Medical Devices Research Articles

Interlaboratory comparison of endotoxin contamination assessment of nanomaterials.

Endotoxin contamination is a significant hurdle to the translation of nanomaterials for biomedical applications. Multiple reports now describe that more than one-third of nanomaterials fail early pre-clinical assessment due to levels of endotoxin above regulatory requirements. Additionally, most immunological studies or in vivo studies testing nanomaterials in the literature lack inclusion of this assessment, which may lead to false-positive or false-negative results if high levels of the contaminant are present. The currently approved methods for endotoxin contamination assessment rely on enzymatic activity and wavelength absorbance as their endpoint, and many nanomaterials can interfere with such assays. For this reason, we devised an interlaboratory comparison of endotoxin contamination assessment for a range of nanomaterials to challenge the current international organization for standardization and pharmacopeia standards. Herein, we show that detected endotoxin levels could vary considerably between groups, and, in some instances, nanomaterials could both pass and fail regulatory endotoxin limits for medical devices depending on the group undertaking the assessment, all while passing all quality criteria standards. This work emphasises the requirement for multiple assays to fully assess the endotoxin levels in a nanomaterial and highlights the need for additional assays to be developed in this space.

Real-World Safety of Prostate Cancer Focal Therapy: MAUDE Database Analysis.

Objective: The aim of this study was to assess the real-world safety profile of medical devices used in focal prostate cancer treatment utilizing the Manufacturer and User Facility Device Experience (MAUDE) database. Methods: The MAUDE database was searched for reports on high-intensity focused ultrasound (HIFU), cryoablation, laser ablation, and irreversible electroporation (IRE) devices used in prostate cancer treatment from 1993 to 2023. Adverse events were identified and categorized. Results: We identified 175 reports for HIFU, 1362 for cryoablation, 615 for laser ablation, and 135 for IRE devices, with 28, 284, 126, and 2 respective reports, directly related to prostate cancer treatment. The aggregated data revealed the majority of complications were minor, with 82.5% (n = 363 out of 440 total complications) classified as Clavien-Dindo grade 1 or 2. Common minor complications included erectile dysfunction and urinary retention. Severe complications such as rectal fistulas were noted in HIFU and IRE treatments, along with singular mortality due to pulmonary embolism in cryoablation. Conclusions: Our analyses from MAUDE reveal that devices used in focal therapy for prostate cancer are predominantly associated with minor complications, underscoring their overall real-world safety profile. However, the occurrence of severe adverse events emphasizes the critical importance of rigorous patient selection and meticulous procedural planning. These findings provide valuable insights into the safety profile of focal therapy devices and contribute to the growing body of evidence on their use in prostate cancer treatment.

Measurements of Stray Radiation from Medical Devices in Hospitals

The main objective of this study was to look for the electromagnetic interference produced by medical devices in hospitals and to evaluate its impacts on the proper functions of such devices. However, the present study encountered other important problems with regard to CT scanner and X-ray Imaging systems. Such problems demand fast responses in order to secure health safety for the patients and the operators of such systems. ORIGINAL RESEARCH ARTICLE | Oct. 23, 2024

Next-Generation Approaches for Biomedical Materials Evaluation: Microfluidics and Organ-on-a-Chip Technologies.

Biological evaluation of biomedical materials faces constraints imposed by the limitations of traditional in vitro and animal experiments. Currently, miniaturized and biomimetic microfluidic technologies and organ-on-chip systems have garnered widespread attention in the field of drug development. However, their exploration in the context of biomedical material evaluation and medical device development remains relatively limited. In this review, a summary of existing biological evaluation methods, highlighting their respective advantages and drawbacks is provided. The application of microfluidic technologies in the evaluation of biomedical materials, emphasizing the potential of organ-on-chip systems as highly biomimetic in vitro models in material evaluation is then focused. Finally, the challenges and opportunities associated with utilizing organ-on-chip systems to evaluate biomedical materials in the field of material evaluation are discussed. In conclusion, the integration of advanced microfluidic technologies and organ-on-chip systems presents a potential paradigm shift in the biological assessment of biomedical materials, offering the prospective of more accurate and predictive in vitro models in the development of medical devices.

G4 & the balanced metric family – a novel approach to solving binary classification problems in medical device validation & verification studies

BackgroundIn medical device validation and verification studies, the area under the receiver operating characteristic curve (AUROC) is often used as a primary endpoint despite multiple reports showing its limitations. Hence, researchers are encouraged to consider alternative metrics as primary endpoints. A new metric called G4 is presented, which is the geometric mean of sensitivity, specificity, the positive predictive value, and the negative predictive value. G4 is part of a balanced metric family which includes the Unified Performance Measure (also known as P4) and the Matthews’ Correlation Coefficient (MCC). The purpose of this manuscript is to unveil the benefits of using G4 together with the balanced metric family when analyzing the overall performance of binary classifiers.ResultsSimulated datasets encompassing different prevalence rates of the minority class were analyzed under a multi-reader-multi-case study design. In addition, data from an independently published study that tested the performance of a unique ultrasound artificial intelligence algorithm in the context of breast cancer detection was also considered. Within each dataset, AUROC was reported alongside the balanced metric family for comparison. When the dataset prevalence and bias of the minority class approached 50%, all three balanced metrics provided equivalent interpretations of an AI’s performance. As the prevalence rate increased / decreased and the data became more imbalanced, AUROC tended to overvalue / undervalue the true classifier performance, while the balanced metric family was resistant to such imbalance. Under certain circumstances where data imbalance was strong (minority-class prevalence < 10%), MCC was preferred for standalone assessments while P4 provided a stronger effect size when evaluating between-groups analyses. G4 acted as a middle ground for maximizing both standalone assessments and between-groups analyses.ConclusionsUse of AUROC as the primary endpoint in binary classification problems provides misleading results as the dataset becomes more imbalanced. This is explicitly noticed when incorporating AUROC in medical device validation and verification studies. G4, P4, and MCC do not share this limitation and paint a more complete picture of a medical device’s performance in a clinical setting. Therefore, researchers are encouraged to explore the balanced metric family when evaluating binary classification problems.

Two-Staged Technology for CoCr Stent Production by SLM.

Additive manufacturing of porous materials with a specific macrostructure and tunable mechanical properties is a state-of-the-art area of material science. Additive technologies are widely used in industry due to numerous advantages, including automation, reproducibility, and freedom of design. Selective laser melting (SLM) is one of the advanced techniques among 3D fabrication methods. It is widely used to produce various medical implants and devices including stents. It should be noticed that there is a lack of information on its application in stent production. The paper presents the technological aspects of CoCr stent SLM fabrication, including design of stents and development of regimes for their manufacturing. Physical, chemical, and technological properties of CoCr powder were initially determined. Parametric design of mesh stent models was adopted. A two-stage approach was developed to ensure dimensional accuracy and quality of stents. The first stage involves a development of the single-track fusion process. The second stage includes the stent manufacturing according to determined technological regimes. The single-track fusion process was simulated to assign laser synthesis parameters for stent fabrication. Melting bath temperature and laser regimes providing such conditions were determined. Twenty-seven SLM manufacturing regimes were realized. Dependence of single-tracks width and height on the laser power, exposition time, and point distance was revealed. The qualitative characteristics of tracks imitating the geometry of the stent struts as well as favorable and unfavorable fusion regimes were determined. The results of surface roughness regulating of the stents' structural elements by various methods were analyzed. Thus, this two-staged approach can be considered as a fundamental approach for CoCr stent SLM fabrication.

Machine learning approach to flare-up detection and clustering in chronic obstructive pulmonary disease (COPD) patients.

Chronic obstructive pulmonary disease (COPD) is a prevalent and preventable condition that typically worsens over time. Acute exacerbations of COPD significantly impact disease progression, underscoring the importance of prevention efforts. This observational study aimed to achieve two main objectives: (1) identify patients at risk of exacerbations using an ensemble of clustering algorithms, and (2) classify patients into distinct clusters based on disease severity. Data from portable medical devices were analyzed post-hoc using hyperparameter optimization with Self-Organizing Maps (SOM), Density-Based Spatial Clustering of Applications with Noise (DBSCAN), Isolation Forest, and Support Vector Machine (SVM) algorithms, to detect flare-ups. Principal Component Analysis (PCA) followed by KMeans clustering was applied to categorize patients by severity. 25 patients were included within the study population, data from 17 patients had the required reliability. Five patients were identified in the highest deterioration group, with one clinically confirmed exacerbation accurately detected by our ensemble algorithm. Then, PCA and KMeans clustering grouped patients into three clusters based on severity: Cluster 0 started with the least severe characteristics but experienced decline, Cluster 1 consistently showed the most severe characteristics, and Cluster 2 showed slight improvement. Our approach effectively identified patients at risk of exacerbations and classified them by disease severity. Although promising, the approach would need to be verified on a larger sample with a larger number of recorded clinically verified exacerbations.

Exploring the influence of music on cognitive performance in female assembly line workers at a medical device manufacturing unit.

The significance of enhancing working conditions for the physical health and performance of workers, particularly female workers, underscores the need for research in this domain and the examination of interventions such as music. Previous studies have yielded diverse outcomes regarding the influence of music on individuals' performance; hence, further research in this area appears imperative. The aim of this study is to explore the impact of music on the cognitive and task performance of female assembly operation operators. This study is an interventional (quasi-experimental) study that involved 81 participants from the female workforce of the medical equipment assembly unit in Isfahan, Iran. The evaluation encompassed task performance, working memory using N-Back test, sustained attention using continues performance test (CPT), degree of sleepiness, and mental fatigue using Flicker Fusion test, along with physiological parameters such as heart rate and blood oxygen level. Participants underwent testing both in the presence of classical music and in a condition without music playback. The provision of background music enhanced the workers' sustained attention and working memory. It led to improved task performance and a reduction in drowsiness. Concerning physiological parameters, it resulted in a slight decrease in heart rate at the end of the work shift and a marginal increase in participants' blood oxygen levels. Background music enhanced working memory (p-value = 0.001), sustained attention (p-value = 0.001), and improved the task performance of workers(p-value = 0.005). Additionally, likely due to increased relaxation, it led to a decrease in heart rate (p-value = 0.001) and an increase in blood oxygen levels (p-value = 0.016). Music also played a role in reducing participants' sleepiness (p-value = 0.001).

A Comparative Evaluation of New and Used Dental Explorer Working Tips

Abstract The dental explorer medical device assists multiple functions, including marginal assessment. The working tip quality of this instrument has been previously established as a factor affecting operator judgment. However, little data exists to demonstrate the actual quality of working tips in clinical practice. The purpose of this study is to investigate and quantify if any real, measurable differences of the explorer working tip dimension exist among such instruments currently in service and compare to published medical device industry standards. Twenty new #23 dental explorer instruments from two manufacturers served as controls and sixty-three instruments in circulation at a dental school clinic were observed using light microscopy. The instruments were measured 50 micrometers from the terminus. A one-way analysis of variance (ANOVA) was performed to analyze values among groups. No statistically significant difference between the mean working tip dimension of new instruments was detected between brands. However, statistically significant differences between new and used instruments were detected regardless of brand. The range of values was 92.5–227.5 micrometers with average used instrument tip estimated over 50% wider than the average new instrument. These findings imply that other studies employing a dental explorer may be confounded if the instrument is not measured. Furthermore, the results of this study should serve as a motivating factor toward future research to update quality standards regarding the medical device with a goal of defining acceptable dimensions of the instrument working tip for certain applications in relation to clinical performance and expected outcomes.

Simulation of intestinal perforation in experiment

The current problem of neonatal and pediatric surgery remains the tactics of surgical treatment and postoperative management of patients with perforated peritonitis. Mortality with perforation of the stomach and intestines in children in the newborn period reaches about 40-80 %. The combination of the syndrome of increased intra-abdominal pressure and multiple organ failure causes the extremely serious condition of patients. In this connection, new approaches to the surgical treatment of such patients are currently being actively developed. For this, new medical devices are tested in experimental practice, but the problem of such studies, first of all, lies in the lack of an adequate model of the pathological process. The aim of the work is to analyze the methods of experimental modeling of intestinal perforations described in the public domain. For this, a study was conducted of the most significant scientific publications of such databases as Google Scholar, PubMed, Scopus, eLIBRARY. The present work provides a detailed description of existing options for modeling perforations of various parts of the gastrointestinal tract (stomach, small intestine and colon), depending on the goals of the experiment. Several rather rare techniques based on the introduction of microorganisms are also presented. In addition, the article describes the method proposed by the authors for modeling perforation using laparoscopic access.

Study of Magnetic Hydrogel 4D Printability and Smart Self‐Folding Structure

4D printing technology offers the potential to create smart structures that respond to external stimuli. This study focuses on a novel magnetic hydrogel with promising applications in 4D printing, particularly for medical devices such as guidewire robots, drug delivery systems, and vascular stents. Magnetic‐responsive hydrogels suitable for 4D printing are scarce, and their complex rheological properties pose challenges for printing. The study investigates these properties and optimizes them through adjustments in ink composition and the application of an external magnetic field, improving printability. Using the direct writing (DLP) method, which allows magnetic programming of individual strands, the study achieves greater flexibility compared to the traditional SLA method. Optimized printing parameters and material ratios produced high‐quality single strands, grids, and sheet‐like structures, demonstrating responsiveness to varying magnetic fields. Results confirm that DLP can be effectively applied to hydrogel 4D printing, achieving flexible structures with tunable mechanical properties. Additionally, magnetic‐responsive, self‐folding hydrogel structures were created, with a response speed of 180 ms under a magnetic field. This research establishes a foundation for magnetic hydrogel 4D printing and offers insights for the development of future smart medical devices.

Novel antimicrobial coating for hernia meshes.

Antibiotic coating for several medical devices has been carried out; however, there are only few studies about coating hernia meshes with antimicrobial substances. In this study we checked the capacity of different commercially available hernia meshes to act as drug carrier. The meshes were coated with gentamicin palmitate, chlorhexidine palmitic acid and chlorhexidine palmitate. The coating mass and subsequent in vitro delivery rate were evaluated for gentamicin palmitate by fluorescence polarization. For Chlorhexidine coated devices the coating mass was determined by weighing. The in vitro delivery rate was determined by UV absorption (255 nm). The interaction of each mesh to the different coating substances was observed by scanning electron microscopy. 1. Certain uniformity was observed on the quantity of chlorhexidine coating the surface of each mesh used when compared with gentamicin palmitate coating. 2.We did not detect significant difference between the amounts of gentamicin palmitate released from each mesh. 3. The release of chlorhexidine palmitate and chlorhexidine palmitic acid from UltraPro™ and Mersilene™ were significantly higher (p<0.05) in comparison with the other two meshes. 4. The coating substances covered the surface of the fibers without damaging its structure. 5. The coating substances were distributed all along the fibers in all samples. We suggest the use of chlorhexidine palmitate and chlorhexidine palmitic acid, as well as gentamicin palmitate, for coating of hernia meshes aiming prevention of infections. Further investigation of the bactericidal effect of coated hernia meshes against biofilm form of S. aureus and other device-related infections is suggested.

An IoT Healthcare System With Deep Learning Functionality for Patient Monitoring

ABSTRACTCurrently, healthcare systems operate under conventional management practices and entail storing and processing substantial medical data. Integrating the Internet of Things (IoT) and wireless sensor networks (WSNs) technologies has facilitated the development of IoT‐enabled healthcare, which possesses advanced data processing capabilities and extensive data storage. This paper proposes a WSN and IoT framework for patient monitoring in high‐speed 5G communications. Based on an artificial neural network (ANN), an intelligent health monitoring system was developed using IoT technology to monitor a person's blood pressure, heart rate, oxygen level, and temperature. Furthermore, the system helps the elderly being in critical cases in their homes to communicate and update their medical condition with the hospital, especially in critical cases, to be treated as soon as possible, especially in remote areas. The experimental results showed the superiority and effectiveness of the proposed system. Moreover, relying on ANNs to extract the basic features, the accuracy reached 96%. The proposed system was implemented practically, and the results were displayed in real time and compared with commercial medical devices. Maximum relative errors are heart rate (2.19), body temperature (2.94), systolic blood pressure (3.4), diastolic blood pressure (2.89), and SpO2 (1.05). On the other hand, the proposed system is much faster than other wireless communication methods, regardless of the detection quality.

Comparative Analysis of Blood Transfusion Accuracy and Hemolysis Rate of Transfusion Cartridge Set Between Conventional Infusion Pumps and Cylinder-Type Infusion Pumps

Background: Infusion pumps are critical in delivering fluids, including medications and blood products, in controlled amounts. However, conventional pumps can cause hemolysis and other issues such as flow variations and infection risks, especially during blood transfusions. To address these limitations, a novel cylinder-type infusion pump, the Anyfusion H-100, was developed, which includes a specialized blood transfusion cartridge set that combines syringe and peristaltic infusion methods. This study evaluates the accuracy and hemolysis rates of the Anyfusion H-100 compared to conventional pumps, aiming to confirm its viability as a safe and effective medical device for blood transfusions. Methods: This study evaluated six different infusion rates (10–180 cc/hr) and conducted 57 transfusion trials, 20 of which used a 1:1 blood–saline dilution. Blood transfusion accuracy was measured using research-grade packed red blood cells, and hemolysis rates were assessed before and after transfusion by chi-square tests and independent sample t-tests. Results: Anyfusion demonstrated an average transfusion error rate of 3.77%, compared to 4.00% for the Terufusion, with no statistically significant difference in hemolysis rates (p = 0.697). Bland–Altman plots confirmed their equivalent performance, with hemolysis rates of 0.566 ± 0.095% for Anyfusion and 0.518 ± 0.126% for Terufusion. Conclusions: Anyfusion provides an accurate and reliable blood transfusion performance comparable to that of Terufusion, with no significant difference in hemolysis rates; its integration of syringe and infusion methods shows a potential for safer and more efficient transfusion practices, especially in pediatric and emergency settings.

Electrospinning Recombinant Spider Silk Fibroin-Reinforced PLGA Membranes: A Biocompatible Scaffold for Wound Healing Applications.

Polylactide-polyglycolide (PLGA) is one of the most attractive polymeric biomaterials used to fabricate medical devices for drug delivery and tissue engineering applications. Nevertheless, the utilization of PLGA in load-bearing applications is restricted due to its inadequate mechanical properties. This study examines the potential of recombinant silk fibroin (eADF4), a readily producible biomaterial, as a reinforcing agent for PLGA. The PLGA/eADF4 composite membranes were developed by using the process of electrospinning. The spinnability of the electrospinning solutions and the physicochemical, mechanical, and thermal properties of the composite membranes were characterized. The addition of eADF4 increased the viscosity of the electrospinning solutions and enhanced both the mechanical characteristics and the thermal stability of the composites. This study demonstrates that PLGA membranes reinforced with recombinant spider silk fibroin are noncytotoxic, significantly enhance cell migration and wound closure, and do not trigger an inflammatory response, making them ideal candidates for advanced wound healing applications.

No Ear Left Behind: Wireless Earbuds for Low-Cost Hearing Screening

Hearing loss is particularly harmful for language acquisition and neuro-development if it is left undetected in early childhood. Newborn hearing screening technologies using otoacoustic emissions (OAE) rely on detecting soft sounds generated by a healthy cochlea. High-income countries like the United States frequently implement hearing screening programs for every child at birth. However, such universal hearing screening is significantly less common in low- and middle-income countries, partly due to the conventional wisdom that the test requires sensitive and expensive acoustic hardware that costs thousands of dollars. In our MobiSys paper[1], we present the first wireless earbud design for low-cost hearing screening. Our hardware-software system reliably performs hearing screening using low-cost acoustic hardware, while being in the form-factor of a wireless earbud (Figure. 1a,b). The earbud hardware is designed to work across a large age range from newborns to adults. By developing low-cost and open-source wearable technology, our work may help address global health inequities in hearing screening by democratizing these medical devices.

Stability‐Enhanced Variable Stiffness Metamaterial with Controllable Force‐Transferring Path

AbstractSelf‐contact variable stiffness (SVS) metamaterial offers specific patterns of elastic strain energy storage by changing its force‐transferring path. The change of the elastic strain energy storage patterns further influences the stiffness variation of the SVS metamaterials. However, challenges still arise because typically fabricated SVS metamaterials inevitably contain structural irregularities, eccentricities, and defects. These microstructural imperfections impede the stable generation of designed strain energy storage patterns in the metamaterial, implying that the SVS metamaterials cannot achieve expected stiffness variations. To address this burning question, an SVS metamaterial/meta‐structure design paradigm with eccentric unit designs is proposed, which can realize both stable stiffness variations and high load‐bearing. The theoretical, simulation, and experimental results demonstrate that the SVS chain meta‐structure achieves ≈110 times stiffness variation between the low and high loading conditions. Its load‐bearing can reach more than 1500 N when the meta‐structure falls into the high stiffness stage. Furthermore, some typical functions are demonstrated using the stability‐enhanced SVS metamaterial, including customized mechanical protections for human joints and information transformation regulated by remote mechanical input signals. The results can provide a useful solution for generating a more feasible stability‐enhanced SVS metamaterial/meta‐structure and promote their potential applications in aerospace, medical devices, and robotics.

Performance prediction of IPMC modified with SiO2-SGO based on backpropagation neural network

Ionic polymer–metal composites (IPMCs) constitute a new type of artificial muscle material that is commonly used in bionic soft robots and medical devices because of its small driving voltage and considerable deformation. However, IPMCs are limited by performance issues such as low output force and small operating time away from water. Silicon dioxide sulfonated graphene (SiO2-SGO) particles are often used to improve the performance of polymer membranes because of their hydrophilicity and high chemical stability. Reported here is the addition of SiO2-SGO particles prepared by in situ hydrolysis to perfluorosulfonic acid in order to improve the IPMC properties. Also, a predictive model was constructed based on a backpropagation neural network, with the SiO2-SGO doping amount and the IPMC excitation voltage in the input layer and the driving displacement in the output layer. The results show that the IPMC prepared with 1.0 wt. % doping content performed the best, with a maximum output displacement of 47.7 mm. The correlation coefficient (R2) was 0.9842 and the mean square error was 0.000 370 73, which show that the predictive model has high predictive accuracy and is suitable for predicting the performance of the SiO2-SGO-modified IPMC.

A Sub-1 ppm/°C Reference Voltage Source with a Wide Input Range

With the continuous advancement of electronic technology, the application of high-voltage integrated circuits is becoming increasingly prevalent in fields such as power systems, medical devices, and industrial automation. The reference circuit within high-voltage integrated circuits must not only exhibit insensitivity to temperature variations but also maintain stability across a broad voltage supply. This paper presents a bandgap reference (BGR) source capable of operating over a wide input range. This BGR employs a high-order curvature compensation method to eliminate nonlinear voltage terms, resulting in minimal temperature drift. The circuit achieves an impressive temperature coefficient (TC) of 0.88 ppm/°C over a temperature range from −40 °C to 130 °C. To ensure stable operation within a 4–40 V range, the design incorporates a pre-regulation circuit that stabilizes the supply voltage of the BGR core at a fixed value, thereby enhancing the ability to withstand variations in power supply voltage.

Integration of Metrology in Grinding and Polishing Processes for Rotationally Symmetrical Aspherical Surfaces with Optimized Material Removal Functions

Aspherical surfaces, with their varying curvature, minimize aberrations and enhance clarity, making them essential in optics, aerospace, medical devices, and telecommunications. However, manufacturing these surfaces is challenging because of systematic errors in CNC equipment, tool wear, measurement inaccuracies, and environmental disturbances. These issues necessitate precise error compensation to achieve the desired surface shape. Traditional methods for spherical optics are inadequate for aspherical components, making accurate surface shape error detection and compensation crucial. This study integrates advanced metrology with optimized material removal functions in the grinding and polishing processes. By combining numerical control technology, computer technology, and data analysis, we developed CAM software (version 1) tailored for aspherical surfaces. This software uses a compensation correction algorithm to process error data and generate NC programs for machining. Our approach automates and digitizes the grinding and polishing process, improving efficiency and surface accuracy. This advancement enables high-precision mass production of rotationally symmetrical aspherical optical components, addressing existing manufacturing challenges and enhancing optical system performance.