Bio-medical materials and engineering最新文献

Background: The differences in bony alignment of the lower extremities during gait compared to standing remain unclear.

Objective: This study aimed to evaluate three-dimentional (3D) lower extremity alignment in healthy elderly individuals during the stance phase of gait and compare it with static standing alignment.

Methods: Thirty-four knees (9 females, 8 males; mean age 73.2 years) were assessed using single-plane X-ray fluoroscopy and a 3D to two-dimensional (2D) image matching technique. Alignment during stance phase and standing was evaluated in a world coordinate system, using the direction of gravity and frontal X-ray (aligned with the gait direction) as references.

Results: Compared to standing, the femur (3.5°), tibia (3.2°) and tibial joint line relative to the floor (3.3°) exhibited increased lateral inclination during stance phase (p < 0.01). In the transverse plane, the femur showed a significant increase in external rotation during stance phase (5.0°, p < 0.01) compared to standing, with no significant difference in tibial rotation.

Conclusion: Lower extremity alignment significantly differs between static standing and gait, making it challenging to accurately infer the alignment during gait from standing assessments. This approach offers a practical means for assessing functional lower extremity alignment, potentially improving clinical outcomes in realignment surgeries.

Background: Lung cancer is a leading cause of cancer-related deaths worldwide, making early diagnosis crucial for improving treatment success and survival rates. Traditional diagnostic methods, such as biopsy and manual CT image interpretation, are time-consuming and prone to variability, highlighting the need for more efficient and accurate tools. Advances in deep learning offer promising solutions by enabling faster and more objective medical image analysis.

Objective: This study aims to classify benign, malignant, and normal lung CT images using advanced deep learning techniques, including a specially developed CNN model, to improve diagnostic accuracy.

Methods: A dataset of 1097 lung CT images was balanced using GANs and preprocessed with techniques like histogram equalization and noise reduction. The data was split into 70% training and 30% testing sets. Models including VGG19, AlexNet, InceptionV3, ResNet50, and a custom-designed CNN were trained. Additionally, Faster R-CNN-based region proposal methods were integrated to enhance detection performance.

Results: The custom CNN model achieved the highest accuracy at 99%, surpassing other architectures like VGG19, which reached 97%. The Faster R-CNN integration further improved sensitivity and classification precision.

Conclusion: The results demonstrate the effectiveness of GAN-supported deep learning models for lung cancer classification, highlighting their potential clinical applications for early detection and diagnosis.

Background: To alleviate the workload of medical staff and provide personalized care for hepatitis patients, this study focuses on developing a hepatitis care robot.

Objective: The objective of this study is to integrate the RP-lidarA1 sensor into a hepatitis care robot to achieve high-precision environmental perception, mapping, and navigation, thereby improving healthcare services.

Methods: The RP-lidarA1 sensor was utilized for environmental scanning, and the MPU6050 chip was used to collect attitude data. An improved RBPF-SLAM algorithm was employed for high-precision map construction. For positioning and navigation, a combination of the A* algorithm and Dynamic Window Approach (DWA) algorithm was used to optimize path planning and obstacle avoidance.

Results: Simulation experiments demonstrated that the improved algorithm reduced the number of particles to 50 in a 140 m² area and shortened the map construction time to 1200 s. The A* algorithm effectively planned optimal paths, while the DWA algorithm improved navigation efficiency. Satisfaction surveys indicated that 92.4% of hepatitis patients and 81.8% of nurses were highly satisfied with the robot's performance.

Conclusions: The hepatitis care robot integrating the RP-lidarA1 sensor showed excellent performance in autonomous navigation, map construction, and obstacle avoidance, significantly enhancing the quality and efficiency of medical services.

Background: Tuberculosis (TB) is a global health challenge from a single infectious agent, Mycobacterium tuberculosis (MTB), and it demands improved diagnostics and therapies.

Objective: This work explored a novel method for detecting MTB by combining nanogold labeling (NGL) technology with silver staining to enhance sensitivity and specificity.

Methods: Nanogold particles (NGPs) were characterized using ultraviolet absorption spectroscopy (UVAS), and their morphology was observed via transmission electron microscopy (TEM). The silver staining enhancement (SSE) system was optimized for a reaction time of 11 min. Fifty drug-resistant tuberculosis (DRT) patients were randomly assigned to a control (Ctrl) group receiving conventional nursing and an experimental (Exp) group treated with continuous nursing intervention (CNI). Quality of Life Instrument for Tuberculosis Patients (QLI-TB) scores were compared over 6 months.

Results: Unmarked NGPs were evenly distributed, while labeled NGPs maintained complete morphology with a gray halo. The detection limit was established at 0.582, reaching as low as 1 pmol/L. For sputum specimens, detection rates were 38.7% for culture, 41.94% for PCR, and 43.54% for nanogold SSE, with no significant differences (P > 0.05). However, patients in the Exp group exhibited significant improvements in physical, psychological, and social functions, as well as the tuberculosis-specific module (TSM) compared to the Ctrl group (P < 0.05).

Conclusions: We demonstrated an innovative method for detecting MTB, demonstrating promising results through method optimization and analysis.

Background: Wound healing proceeds through a complex collaborative process. It has been shown that during the intermediate phase of the wound healing process, fibroblasts migrate into wound area and contract to contribute to the closure of the wound area. Moreover, previous studies have shown that fibroblast alignment was observed on the mature stage of wound scar. These studies clearly indicate that fibroblasts play a critical role in wound healing process, however, the whole mechanism of wound healing remains still unclear.

Objective: Fibroblasts are pre-aligned to evaluate the effect of cell alignment on cell migration rate.

Methods: The cell alignment was accomplished by PDMS microstamping with fibronectin and application of cyclic stretching. Wound was created by physical scratching and then the wound closure rate was measured.

Results: The pre-aligned cells perpendicular to the direction of scratched wound exhibited significantly higher migration rate, compared to non-aligned control cells. Moreover, pre-aligned cells with thick actin filaments by cyclic stretching migrated faster than those with less development of actin filament structures by microstamping.

Conclusion: The wound closure can be accelerated by the adequate alignment of fibroblasts as well as the development of actin filament structures.

Background: Urethral stricture (US) is a common condition that considerably affects patients' quality of life.

Objectives: This study aimed to explore the adoption value of the extracellular vesicle (EV)- small intestinal submucosa (SIS) complex in the repair of USs.

Methods: EVs were extracted from healthy male New Zealand white rabbits, and SIS was prepared using peracetic acid (PAA) oxidation and decellularization. The morphology and particle size of the prepared EV-SIS complex were evaluated using electron microscopy and qNano nanoparticle analyzer, and the labeled proteins of EVs were detected using Western blot method. EV-SIS the complex was implanted in a rabbit model of US, and urodynamic parameters were assessed.

Results: The EV-SIS complex displayed a full morphology, intact membrane structure, and uniform particle size. The protein concentration of EVs in the complex was approximately 0.351 µg/µL, with a yield of approximately 1.86 µg/10⁶ cells. The complex exhibited remarkable repair effects in the rabbit model of US, with bladder capacity, maximal urethral pressure, and minimal urethral pressure all markedly superior to those in the US group (P < 0.05).

Conclusion: The EV-SIS complex demonstrates potential clinical value in the repair of USs, improving urodynamic parameters, and offering a promising therapeutic option for patients with US.

Background: Dissociation is a special type of dislocation that is rarely seen in bipolar hemiarthroplasty.

Objective: To investigate the clinical and biomechanical causes of dissociative dislocation of acetabular cup components in the hips of patients after bipolar hemiarthroplasty (BHA).

Methods: BHA heads were divided into three groups according to their design. Cam-out and pull-out biomechanical tests were conducted to investigate the separation strengths of the BHA heads.

Results: Among the 1684 BHA surgeries performed, the revision surgery rate was 4% (68 hips) and dissociation rate was 0.8% (15 hips). According to the cam-out test result, the highest values in the parameters ultimate force (F_max) ultimate torque (T), vertical displacement at maximum force (δ_m), rotation at maximum force (ϕ_m), maximum principal strain (Ɛ_max), minimum principal strain (Ɛ_min), average normal strain (Ɛ_av), maximum shear strain (γ_max), uniaxial normal strain (Ɛ_un) were detected in Type 2 BHA head. The pull-out values of the implants were sufficient to prevent the distraction force that may occur on the implant due to manual traction applied to the hip dislocations. However, in closed reduction maneuvers, cam-out-shaped deformation forces may cause dissociation in Types 1 and 3, but not in Type 2 BHA heads. According to the pull-out test results, while high values were detected in the parameters Fmax and stiffness (k) in the Type 2 BHA head, δm and maximum force (E) parameters were found to be high in the Type 1 BHA head. In the cam-out test, a strong positive relationship was found between the thickness and width of the polyethylene locking ring and F_max, T, δ_m, ϕ_m, Ɛ_max, γ_max, Ɛ_un.

Conclusion: Better BHA head designs and polyethylene designs may help resolve the rare problem of dissociation, which almost always leads to resurgical procedures.

Introduction: The impact of rotational angle between the femoral and tibial components is often overlooked in the 2D evaluation of varus/valgus stability after TKA with anterior-posterior knee X-rays. The rotation angle between the femoral and tibial components may influence the measured angle and distance between these components in 2D stress X-rays following TKA.

Purpose: The purpose of this study was to assess the impact of the rotational angle between the femoral and tibial components on the evaluation of varus/valgus stability using stress X-rays following total knee arthroplasty (TKA).

Methods: This prospective study analyzed 48 consecutive rTKAs (three males, aged 68 ± 6.4 years; 45 females, aged 75 ± 5.9 years). Postoperative varus/valgus stress X-rays were taken at maximum manual stress during knee extension under anesthesia, and were analyzed three-dimensionally using a 2D-3D image matching technique with 3D bone and component models. The rotation angles of the components (CR angles) were assessed under conditions of no stress, valgus stress, and varus stress. Additionally, the varus/valgus angle (VV angle) between components was evaluated under the same conditions. Medial joint opening (MJO) and lateral joint opening (LJO) were also measured in both stressed and non-stressed states.

Results: The CR angles under no stress, valgus stress, and varus stress were 9.9 ± 5.5°, 10.1 ± 6.2°, and 10.8 ± 5.1°, respectively. The VV angles under no stress, valgus stress, and varus stress were 3.6 ± 1.1°, 1.1 ± 1.4°, and 7.1 ± 1.9°, respectively. The MJO in the non-stress condition and under valgus stress were 0.0 ± 0.4 mm and 1.3 ± 1.0 mm, respectively. The LJO in the non-stress condition and under varus stress were 0.9 ± 0.9 mm and 2.9 ± 2.7 mm, respectively.

Conclusions: This prospective study revealed two key findings: (1) the CR angle in varus stress was significantly more externally rotated compared to the CR angle in the non-stress condition, and (2) no significant correlations were found between the rotational angle of the components and the VV angle, MJO, or LJO.

Background: Ischemic stroke is a medical condition caused by occlusion of blood vessels in brain, resulting in disruption of blood flow to the brain and triggering irreversible damage to the neuronal cells. While stem cells transplantation has been proposed as a potential alternative therapym for ischemic stroke, its effectiveness is limited due to low cell survival rate and potential side effects following transplantation. To overcome these challenges and enhance therapeutics efficacy, researchers have focused on developing various biomaterials to create a sustainable cellular microenvironment or to modify the properties of donor stem cell which could optimize their reparative functions in injured brain tissues.

Objective: This review aims to explore and discuss the different types of biomaterials that have been applied in the treatment of ischemic stroke, shedding light on their potentials as promising therapeutics options for this debilitating condition.

Methods: Literature search was performed to identify publications studying the potential of three biomaterials namely: nanobioparticles, hydrogels and extracellular vesicles for ischemic stroke therapy in vitro, in vivo or in clinical using four databases, namely: PubMed, ScienceDirect, Web of Science and Scopus.

Results and discussion: The major benefits obtained from the application of nanobioparticles for ischemic stroke therapy included as the nanocarrier for drug/cell delivery, cell tracking, real time imaging, promote cell proliferation, while hydrogels provided scaffold support and conferred neuroprotection to stem cells, as well as provided neurotropic effects and controlled drug release for localized treatment. Lastly the extracellular vesicles were identified as a cell-free treatment strategy in promoting angiogenesis, neuronal differentiation and neurogenesis for ischemic stroke treatment.

Conclusion: Biomaterial-based therapies have their own potentials and further clinical investigations are strongly recommended to translate the therapies into more conscientious evidence-based therapy for clinical application.

Background: Vessel segmentation is a critical aspect of medical image processing, often involving vessel enhancement as a preprocessing step. Existing vessel enhancement methods based on eigenvalues of Hessian matrix face challenges such as inconsistent parameter settings and suboptimal enhancement effects across different datasets.

Objective: This paper aims to introduce a novel vessel enhancement algorithm that overcomes the limitations of traditional methods by leveraging a multilayer perceptron to fit a vessel enhancement filter function using eigenvalues of Hessian matrix. The primary goal is to simplify parameter tuning while enhancing the effectiveness and generalizability of vessel enhancement.

Methods: The proposed algorithm utilizes eigenvalues of Hessian matrix as input for training the multilayer perceptron-based vessel enhancement filter function. The diameter of the largest blood vessel in the dataset is the only parameter to be set.

Results: Experiments were conducted on public datasets such as DRIVE, STARE, and IRCAD. Additionally, optimal parameter acquisition methods for traditional Frangi and Jerman filters are introduced and quantitatively compared with the novel approach. Performance metrics such as AUROC, AUPRC, and DSC show that the proposed algorithm outperforms traditional filters in enhancing vessel features.

Conclusion: The findings of this study highlight the superiority of the proposed vessel enhancement algorithm in comparison to traditional methods. By simplifying parameter settings, improving enhancement effects, and showcasing superior performance metrics, the algorithm offers a promising solution for enhancing vessel parts in medical image analysis applications.