surgical resection of rec-tal cancer in a patient with a rare neuromuscular disease-Facioscapulohumeral Muscular Dystrophy(FSHD)compli-cated by restrictive ventilatory dysfunction.Methods Clinical data of a patient with FSHD complicated by moder-ate-to-severe restrictive ventilatory dysfunction undergoing rectal cancer surgery were retrospectively collected;the clinical manifestations,complication,preoperative evaluation,intraoperative anesthesia management and postopera-tive pain treatment were analyzed and summarized.Results FSHD is a rare genetic disorder,and preopera-tive multidisciplinary evaluation is critical.In this case,total intravenous anesthesia was employed,with invasive arterial pressure monitoring,blood gas analysis,body temperature,sufficient analgesia,close respiratory monitoring and lung protective ventilation strategy after preoperative multidisciplinary evaluation.After thorough sputum suction,lung expansion,and complete recovery of muscle strength,the patient was successfully extubated;ensuring respiratory monitoring after surgery,sufficient analgesia was administered,and transferred to the ICU for monitoring,and ultimately discharged with satisfactory treatment results.Conclusions For patients with rare neuro-muscular diseases such as FSHD,thorough preoperative evaluation and optimization are essential.Clinicians should be aware of related complications,such as restrictive ventilatory dysfunction,and develop individualized anesthesia plans.Intraoperative monitoring,particularly of the respiratory and hemodynamic systems,should aim to prevent hypoxia and carbon dioxide retention,thereby reducing the risk of complications.

Objective To explore the relationship between axillary artery and axillary vein by combining computed tomography angiography computed tomography angiography(CTA)and computed tomography venography(CTV),and to provide imaging data for establishing an effective blood circulation pathway for vascular injury in clinical transaxillary surgery.Methods The image data of 30 patients who underwent left upper limb and axillary CTA and CTV at the same time were collected.After three-dimensional reconstruction of the images by GE AW4.6 workstation,the course,branch type and variation of axillary artery,the course of axillary vein,the reflux of subordinate branches and the relationship between axillary artery and axillary vein were observed.The length of the whole segment,the length of segment and the inner diameter of the starting point of each segment were measured and statistically analyzed.Results According to the number of branches from the main trunk,the axillary artery was divided into 7 types.According to the variation of the number of blood vessels,the axillary vein was divided into 5 types;The unknown vein branches converge into 32 branches,of which the first segment accounted for 37.5％,the second segment accounted for 46.9％,and the third segment accounted for 15.6％.According to the absence of arterial branches,the relationship between axillary artery and axillary vein was divided into 2 types.Conclusion There are many types of branches of axillary arteries and branches of axillary veins,and the variation types are complex.The changes of branches of axillary arteries affect the distribution of branches of axillary veins.Combined with CTA and CTV images,the relationship between axillary vessels can be reflected clearly and intuitively,which can provide imaging reference for the establishment of new ways of blood supply and reflux in clinical axillary treatment.

Cervical spine health issues not only seriously affect patients' quality of life but also impose a heavy burden on the social healthcare system. Existing guidelines lack sufficient clinical guidance on lifestyle and work habits, such as exercise, posture, daily routine, and diet, making it difficult to meet practical needs. To address this, relying on the China Association of Chinese Medicine, Wangjing Hospital of China Academy of Chinese Medical Sciences took the lead and joined hands with more than ten institutions to form a multidisciplinary guideline development group. For the first time, the group developed the Guidelines for Cervical Spine Health Intervention based on evidence-based medicine methods, strictly following the standardized procedures outlined in the World Health Organization Handbook for Guideline Development and the Guiding Principles for the Formulation/Revision of Clinical Practice Guidelines in China (2022 Edition). This proposal systematically explains the methods and steps for developing the guideline, aiming to make the guideline development process scientific, standardized, and transparent.
Humans ; Practice Guidelines as Topic/standards* ; Cervical Vertebrae ; China

Objective: To investigate the characteristics of malignant tumor incidence and mortality in cancer registration areas of Zhejiang Province in 2021. Methods: Based on the 2021 cancer registration data from 22 national cancer registries in Zhejiang Province, the crude incidence, crude mortality, and cumulative rate for 0 to 74 years were calculated. Age standardized was performed using the age composition of the standard population from the Fifth National Population Census in 2000 and Segi's world standard population. The incidence and mortality characteristics of malignant tumor in different genders, urban/rural areas and ages were described. The order of crude incidence and mortality of malignant tumor were analyzed. Results: In 2021, there were 116 639 new malignant tumor cases in Zhejiang Province. The crude, Chinese population standardized, and world population-standardized incidences were 530.93/100 000, 304.83/100 000, and 288.20/100 000, respectively. The cumulative incidence for 0 to 74 years was 31.92%. There were 40 475 death cases. The crude, Chinese population-standardized, and world population-standardized mortalities were 184.24/100 000, 79.40/100 000, and 78.97/100 000, respectively. The cumulative mortality for 0 to 74 years was 8.37%. The Chinese population-standardized incidence for males and females were 286.34/100 000 and 323.45/100 000, respectively, and the Chinese population-standardized mortality were 106.25/100 000 and 54.17/100 000, respectively. The Chinese population-standardized incidence for urban and rural were 316.85/100 000 and 285.11/100 000, respectively, and the Chinese population-standardized mortality were 75.59/100 000 and 85.48/100 000, respectively. The crude incidence and crude mortality of malignant tumor both increased with age, peaking in the groups aged 80-<80 and ≥85 years at 1 845.06/100 000 and 1 656.88/100 000, respectively. The top ten malignant tumors with the highest crude incidence were, in descending order: lung cancer, thyroid cancer, breast cancer, prostate cancer, colorectal cancer, gastric cancer, liver cancer, cervical cancer, lymphoma, and brain tumors. These accounted for 80.34% of all new malignant tumor cases. The top ten malignant tumors with the highest crude mortality were, in descending order: lung cancer, liver cancer, colorectal cancer, gastric cancer, pancreatic cancer, prostate cancer, breast cancer, esophageal cancer, lymphoma, and gallbladder cancer. These accounted for 82.26% of all malignant tumor deaths. Conclusions In 2021, the cancer registration areas of Zhejiang Province were characterized by a relatively high malignant tumor incidence and a comparatively low mortality compared to national data. Males and the elderly emerged as key populations for targeted prevention and control. It is recommended to enhance screening, early diagnosis, and early treatment for lung cancer, thyroid cancer, prostate cancer, breast cancer, and gastric cancer malignancies.