Frontiers in medical technology最新文献

Hip replacement surgery requires high precision in aligning intraoperative anatomical structure localization with preoperative imaging spatial alignment. To address the registration difficulties caused by the limited number and sparse distribution of intraoperative probe acquisition points, our paper proposes a method based on point cloud registration between an intraoperative probe tracked by a passive binocular optical tracking system (NDI) and a CT surface, aimed at improving patient registration accuracy in intraoperative navigation scenarios. First, we define the patient-registration problem and describe the methods for acquiring pre-operative and intra-operative data. Subsequently, the centroids of the NDI optical tracking markers are employed as common features shared by the patient and image spaces, and an initial registration is performed using a three-point method. Finally, an improved ICP algorithm is used to perform accurate registration between the two point clouds, and the registration results are validated using a fixture platform. In the experiments conducted on 3D-printed acetabular and femoral models, the target registration errors (TRE) of the proposed method for registering the acetabular model and the femoral model are (0.55 $\pm$ 0.15) mm and (0.67 $\pm$ 0.18) mm, respectively. The experimental results demonstrate that the proposed method achieves good registration accuracy and stability under phantom experimental conditions. Using the TRE as the primary evaluation metric to measure the spatial localization error of target points, the method exhibits superior geometric registration performance compared to the traditional iterative closest point (ICP) algorithm. Additionally, it features a concise workflow and ease of implementation, providing a feasible technical solution for sparse point cloud registration in intraoperative navigation scenarios.

Introduction: Pre-anesthetic assessment involves a series of evaluations for airway management. However, the lack of quantitative analysis may limit its reliability. In this study, we propose an optimized YOLO11-Pose framework with a DeBiFormer module for automated, image-based pre-anesthetic assessment.

Methods: The proposed model performs single-stage inference to localize clinically relevant facial and hand keypoints associated with mouth opening, thyromental distance, and neck mobility. The framework was evaluated on a dataset collected from Ruijin Hospital under controlled acquisition conditions.

Results: Experimental results demonstrated high detection performance. Measurement-based evaluations, including Bland-Altman analysis, pixel-level error, and normalized mean error (NME), indicated reliable agreement with reference annotations. In addition, Mallampati classification was evaluated to assess clinical applicability. The model achieved an accuracy of 77.34% in the four-class setting and improved performance in a clinically motivated binary setting, with an accuracy of 83.99% and a quadratic weighted kappa of 0.65, indicating substantial agreement.

Discussion: These results suggest that the proposed method provides robust and clinically meaningful assessment of airway characteristics and may support automated pre-anesthetic evaluation in clinical practice.

Hearing impairment is a growing public health challenge among older adults in India, with low uptake of hearing aids despite potential benefits for communication, social participation, and health-related quality of life (HRQoL). This study evaluated the cost-utility of hearing aid provision for older adults (≥60 years) with hearing impairment in India to inform policy and financing decisions. A cost-utility analysis compared hearing aid use with no hearing aid over a 3-year decision tree and a 15-year Markov model. Data were collected in 2023 from 636 participants (276 users, 360 non-users). HRQoL was measured using EQ-5D-5L and converted to QALYs with the India value set. Costs were based on the government ceiling price for digital behind-the-ear hearing aids (₹8,000 per ear), modelled for unilateral and bilateral use. ICERs and budget impact were estimated. Mean EQ-5D-5L utility was higher among hearing aid users than non-users (0.832 vs. 0.601), with corresponding QALYs of 5.824 vs. 4.207 (incremental gain 1.617 QALYs). In the 3-year decision tree, ICERs were ₹5,419/QALY (one-year) and ₹10,359/QALY (two-year). In the discounted 15-year Markov model, ICERs were ₹3,076/QALY (one-year) and ₹5,971/QALY (two-year). Budget impact was ₹1,230 crore over 3 years (₹410 crore annually) for the modelled scale-up among older adults. Hearing-aid provision for older adults with hearing impairment in India is highly cost-effective in short- and long-term modelling. Prioritising access within healthy ageing and universal health coverage, alongside strengthened assessment, fitting, counselling, and follow-up, could maximise real-world benefits.

Introduction: Reliable electricity is fundamental to effective healthcare delivery; however, healthcare facilities in low- and middle-income countries continue to experience chronic energy shortage and frequent power interruptions. In rural India, Primary Health Centres (PHCs) often struggle to provide essential care due to unreliable electricity. This study explored healthcare providers' perspective on the impact of solar energy interventions on healthcare infrastructure and service delivery in an aspirational district of Karnataka, India.

Methods: A qualitative phenomenological study was conducted across the Yadgir district of North Karnataka, India. Focus Group Discussion (FGDs) and In-depth Interviews (IDIs) were carried out with 55 participants (16 men and 39 women), primarily healthcare providers, including medical officers, nurses, technicians, Accredited Social Health Activists (ASHAs), and other support staff. The interviews and discussions were audio-recorded, transcribed, translated into English, and thematically analysed. The study adhered to the Consolidated Criteria for Reporting Qualitative Research (COREQ) guidelines and applied the Harmonized Healthcare Assessment (HHFA) framework.

Results: Four main themes emerged: (1) strengthened service availability; (2) enhanced service readiness; (3) advanced quality of care; and (4) improved data management, costs, operation, and maintenance. Solarisation of healthcare facilities significantly improved service quality, reliability, and resilience by enabling safe maternal deliveries, ensuring reliable vaccine cold storage, and supporting timely emergency care. The perspectives of healthcare providers offer a sustainable pathway to universal health coverage in underserved regions.

Background and aims: Chronic appendicitis complicated with diarrhea presents diagnostic and therapeutic challenges due to its atypical and prolonged symptoms, often mimicking functional gastrointestinal disorders. This study aimed to evaluate the clinical characteristics and therapeutic efficacy of Direct-visualization Endoscopic Retrograde Appendicitis Therapy (D-ERAT) in these patients.

Methods: We retrospectively analyzed 55 patients with chronic appendicitis and diarrhea who underwent D-ERAT under direct endoscopic visualization. Baseline demographic, clinical, and laboratory data, imaging findings, intraoperative endoscopic observations, and postoperative recovery indicators were collected. Diarrhea frequency, stool consistency, inflammatory markers, postoperative complications, and quality of life were assessed. Patients were followed up at 1, 3, and 6 months postoperatively.

Results: Preoperatively, patients experienced a mean of 7.5 ± 2.5 diarrhea episodes per day, with Bristol stool types 5-7. Abdominal CT identified appendiceal abnormalities in all patients, while ultrasound detected 69.1%. Endoscopic findings revealed intraluminal fecaliths in 91.5% and mucosal fibrosis in 87.27%. The patency of the appendiceal lumen was well restored in all cases after the operation. Postoperatively, diarrhea frequency decreased to 1.5 ± 0.4/day, and stool consistency normalized to Bristol types 3-4. Inflammatory markers, including WBC, neutrophil percentage, and CRP, significantly improved. At 6 months, 85.5% of patients remained largely asymptomatic, indicating stable medium-term efficacy. No major adverse events occurred.

Conclusions: D-ERAT is a safe and effective minimally invasive therapy for chronic appendicitis with diarrhea, offering rapid symptom relief, preserved appendiceal function, and shorter hospitalization.

Introduction: Patient-specific cranial implants fabricated using powder bed fusion technologies require rigorous dimensional validation to ensure reliable digital-to-physical translation, particularly when complex architectures are employed. However, multistage quantitative evaluations that distinguish deviations introduced during additive manufacturing and post-processing remain limited.

Methods: A multistage dimensional accuracy assessment workflow based on high-resolution micro-computed tomography (micro-CT) was applied to a representative patient-specific cranial implant featuring a Voronoi-based macrostructure fabricated in Ti-6Al-4 V using Electron Beam Melting (EBM). The implant was digitized in the unpolished and surface-finished conditions. Three-dimensional surface models were compared with the original virtual design using full-field deviation analysis to quantify geometric variations attributable to manufacturing and post-processing.

Results: After the finishing procedure, the surface roughness decreased significantly, with Ra reduced from 19.41 µm to 1.43 µm and Rz from 83.28 µm to 6.31 µm. A comparison between the virtual model and the unpolished implant revealed dimensional deviations predominantly within -0.20 to +0.35 mm, with localized positive deviations up to +0.55 mm associated with powder adhesion and support interaction. Following post-processing, deviations shifted predominantly toward negative values owing to controlled material removal, with a mean deviation of -0.05 mm and a maximum negative deviation of -0.18 mm. Surface finishing reduced the maximum positive deviation from +0.55 mm to +0.04 mm, corresponding to an approximate 93% reduction in positive dimensional deviation. The overall topology and structural continuity of the Voronoi-based architecture were preserved throughout manufacturing and finishing.

Discussion: This proof-of-concept study demonstrated the feasibility of a multistage micro-CT-based workflow for the dimensional validation of complex patient-specific cranial implants fabricated by EBM. The proposed methodology enables differentiation between manufacturing- and post-processing-induced deviations and supports reproducible quality assessment of additively manufactured cranial implant geometries.

In this work, SARS disorder denotes a generic acute severe respiratory distress condition characterized by abnormal respiratory rate, oxygen saturation, fever, and cardiovascular stress indicators, and does not represent a COVID-19 diagnostic system. Our research aims at analyzing a context-aware SARS disorder management system through the implementation of a multi-agent simulation framework using the NetLogo setting. The system relies on the use of interacting agents as well as non-monotonic, context-sensitive reasoning to reduce uncertainty and deal with the possible inconsistencies that happen due to biosensor recordings. A knowledge-based inference component is the combination of physiological sensor outputs and domain specific contextual data to assist in making informed decisions. The research involved the use of several machine-learning classifiers, that is, Naïve Bayes, Multinomial Naïve Bayes, Decision Table, Logistic Regression, and Sequential Minimal Optimization (SMO) so as to evaluate their appropriateness in being incorporated into the developed structure. To measure the system performance, standard evaluation measures were used such as True Positive (TP), False Positive (FP), Precision, Recall, F-Measure, Matthews Correlation Coefficient (MCC), Receiver Operating Characteristic (ROC) curve, and the Precision-Recall curve (PRC). The framework includes a list of physiological, environmental, and contextual variables, such as electrocardiographic parameters, heart-rate parameters, blood-pressure parameters, arterial oxygen saturation parameters, core body temperature, room temperature, the past history of the patient, and parameters that relate to alerts. The classification task is to produce probabilistic forecasts that help to define whether a patient should be alerted or clinical staff members informed in order to facilitate context-specific healthcare response.

Background: Postoperative hemorrhage from the gastroduodenal artery (GDA) is a rare but life-threatening complication following upper gastrointestinal surgery. Its management is particularly challenging due to the frequent co-occurrence of hypovolemic shock, complex intra-abdominal infection, and malnutrition, which collectively contribute to high morbidity and mortality.

Methods: We conducted a retrospective analysis of patients who underwent either gastrectomy or pancreaticoduodenectomy and subsequently developed delayed massive GDA bleeding between January 2021 and June 2025 in the Department of General Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine.

Results: Six patients was included in this study, of whom five had undergone radical D2 lymphadenectomy and developed duodenal stump leakage or anastomotic leakage and one had undergone pancreaticoduodenectomy. All cases experienced massive postoperative arterial hemorrhage. Emergent angiographic arterial embolization was successfully performed in all cases, achieving effective hemostasis with satisfactory outcomes. Specifically, one patient required four sequential interventions, one required three, one required two, and the remaining three achieved hemostasis after a single emergent procedure. Notably, acute liver function abnormalities were observed in two cases following embolization of the common hepatic artery.

Conclusion: Massive postoperative GDA hemorrhage is a life-threatening complication after abdominal surgery. Emergent arterial embolization proves to be a rapid, minimally invasive, effective, and safe therapeutic option for this critical condition.

Flexible biopsy needles are essential for minimally invasive cancer diagnostics, enabling core biopsy sampling through endoscopic and catheter-based procedures. These approaches allow clinicians to access deep-seated or anatomically challenging lesions while reducing patient risk compared to traditional percutaneous methods. However, the shift toward minimally invasive techniques imposes competing design demands on the biopsy needle tip, which must be miniaturized and flexible enough to navigate narrow lumens while maintaining cutting efficiency and retaining adequate tissue samples for clinical diagnosis. This review presents a patent-based analysis of flexible core biopsy needle designs, focusing on mechanisms at the needle tip that govern tissue cutting and retention. We systematically evaluated 65 international patent applications and developed a classification framework for cutting and gripping strategies. Using this framework, we identified dominant technological trends and highlighted underexplored concepts. Forward-cutting tips combined with suction or macroshape grips that engage the sample from the front dominate current designs due to their mechanical simplicity. However, alternative approaches such as compliant tip designs and multidirectional cutting mechanisms offer opportunities to enhance tissue yield without increasing device diameter. Implementing these innovations could reduce the need for repeated insertions, improve sampling efficiency, and enable access to lesions previously considered unreachable. This review provides an overview of flexible core biopsy needle designs and offers insights to guide future innovations that advance minimally invasive cancer diagnostics.

Osteomyelitis is a severe bone infection caused by bacterial invasion, posing significant therapeutic challenges due to biofilm formation and antibiotic resistance. In recent years, nanozymes-a class of functional nanomaterials with enzyme-like catalytic activities-have shown considerable potential in antimicrobial applications owing to their high stability, tunable catalytic activity, and low tendency to induce resistance, positioning them as promising alternatives to conventional antibiotics. This review systematically examines the therapeutic prospects of nanozyme-based delivery systems for treating osteomyelitis. We detail the antibacterial mechanisms of nanozymes exhibiting various enzyme-mimicking activities-primarily peroxidase-, oxidase-, haloperoxidase-, and hydrolase-like functionalities-such as generating reactive oxygen species (ROS) by catalyzing endogenous hydrogen peroxide and physically degrading biofilm components. This review aims to provide a theoretical foundation and novel insights for developing efficient and safe nanozyme-based antimicrobial agents against osteomyelitis.