Biomechanics and Modeling in Mechanobiology最新文献

Active arterial mechanics, governed by vascular smooth muscle contraction, are critical to physiological regulation, cardiovascular disease progression, and clinical diagnosis. Although various in vivo methods have been developed to assess arterial stiffness, most cannot distinguish the contribution of smooth muscle tone; therefore, quantitative characterization of arterial activity remains challenging. In this study, we developed a pressure–area analysis framework integrating ultrasound imaging, blood pressure measurement, neural network-based segmentation of arterial cross-sectional area, and biomechanical model-driven inversion to infer active mechanical properties. A total of 233 volunteers (aged 18–65  year) were recruited to acquire cross-sectional ultrasound videos of the right common carotid artery for training the neural network. The segmentation results demonstrate good spatial and temporal performance of the neural network. We further recruited 10 additional volunteers (aged 25 ± 3  year) to perform a 1 min step test, followed by pressure–area measurements over a 30 min recovery period. Using the proposed approach, we quantified post-exercise changes in carotid arterial active mechanics relative to baseline (i.e., the resting state). Results showed that active mechanics remained elevated for approximately 15 min compared to baseline (p < 0.05), whereas systolic pressure differed significantly only within the first approximately 5 min post-exercise (p < 0.001). These results indicate a dissociation between blood pressure and smooth muscle recovery, which may offer new insight into vascular smooth muscle regulation during physiological stress.

Due to the limited availability of human body donor brains, biomechanical testing for material parameter identification is often done on animal tissue. So far, only one study has compared human and animal brain tissue under indentation, which provides data for the small strain regime and hence is not applicable to large-strain scenarios like surgery. Here, we compare the large-strain behavior of human and porcine brain tissue from four anatomical regions (corona radiata, putamen, cerebellar white matter, and brain stem) under compression, tension, and shear. Our results from cyclic loading tests show that samples from the cerebral white matter behave similarly for both species under all loading modes, whereas samples from the cerebellar white matter are similar only under compression-tension, but not shear loading. For regions with mixed gray and white matter, we observe a softer behavior for porcine samples under all loading modes. The stress relaxation behavior is similar in both species, except for samples from the putamen. These findings indicate that porcine brain tissue can be used as an alternative for human tissue to study general tissue mechanics. However, since the porcine brain is much smaller and therefore, less brain regions can be characterized mechanically, human brain data are still needed to calibrate full brain simulation models.

Type II endoleak (T2EL), the most common complication after endovascular aortic aneurysm repair (EVAR), remains a leading cause of reintervention due to persistent retrograde flow from patent inferior mesenteric artery (IMA) and lumbar arteries (LAs). The influence of specific anatomical features of these vessels on the hemodynamic environment remains poorly understood. This study evaluated two key anatomical characteristics: branch vessel count and luminal diameter. Eight post-EVAR models were constructed. Computational fluid dynamics (CFD) simulations were performed to quantify key hemodynamic parameters, including flow velocity, pressure, wall shear stress (WSS), oscillatory shear index (OSI), and relative residence time (RRT). IMA patency and an increased LA number synergistically primarily altered flow field patterns and shear stress distribution, while larger vessel diameters significantly affected flow rate, WSS directionality, and RRT. Enlarged IMA diameter combined with multiple patent LAs expanded retrograde flow regions and created high-shear-stress environments that inhibited thrombus formation, which may promote T2EL persistence and sac expansion. A risk-stratified embolization strategy was proposed: high-risk patients (IMA ≥ 2.5 mm with ≥ 2 patent LAs) should undergo embolization of IMA and LAs ≥ 2 mm; intermediate-risk (IMA 2.0–2.5 mm or ≤ 1 LA) receive IMA embolization; low-risk patients (IMA < 2.0 mm with ≤ 1 LA) require standard clinical follow-up. This study confirms that an increased number of LAs primarily alters flow field patterns and shear stress distribution within the aneurysm sac, while enlargement of branch vessel diameters elevates perfusion flow rate and pressure. These findings provide a hemodynamic basis for assessing T2EL risk.

When a Transcatheter heart valve (THV) is implanted in a bicuspid aortic valve (BAV), the interventional valve may experience elliptical deformation, thereby reducing its durability. In this study, a novel Asymmetric Artificial Interventional Valve (AAIV) was designed. The deployment of the AAIV in the BAV was simulated and compared to that of a THV. The synergistic effects of the AAIV (0.1, 0.2, and 0.3) eccentricity and annulus eccentricity (0.1, 0.2, and 0.3) on the deployment of the interventional valve were studied. Besides, the influence of native leaflet calcification on the deployment of the AAIV was also studied. The results demonstrated the maximum stress of the AAIV (0.590 MPa) is 8.2% lower than that of the THV (0.643 MPa). When the AAIV eccentricity is equal to the annulus eccentricity, the stress of the prosthetic valve is the highest, representing the most unfavorable condition for the long-term durability of the prosthetic valve. Calcification of the native leaflet can increase the stress of the prosthetic valve. In addition, with the increase of annulus eccentricity, the stress of the prosthetic valve tends to increase. This study might provide insights for the design of personalized high-performance interventional valves and their rational selection in clinical practice.

Pressure ulcers remain a persistent and serious complication in clinical care, often originating in deep soft tissues before becoming visible on the skin surface and leading to suffering, prolonged hospital stays, and increased healthcare costs. Individual variability in soft tissue composition and mechanical properties plays a critical role in modulating internal stress and strain distributions during prolonged loading. In this study, we used anatomically representative finite element models to investigate inter-individual differences in tissue vulnerability under localized pressure. Two multilayered models, incorporating variations in epidermal, dermal, adipose, and muscular thickness, density, and stiffness, were subjected to clinically relevant pressure magnitudes (2–10 kPa), simulating conditions associated with immobility and device-related compression. Mechanobiological metrics, including effective stress, effective strain, and percentile-based exposure thresholds, were computed to quantify internal tissue load transmission and damage risk. Model outputs revealed that high stress localized in superficial layers, while strain peaked in deeper tissues, especially adipose and muscle. Simulated reductions in tissue stiffness, reflecting age- or disease-related softening, further exacerbated internal loading, increasing stress-exposed tissue volume by up to 1.5 times and strain-exposed volume by up to 1.2 times. These results highlight the biomechanical consequences of anatomical and material variability and support the development of personalized risk assessment tools. The proposed modeling approach contributes to mechanobiology-informed strategies for pressure ulcer prevention in high-risk populations.

The rising prevalence of central nervous system (CNS) diseases has imposed substantial social and economic burdens on healthcare systems. The blood–brain barrier (BBB), a highly selective physiological barrier in the CNS, severely restricts the delivery of most therapeutic agents to the brain, thereby limiting treatment efficacy. Stable cavitation of microbubbles induced by focused ultrasound (FUS) offers a promising strategy for transiently and non-invasively opening the BBB, holding significant clinical potential. However, the underlying biophysical mechanisms remain challenging for understanding, particularly the disruption of tight junctions (TJs) during stable cavitation and the mechanical responses of the BBB under long-term loading. In this study, a three-dimensional (3D) finite element simulation is conducted to model the mechanical behavior of endothelial cells and TJs using the Yeoh hyperelastic model and a modified standard linear solid (MSLS) model, respectively. This framework enables simulation of coupled interactions among oscillating bubbles, surrounding fluid, and the BBB. Numerical results reveal that stable cavitation induces pronounced periodic deformation of the BBB, with localized stress concentrations prominently occurring in TJ regions during bubble expansion. The occurrence of the flow recirculation is correlated to the stress imposing on the BBB. Compared to a linear elastic model, the present nonlinear material formulation demonstrates enhanced deformation and effectively suppressed peak shear stresses of the BBB. We find the fluid stress exerted on the BBB obtained is not large enough to lead to rupture of the TJs. Furthermore, our results indicate a typical fatigue-like feature in TJs under cyclic loading, wherein the von Mises stress is characterized by an initial softening followed by hardening. This suggests that fatigue-like behavior under long-term loading might be the dominant mechanism for the failure of TJs under stable cavitation. These findings contribute to the understanding of the biomechanical mechanisms underlying FUS-microbubble-mediated BBB opening (FUS-BBB) and provide a theoretical foundation for its application in CNS drug delivery and brain disease treatment.

We propose a new healing metric for improved tracking of the wound healing process across arbitrary wound geometries. A Fickian diffusion equation with a logistic nonlinear term is solved using the open-source finite element framework FEniCSx. The model is verified and calibrated by comparing finite element simulation results with experimental data from the literature, focused on the circular rabbit ear wound. To address the limitations of fixed-threshold metrics, we introduce a spatial healing metric, (beta), which captures the average cell density across the wound domain. This metric reflects healing differences arising from geometry and variations in diffusion and mitotic parameters. Parametric sweeps over the diffusion coefficient–mitotic generation (D–s) space reveal that different parameter combinations can yield the same healing time but with quite different spatial profiles. We also study multiple wound geometries to validate the applicability of the proposed metric. Our results demonstrate that the proposed (beta) metric exposes limitations of the classical threshold-based approach, particularly under conditions of high diffusion and low mitotic generation, where traditional metrics suggest full healing despite spatial discrepancies in cell density.

End-to-side anastomoses are commonly utilised in peripheral arterial bypass surgery and are plagued by high rates of re-stenosis which are contributed to by non-physiological blood flow impacting the arterial and graft structures. Computational simulations can examine how patient-specific surgical decisions in bypass graft placement and material selection affect blood flow and future risk of graft restenosis. Despite graft geometry and compliance being key predictors of restenosis, current simulations of femoro-popliteal artery grafts do not consider the interaction of flowing blood with compliant vessel, graft, and suture structures. Utilising fluid–structure interaction simulations, this study examines the impact of surgical technique, such as anastomosis angle, graft material, and suture material, on blood flow and fluid–structure forces in patient-specific asymptomatic arterial tree versus side-to-end peripheral grafts for symptomatic atherosclerotic disease. To render these complex simulations numerically feasible, our pipeline uses regional suture mechanics and a pre-stress pipeline previously validated in small-scale idealised models. Our simulations found that higher anastomosis angles generate larger regions of slow and recirculating blood, characterised by non-physiologically low shear stress and high oscillatory shear index. The use of compliant graft materials reduces regions of non-physiologically high shear stress only when used in combination with compliant suture materials. Altogether, our fluid–structure interaction simulation provides patient-specific platforms for vascular surgery decisions concerning graft geometry and material.

For biological cells, their viscoelastic properties play critical roles in both physiological and pathological processes, and indentation has emerged as a key technique to extract mechanical properties. If purely elastic behavior is assumed, the achieved elastic moduli become depth-dependent and highly scattered, underscoring the need to account for cellular viscoelasticity. However, the complexity of existing methods poses significant challenges for the practical extraction of viscoelastic parameters from standard indentations. In this work, we formulate explicit expressions describing spherical and conical indentation responses for viscoelastic cells elucidated by power-law rheology (PLR) model. Combining Lee and Radok’s approach and traditional Hertzian and Sneddon’s contact models, the relations between apparent modulus and loading time are obtained analytically, which are independent of loading velocity. Notably, the linear dependence of the normalized apparent modulus on loading time on a logarithmic scale can be utilized as a signature of the PLR behavior of cells, and its explicit expression can be directly adopted to accurately extract the viscoelastic parameters of cells. Applications of this approach to standard indentations enable robust extraction of viscoelastic parameters, with high consistency demonstrated across both virtual numerical experiments and actual experiments. This work presents a straightforward and reliable approach to accurately determine the viscoelastic properties of biological cells from standard indentations, without the need for complex fitting procedures or velocity-dependent corrections.

Coagulation is essential for haemostasis but can lead to harmful thrombus formation in conditions such as atrial fibrillation. Computational fluid dynamics (CFD) models that incorporate coagulation with blood flow can simulate this process, but their complexity often limits their use in clinical settings. This study focuses on fibrin formation during the peak thrombin phase, a brief but critical period in the thrombogram, and employs Gaussian Process Emulators to improve computational efficiency. A simplified coagulation model is integrated into a CFD framework and validated using data from an ex vivo experiment. Model inputs are varied within physiological ranges to train an emulator that predicts fibrin concentration and haemodynamic changes associated with thrombus development. A global sensitivity analysis (GSA) is performed to identify the relative influence of each input parameter. The model is then applied to a two-dimensional idealised representation of the left atrium (LA) to evaluate its suitability for cardiac simulations and to compare thrombus formation dynamics between small vessel and atrial flow. The model accurately captures fibrin formation in microchannels and the GSA and reveals potential mechanisms underlying thrombus growth in vessels while the LA simulation simulated various stages of thrombogenesis in the LA. The use of emulators enables efficient and precise predictions, enhancing the clinical feasibility of thrombosis modelling. These findings provide a foundation for the development of predictive tools to assess thrombus formation and stroke risk in patients.