Annals of Biomedical Engineering最新文献

Purpose

Changes in residual limb volume and shape pose significant challenges in achieving and maintaining an accurate and comfortable fit for prosthetic socket. While numerous techniques for measuring residual limb volume have been proposed, their clinical application remains limited by insufficient resolution and the inability to perform in-socket measurements. To address this issue, this study develops a novel method for predicting residual limb soft tissue deformation to guide prosthetic socket design.

Methods

A three-dimensional (3D) finite element (FE) model of the human thigh was developed to simulate the soft tissue deformation during daily activities, driven by muscle contraction to replicate natural biomechanics. The model included hard tissue and muscle components, with the muscle modeled as a structure of evenly distributed, contractile fibers that generate movement. Parameters controlling fiber contraction were iteratively adjusted to best match the calculated tissue deformation and that observed in physical muscle models.

Results

The optimized FE model significantly improved the accuracy of predicting dynamic soft tissue deformation, with average errors of 0.83% and 1.86% for tissue expansion and contraction regions, respectively. For various gait patterns, the average differences in equivalent volume and cross-sectional area changes were also less than 0.83% and 1.86%, respectively.

Conclusion

The model demonstrated consistent prediction accuracy across different gait data. The fiber-driven soft tissue model developed offers a valuable tool for pre-design simulations of prosthetic sockets and orthoses. It is equally applicable to other wearable devices that interface with the skin, providing a robust framework for improving device design and functionality.

Purpose

Vascular remodelling is increasingly recognised as a key pathological feature in Chronic Obstructive Pulmonary Disease (COPD), with changes in pulmonary blood flow offering early biomarkers of disease. However, computational models capable of capturing the evolution of pulmonary haemodynamics across COPD severity stages are lacking. This study presents an anatomically based in silico model of the pulmonary circulation designed to investigate haemodynamic changes in response to vascular remodelling and parenchymal destruction in smokers without COPD and in patients with varying stages of COPD.

Methods

A one-dimensional, steady-state model of pulmonary blood flow was adapted to simulate extra-acinar arterial remodelling and intra-acinar capillary pruning consistent with emphysema. The model was parameterised using morphometric and clinical haemodynamic data at rest and during exercise across GOLD stages 1–4.

Results

Model-predicted mean pulmonary arterial pressure (mPAP) increased progressively from 13.5 mmHg (baseline) to 16.1 mmHg (GOLD 2), 21.2 mmHg (GOLD 3), and 25.9 mmHg (GOLD 4), with increasing vascular remodelling, matching clinical data within reported error bounds. In the most severe COPD case, GOLD 4, 70% of arterial vessels and 35% of acinar units were modified to represent disease. Height-dependent flow and pressure gradients were markedly altered in GOLD 4 indicating significant redistribution and increased heterogeneity of pulmonary blood flow.

Conclusion

This model reproduces clinically measured mPAP and pulmonary vascular resistance values across COPD stages and quantifies how specific degrees of remodelling and pruning drive haemodynamic deterioration. This model provides a tool for hypothesis testing, patient stratification, and evaluation of potential targeted therapies in obstructive lung disease.

Purpose

In clinics, musculoskeletal assessment mainly relies on conventional imaging which is expensive, involves radiation exposure, and lacks accessibility. Inferring skeletal morphology from 3D body surface scans shows potential as an alternative screening aid, although lacks detail in particular at extremities. This study leverages Statistical Shape Models (SSMs) to estimate position and orientation of the hand and foot bones from the skin surface.

Methods

Two datasets (140 feet, 79 hands with diverse morphologies and poses) were collected. For each dataset, a coupled skin-bone SSM was created. A nested cross-validation approach was used to optimize hyperparameters and prevent overfitting while fitting the isolated skin model of the coupled SSM to unseen skin data to infer bone structure and position.

Results

For the feet, the mean absolute error (MAE) was 1.68 mm, with the highest errors occurring at the hindfoot. Similarly, for the hands, the MAE reached 1.37 mm, with the largest deviations observed at carpal bones.

Conclusion

This study demonstrates the feasibility of predicting bone morphology from skin surfaces using SSM-based shape completion, offering a potential non-invasive and accessible alternative to traditional imaging for musculoskeletal assessments.

Purpose

Prolonged wear of generic respiratory masks such as the N95 could provide discomfort due to poor fitting to the user face morphology and excessive tightening. This study aims to personalize the design of respiratory masks and simulate the fitting using finite element analysis.

Methods

A cohort of 10 participants was recruited to evaluate the fit of a 3D respiratory mask created by scanning the face with the ARKit framework and a high-resolution 3D infrared camera. The respiratory mask pressure and seal were calculated using numerical simulations with Ansys Mechanical. A pressure map illustrates the pattern that the respiratory mask will produce on a given user’s face, to assert the desired comfort criteria. A map of the gap between the mask and the face shows the sealing capability of the mask. To ensure the consistency of the numerical results, experimental pressure measurements were also performed on the participants. Facial pressure calculation and measurement tests were performed under three levels of tightening. User’s feedback on the respiratory mask was also obtained.

Results

Simulation results appeared to be lower than those obtained experimentally, so a global correction was made. Only 14% of the results obtained after correction differ by more than 1N from the experimental reference value.

Conclusion

The outcome of this study could provide insights in the design of respiratory masks through face scanning technologies and numerical simulation. Moreover, it could contribute to fully customize the respiratory mask to the user’s face, for enhanced comfort and proper sealing.

Purpose

Glioblastoma multiforme is an aggressive, potentially fatal form of brain cancer characterised by an extremely poor prognosis. Glioblastoma spheroids can recapitulate the major three-dimensional tumour characteristics, encompassing cell-cell interactions, extracellular matrix deposition, and diffusion gradients for in vitro assessment. Furthermore, insufficient characterisation, inconsistent reproducibility, and inadequately standardised protocols restrict the use of spheroids as substitutes for in vivo models.

Methods

Here, we propose the fabrication of a polycaprolactone scaffold using a 3D printing system that can induce spheroid formation when seeded with glioblastoma cells. In this current study, U87-MG cells were seeded on 3D printed polycaprolactone scaffolds. The printed scaffolds containing spheroids were assessed for biocompatibility using Live/Dead staining, ATP-based viability assay, and analysis of GFAP expression. To demonstrate the practicability of the printed scaffold as a model for drug screening, U87-MG spheroids were exposed to temozolomide, and the cell viability was quantified.

Results

U87-MG spheroid formation was observed within 24 h, indicating the suitability of 3D printed PCL scaffolds for spheroid generation. Live/Dead staining and luminescent ATP-based viability assays confirmed the biocompatibility of the scaffold and its capacity to support cellular proliferation. Analysis of GFAP expression confirmed the stemness of the U87-MG spheroids formed in the 3D printed PCL scaffolds. The spheroids were susceptible to temozolomide, with pronounced cell death and loss of architecture, as observed on the 7th day. The comparable drug response profiles observed in all three scaffold groups further support the use of 3D printed PCL scaffolds as a viable platform for drug screening.

Conclusion

3D printed PCL scaffold supported the formation of U87-MG spheroids without the need for external cues and presents a robust platform for drug screening applications.

Infertility, a pressing global health concern, affects a substantial proportion of individuals worldwide. While advancements in assisted reproductive technology (ART) have offered effective interventions, conventional in vitro fertilization-embryo transfer (IVF-ET) procedures still encounter significant hurdles in enhancing pregnancy success rates. Key challenges include the inherent subjectivity in embryo grading and the inefficiency of multi-modal data integration. Against this backdrop, the adoption of AI-driven technologies has emerged as a pivotal strategy to address these issues. This article presents a comprehensive review of the progress in AI applications for embryo grading and pregnancy prediction from a novel perspective, with a specific focus on the utilization of different modal data, such as static images, time-lapse videos, and structured tabular data. The reason for this perspective is that reorganizing tasks based on data sources can not only more accurately depict the essence of the problem but also help clarify the rationality and limitations of model design. Furthermore, this review critically examines the core challenges in contemporary research, encompassing the intricacies of multi-modal feature fusion, constraints imposed by data scarcity, limitations in model generalization capabilities, and the dynamically evolving legal and regulatory frameworks. On this basis, it explicitly identifies potential avenues for future research, aiming to provide actionable guidance for advancing the application of multi-modal AI in the field of ART.

Occupational activities that require high knee flexion, such as kneeling and squatting, are associated with a higher prevalence of knee osteoarthritis (OA). It is generally accepted that excessive contact pressures in the joint may cause degeneration of healthy knee joints. Ailments in the patellofemoral (PF) joint were a common cause for knee pain in clinical observations. Knee savers have been used in sports and occupational activities to protect the knee joints during tasks involving high knee flexion. The biomechanics of the effects of knee savers on musculoskeletal loading have not been investigated. The purpose of the current study was two-fold: first was to develop a biomechanical model that accounts for the effects of the interface contact forces between thigh and shank, or between thigh-shank and knee savers; and second was to evaluate, using the biomechanical modeling, the effects of knee savers on musculoskeletal loading in the knee joint in high knee-flexion tasks. Five healthy male subjects (age (20.6 pm 1.96) years, body mass (87.74 pm 9.98) kg, height (1.81 pm 0.08) m) participated in the study. The subjects started from a standing posture, squatted down to a working posture, and returned to the standing posture, while subjects’ heels remained on the ground during the tasks. The tasks were repeated without and with knee savers. The musculoskeletal loadings in the knees were calculated using inverse dynamic modeling. Our results indicated that the wearing of knee savers in the high knee-flexion tasks helped to reduce the contact forces in the PF joint by about 20%. Our findings suggest that wearing knee savers may help reduce the risks of the knee OA for workers who are frequently required to perform high knee-flexion tasks for extended time.

Purpose

Repetitive head impacts in sports have been of increasing concern due to their potential impact on long-term brain health. Despite this recognition, head impacts have rarely been investigated in the sport of rodeo. This study tracked and characterized head acceleration events (HAEs) experienced by collegiate rodeo athletes in the roughstock events of Bareback, Saddle Bronc, and Bull Riding.

Methods

Instrumented mouthguards were used to track HAEs in 13 Bareback, Saddle Bronc, and Bull Riding athletes at National Intercollegiate Rodeo Association (NIRA)-sanctioned competitions. HAEs were subsequently video verified and categorized based on the cause of HAE.

Results

A total of 112 rides were monitored across five collegiate rodeo competitions capturing 344 HAEs. Bareback was associated with the highest frequency of HAEs of the three events but the lowest median linear acceleration. The most common mechanism of HAE across the events was whiplash, rather than direct head contact.

Conclusion

Collegiate rodeo athletes in Bareback, Saddle Bronc, and Bull Riding experience significant HAEs throughout a rodeo season that varies based on event and mechanism of HAE.