Objective To analyze the global scientific research collaboration trends in the field of digital therapeutics through statistical analysis of digital therapeutics-related papers. Methods Digital therapeutics-related papers were retrieved from literature databases. The trends in the number of papers from different countries and institutions in this field were analyzed, a global collaboration network was constructed. The social network indicators were calculated, and the importance of each country and institution in global collaboration were evaluated using the technique for order preference by similarity to ideal solution (TOPSIS) method. Results As of the retrieval date, there were a total of 3224 scientific papers were identified in the field of digital therapies, with 3171 papers (98.36%) published from 2014 to present. The United States had the highest number of publications (1097 papers), and its collaboration partners (75) and collaboration frequency (851 times) were second only to the United Kingdom. The United States received the highest TOPSIS score due to its central position in the global collaboration network. The United Kingdom ranked second in terms of publication volume (776 papers), with slightly higher number of collaboration partners (77) and collaboration frequency (865 times) compared to the United States, but with a slightly lower TOPSIS score. Harvard University, King’s College London, University College London, University of Oxford, and the University of Melbourne had a significant number of collaboration partners and frequency, resulting in higher TOPSIS scores. Among them, Harvard University and King’s College London had a clear advantage. Conclusion The field of digital therapeutics has rapidly development in the past decade, with the United States and the United Kingdom taking an early lead in scientific research and achieving fruitful results. They occupy a central position in the global collaboration network. Other countries are relatively behind the United States and United Kingdom. Research institutions such as Harvard University and King’s College London have seen a rapid increase in output in recent years, driving the development of the field towards intelligence and personalization.

In recent years, the demand for sterilization and disinfection devices has surged, and ultraviolet sterilization, as the most commonly used sterilization and disinfection method in medical and health systems, has become more popular. The research and development of different emitting ultraviolet light source devices, optical materials and devices have also received great attention. This article investigated the clinical use of ultraviolet light equipment, and ultimately focused on the development status of different light source generation devices that emit ultraviolet C (UVC) light and the related progress in the study of photobiological effects and discussed the construction, emission principle, advantages and disadvantages, and emission wavelength of five light source generation devices that can emit UVC light, including mercury vapor ultraviolet lamps, UVC-LED ultraviolet lamps, excimer ultraviolet lamps, microwave plasma ultraviolet lamps, and laser ultraviolet emitters, and summarized the photobiological effects and analyzed their potential medical application prospect.

As a new non-antibiotic treatment method, ultraviolet in the wavelength range of 100-400 nm has been shown to have certain antibacterial properties. The sterilization effect varies from wavelength to wavelength of ultraviolet, and the biosafety also varies. In recent years, lots of research reports have emerged in this field, especially for ultraviolet C (UVC) in the wavelength range of 200-280 nm, which has become a hot research topic. This paper reviewed the new findings in this wavelength range, including the mechanism, factors and effectiveness of action of UVC inactivation of different pathogenic microorganisms, analyzed the biosafety of UVC technology, and also briefly summarized the research progress of UVC technical devices in clinical applications, aiming to provide a reference for related research.

Objective To explore the effects of 275 nm ultraviolet C (UVC) light irradiation on the survival and growth of skin cells and vascular endothelial cells, as well as the effects of long-term and short-term irradiation on the skin of nude mice, and to identify its safety. Methods Human immortalized keratinocytes cells and human umbilical vein endothelial cells were irradiated with 275 nm UVC-LED light source developed, designed and processed by the laboratory for different durations to observe the effects of different irradiation dosages on the survival and growth of the cells; the nude mice skin was irradiated for different durations to observe changes in the appearance of the skin, and tissues of irradiated areas were collected for immunohistochemical analysis. Results For low doses of direct irradiation of cells, 275 nm UVC light had certain skin-related cell safety. However, the high dose of 275 nm UVC light irradiation caused more damage to the cells. Meanwhile, neither low-dose nor high-dose irradiation of 275 nm UVC light induced DNA and epidermal damage in nude mice skin. Conclusion The 275 nm UVC light has been identified as promising for clinical applications, and is relatively safe for the skin.

As the importance of preventing the spread of pathogens in the air becomes increasingly prominent, and it is crucial to seek effective air disinfection technology. Upper space ultraviolet irradiation technology, as an efficient, economical and “human-machine coexistence” air disinfection solution, has long been used to prevent the spread of tuberculosis. With the development of solid-state ultraviolet light sources, the new upper space ultraviolet irradiation system has made many improvements compared to traditional systems in terms of light source upgrades, beam shaping, and structural design. The optimization of beam shaping allows ultraviolet rays to irradiate target areas more accurately, improving the disinfection effect. This paper reviewed the upper space ultraviolet irradiation system, discussed the technical principles, research and development status, application fields, and forecasted the future development trends.

Objective To design and manufacture an isolation laminar flow bed based on deep ultraviolet disinfection, in order to meet the clinical demand for sterile laminar flow bed. Methods The traditional laminar flow bed disinfection method was replaced by deep ultraviolet disinfection, and was magnetic opening and closing, and the connection between the bed curtain and the top of the bed was made of environmentally friendly PVC with acrylic adhesive, and the laminar flow effect inside the bed was tested using ANSYS fluid simulation to exhaust from the bottom of the overall upper air intake and exhaust from the bottom of the bed. Results The sterile laminar flow bed initially achieved the effect of isolation, the flow simulation results showed that the laminar flow effect in the bed was good. Conclusion The isolation laminar flow bed based on deep ultraviolet disinfection can achieve the laminar flow effect well under the condition of meeting the isolation conditions, and has better clinical application value and significance.

Objective To analyze the reliability level of positron emission tomography/magnetic resonance imaging (PET/MR) equipment during clinical using the basic method of reliability verification. Methods The data including maintenance and work log of two PET/MR equipment (PET/MR-1 and PET/MR-2) for a certain period of time were extracted, and the reliability parameters, maintainability parameters, supportability parameters, availability and core component status of the equipment were analyzed. The reliability level of the two equipments was compared. Results The total failure time of PET/MR-2 was 253.0 h less than that of PET/ MR-1, reducing 27.4%. The mean interfailure time of PET/MR-2 was 206.2 h longer than that of PET/MR-1 (P<0.05). There was no statistical difference in the reliability parameters of the two devices (P>0.05), and the state parameters of the core components basically maintained stable operation. However, the PET/MR-1 caused two major failures of the core components due to the failure of the auxiliary system. Conclusion Based on the basic method of reliability verification, the analysis of the reliability level of PET/ MR equipment in the clinical use process can provide an objective evaluation of the long-term stability of the equipment for medical institutions, and indicate the direction of the key points of maintenance work.

Objective To explore the human-machine interface collaboration of positron emission tomography/magnetic resonance imaging (PET/MR) equipment, and to explore the clinical usability evaluation method of this kind of equipment. Methods The usability evaluation system was established by using analytic hierarchy process, an expert group was set up and the expert authority coefficient was calculated. The usability questionnaire was designed by Delphi method, and the technicians and doctors who operated the equipment were investigated, and the questionnaire scoring table of UIH PET/MR equipment was collected nationwide. Results A total of 79 survey questionnaires were collected, involving 18 hospitals. The usability evaluation score of the physiological signal gating unit interface was the lowest, and the PET passive quality control usability evaluation score was the highest. Personnel with deputy senior or senior professional titles had slightly higher scores on indicators than those with intermediate or lower levels. The scores of personnel with different operating hours on various interfaces had the same trend, and the scores of users within 3 months were significantly lower than the other two groups, with significant differences (P<0.05). There were significant differences in the scores of six specific evaluation parameters among personnel with different operating hours (P<0.05). Conclusion The usability evaluation system established based on the analytic hierarchy process can be used for the clinical usability evaluation of PET/MR devices. The usability survey questionnaire formed based on the Delphi method provides a strong reference for exploring the usability evaluation methods of PET/MR devices.

Objective To evaluate the reliability of positron emission tomography/computed tomography (PET/CT) equipment inclinical use, to analyze the key parameters affecting the quality control pass rate, and to explore the specific practical methods for evaluating the reliability of equipment in use. Methods The maintenance records of PET/CT equipment were reviewed and analyzed, and the parameters related to the availability, maintenance and maintenance of PET/CT equipment were counted. The pass rates of active quality control LUT drift, energy drift, and TOF drift of PET detectors were calculated and analyzed by Pearson correlation with environmental factors. Results Both inherent availability (Ainh) and reachable availability (Aa) consistently exceeded 98%, and the change trend of both was consistent, and Aa was slightly lower. The mean time between failure peak occurred in the fourth year and exceeded the average level of the three years prior to commissioning. The LUT drift coefficient had a 100% pass rate and was significantly negatively correlated with system humidity (r=-0.133, P=0.025). The energy drift coefficient had a 78.32% quality control pass rate, significantly correlated with the outer ring temperature (r=0.162, P=0.006). Therefore, it was advisable for operators to monitor the temperature and humidity of the machine room closely. Conclusion In the fourth year since commissioning, the PET/CT equipment has progressed from the initial stage to the normal period stage. During PET detector quality control, it was found that the energy drift coefficient often goes out of range, which may be related to environmental factors. This study outlines practical methods for evaluating the reliability of PET/CT equipment in clinical use, offering valuable reference information for improving reliability and comparing equipment.

Objective To analyze the long-term stability of magnetic resonance imaging (MRI) equipment performance using Minitab. Methods The Minitab 17.0 software was used to analyze the long-term stability of the performance of three MRI devices (MRI-1, MRI-2 and MRI-3). The analysis of performance test items included image homogeneity, signal-to-noise ratio, slice thickness, and aspect ratio. The spatial resolution of MRI was analyzed using time-series method. Results The long-term quality control process for most performance testing items was classified as level Ⅰ, with a process performance index Pp>1.67; for MRI-1 and MRI-2 devices, the process performance of all testing items was at least level Ⅱ or higher; the image homogeneity of MRI-3 equipment was classified as level Ⅳ, indicating that the influence factors should be identified and the frequency of testing should be increased. Conclusion By using Minitab to perform process capability analysis on MRI equipment, it is possible to objectively assess the performance stability throughout the life cycle of MRI equipment, which is helpful in monitoring the operation status of the equipment and determining the frequency of quality control testing; the results of process performance analysis can be used to assess the maintenance status of the equipment and determine the replacement cycle of key components. This ensures that the performance of equipment remains in a good state, provides a reliable foundation for diagnosis and therapeutic services.

Objective To study the human-computer interaction usability of linear digital radiography (DR) equipment based on the usability concept of human-computer interaction research orientation. Methods The expert group of this project discussed and determined the project indicators of usability evaluation, and established the usability evaluation model using Delphi method. By users’ scoring five domestic DR models respectively, the usability evaluation results among user groups of different using time on different models were compared. Results The mean total score and interface score of the 5 DR models showed significant differences among the three groups (P<0.05). The score of the group with less than 3 months was significantly lower than the scores of the other groups, while there was no significant difference between the other two groups (P>0.05). In addition, the usability evaluation results of different DR models were significantly different in terms of the average total score and the group with more than 1 year. Conclusion Usability evaluation can have a comprehensive view on the safety and effectiveness of DR man-machine interfaces, which is helpful to the research and development of DR equipment and the improvement of domestic equipment.

Objective To collect the eyeground color images of diabetic patients, and to establish a computer vision model, to explore its application in the referral of diabetic retinopathy (DR). Methods The eyeground images of diabetic patients in Suzhou area were collected. The training set (n=350) and the internal validation set (n=100) were from Lixiang Eye Hospital of Soochow University, and the test set (n=200) was from Suzhou Municipal Hospital. The eyeground photos were classified into referrable DR group and the non-referrable DR group. The performance of models was evaluated based on test set and compared with two ophthalmologists. In addition, the Grad-CAM technology was used to visually interpret the computer vision model. Results The performance ofEfficientNet model was the best among all models and superior to specificity for ophthalmologists with low years of experience [accuracy (ACC) was 0.840, sensitivity (SE) was 0.793, and specificity (SP) was 0.859]. However, it was slightly lower than that of senior physicians (ACC was 0.925, SE was 0.862, SP was 0.951). With the assistance of the EfficientNet model, the ACC rose to 0.915, SE to 0.828, and SP to 0.951. Similarly, the ACC of senior physicians reached 0.965, SE was 0.931, and SP was 0.979. Conclusion Computer vision models based on deep convolutional neural networks show practicable performance in DR referral binary classification, better than junior ophthalmologist. The model can assist ophthalmologists in diagnosis and improve ACC.

Objective To explore the application of automated machine learning (AutoML) based on the texture features in distinguishing early and advanced stages of esophageal squamous cell carcinoma by magnifying endoscopy with narrow-band imaging (NBI-ME). Methods A total of 1507 NBI-ME images of esophageal squamous cell carcinoma were collected from the Endoscopy Centre of The First Affiliated Hospital of Soochow University. These images were randomly divided into a training set (n=1264) and a validation set (n=243). MATLAB software was used to extract a total of 32 texture features from the whole endoscopic images. The above variables were loaded into the H2O platform for AutoML binary classification modeling. In addition, 278 endoscopic images from the Second Affiliated Hospital of Soochow University were collected as an external test set. Moreover, one junior endoscopist and one senior endoscopist were invited to interpret the images from the external test set. Receiver operating characteristic (ROC) area under curve (AUC) and accuracy (ACC) were used to evaluate the efficiency of identification. Results The AutoML model based on random forest algorithm performed best in the external test set, with AUC of 0.975 and ACC of 0.939, which was significantly better than other models, including the generalized linear model (AUC: 0.776, ACC: 0.687) and the extreme gradient boosting model (AUC: 0.968, ACC: 0.863). It was also better than that of the junior endoscopist (AUC: 0.868, ACC: 0.871) and the senior endoscopist (AUC: 0.919, ACC: 0.921). Conclusion The AutoML model based on the texture features of endoscopic images shows excellent discriminative ability in judging the staging of esophageal carcinoma.

Objective To develop computer vision models for endoscopic bowel preparation scoring based on deep learning. Methods A total of 2394 endoscopic images from the Gastrointestinal Endoscopy Centre of the First Affiliated Hospital of Soochow University (n=600) and the HyperKvasir database (n=1794) were collected, scored by endoscopists according to the Boston bowel preparation scale (BBPS, 0-3, four categories). They were randomly divided into training sets (1439 pieces), verification sets (478 pieces) and test sets (477 pieces) according to 6∶2∶2. Three deep learning networks (DenseNet169, DenseNet121, EfficientNet B3) were used to develop the bowel preparation classification models by transfer learning. Metrics such as confusion matrices in the test set were used for model evaluation. Meanwhile, the models were compared with senior and junior endoscopists. Results The three deep learning-based bowel preparation classification models were successfully developed. The classification accuracy of all models was high, and the average classification accuracy was 0.897, which was similar to the clarification performance of junior endoscopist (0.914) and lower than that of senior endoscopist (0.941). Among them, the best performing model was the DenseNet169 model, which had the highest classification accuracy (0.914) and the highest average precision (0.892). In addition, the visual interpretation of the models’ classification results was presented in the form of heat maps by using gradient-weighted class activation mapping. Conclusion The endoscopic bowel preparation classification model developed using deep learning is feasible, and the classification and generalization ability of the model can be further improved by expanding the sample source through multicenter studies.

Objective To explore the application effects of the model constructed by using deep convolutional neural networks (DCNNs) and transfer learning in the diagnosis of osteoporosis based on knee joint X-ray images. Methods The knee joint X-ray images were collected from Jintan Hospital Affiliated to Jiangsu University, which were randomly classified into training set (n=400) and internal validation set (n=100) at a ratio of 8∶2. Four DCNNs (ResNet, Xception, NASNet and EfficientNet) were selected, which had been pre-trained in ImageNet dataset, and the parameters of their first pre-training were frozen as the model framework of the single training group. A total of 5856 images were randomly selected from the Kermany Chest X-Ray2017 dataset and performed secondary pre-training on these four DCNNs as the model framework for the secondary training group. Two sets of model frameworks were used for target-training on knee joint X-ray image, and a classification model for osteoporosis was constructed. Eighty-five images were randomly selected from the Wani-Knee X-Ray2021 dataset as anexternal test set. The performance of the classification model was evaluated according to its performance in internal validation and external test sets. Results The accuracy of the models in the secondary training group was higher than that in the single training group. Among the four DCNNs, EfficientNet model performed significantly better than the other three models. In the internal validation set, the accuracy of EfficientNet model in the secondary training group was 0.918, with F1-score 0.918, and the area under curve (AUC) of receiver operating characteristic was 0.932; in the external test set, the accuracy was 0.824, F1-score was 0.848, and AUC was 0.846. Conclusion The knee joint X-ray deep learning model established by chest X-ray secondary pre-training is superior to the single pre-training model in the application of osteoporosis classification. The use of DCNNs and transfer learning techniques can help small sample datasets perform tasks such as classification and prediction more accurately.

Objective Based on DeepLab V3+ network framework, to construct a deep learning computer vision model to achieve more accurate semantic segmentation of upper gastrointestinal ulcer endoscopic images. Methods The encoder of the DeepLab V3+ network framework initially extracted features from images using multiple parallel dilated convolutional layers with varying sampling rates, followed by global average pooling to achieve multi-scale feature extraction. In the decoder section, the deep feature layer was up-sampled four times while the shallow feature layer was stacked and adjusted in size to match that of the input image before generating predictions. The prediction results of the model were obtained. Results In the internal validation set, the accuracy (ACC) of the model was 0.963, and the mean intersection over union (mIoU) was 0.927. In the external test set, the ACC and mIoU were 0.958 and 0.915. All of them were better than the traditional algorithm U-Net (internal validation set ACC was 0.810, mIoU was 0.785; the external test set ACC was 0.779 and mIoU was 0.732). Conclusion The DeepLab V3+ network framework has high accuracy in identifying lesions, and has good clinical practice.

Cerenkov luminescence (CL) is a luminescence phenomenon with spectral peaks located near blue-violet light, which has been extensively studied in medical diagnosis and treatment since its discovery. Medical imaging technology based on Cerenkov luminescence has the characteristics of remote, non-invasive and efficient, and is expected to become a reliable dose assessment tool in clinical radiotherapy. On the basis of expounding the mechanism of CL phenomenon, this paper further reviews the related technology in tumor radiotherapy, in order to provide more reference for the monitoring, evaluation and quality assurance of tumor radiotherapy.

Pulmonary diseases have a significant impact on human health and life safety, and abnormalities in the lungs are a direct response to lung diseases. The study of lung sounds is of great significance in clinical diagnosis. With the continuous development of electronic auscultation technology, the feature extraction and classification techniques of modern lung sounds have also been further studied. At present, the research of lung sound classification is to combine signal analysis with deep learning algorithm to improve the practical application of auxiliary electronic stethoscope. This paperaims to elaborate on the concept of lung sounds, analyze the current development status of lung sound classification, and discuss the shortcomings of lung sound classification technology. The goal is to an outlook on future research directions and application development trends in the field of lung sound classification.

Cerebral microbleeds (CMBs) is one of the most common imaging markers in the brain of elderly patients with cerebral small vessel disease (CSVD). It can be used as a marker of the severity of other imaging features of CSVD and is closely related to cognitive function, but it is difficult to be detected under conventional sequences. In recent years, the rapid emergence of specific magnetic sensitive new sequences for CMBs lesions has continuously improved the detection rate of CMBs, but different sequences have different imaging mechanisms and diagnostic advantages, and the applicable research levels are also different. The purpose of this paper is to review the detection efficiency of different magnetic sensitive new sequences for cerebral microbleeds, in order to recommend an efficient imaging diagnosis method for CMBs and improve the diagnosis rate of CSVD disease.

The occurrence of patients falling or falling out of bed will bring heavy burden to the patients themselves and the society. In recent years, the deep integration of “Internet of Things + medical” has developed rapidly. Internet of things technology is used to monitor and warn patients’ fall events. This paper reviews the technical equipment, classification and application of the Internet of Things monitoring and early warning system for patients’ falls. The purpose of this paper is to summarize the relevant experience and shortcomings of the application of Internet of Things technology in monitoring and early warning of patients’ falls and falling bed events, and to provide reference for follow-up research.

The multi-dimensional and multi-parameter imaging of dual energy spectrum CT can be used for the diagnosis and differential diagnosis of tumors, prediction of pathological grading, tumor prognosis and curative effect follow-up. For the application of dual energy spectrum CT to renal cell carcinoma, it mainly focuses on the virtual flat scan single energy image/iodine map, helpful for the discovery of renal masses, the correlation between the characteristics of energy spectrum curve and pathological grading, the diagnosis and differential diagnosis of different histological types of renal cell carcinoma, perfusion imaging and microvascular development of renal cell carcinoma, efficacy evaluation of comprehensive treatment, radiomics and texture analysis,etc. The purpose of this paper is to explain the basic principle of dual-energy spectral CT imaging and its wide application in clinic, and to review the emerging radiomics and artificial intelligence in recent years.

Acute respiratory distress syndrome (ARDS) is a common critical illness caused by acute lung injury in clinical practice. There are significant differences between individuals, difficult treatment, and high mortality rates, and personalized monitoring and guidance are urgently needed. The existing classical monitoring means such as CT and single photon emission computed tomography cannot simultaneously realize the non-invasive, bedside and visual monitoring of ARDS mechanical ventilation treatment. The electrical impedance tomography (EIT) technology, as a new non-invasive functional imaging tool, has been increasingly applied to the whole process management of ARDS patient treatment. This article aims to review the principles, functions, and application progress of EIT technology in the whole process management of mechanical ventilation treatment for ARDS patients, in order to provide a reference basis for the development of EIT technology and further research on its clinical application in ARDS.

Magnetic response shape memory polymer shape memory polymer (SMP) is a new type of material that realizes magnetic response by introducing magnetic particles on the basis of SMP. Its remote non-contact conduction control method provides a new solution for clinical treatment and the development of new intelligent medical equipment. This paper aims to introduce the concept of magnetothermal effect and expound the mechanism of magnetothermal response shape memory, review the research progress of magnetic response SMP in different fields of medicine, especially the innovative combination with 4D printing technology, analyze the advantages and problems of magnetic response SMP, and prospect the future application.

Anterior cruciate ligament reconstruction (ACLR) of knee joint is the primary treatment for anterior cruciate ligament (ACL) injury. Anterolateral structure reconstruction (ALSR) is used in patients with high axial displacement of the ACL that cannot be resolved by ACLR. In recent years, many studies have shown that ALSR can reduce the residual axial displacement of the knee joint after pure ACLR and maintain its rotational stability. In order to further understand the research progress of ALSR, this paper aims to summarize the anatomy of anatomical structure, biomechanical characteristics, surgical indications of ALSR, clinical outcomes and surgical methods, to guide clinical diagnosis and treatment.

The comprehensive evaluation for the value of medical consumables is carried out from multiple dimensions such as safety, effectiveness, and economy, with the aim of providing auxiliary support for decision-making related to medical consumables in the health field, so as to improve the scientificity, homogeneity and standardization of decision-making. This paper aims to review the research progress of comprehensive evaluation methods for the value of medical consumables both domestically and internationally, with the aim of providing reference for further promoting the development and application of value comprehensive evaluation methods in the field of medical consumables in China.

The external interventional therapy device has the characteristics of non-contact with blood, fundamentally avoiding blood infection, blood biocompatibility and other problems, and has important research significance in the treatment of cardiovascular diseases. This paper summarized and classified the functional characteristics of external interventional therapy devices, briefly described the basic theory of external interventional therapy devices and the main research results achieved at present, and analyzed the future development trend of external interventional therapy devices, providing reference for further research and development and clinical transformation of such devices.

In recent years, the application research of 3D printing technology in gynecology has been increasing, effectively promoting the development of gynecology in the medical field. 3D printing can achieve refined and personalized diagnosis and treatment of various gynecological diseases, with significant clinical application effects and broad application prospects in gynecology, which is conducive to improving the diagnosis and treatment level of doctors. This paper aims to explain the specific application of 3D printing model, design of 3D printing source applicator, 3D printing template and 3D bioprinting in gynecology, summarizes the advantages and disadvantages of 3D printing technology in gynecology, in order to provide new ideas for clinical work.

The early diagnosis of cervical spondylotic myelopathy (CSM) allows doctors to timely intervene with patients and formulate treatment plans, which is of great clinical significance for the functional recovery of patients. It is a direction that spine surgery has been exploring in recent years. With the advancement of science and technology, more and more new technologies have been applied to the clinical treatment of CSM. Diffusion tensor imaging (DTI) has made it possible to evaluate microstructures of the spinal cord. Compared with traditional MRI, DTI has a higher sensitivity and also plays an important role in predicting the prognosis of spinal cord diseases. This paper reviewed the application and technical progress of DTI in CSM in recent years from the perspective of clinical application, in order to provide reference for the clinical diagnosis and treatment of CSM.

Intra-operative radiation therapy (IORT) is a single high-dose radiation therapy that is administered during surgery to the tumor bed, visible tumors, or sites prone to recurrence and metastasis of patients. In view of of its clinical advantages, IORT has shown a rapid development trend in the treatment of various cancers at home and abroad. However, there is a lack of systematic research on existing IORT devices in China. This paper analyzed and introduced the problems in clinical application of the equipment and technology of the main manufacturers of IORT in detail, and provided suggestion for the future procurement and research and development of hospitals and research and development units, so as to promote the further development of clinical and medical equipment in the field of IORT.

Coronary CT angiography (CCTA) has become an important non-invasive method for the evaluation of coronary artery disease. With the wide application of CCTA in clinical practice, its high radiation carcinogenic risk and adverse reactions of contrast medium have attracted more and more attention. Double-low scanning (low radiation dose and low contrast medium dosage) is a research hotspot of CT angiography at present, which reduces radiation dose and iodine contrast medium dosage on the premise of ensuring diagnostic efficiency. Especially with the rapid development of computer technology, iterative reconstruction algorithm provides more powerful power for double-low scanning, and its application prospect is more extensive. This paper reviewed the history and clinical application of CCTA, and the application and research progress of double-low scanning in CCTA, in order to provide reference for the clinical diagnosis of coronary artery disease in the future.

The advent of laparoscopic surgical robots has reduced the surgical trauma of patients, shortened the postoperative recovery period, and promoted the development of surgery toward precision and minimally invasive surgery. However, its narrow surgical field of view and lack of physical feedback have increased the difficulty of surgery. In recent years, with the advancement of augmented reality (AR) technology, it has gradually been widely used in the medical field. Due to its visualization characteristics, augmented reality has unique advantages in intraoperative navigation in surgical procedures (especially in laparoscopic surgery). In laparoscopic robotic surgery, the use of an augmented reality-based intraoperative navigation system can significantly enhance the surgeon’s perception of the surgical environment and help improve surgical safety and precision. This paper reviewed current research advances in augmented reality technology and its current status of application in laparoscopic robotic surgery.

Airway management is an important technique of respiratory support therapy. Poor airway management may lead to body injury, brain hypoxia and even death. Preoperative airway evaluation is essential for perioperative airway management, and it is also a hot issue and key field of anesthesiology at home and abroad. This paper we summarized many difficult airway predictors, patented technologies of difficult airway evaluation, decision support system of difficult airway evaluation and its implementation in order to understand the technology development and give some advice on the research and application of difficult airway predictors and decision-making process.

Infectious diseases caused by pathogenic microorganisms seriously threaten human health. At present, there are a variety of microbial analysis methods, such as enzyme-linked immunosorbent assay, polymerase chain reaction and microscopebased morphological detection methods, among which the morphological detection method has the characteristics of low cost and high accuracy. With the development of computer technology and the continuous exploration of the application of artificial intelligence (AI) in the field of biomedicine, automatic morphological recognition of microbiological images under the microscope has become possible. This paper aims to analyze the application of morphological diagnosis techniques based on AI in viruses, bacteria, parasites and fungi at home and abroad in recent years, and to discuss shortcomings and challenges of the existing research, to further propose a new research idea: the development of a fully automatic portable highly pathogenic microorganism analyzer using AI, miniaturization, automatic control and other technologies. The device will be used for real-time detection of pathogenic microorganisms, which is of great significance for biosafety early warning.

Endotracheal intubation is one of the common methods to solve breathing difficulties through mechanical ventilation during emergency treatment, but the treatment is often delayed due to the lack of professional medical staff during out-of-hospital emergency treatment, and the treatment of patients with respiratory infectious diseases will increase the exposure risk of medical staff. Remote endotracheal intubation technology realizes remote and accurate endotracheal intubation through robot, optical/magnetic navigation, multi-modal sensing and artificial intelligence technologies, effectively improving the success rate of intubation treatment and significantly reducing the risk of infection. The paper searched and combed the patent applications of technologies and devices related to remote endotracheal intubation, summarized and discussed in four directions, including the distribution of patent applications, key technologies, development trends and future application scenarios, clarified the advantages of current technologies, and expounded the potential limitations, in order to provide beneficial enlightenment for the research and development of intelligent medical devices for remote endotracheal intubation.

With the progress of the research on basilar invagination (BI) with atlantoaxial dislocation (AAD), the surgery of the skull base area has been widely used. Due to the complexity of the structure of the skull base and the difficulty of observing it, the exacerbation of the symptoms caused by the failure of the first operation is not an isolated phenomenon. As a result, the revision surgery for the failed first operation is also receiving more and more attention. Revision surgery is more difficult and complicated than the primary surgery, and there are few relevant literatures. This paper aims to review the progress of revision surgery in BI patients with AAD, and explain it from four perspectives: the reasons for revision surgery, surgical treatment strategies, related assistive technologies, and the future prospects of such revision surgery.

Neuroblastoma (NB) is a solid tumor that often occurs in infants and high risk patients usually with poor prognosis. Studying the role of exosomes in NB is conducive to early diagnosis and accurate treatment of the disease. This paper focuses on describing characteristics of exosomes and its role in the occurrence, development, invasion, metastasis and resistance of tumors. The diagnostic and therapeutic value of exosomes and its clinical application were analyzed. The research is expected to provide noninvasive, rapid and sensitive early diagnosis ways for patients, and provide strategies and basic ideas for the development of in vitro diagnostic reagents for NB exosomes, which is conducive to improving the quality of life and survival rate of children.

The edge products of medical devices referred to herein involve the collection and monitoring of human physiological data, the regulation of physiological functions, and the relief of disease symptoms, which are related to the health of the public. With the growth of product types and market size, the control of their safety and effectiveness is an urgent task faced by regulatory authorities. The regulatory authorities need to first clarify its management attributes in order to determine reasonable regulatory policies. At present, although there are documents such as The Classification Catalogue of Medical Devices which can be used as the basis for the definition of management attributes of some edge products, it still cannot cover all such products. There are still issues with defining product management attributes in regulatory work, and even regulatory loopholes that have caused confusion for manufacturers and users. This paper first clarifies three situations of medical device edge products from regulatory perspective, and analyzes the current international and domestic relevant regulations, documents and regulatory policies. Combined with the current product characteristics, the key elements such as working mechanism, structural design, application scenarios and population were analyzed in detail, and the conditions required for various products to be used as medical device management are clarified. This paper puts forward technical suggestions for the definition of management attributes and provides reference for the regulatory authorities and industry.

Accurate preoperative prediction of tumor regression grade (TRG) after neoadjuvant chemoradiotherapy (NCRT) in patients with locally advanced rectal cancer before surgery can help to provide an individualized treatment plan for patients. Imaging methods are the primary means of predicting TRG, but the predictive efficacy of traditional imaging methods is unsatisfactory. The development of several new imaging techniques, including contrast enhanced and functional imaging, provides new means, radiomics can provide more objective support for clinical concerns such as efficacy, prognosis, and treatment decisions by using computers to identify deep-seated information in a large number of images. This paper aims to review a large number of applied studies on imaging to predict TRG in rectal cancer after NCRT, to understand its latest progress.

Objective Aiming at the case that the radiotherapy marker appears in two slices of CT image series, a method is proposed to determine the longitudinal position of the center of marker based on the volume ratio (VR) of marker structures, and then to determine the longitudinal position of the primary isocenter of radiotherapy, and the method is tested and preliminarily applied. Methods A Siemens CT simulator was used to scan the water phantom and a metal marker on it by using the radiotherapy pelvic scanning protocol RT_Pelvis, and the slice thickness and interval were both 5 mm. According to different reconstructed initial position offsets (ΔBegin), 50 different CT image series were reconstructed at an interval of 0.1 mm, corresponding to 50 nominal longitudinal position deviations of the center of marker (ΔLNGm). For the CT image series in which the marker appeared on two slices, corresponding two structures of marker were obtained by manually delineating, and the volume ratio (VR) of marker structures was calculated to study the variation trend of VR with the longitudinal position deviation of theΔLNGm. Finally, 20 patients with pelvic tumors were selected, and the above variation trend was applied to calculate the values of ΔLNGm, and then obtain the corresponding data of the longitudinal position of primary isocenter. Results The ΔBegin values range from 1.9 mm to 3.7 mm in 19 CT image sequences, and the marks appear on the two-layer CT images,and the marks appear on the two-layer CT images. As ΔLNGm gradually increased from 1.6 mm to 2.5 mm, the VR value also gradually increased from close to 0 to 1. Using the formula: VR=a+b×ΔLNGm +c×ΔLNGm 2 for fitting, the values of a, b and c were 0.7334, -1.4277 mm-1 and 0.6129 mm-2, respectively. For the selected 20 patients with pelvic tumors, values of VR were calculated by delineating the structures of the marker, and ΔLNGm was calculated by manually looking up tables and using formulas to solve equations. The results of the two above methods were consistent. Conclusion For the case where the radiotherapy marker appear in two slices of CT image series, the structure VR of the marker changes with the ΔLNG at the center of the marker. Using this trend, the longitudinal position of the center of marker can be calculated, and then the longitudinal position of the primary isocenter can be determined. This study provides a useful reference for medical physicists to determine the precise location of the primary isocenter in radiotherapy.

Objective To evaluate and compare the accuracy of three domestic softwares including PVMED-iCurve, AccuContour and DeepViewer on automatic delineation of the brain stem structure for patients with head and neck neoplasms. Methods A total of 20 patients with head and neck neoplasms were enrolled from January 2021 to October 2022. The brain stem structure of patients with head and neck neoplasms was automatically delineated by using PVMED-iCurve, AccuContour and DeepViewer respectively. Taking manual delineation as the reference standard, compared the results of volume difference (ΔV%), Hausdorff distance (HD), and Dice similarity coefficients (DSC) of the above three kinds of automatic delineation, the effect of the three kinds of software on automatic delineation of brain stem structure was evaluated. Results PVMED-iCurve, AccuContour and DeepViewer were used to automatically delineate the brain stem structure of patients with head and neck neoplasms, and ΔV% were 6.01%±17.77%, -2.49%±9.33% and -9.68%±11.17% respectively. HD were (7.74±3.05), (2.83±1.18) and (4.00±2.16) mm respectively. DSC were 0.81±0.05, 0.89±0.05 and 0.85±0.06 respectively. Pairwise comparison between the three software showed statistically significant differences in DSC (P<0.05). Conclusion The three kinds of software can automatically delineate the brain stem structure of patients with head and neck neoplasms, and all can achieve good sketching effect. Compared with the three kinds of software, AccuContour is best in volume, position and shape of automatically delineating the brain stem.