中国医疗器械杂志最新文献

The gradient coils of MRI equipment can induce vibrations in implantable medical devices, causing periodic vibrations of implantable medical devices with respect to the surrounding tissue. This not only results in instrument failure but also causes discomfort to the patient. Therefore, studying the vibration characteristics of implantable devices under different scanning sequences and the orientation of the device relative to the magnetic field is crucial for comprehending vibration performance. This study observed the vibration spectra of a full cranial bone-implanted neurostimulator by using laser vibrometry under typical rapid imaging sequences and explored the impact of different magnetic field orientations on vibration. The results demonstrated that the rapid echo sequences induced diverse and rich vibration components, whereas the planar echo sequences caused relatively simple vibrations. Additionally, the strongest vibrations normally occurred in the maximum conductive surface parallel to the phase-coded direction. It revealed the factors influencing the vibrations of skull fixation active implantable devices and provided guidance for enhancing device safety and protecting patient well-being during MR examinations.

At present, the C-arm structure accelerators commonly used in radiotherapy equipment are complex in operation and have potential safety hazards when realizing non-coplanar treatment. By combining with medical robotic arm technology, a spherical radiotherapy accelerator motion system is designed. The beam module is clamped by the medical robotic arm structure to achieve three-dimensional multi-angle irradiation treatment within the non-coplanar angle range. Firstly, the rotating mechanism, beam module, and MLC module of the spherical radiotherapy equipment are designed. Then, the double-plane counterweight method is used to calculate the dynamic balance of the equipment, ensuring that the beam center point does not rotate during the treatment process. Finally, the strength check and reliability analysis of the transmission component gear are conducted. The results show that the designed spherical radiotherapy accelerator motion system can meet the requirements of stable, accurate, and fast precision radiotherapy, which is conducive to improving the treatment efficiency.

Brain-computer interface (BCI) technology is an innovative and cutting-edge medical advancement that enables direct interaction between the brain and external devices, facilitating the reconstruction of daily functions for patients or serving as a method for neuro-regulation therapy. Although this technology offers a broad range of clinical applications, there are problems as potential risks, individual variations, and the need for long-term monitoring of its effects during utilization. Consequently, the comprehensive evaluation of its safety and effectiveness poses a considerable challenge for regulatory agencies. This study provides a concise introduction to the development history and various types of BCI technology, followed by a summary of the regulatory situation for different types of BCI medical devices in the United States. Furthermore, the regulatory requirements imposed by the US FDA on this product category are analyzed. Finally, the article concludes by presenting a summary and future perspective on the current development of BCI technology, with the aim of offering beneficial insights and guidance for the regulation of BCI medical devices.

Compared with total knee arthroplasty, unicondylar knee replacement has the advantage of preserving the knee tissue structure and motor function to the greatest extent. Pre-clinical in-vitro test is an important tool to evaluate the safety and effectiveness of unicondylar knee prostheses, and it is also a key focus of the product registration process. Through collection, comparison, and analysis of current regulations, technical standards, guidelines, and related research literature, this paper expounds on the relevant research methods for the pre-clinical in-vitrotesting of unicondylar knee prostheses. At the same time, in conjunction with current evaluation requirements and experience, the study discusses the focus of pre-clinical performance research for unicondylar knee prostheses during the registration process to clarify the performance evaluation requirements of this product category. This aims to provide a reference for the pre-clinical performance research of unicondylar knee prostheses and to standardize industry testing standards.

Objective: To investigate the clinical value of MRI modified water-lipid separation technique (mDIXON-Quant) in terms of T2* values and fat fraction (FF) values for evaluating the degree of cervical intervertebral disc degeneration.

Methods: A total of 118 patients who underwent routine MRI of the cervical vertebra and the mDIXON-Quant examination in Fuyang People's Hospital from March 2019 to January 2024 were collected. The T2* values of C2/3 to C6/7 intervertebral discs and FF values of the upper and lower vertebral bodies were measured. Cervical intervertebral disc degeneration was graded according to the Pfirrmann criteria. The T2* values and FF values of different patients were compared with the Pfirrmann grades, and the correlation between T2* values, FF values, and Pfirrmann grades was analyzed by Spearman correlation.

Results: The T2* values of cervical intervertebral discs in grades I, II, III, IV, and V all showed a decreasing trend ( P＜0.05). The decreasing order of FF values in the upper cervical vertebra was IV, V, III, II, and I ( F=93.28, P＜0.05), and the decreasing order of FF values in the lower cervical vertebra was IV, III, V, II, and I ( F=112.037, P＜0.05). Spearman correlation analysis showed that the T2* values of cervical intervertebral discs were negatively correlated with the Pfirrmann grades ( P＜0.05), and the FF values of the upper and lower vertebrae were positively correlated with the Pfirrmann grades ( P＜0.05).

Conclusion: The mDIXON-Quant technique can be used to quantify the T2* values and FF values of cervical intervertebral disc degeneration and plays an important role in accurate clinical diagnosis and evaluation of treatment effects.

Objective: To lay a foundation for formulating clinical evaluation and regulatory policies regarding radiotherapy equipment in China.

Methods: Comprehensive retrieval and comparison of the regulatory requirements for radiotherapy equipment from regulatory agencies in the United States, the European Union, and China are conducted, and their similarities and differences are analyzed.

Results: For mature radiotherapy systems in the European and American regions, the comparison of performance parameters serves as an important basis for determining whether a product can be marketed. Both the European Union and China regard the clinical evaluation report as a crucial part of the medical device review and submission process.

Conclusion: Identifying clear state of the art standards, performance parameters, and clinical indicator parameters, and establishing relevant technical guidelines are important directions for promoting the standardized development of radiotherapy equipment supervision.

Objective: Automatic planning is a commonly used alternative to manual planning. This study evaluated the clinical performance of automatic plans available in commercial treatment planning systems for nasopharyngeal carcinoma (NPC) treatment by comparing automatic planning with manual planning.

Methods: A total of 14 patients with nasopharyngeal carcinoma were enrolled in the study. For each patient, three different sets of clinical goals were used to generate three hybrid automatic plans based on 3D dose distribution prediction and three automatic plans based on script, respectively, which were compared with the manual plans used in clinic.

Results: The dose coverage performance of the automatic planning based on 3D dose distribution prediction on the planning target volume (PTV) was comparable to that of the manual planning. Automatic planning based on 3D dose prediction achieved the level of manual planning in most organs at risk. However, automatic planning based on scripts did not perform well in the prediction of some organs at risk, especially the parotid gland.

Conclusion: The hybrid automatic plan based on 3D dose distribution prediction can reach the level of manual planning and have good robustness with the change of clinical objective.

To ensure the quality of care for inpatients in ophthalmic hospitals, address the complex and variable conditions of postoperative patients, and conduct more comprehensive, accurate and real-time monitoring of patients, an intelligent monitoring system based on computer vision and artificial intelligence has been designed. This system is employed for real-time monitoring of patient health conditions and intelligent care, with primary applications in medical monitoring, rehabilitation therapy, and inpatient care. It comprises intelligent data acquisition devices, smart cameras, continuous physiological data analysis algorithms, AI algorithms, and software. Given the complex and variable conditions of postoperative patients in ophthalmic hospitals, a comprehensive, accurate, and real-time monitoring of patients is required. Therefore, it is necessary to explore a monitoring technology that imposes low physiological and psychological burdens. The intelligent monitoring system can continuously collect patients' physiological parameter indicators and transmit the monitoring data to doctors' workstations or nurse stations after analysis using intelligent algorithms, providing new tools for patient monitoring, disease assessment, risk warning, and more. Furthermore, through the application of computer vision and artificial intelligence technologies, the system can analyze facial expressions, body postures, and other data to identify patients' emotional states and bedridden postures, enabling the timely detection of abnormal situations and implementation corresponding measures. This helps improving the daily work of medical staff, enhance the nursing safety in single-patient rooms in wards, and potentially find applications in the care of critically ill patients and elderly patients, thereby improving nursing efficiency and quality.

Objective: Referring to the application of the NEH (Nawaz-Enscore-Ham) algorithm in flow shop scheduling, this paper proposes an optimization method of hospital medical consumables discrete scheduling based on the extended NEH algorithm, in order to obtain the optimal medical consumables discrete scheduling scheme and achieve the optimization of medical consumables discrete scheduling.

Methods: Thoroughly analyze the scheduling needs of medical consumables in hospitals, predict the demand for medical consumables in each department. Construct a discrete scheduling optimization model for medical consumables and determine the constraint conditions for building the model (residual coefficient matrix, efficiency constraint matrix, and time window function). Then, solve the discrete scheduling optimization model for medical consumables based on the extended NEH algorithm.

Results: By comparison the data before and after the experiment, it is found that the discrete scheduling time and cost of medical consumables in experimental departments have decreased to varying degrees, and all the differences are statistically significant ( P<0.05).

Conclusion: Through experiments, it is known that the optimized medical consumables discrete scheduling scheme proposed meets the requirements of discrete scheduling time and cost, providing a better solution for hospital medical consumables discrete scheduling.

In recent years, cardiovascular disease has become a common disease. With the development of machine learning and big data technologies, the processing ability of electrocardiogram (ECG) signals has been greatly enhanced through new computer technologies, enabling the auxiliary diagnosis technology for cardiovascular disease (CVD) to achieve new improvements. This article discusses the application of machine learning in ECG processing, especially in the auxiliary diagnosis of diseases. Firstly, the conventional signal preprocessing methods are introduced, and then the EEG signal processing methods based on feature extraction and fuzzy classification are explored. Secondly, the application of auxiliary diagnosis in CVD is further summarized. Finally, the advantages and disadvantages of the two methods are analyzed, and based on this, a design of an auxiliary diagnostic system compatible with the two methods is proposed, providing a new perspective for similar applied researches in the future.