Search Results (91)

Background/Objectives: The simulation of human movement offers transformative potential for the design of medical devices, particularly in understanding the cause–effect dynamics in individuals with neurological or musculoskeletal impairments. This study presents a simulation-driven framework to determine the optimal ankle–foot orthosis (AFO) stiffness for mitigating the risk of ankle sprains due to excessive subtalar inversion during high-impact activities, such as landing from a free fall. Methods: We employed biomechanical simulations to assess the influence of translational stiffness on subtalar inversion control, given that inversion angles exceeding 25 degrees are strongly correlated with injury risk. Simulations were conducted using a musculoskeletal model with and without a passive AFO; the stiffness varied in three anatomical directions. A Design of Experiments (DoE) approach was utilized to capture nonlinear interactions among stiffness parameters. Results: The results indicated that increased translational stiffness significantly reduced inversion angles to safer levels, though direction–dependent effects were noted. Based on these insights, we developed a 4D visualization tool that integrates simulation data with an interactive color–coded interface to depict ”safe design” zones for various AFO stiffness configurations. This tool supports clinicians in selecting stiffness values that optimize both safety and functional performance. Conclusions: The proposed framework enhances clinical decision-making and engineering processes by enabling more accurate and individualized AFO designs. Full article

Healthcare-associated infection, mainly through medical device-associated infection, remains a critical issue in hospital care. Bacterial adhesion, proliferation, and biofilm formation on the device surface have been considered the foremost cause of medical device-associated infection. Different means have been explored to reduce microbial attachment and proliferation, including forming a bactericidal or microbial adhesion-resistant surface layer. Fear of limited bactericidal capability if the dead microbes remained adhered to the surface has withheld the widespread use of a bactericidal surface in medical devices if it was intended for long-term use. By contrast, constructing a microbial adhesion-resistant or antifouling surface, such as a surface with zwitterionic functionality, would be more feasible for devices intended to be used for the long term. Nevertheless, a sophisticated multi-step chemical reaction process would be needed. Instead, a simple immersion method that utilized a novel mussel-inspired catechol compound with zwitterionic sulfobetaine functionality, ZDS, was explored in this investigation for the surface modification of substrates with distinctively different surface characteristics, including titanium and polyvinyl chloride. Dopamine, NaIO₄ oxidants, and chemicals that could affect ionic interactions (NaCl and polyethyleneimine) were added to the ZDS-containing immersion solution to compare their effects on modifying titanium and PVC substrates. Furthermore, a layer-by-layer immersion method, in which the substrate was first immersed in the no-ZDS-added dopamine-containing solution, followed by the ZDS-containing solution, was also attempted on the PVC substrate. By properly selecting the immersion solution formulation and additional NaIO₄ oxidation modification, the antibacterial capability of ZDS-modified substrates can be optimized without causing cytotoxicity. The maximum antibacterial percentages against S. aureus were 84.2% and 81.7% for the modified titanium and PVC substrate, respectively, and both modified surfaces did not show any cytotoxicity. Full article

The Internet of Medical Things (IoMT) is revolutionizing healthcare by integrating smart diagnostic devices with cloud computing and real-time data analytics. The emergence of infectious diseases, including COVID-19, underscores the need for rapid and decentralized diagnostics to facilitate early intervention. Traditional centralized laboratory testing introduces delays, limiting timely medical responses. While point-of-care molecular diagnostic (POC-MD) systems offer an alternative, challenges remain in cost, accessibility, and network inefficiencies. This study proposes an IoMT-based architecture for fully automated POC-MD devices, leveraging WebSockets for optimized communication, enhancing microfluidic cartridge efficiency, and integrating a hardware-based emulator for real-time validation. The system incorporates DNA extraction and real-time polymerase chain reaction functionalities into modular, networked components, improving flexibility and scalability. Although the system itself has not yet undergone clinical validation, it builds upon the core cartridge and detection architecture of a previously validated cartridge-based platform for Chlamydia trachomatis and Neisseria gonorrhoeae (CT/NG). These pathogens were selected due to their global prevalence, high asymptomatic transmission rates, and clinical importance in reproductive health. In a previous clinical study involving 510 patient specimens, the system demonstrated high concordance with a commercial assay with limits of detection below 10 copies/μL, supporting the feasibility of this architecture for point-of-care molecular diagnostics. By addressing existing limitations, this system establishes a new standard for next-generation diagnostics, ensuring rapid, reliable, and accessible disease detection. Full article

Anticoagulants, including warfarin, are often administered to patients who are exhibiting early symptoms of thromboembolic episodes or who have already experienced such episodes. However, warfarin has a limited therapeutic index and might cause bleeding and other clinical problems. Warfarin inhibits the vitamin K epoxide reductase complex subunit 1 (VKORC1), an enzyme essential for activating vitamin K, in the coagulation cascade. Genetic factors, such as polymorphisms, can change the natural function of VKORC1, causing variations in the medication reaction among individuals. Hence, before prescribing warfarin, the patient’s genetic profile should also be considered. In this study, an electrochemical genosensor capable of detecting the VKORC1 1639 G>A polymorphism was designed and optimized. This analytical approach detects the electric current obtained during the hybridization reaction between two 52 base pair complementary oligonucleotide sequences. Investigating public bioinformatic platforms, two DNA sequences with the A and G single-nucleotide variants were selected and designed. The experimental protocol of the genosensor implied the formation of a bilayer composed of a thiolate DNA and an alkanethiol immobilized onto gold electrodes, as well as the formation of a DNA duplex using a sandwich-format hybridization reaction through a fluorescein labelled DNA signalling probe and the enzymatic amplification of the electrochemical signal, detected by chronoamperometry. A detection limit of 20 pM and a linear range of 0.05–1.00 nM was obtained. A clear differentiation between A/A, G/A and G/G genotypes in biological samples was successfully identified by his novel device. Full article

Chronic total occlusions (CTOs), defined as complete coronary artery blockages persisting for over three months, are frequently encountered in up to 25% of coronary angiograms. Although percutaneous coronary intervention (PCI) for CTO remains technically challenging, advancements in guidewires, microcatheters, re-entry devices, and intravascular imaging, along with the expertise of specialized operators, have significantly improved procedural success rates, now exceeding 90% in expert centers. While recent evidence, such as the SYNTAX II study, emphasizes the importance of complete revascularization, over half of CTO cases continue to be managed conservatively with optimal medical therapy (OMT), partly due to the limited high-quality randomized evidence supporting revascularization. Observational studies have demonstrated that successful CTO-PCI is associated with improved angina relief, quality of life, left ventricular function, and possibly long-term survival. Extended observational follow-up, such as the Korean and Canadian registries, suggests long-term reductions in cardiac and all-cause mortality with CTO revascularization. However, randomized controlled trials (RCTs) have primarily shown symptomatic benefit, with no consistent reduction in major adverse cardiac events (MACE) or mortality, likely due to limited sample sizes, short follow-up, and treatment crossovers. Various strategies, including the hybrid algorithm, guide CTO interventions by balancing antegrade and retrograde techniques based on lesion complexity. Imaging modalities such as coronary CT angiography and intravascular ultrasound play a pivotal role in planning and optimizing these procedures. Future innovations, such as real-time fusion imaging of CCTA with coronary angiography, may enhance lesion visualization and guidewire navigation. While current guidelines recommend CTO-PCI in selected symptomatic patients with demonstrable ischemia or viable myocardium, the decision should be individualized, incorporating anatomical feasibility, comorbidities, patient preferences, and input from a multidisciplinary Heart Team. Looking ahead, adequately powered RCTs with extended follow-up are essential to determine the long-term clinical impact of CTO-PCI on hard outcomes such as mortality and myocardial infarction. Full article

Background: Chronic mitral regurgitation (MR) is categorized into primary and secondary MR (SMR). While primary MR arises from structural abnormalities of the mitral valve apparatus, SMR is a consequence of cardiac remodeling, typically due to heart failure or atrial fibrillation. Management strategies differ significantly, with primary MR requiring direct valvular intervention and SMR necessitating a comprehensive approach incorporating guideline-directed medical therapy (GDMT), revascularization, and resynchronization strategies. The MitraClip, a transcatheter edge-to-edge repair (TEER) device, has emerged as a recommended intervention for symptomatic severe SMR despite optimal GDMT. Objectives: This study aims to evaluate national trends in MitraClip placements in the U.S. from 2016 to 2021 and to assess 90-day readmission events following the procedure. Additionally, we analyze patient and socioeconomic factors associated with heart failure readmissions post-MitraClip placement to optimize patient selection criteria. Methods: The study utilized data from the National Inpatient Sample (NIS) for the years 2016–2021 and the National Readmissions Database (NRD) for 2021. Patients who underwent MitraClip placement were identified using ICD-10 code 02UG3JZ. We stratified the population based on demographics, hospital resource utilization, and comorbidities. Index admissions were classified based on the presence or absence of heart failure remissions within 90 days post-procedure. Statistical analyses, including ANOVA and logistic regression, were conducted to identify factors associated with readmissions. Results: MitraClip utilization demonstrated a rising trend from 2016 to 2021, with total annual procedures increasing from 869 to 2488. Mean patient age remained stable at 76–79 years, with a nearly equal sex distribution. In-hospital mortality remained low (1–3%) throughout the study period. A steady increase in hospital charges was observed, alongside a decline in the mean length of stay. Analysis of 4918 index admissions for MitraClip placement in 2021 identified 780 total readmissions within 90 days, with 206 (26.4%) attributed to heart failure. Factors significantly associated with increased risk of heart failure readmissions included atrial fibrillation (OR 3.77, CI 1.82–4.23), pulmonary hypertension (OR 3.96, CI 1.49–5.55), and chronic lung disease (OR 1.91, CI 1.32–2.77). Conclusions: The increasing adoption of MitraClip underscores its growing role in managing SMR. However, heart failure readmissions remain a significant concern. Identifying high-risk patient profiles can refine selection criteria and enhance post-procedural management strategies to improve clinical outcomes. Further research is needed to optimize patient selection and refine risk stratification for MitraClip interventions. Full article

Printed electronics employ established printing methods to create low-cost, mechanically flexible devices including batteries, supercapacitors, sensors, antennas and RFID tags on plastic, paper and textile substrates. This review focuses on the specific contribution of screen printing to that landscape, examining how ink viscosity, mesh selection and squeegee dynamics govern film uniformity, pattern resolution and ultimately device performance. Recent progress in advanced ink systems is surveyed, highlighting carbon allotropes (graphene, carbon nano-onions, carbon nanotubes, graphite), silver and copper nanostructures, MXene and functional oxides that collectively enhance mechanical robustness, electrical conductivity and radio-frequency behavior. Parallel improvements in substrate engineering such as polyimide, PET, TPU, cellulose and elastomers demonstrate the technique’s capacity to accommodate complex geometries for wearable, medical and industrial applications while supporting environmentally responsible material choices such as water-borne binders and bio-based solvents. By mapping two decades of developments across energy-storage layers and functional electronics, the article identifies the key process elements, recurring challenges and emerging sustainable practices that will guide future optimization of screen-printing materials and protocols for high-performance, customizable and eco-friendly flexible devices. Full article

Objective: Current good manufacturing practice (cGMP) guidance for positron emission tomography (PET) drugs has been established in Europe and the United States. In Japan, the Pharmaceuticals and Medical Devices Agency (PMDA) approved the use of radiosynthesizers as medical devices for the in-house manufacturing of PET drugs in hospitals and clinics, regardless of the cGMP environment. Without adequate facilities, equipment, and personnel required by cGMP regulations, the quality assurance (QA) and clinical effectiveness of PET drugs largely depend on the radiosynthesizers themselves. To bridge the gap between radiochemistry standardization and site qualification, the Japanese Society of Nuclear Medicine (JSNM) has issued guidance for the in-house manufacturing of small-scale PET drugs under academic GMP (a-GMP) environments. The goals of cGMP and a-GMP are different: cGMP focuses on process optimization, certification, and commercialization, while a-GMP facilitates the small-scale, in-house production of PET drugs for clinical trials and patient-specific standard of care. Among PET isotopes, N-13 has a short half-life (10 min) and must be synthesized on site. [¹³N]Ammonia ([¹³N]NH₃) is used for myocardial perfusion imaging under the Japan Health Insurance System (JHIS) and was thus selected as a working example for the manufacturing of PET drugs in an a-GMP environment. Methods: A [¹³N]NH₃-radiosynthesizer was installed in a hot cell within an a-GMP-compliant radiopharmacy unit. To comply with a-GMP regulations, the air flow was adjusted through HEPA filters. All cabinets and cells were disinfected to ensure sterility once a month. Standard operating procedures (SOPs) were applied, including analytical methods. Batch records, QA data, and radiation exposure to staff in the synthesis of [¹³N]NH₃ were measured and documented. Results: 2.52 GBq of [¹³N]NH₃ end-of-synthesis (EOS) was obtained in an average of 13.5 min in 15 production runs. The radiochemical purity was more than 99%. Exposure doses were 11 µSv for one production run and 22 µSv for two production runs. The pre-irradiation background dose rate was 0.12 µSv/h. After irradiation, the exposed dosage in the front of the hot cell was 0.15 µSv/h. The leakage dosage measured at the bench was 0.16 µSv/h. The exposure and leakage dosages in the manufacturing of [¹³N]NH₃ were similar to the background level as measured by radiation monitoring systems in an a-GMP environments. All QAs, environmental data, bacteria assays, and particulates met a-GMP compliance standards. Conclusions: In-house a-GMP environments require dedicated radiosynthesizers, documentation for batch records, validation schedules, radiation protection monitoring, air and particulate systems, and accountable personnel. In this study, the in-house manufacturing of [¹³N]NH₃ under a-GMP conditions was successfully demonstrated. These findings support the international harmonization of small-scale PET drug manufacturing in hospitals and clinics for future multi-center clinical trials and the development of a standard of care. Full article

The accurate identification of look-alike medical vials is essential for patient safety, particularly when similar vials contain different substances, volumes, or concentrations. Traditional methods, such as manual selection or barcode-based identification, are prone to human error or face reliability issues under varying lighting conditions. This study addresses these challenges by introducing a real-time deep learning-based vial identification system, leveraging a Lightweight YOLOv4 model optimized for edge devices. The system is integrated into a Mixed Reality (MR) environment, enabling the real-time detection and annotation of vials with immediate operator feedback. Compared to standard barcode-based methods and the baseline YOLOv4-Tiny model, the proposed approach improves identification accuracy while maintaining low computational overhead. The experimental evaluations demonstrate a mean average precision (mAP) of 98.76 percent, with an inference speed of 68 milliseconds per frame on HoloLens 2, achieving real-time performance. The results highlight the model’s robustness in diverse lighting conditions and its ability to mitigate misclassifications of visually similar vials. By combining deep learning with MR, this system offers a more reliable and efficient alternative for pharmaceutical and medical applications, paving the way for AI-driven MR-assisted workflows in critical healthcare environments. Full article

High-intensity focused ultrasound (HIFU) is a non-invasive technology widely used for facial and body rejuvenation, skin tightening, and fat reduction. It stimulates collagen production and induces apoptosis in fat cells, offering an effective alternative to surgical procedures with minimal downtime and reduced recovery periods. As a result, HIFU has become an increasingly popular choice for patients seeking non-surgical esthetic enhancements. A comprehensive literature search was conducted using PubMed, Scopus, and SpringerLink to assess HIFU-related complications. Twenty-two studies published between 2010 and 2025 were identified, all involving female participants. The findings confirm that HIFU is generally safe and effective, with most complications being mild and transient, such as temporary erythema, swelling, and discomfort. These side effects typically resolve within a few hours to days without requiring medical intervention. However, rare but significant complications like fat atrophy, nerve irritation, and hyperpigmentation have been linked to improper device settings, inadequate practitioner expertise, and insufficient patient assessment. Ensuring proper training, adherence to standardized treatment protocols, and individualized patient evaluations can significantly minimize these risks and optimize patient outcomes. Long-term follow-up studies and further research on standardized safety protocols, optimal energy settings, and patient selection criteria are essential for enhancing the effectiveness, predictability, and safety of HIFU in esthetic medicine. Full article

The rapid proliferation of Internet of Things (IoT) devices in healthcare, from wearable sensors to implantable medical devices, has revolutionised patient monitoring, personalised treatment, and remote care delivery. However, the resource-constrained nature of IoT devices, coupled with the sensitivity of medical data, presents critical security challenges. Traditional encryption methods, while robust, are computationally intensive and unsuitable for IoT environments, leaving sensitive patient information vulnerable to cyber threats. Addressing this gap, lightweight encryption methods have emerged as a pivotal solution to balance security with the limited processing power, memory, and energy resources of IoT devices. This paper explores lightweight encryption methods tailored for IoT healthcare applications, evaluating their effectiveness in securing sensitive data while operating under resource constraints. A comparative analysis is conducted on encryption techniques such as AES-128, LEA, Ascon, GIFT, HIGHT, PRINCE, and RC5-32/12/16, based on key performance metrics including block size, key size, encryption and decryption speeds, throughput, and security levels. The findings highlight that AES-128, LEA, ASCON, and GIFT are best suited for high-sensitivity healthcare data due to their strong security features, while HIGHT and PRINCE provide balanced protection for medium-sensitivity applications. RC5-32/12/16, on the other hand, prioritises efficiency over comprehensive security, making it suitable for low-risk scenarios where computational overhead must be minimised. The paper underscores the significant trade-offs between efficiency, security, and resource consumption, emphasising the need for careful selection of encryption methods based on the specific requirements of IoT healthcare environments. Additionally, the paper highlights the growing demand for lightweight encryption methods that balance energy efficiency with robust protection against cyber threats. These insights offer valuable guidance for researchers and practitioners seeking to enhance the security of IoT-based healthcare systems while ensuring optimal performance in resource-constrained settings. Full article

This paper addresses the critical challenge of optimal allocation and scheduling of Internet of Things (IoT) tracking devices for patient monitoring in healthcare facilities, where limited resources must be efficiently distributed to minimize cost and maximize care quality. We formulate this healthcare management problem as a specialized variant of the Resource-Constrained Scheduling Problem that incorporates patient-specific factors such as duration of stay and priority. After establishing the computational complexity of the problem, we propose a Non-dominated Sorting Genetic Algorithm II (NSGA-II) to address the complex problem of balancing multiple objectives: cost minimization and quality of care maximization. Our approach offers a set of optimal trade-offs, enabling informed decision-making to select the best final solution. Computational experiments conducted on both simulated scenarios and real-world healthcare facility datasets demonstrate that our approach outperforms existing methods, achieving between 1.2 and 3.0 times more solutions than the state of the art. Moreover, in comparison to manual scheduling by medical center managers, our method achieves cost savings of up to 12% (with an average of 6.3%) and quality improvements of up to 20% (with an average of 10%) across the tested experiments. The proposed method scales effectively to realistic healthcare settings with varying numbers of patients and tracking devices, maintaining solution quality while keeping computational time within practical limits for daily operational use. Our findings contribute to both healthcare operations research and clinical practice by providing an efficient methodology for optimizing the use of limited monitoring resources while prioritizing patient safety. Full article

Background/Objectives: Bipolar disorder (BD) is a complex and chronic mental health condition that poses significant challenges for both patients and healthcare providers. Traditional treatment methods, including medication and therapy, remain vital, but there is increasing interest in the application of artificial intelligence (AI) to enhance BD management. AI has the potential to improve mood episode prediction, personalize treatment plans, and provide real-time support, offering new opportunities for managing BD more effectively. Our primary objective was to explore the potential role of AI in transforming the management of BD, specifically in mood tracking, prediction, and personalized treatment regimens. Methods: To explore the potential role of AI in transforming BD management, we conducted a review of recent literature using key search terms. We included studies that discussed AI applications in mood tracking, prediction, and treatment personalization. The studies were selected based on their relevance to AI’s role in BD management, with attention to the PICO criteria: Population—individuals diagnosed with BD; Intervention—AI tools for mood prediction, treatment personalization, and real-time support; Comparison—traditional treatment methods (when available); Outcome—measures of mood episode prediction, treatment effectiveness, and improvements in patient care. Results: The findings from recent research reveal promising developments in the use of AI for BD management. Studies suggest that AI-powered tools can enable more proactive and personalized care, improving treatment outcomes and reducing the burden on healthcare professionals. AI’s ability to analyze data from wearable devices, smartphones, and even social media platforms provides valuable insights for early detection and more dynamic treatment adjustments. Conclusions: While AI’s application in BD management is still in its early stages, it presents transformative potential for improving patient care. However, further research and development are crucial to fully realize AI’s potential in supporting BD patients and optimizing treatment efficacy. Full article

Background and Clinical Significance: Takotsubo cardiomyopathy (TCM), an acute stress-induced left ventricular dysfunction, stems from catecholaminergic surges leading to transient myocyte stunning, calcium overload, and microvascular dysregulation. Although most cases resolve spontaneously, roughly 10% deteriorate into fulminant cardiogenic shock, warranting mechanical circulatory support (MCS). Impella^® provides direct transvalvular LV unloading but carries elevated risks of hemolysis, vascular compromise, and thrombogenicity. Conversely, the intra-aortic balloon pump (IABP) enhances diastolic coronary perfusion and marginally reduces afterload via counterpulsation, albeit with less potent LV decompression. Optimal MCS selection in TCM-associated shock therefore hinges on balancing hemodynamic benefits against procedural morbidity. Case Presentation: A 72-year-old female with coronary artery disease, paroxysmal atrial fibrillation (status post–left atrial appendage occlusion), and stage 3 chronic kidney disease presented with anterior ST-segment elevations (V2–V4) and troponin I >1000 ng/L, progressing rapidly to cardiogenic shock and respiratory failure. Coronary angiography revealed mild luminal irregularities, while echocardiography demonstrated severely reduced ejection fraction (5–10%) with characteristic apical ballooning. Refractory elevations in pulmonary capillary wedge pressure, despite escalating inotropes and vasopressors, prompted IABP insertion for partial LV offloading. Over one week, her ejection fraction improved to 35%, facilitating weaning from pressor support, extubation, and discharge on guideline-directed medical therapy. Conclusions: In TCM complicated by shock, meticulous MCS selection is paramount. Although Impella confers more robust unloading, heightened device-related complications may be unjustified in a largely reversible disease. IABP can sufficiently stabilize hemodynamics, enable myocardial recovery, and mitigate morbidity, underscoring the importance of individualized decision-making in TCM-related shock. Importantly, no trial has shown that MCS confers a proven long-term mortality benefit beyond initial hemodynamic rescue. Full article

The integration of artificial intelligence in interventional radiology is an emerging field with transformative potential, aiming to make a great contribution to the health domain. This overview of reviews seeks to identify prevailing themes, opportunities, challenges, and recommendations related to the process of integration. Utilizing a standardized checklist and quality control procedures, this review examines recent advancements in, and future implications of, this domain. In total, 27 review studies were selected through the systematic process. Based on the overview, the integration of artificial intelligence (AI) in interventional radiology (IR) presents significant opportunities to enhance precision, efficiency, and personalization of procedures. AI automates tasks like catheter manipulation and needle placement, improving accuracy and reducing variability. It also integrates multiple imaging modalities, optimizing treatment planning and outcomes. AI aids intra-procedural guidance with advanced needle tracking and real-time image fusion. Robotics and automation in IR are advancing, though full autonomy in AI-guided systems has not been achieved. Despite these advancements, the integration of AI in IR is complex, involving imaging systems, robotics, and other technologies. This complexity requires a comprehensive certification and integration process. The role of regulatory bodies, scientific societies, and clinicians is essential to address these challenges. Standardized guidelines, clinician education, and careful AI assessment are necessary for safe integration. The future of AI in IR depends on developing standardized guidelines for medical devices and AI applications. Collaboration between certifying bodies, scientific societies, and legislative entities, as seen in the EU AI Act, will be crucial to tackling AI-specific challenges. Focusing on transparency, data governance, human oversight, and post-market monitoring will ensure AI integration in IR proceeds with safeguards, benefiting patient outcomes and advancing the field. Full article