Annals of Biomedical Engineering最新文献

Purpose: In clinical diagnosis, diabetes, and arthritis were often considered independent, which leads to diabetics getting worse by ignoring early arthritis symptoms. Therefore, the fatigue damage mechanism of articular cartilage in a hyperglycemic environment must be clarified.

Methods: Under simulating physiological loads, this study delved into glycated cracked cartilage's fracture toughness and damage mechanism. Moreover, by introducing the glucose concentration as a crucial variable, a constitutive model of the ratcheting behavior of glycated cracked cartilage was established, which is utilized to predict the impacts of glycation on cartilage.

Results: The glycation environment causes cartilage hardening, which, in turn, leads to a substantial 38.1% reduction in the initial strain required for crack extension, despite an enhancement in tensile strength. This observation was further supported by the study of dynamic mechanical behavior. Through scanning electron microscopy (SEM), it was noticed that this mechanistic change takes place after collagen fibers harden and adhere to one another in the glycation environment.

Conclusion: Overall, these results hold significant implications for understanding osteoarthritis (OA) in diabetic patients and for the development and protection strategies related to this condition. Therefore, once there are symptoms of cartilage discomfort, diabetic patients need to pay special attention to the moderation of exercise and joint protection compared to healthy people.

Purpose: Orthostatic intolerance is a category of disorders characterized by inadequate hemodynamic compensation upon standing. In this study, we developed a portable, active abdominal compression binder intended for individuals with orthostatic intolerance. We present proof-of-concept evidence in healthy volunteers demonstrating the binder's ability to provide consistent abdominal compression, reduce tachycardic response upon standing, and maintain user comfort.

Methods: We designed and fabricated a novel active binder that applies motor-driven abdominal compression upon the detection of standing. Twenty healthy volunteers (ages 18-50 years) completed three randomized supine-to-standing trials: no binder, a commercial passive binder, and the novel active binder. Throughout each trial, compression pressure, heart rate, and respiration were continuously monitored and comfort was assessed via post-trial Likert-scale survey.

Results: The active binder achieved a higher mean compression pressure (≈ 11 mmHg) with significantly lower intersubject variability (standard deviation (SD) ≈ 1 mmHg) than the passive binder (mean ≈ 8 mmHg; SD ≈ 3 mmHg). Active compression reduced the standing heart rate by 4.4 bpm compared to control (p < 0.05) vs. a 1 bpm reduction with the passive binder (p > 0.05). Neither the active nor the passive abdominal binders impeded respiration. Survey responses demonstrated that the active binder was at least as comfortable as the passive and was rated easier to don.

Conclusion: These findings suggest that active abdominal compression may serve as a more efficacious, consistent, and user-friendly alternative to passive binders for mitigating orthostatic intolerance.

Clinical trial number: Not applicable.

Background: Hemodynamic abnormalities of the offending vessels may be the main cause of primary hemifacial spasm (HFS). The aim of this study was to explore the mechanism of HFS and provide potential therapeutic strategies by using computational fluid dynamics (CFD).

Methods: We retrospectively analyzed 74 HFS patients. Based on MRI, 68 symptomatic and 31 asymptomatic neurovascular contact (NVC) models at the root exit zone of the facial nerve were reconstructed. CFD was used to calculate hemodynamic parameters. Time-series parameters were compared between groups by linear mixed-effects models. Receiver operating characteristic curve was used to evaluate non-time-series parameters and determine optimal cutoff values, while restricted cubic spline was applied to those parameters that performed well to assess their nonlinear relationship with HFS.

Results: At the center of the NVC region, the symptomatic NVC group exhibited significantly higher time-averaged wall shear stress (TAWSS, p < 0.001) and time-averaged wall shear stress ratio (TAWSSR, p < 0.001), while exhibiting significantly lower endothelial cell activation potential (ECAP, p = 0.017) and relative residence time (RRT, p < 0.001). Linear mixed-effects models indicated that, at the NVC center in the symptomatic group, wall shear stress, wall shear stress ratio, and wall pressure gradient were significantly higher throughout the entire cardiac cycle compared with the asymptomatic group (Group-p < 0.001). TAWSSR at the NVC center point (NVCP) showed better discriminatory ability in differentiating symptomatic from asymptomatic cases (AUC = 0.947, DeLong test p < 0.05). However, no statistically robust nonlinear relationship was found between NVCP's TAWSSR, TAWSS, or RRT and HFS.

Conclusion: The NVC region in HFS patients suffer greater hemodynamic forces and steeper fluctuations compared to asymptomatic NVC cases, suggesting mechanical effects involved in HFS pathogenesis. Hemodynamic parameters may serve as reliable indicators for diagnosis, localization of the compression site, and guidance of endovascular treatment in HFS.

Purpose: Finite element (FE) modeling is a powerful computational tool used to simulate complex systems. In recent years, a considerable number of publications have reported the use of the FE method to study the cochlea and cochlear implants (CIs). However, large variability exists in the development of cochlear FE models.

Objective: To present a systematic review of FE macromechanical modeling of the cochlea, identifying the techniques used and associated limitations across existing studies.

Method: A literature search was conducted through PubMed, Scopus, and IEEE-Xplore databases of studies using FE modeling to study the cochlea and CIs. Studies published between January 1, 1985, and February 15, 2025, were assessed using the Covidence systematic review platform ( www.covidence.org ).

Results: A total of 1209 publications were found through the initial database search. After screening and full-text review, 77 studies met the inclusion criteria. Two primary modeling strategies were identified: simplified uncoiled model or realistic coiled model, including either two chambers or three chambers by incorporating the scala media and Reissner's membrane. Substantial variation was observed in material assumptions, particularly regarding basilar membrane stiffness. Validation was inconsistent; most studies compared model outputs with established experimental data such as Greenwood's frequency-place function, while some used computational comparisons or limited clinical data.

Conclusion: FE cochlear models provide valuable insight into cochlear mechanics yet remain constrained by simplified geometries, non-standardized material parameters, and insufficient experimental validation. Future work should integrate imaging and functional data and establish standardized modeling, material properties, and validation frameworks to improve physiological and clinical relevance.

Introduction: The conventional derivation of the pressure pulse wave velocity (PWV) relies on the wave equation for blood flow in a uniform elastic artery, wherein PWV is considered dependent on the linear elasticity of the artery and on the blood density. Arterial elasticity is represented by transverse compliance, i.e., assuming that the artery is fixed lengthwise. However, arteries exhibit a nonlinear and anisotropic stretch-stress behavior, challenging the conventional PWV equation based on a linear stretch-stress relationship. Moreover, the ascending thoracic aorta (ATA) undergoes dynamic axial elongation during the cardiac cycle, which co-determines its biomechanical response. This study establishes a derivation for understanding how this dynamic axial elongation affects local PWV in a hyperelastic ATA.

Methods: ATA compliance was analytically derived by relating the diameter change to changes in the intraluminal pressure and axial stretch. Synthetic pressure-diameter curves were generated using the Gasser-Ogden-Holzapfel model, assuming a thin-walled cylinder with an axial stretch of 1.2 at diastolic pressure and axial strains of 0, 2, 4, 6, and 8% superimposed to the diastolic-to-systolic pressurization. Compliance values were calculated using two methods: 1) the slope of diameter-pressure curves and 2) our analytical derivation. For comparison, PWV was determined by using the obtained compliance values in the conventional wave equation.

Results: Our derived compliance agreed with the compliance calculated from the slope of the diameter-pressure curves. PWV increased with axial strains, even at a constant pressure.

Conclusion: In clinical studies, it is important to consider the influence of dynamic axial elongation on PWV measurements.

The computer-assisted automatic planning (CAAP) technology for percutaneous liver tumor ablation plays a crucial role in enhancing the precision and safety of minimally invasive treatments. CAAP reduces the manual workload of clinicians through path planning and treatment parameter optimization, while simultaneously improving planning efficiency and clinical reliability. This paper first reviews the basic principles of thermal ablation, including path planning, treatment parameter optimization, and temperature field modeling, and outlines the theoretical foundations of CAAP's key technologies. The existing methods are then classified according to their technical characteristics, covering traditional optimization algorithms, intelligent optimization methods, and deep reinforcement learning techniques. The focus is on single-needle and multi-needle path planning, multi-objective optimization, and dynamic environmental adaptability technologies. Furthermore, the performance of these methods in automation, real-time processing, and multi-physics modeling is evaluated. Finally, potential future developments are proposed.

Rapid reconstruction of a curved defect model within the allocated surgery time is a critical aspect of intraoperative bioprinting for cranial defect treatment. However, current data acquisition and defect reconstruction methods often involve manual intervention, which is impractical for real-time intraoperative printing due to their intricate and time-intensive nature. To tackle this challenge, this study introduces an online acquisition approach and a real-time automatic reconstruction algorithm for intraoperative defect data. Initially, a surface preprocessing scanning technique is proposed to address bone surface reflections and complex noise from blood and cranial tissues in live defective skulls, ensuring the acquisition of reliable defect data. Subsequently, an integrated reconstruction algorithm is developed for the obtained defect data. This algorithm seamlessly incorporates various techniques, including range filtering-based point cloud denoising, defect edge detection, patch creation utilizing the boundary-center method, and defect surface optimization based on the harmonic function. These components enable the algorithm to autonomously achieve immediate defect surface reconstruction. Finally, the effectiveness of the integrated algorithm is demonstrated through its application in surgical procedures on live rat cranial defects and human cranial defect models, showcasing its feasibility, superior accuracy, and practicality compared to software-based reconstruction methods. The algorithm is user-friendly, catering to both medical professionals and non-professionals, and fulfills the requirements of clinical intraoperative cranial treatment.

Purpose: The 30-second Chair Sit-to-Stand Test (30 s CST) is widely used to assess lower-limb function and reflects complex motor coordination across neural systems. However, conventional scoring methods are often inconsistent and fail to capture variations in compensatory movement strategies or require invasive instrumentation. This study presents a smartphone-based system that automatically detects rising strategies across repeated CST cycles, providing an automated approach to extract cycle-level biomarkers of motor performance.

Methods: Thirty-five adults 10 younger, 20 older, and 5 with Parkinson's disease performed supervised 30-s CST trials while wearing a waist-mounted smartphone that recorded accelerometer and gyroscope data at 400 Hz. Cycle detection used amplitude-adaptive thresholds and dominant-frequency intervals for robust segmentation of CST cycles. Rising strategies were classified with rule-based method that uses trunk pitch dynamics and cycle duration. Agreement with video annotations was assessed using Intraclass Correlation Coefficients (ICC (2, 1)), Bland-Altman analysis, and macro F1 scores.

Results: The algorithm detected 660 CST cycles with 99% accuracy, and the average mean absolute error across participants was under 40 ms. Bland-Altman analysis showed negligible bias (- 0.012 s) and narrow limits of agreement (- 0.134 to 0.110 s). Strategy classification achieved macro F1 = 0.94. Flexion cycles were consistently longer than Momentum Transfer cycles (e.g., older adults: 2.63 vs. 1.45 s).

Conclusion: Automated CST analysis reveals movement signatures not captured by standard timing, offering a richer characterization of mobility patterns. While these findings demonstrate technical feasibility and highlight clinically relevant variations, their application for diagnostic or personalized rehabilitation purposes remains preliminary and requires validation in larger cohorts.