Biomechanics and Modeling in Mechanobiology最新文献

Lymphedema is a chronic condition characterized by impaired lymphatic drainage, leading to fluid accumulation, swelling, and progressive tissue remodeling. Compression therapy is the primary treatment used to alleviate swelling and enhance fluid drainage, yet its precise impact on interstitial fluid dynamics remains to be understood. In this study, we developed a poroelastic computational model that simulates fluid flow and tissue deformation in the lower limb under different compression strategies and compression levels. A key feature of our work is the integration of patient-specific geometries, allowing for a more physiologically accurate representation of tissue mechanics and fluid redistribution. We simulated edema formation induced by venous insufficiency by increasing blood capillary pressure from a baseline of 10–80 mmHg, and we observed that interstitial fluid pressure (IFP) increased from a baseline value of 0 mmHg to 8 mmHg, highlighting the impact of vascular dysfunction on fluid accumulation. Simulating complete blockage of lymphatic capillaries resulted in even higher IFP values (40 mmHg) compared to models with functional lymphatics, where IFP remained around 8 mmHg for high capillary pressures, underscoring the critical role of lymphatic drainage. We further showed that an increase in tissue permeability increases gravity-driven fluid pooling, potentially exacerbating swelling in lymphedematous limbs. Additionally, we incorporated an interface pressure derived from Laplace’s law to offer a more realistic estimation of IFP and volume changes, emphasizing its importance for refining compression models and optimizing treatment strategies. These findings contribute to a deeper understanding of compression therapy’s role in interstitial fluid drainage and provide a foundation for improving patient-specific lymphedema management.

Aortic dissection is a life-threatening disease with high mortality rates. The degradation of the layers of the aorta wall causes tears, which then propagate further due to high-pressure blood penetrating the vessel wall, creating a false lumen. The intimal flap separating the true and false lumen can either bulge inwards constricting the true lumen’s blood flow or bulge outwards leading to catastrophic rupture and internal bleeding. Therefore, to understand the role of critical pressure on tear propagation, a computational study of the initiation and propagation of tears of various sizes and at multiple depths and locations in three-dimensional aortas was conducted. Tears were modelled using the extended finite element method, and the wall of the aortas is an anisotropic hyperelastic material. Blood-pressure-loaded aorta geometries were obtained from the corresponding unloaded geometries using an iterative procedure to match the in vivo geometries. Pressure-driven tear initiation and propagation were studied. Our results show that when the tear surface’s normal is perpendicular to the blood flow, the critical pressure required to cause further propagation is higher for the shorter and deeper tears and reduces when the initial tear size increases. When the normal is parallel to the blood flow, the difference in critical pressure with an increase in tear depth is small and is more likely to propagate transversely. Also, the critical pressure decreases with an increase in the diameter of the aorta for all the tear orientations. This study concludes that tear size, depth inside the medial layer and the diameter of the aorta near the tear location are critical parameters in assessing the risk of further propagation.

We present a 1D-0D model that couples a 0D description of lung mechanics to the closed-loop Anatomically-Detailed Arterial-Venous Network (ADAVN) model. We show that our model can satisfactorily reproduce a set of cardiovascular indices of interest observed in healthy young males at rest. Next, we assess the impact of respiration on cardiac performance and on the periodicity and average values of pressure and flow waveforms in different vascular districts. In particular, our results confirm that respiration has a fundamental pumping function, which aids venous return, and that its action affects mainly the average of haemodynamic variables on the arterial side, while on the venous side it has a significant effect on wave periodicity and triggers a complex interplay in terms of waveform conformation. Additionally, we assess the sensitivity of model predictions to variations in model parameters through a local sensitivity analysis, both in the presence and absence of respiration, highlighting a strong relationship between the arterial and venous side of the model.

Understanding how demographics and risk factors differentially affect the nonlinear orthotropic mechanical properties of human femoropopliteal arteries (FPAs) is critical for improving computational models of device–artery interactions. However, directly assessing these effects is challenging due to their intricate interrelationships and multifaceted impact on arterial mechanics. This study aimed to quantify the independent and combined effects of aging, diabetes, obesity, hypertension, and coronary artery disease on the mechanical behavior of human FPAs using machine learning (ML). FPAs from 450 tissue donors 12–99 years old (average age 51 ± 18 years, 66% male) were evaluated using multi-ratio planar biaxial extension. ML models, optimized through hyperparameter tuning and cross-validation, were used to describe subject-specific nonlinear orthotropic arterial properties based on demographics and risk factors. Age accounted for 60% of the variability in arterial mechanics and had a stronger influence longitudinally than circumferentially. The presence of diabetes and coronary artery disease each added 13 and 11 years to vascular age circumferentially but < 3 years longitudinally. Obesity and hypertension each added 4 years to vascular age circumferentially and less than 3 years longitudinally. Compound effects of diabetes, hypertension, and obesity aged the artery more than 21 years circumferentially and 7 years longitudinally. These findings highlight the differential impact of risk factors on orthotropic arterial mechanics and demonstrate the potential of our approach for predicting subject-specific vascular properties. Incorporating these findings into computational models can enhance the accuracy of device–artery interaction simulations by accounting for individual-specific vascular characteristics.

The tracheal stent is one of the treatment modalities for tracheal stenosis. However, the mismatch of mechanical properties between the tracheal stent and the trachea may lead to stent migration. The aim of this study is to design a tracheal stent with J-shaped load–deformation behavior based on a multi-objective optimization method. Four design parameters were selected as optimization variables. The optimization objectives were the loads at 5%, 10%, 15%, and 20% deformation during uniaxial tensile test. The optimal Latin hypercube sampling was used to generate training samples, and Kriging surrogate model was constructed between tracheal stent design parameters and mechanical properties. An optimized stent model was established after obtaining the optimal stent design parameters by NSGA-II algorithm. Additionally, a commercial silicone stent model was established as the control. The results indicate that ligament angles and the width of circular arc connected ligaments play a prominent role in the load–deformation curve of the stent. The radial supporting performance (39.79 MPa vs. 4.63 MPa) and anti-migration properties (16.1 N vs. 13.7 N) of the optimized stent are superior to those of the silicone stent. This work demonstrates that a tracheal stent exhibiting a J-shaped load–deformation behavior was designed, which could reduce stent migration.

Developing clinically viable tissue-engineered structural cardiovascular implants—such as vascular grafts and heart valves—remains a formidable challenge. Achieving reliable and durable outcomes requires a deeper understanding of the fundamental mechanisms driving tissue evolution during in vitro maturation. Although considerable progress has been made in modeling soft tissue growth and remodeling, studies focused on the early stages of tissue engineering remain limited. Here, we present a general, thermodynamically consistent model to predict tissue evolution and mechanical response throughout the in vitro maturation of passive, load-bearing soft collagenous constructs. The formulation utilizes a stress-driven homeostatic surface to capture volumetric growth, coupled with an energy-based approach to describe collagen densification via the strain energy of the fibers. We further employ a co-rotated intermediate configuration to ensure the model’s consistency and generality. The framework is demonstrated with two numerical examples: a uniaxially constrained tissue strip validated against experimental data and a cruciform-shaped biaxially constrained specimen subjected to load perturbation. These results highlight the potential of the proposed model to advance the design and optimization of tissue-engineered structural cardiovascular implants with clinically relevant performance.

Alternatives to Diffusion-Tensor-Imaging tractography methods for determining fibre orientation fields in skeletal muscle include Laplacian flow simulations. Such methods require flux boundary conditions (BCs) at the tendons and/or along the inner aponeuroses, which can significantly influence the gradients of the resulting Laplacian flow. Herein, we propose a novel method based on solving the 3D steady-state thermal heat equations to determine the fibre architecture in a bi-pennate muscle, specifically the m. rectus femoris. Additionally, we propose a semi-automated algorithm that provides the geometrical representation of the anterior aponeurosis, which, along with the thermal-based fibre field, is particularly well suited for Finite Element (FE) simulations. The semi-automated reconstruction of the aponeurosis shows a good correlation with manual segmentation, yielding a dice coefficient (DSC) of 0.83. The metamodel-based approach resulted in fluxes with a mean angular deviation of (14.25^circ ,pm ,10.36^circ) and a fibre inclination from the muscle’s longitudinal axis of (0.44^circ ,pm ,4.48^circ). Comparing the mechanical output of the same m. rectus femoris muscle geometry informed by the two respective fibre architectures showed that the most significant contributing factor was the relative fibre inclination. Compared to the standard deviation in the undeformed configuration ((0.44^circ ,pm ,4.48^circ)), the standard deviation of relative fibre inclination during passive stretching at low applied loads, for instance, at (30%) of the maximum applied load, showed a significant decrease ((0.49^circ ,pm ,2.24^circ)). Similarly, at maximum isometric contraction, the relative fibre inclinations at (10%) initial fibre pre-stretch are (0.19^circ ,pm ,1.23^circ), indicating a drop in standard deviation from the undeformed configuration ((0.44^circ ,pm ,4.48^circ)). The current study demonstrates that despite the initial deviations in fibre orientations and relative fibre inclinations, thermal flux-based fibre orientations not only exhibit comparable results to DTI-based fibre tractography for the macroscopic analysis of the m. rectus femoris but also result in homogeneous stretch fields and improved numerical convergence. The proposed methods may be applied to determine inner aponeuroses of other bi- or multi-pennate muscles, enabling efficient in-silico computations of the musculoskeletal system.

Arterial growth and remodeling (G&R), in response to biomechanical stimuli, plays a pivotal role in vascular health. Disruptions in G&R, often seen in conditions such as aneurysms and atherosclerosis, can lead to pathological changes and pose significant health risks. Assessing risk should not only consider the current state of the aneurysm but also how it develops over the subsequent months. Herein, we make a controlled, subject-specific assessment of maladaptive aortic tissue growth using data previously obtained for the Fbln4^SMKO mouse model. The computational model uses a locally applied continuum G&R approach coupled with fluid–structure interaction (FSI) simulations. Ten mice were studied, exhibiting varying degrees of aneurysm formation over time. This investigation focused on the ascending aorta, where aneurysms develop in the Fbln4^SMKO mouse. A continuous G&R model was tuned and evaluated using information from 2, 4, and 6 months obtained from CT scans. A G&R model with uniform growth laws showed variable accuracy in predicting circumferential growth across different mice, exhibiting both under- and over-estimations compared to in vivo measurements. Modeling prediction showed to be improved by multiple-domain modeling. There is correlation between (1) the fitted circumferential growth time constants and the observed ascending aorta Young’s modulus and (2) the fitted axial growth time constant and the tortuosity index. Furthermore, the ratio of the circumferential growth time constant to the circumferential stress correlated with mouse lifespan more strongly than diameter change, suggesting that analysis of a G&R model may be valuable in predicting risk of aneurysm rupture.

The plasma membrane is a liquid lipid bilayer containing both dissolved proteins and proteins anchoring the membrane to the underlying actin cortex. Membrane tension, a 2D analog of pressure in a 3D liquid, is believed to play a crucial role in organizing essential processes within cells and tissues. This, along with recent, conflicting data on the speed of membrane tension propagation, highlights the need for a comprehensive mechanical model to describe tension in the cortex-anchored plasma membrane as a function of transmembrane hydrostatic pressure difference and excess membrane area due to cortex contraction. In this study, we present a mechanical model of plasma membrane compartments, separated by "picket fences" of cortex-anchoring proteins permeable to lipids. Beyond hydrostatic pressure, the model incorporates the 2D osmotic pressure exerted by membrane-dissolved proteins. Our findings reveal that the tension-area relationship within a membrane compartment exhibits a seemingly paradoxical feature: in a specific range of membrane surface area, an increase in area leads to a rise in tension. We further model the tension-area relationship for an ensemble of membrane compartments, which exchange membrane area through shared borders, and discuss potential biological implications of this model.