中国医疗器械杂志最新文献

The digital surgical suction system integrates Intelligent digital technologies, features rapid iterations, and has complex components and high control accuracy requirements, which puts forward higher requirements for product quality control and medical device quality management system certification. This study puts forward the key points for quality management system certification in manufacturing of such products through the analysis of the technical characteristics and product life cycle risk of digital surgical suction system, combined with the requirements of ISO 13485:2016 medical device quality management system for regulations. It has certain reference significance for the quality management of enterprises and the medical device quality management system audit of certification bodies.

Aiming at the challenges of poor sampling accuracy, unstable reagent test results, and excessive carryover contamination in high-speed biochemical analyzers, this study systematically investigated the structural design methodology of sampling needles, using Company A's Project B as a case study. The design focused on precise adjustment of needle core dimensions, the application of variable-diameter structures, and strict control of the inner and outer wall roughness of the needle core. Reynolds number calculations and ANSYS simulations were employed to ensure optimal fluid dynamics and needle strength, resulting in the successful development of a sampling needle structure compatible with high-speed instruments. Roughness measurements were conducted on sampling needles from different manufacturers, followed by tests on small-volume quantification, reagent performance, and carryover contamination. The results were analyzed in depth based on varying roughness levels. The research demonstrates that needle core dimensions and variable-diameter structures significantly influence fluid dynamics during sampling and needle strength. The optimized needle structure notably improves sampling stability and precision, enhances cleaning efficiency, and reduces residual liquid adhesion. Furthermore, the scientific setting of parameters such as inner and outer wall roughness is identified as a critical factor determining the overall performance of biochemical analyzers, including quantification accuracy, reagent test reliability, and carryover contamination levels.

Recombinant collagen has emerged as a core material for medical device innovation due to its programmable molecular structure, excellent biocompatibility, and scalable production capabilities. This article reviews the application value of recombinant collagen in regenerative medicine, tissue engineering, drug delivery, and wound repair. By combining molecular design strategies with innovative preparation processes, the intrinsic relationship between material properties and clinical efficacy is elucidated. The review explores bottlenecks in clinical translation and highlights emerging trends, such as AI-driven design for predicting material performance via machine learning and 3D bioprinting technology for promoting the regeneration of complex organs. These advancements demonstrate the multi-dimensional application potential of recombinant collagen and drive its efficient translation from laboratory research to clinical applications.

Digital therapeutics, as a clinically evidence-based medical intervention driven by software programs, have shown immense potential in the early screening, diagnosis, management, and rehabilitation of cardiovascular diseases. This article firstly succinctly outlines the advantages of digital therapeutics in real-time monitoring, personalized and precise management, improving adherence, and optimizing healthcare resources. And then it systematically analyzes the relevant research findings and clinical application value of digital therapeutics in common cardiovascular diseases. Additionally, it delves into the challenges of evidence-based practices, regulation, and data security, and proposes strategies to address these issues, considering patient experience, medical practice, and ethical and legal concerns. The goal is to further promote the role of digital therapeutics in the treatment of cardiovascular diseases and provide new pathways for constructing an efficient, accessible, and secure digital diagnosis and treatment system.

Canaloplasty is a new and effective method for the treatment of glaucoma. During the procedure, a flexible microcatheter equipped with an optical fiber must be inserted and navigated within the Schlemm's canal. However, due to the difficulty in controlling the direction of the catheter during insertion, the success rate of the surgery depends on the experience and proficiency of the surgeon. This paper proposed a magnetic navigation system based on electromagnets to guide the direction of the catheter and assist the surgeon in smoothly performing the catheter insertion operation. The layout of the system was designed based on the requirements of the operation, and the current of the electromagnet was calculated by the optimization algorithm to achieve the control of the magnetic field. Simulations confirmed that the magnetic field variations during the navigation process were within the feasible solution domain, indicating that the system's solution space could meet the requirements for navigating the magnet along the target path. Finally, experiments were conducted for further validation, demonstrating that the system could achieve positional control of the catheter, guiding the magnet along a predetermined path.

With the widespread application of medical device software in clinical diagnosis and treatment, the accuracy and reliability of graphics measurement functions, which are core modules of medical device software, directly impact the quality of medical decision-making. However, the current lack of standardized testing methods both domestically and internationally has led to inconsistencies in verification approaches and testing protocols. Addressing the standardized testing requirements for graphics measurement functions in medical device software, this study systematically analyzes the common characteristics of these measurement functions. Based on the black-box testing methodology and a digital phantom-based standardized testing framework, it constructs a testing indicator system encompassing functional applicability and accuracy, while designing preparation methods for digital phantoms and traceability validation processes. The standardized testing method developed in this study fills a critical gap in the standardization of testing methods for this domain. It provides quantifiable technical criteria for the regulatory review and quality verification of graphics measurement functions in medical device software. This advancement contributes to enhancing the clinical safety of medical software and ensuring regulatory consistency.

miRNA is a class of non-coding small RNAs with significant regulatory functions, capable of influencing various biological processes by modulating post-transcriptional translation. In recent years, the application of miRNAs as biomarkers in in vitro diagnostics (IVD) has garnered considerable attention. Firstly, this article introduces the generation and functional mechanisms of miRNAs, and outlines the roles and potential of miRNAs as biomarkers for various diseases, drawing on recent research findings. Subsequently, five traditional miRNA detection techniques are briefly introduced, their advantages and limitations in clinical diagnostic applications are summarized, and two emerging techniques used in miRNA research are enumerated. Finally, the article analyzes the challenges faced by using miRNAs as biomarkers in current clinical diagnostics, addressing four aspects: intended use, reference intervals, testing procedures, and analytical performance.

Under the U.S. medical product regulatory framework, innovative medical devices used in conjunction with approved drugs for new usage will often raise regulatory issues. To address these regulatory challenges and foster industry innovation, the FDA has proposed a new regulatory pathway. This paper traces the regulatory journey and risk analysis of the FDA in approving new uses of optical imaging agents and contrast agents through the medical device regulatory pathway. On this basis, it discusses the FDA's efforts to expand this pathway to broader applications and analyzes the reasons behind its lack of success. Finally, it discusses the current regulatory status of similar products in China, suggesting that this regulatory pathway may have certain implications for the regulation of similar products in China.

Objective: To establish a high performance liquid chromatography method for the determination of recombinant type Ⅲ human collagen in recombinant human collagen dressing for quality control of the product.

Methods: HPLC was utilized, and its parameters were as follows: an Agilent Eclipse XDB-C18 column (4.6×150 mm, 5 μm) was used with 0.1% TFA solution and 0.1% TFA acetonitrile solution as mobile phase at 30 ℃, the flow rate was 1.0 mL/min, and the detection wavelength was 214 nm.

Results: This method demonstrates high specificity. For dressings with a recombinant type Ⅲ human collagen content greater than 0.1 mg/mL, after hydrolysis treatment, a good linear relationship between concentration and peak area was observed within the range of 0.1 to 1.2 mg/mL ( R ²=0.9994). The average spiked recovery ranged from 90.91% to 94.14%, with a detection limit (LOD) of 0.05 mg/mL and a quantification limit (LOQ) of 0.1 mg/mL. For dressings with a recombinant type Ⅲ human collagen content of 0.1 mg/mL or less, after enzymatic digestion treatment, a good linear relationship between concentration and peak area was obtained within the range of 0.05 to 1.0 mg/mL ( R ²=0.9995). This validates the method's suitability for guiding the detection of low-concentration dressing proteins.

Conclusion: The method is rapid, accurate and reproducible, and can be used to determine the content of type Ⅲ collagen in dressings.

Objective: To propose a CT scanner tube fault diagnosis method based on a BP neural network optimized by particle swarm optimization (PSO) algorithm for identifying typical faults such as filament open circuit, filament half open circuit, scanning noise and arc discharge.

Methods: Key parameters such as anode voltage, current, tube temperature, scanning time, and current fluctuation amplitude are selected, and the data set is constructed based on 357 sets of fault samples, which are divided into training set and test set. PSO is used to optimize the initial weights and thresholds of BP neural network, and PSO-BP model is constructed for fault classification.

Results: The classification accuracies of the model on the training and test sets are 96.25% and 92.31%, respectively, and the Pearson correlation coefficients of each fault type range from 0.894 to 0.971, indicating a strong linear relationship between the fault features and categories. Compared with the traditional methods, the PSO-BP model has obvious advantages in terms of accuracy and robustness.

Conclusion: PSO-based BP neural network can effectively improve the diagnostic performance of typical faults of CT bulb tube, which has a good application prospect and provides a new method for the intelligent diagnosis of CT equipment.