Biomechanics and Modeling in Mechanobiology最新文献

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.

Bone was shown to adapt to mechanical loading through the concept of a mechanostat that regulates cell activity to maintain a specific strain signal within the tissue. Current computer models simulate bone resorption and formation in the presence of key biological agents, reproduce a realistic architecture of trabecular bone along principal stresses and estimate changes in bone strength related to immobilisation, overloading, metabolic diseases or drug therapies. However, clinical diagnostics of bone diseases in vivo rely primarily on X-ray-based densitometry and computer tomography that do not have the resolution to describe bone microarchitecture in full detail and evaluation of personalised bone strength is therefore based on a homogenised description of bone mechanical properties using density and fabric. Continuum-level bone adaptation theories rely primarily on bone density and do not involve local optimisation principles to predict fabric. The inverse problems of predicting applied loads from bone morphology typically exploit density but not fabric. Accordingly, this work formulates and provides analytical solutions for optimal bone adaptation at the homogeneous, anisotropic RVE level using bone density- and fabric-mechanical property relationships for three different mechanostat criteria. Two of these criteria elicit different adaptive responses for tensile and compressive strains. Forward solutions for density and fabric are provided at a continuum point for a given local stress, while inverse solutions for local stress are derived for given density and fabric for all three criteria. The 3D solutions are specialised to 2D and 1D for comprehension and compared among the different criteria. In the future work, the obtained solutions will enable simple forward simulation of personalised bone adaptation and inverse estimation of bone loading for clinical diagnostic tools such as high-resolution peripheral quantitative computed tomography (HR-pQCT) or photon counting computed tomography (PCCT).

Accurately identifying coronary vulnerable plaque that would cause major adverse clinical events based on morphological characteristics remains a major clinical challenge. Plaque biomechanics are closely associated with plaque rupture and could assist in rupture risk stratification to identify high-risk coronary plaques for potential intervention. In vivo optical coherence tomography images of 40 coronary plaques from 40 patients with coronary artery disease were acquired and categorized into three groups according to their morphological characteristics: stable, vulnerable, and ruptured plaques. Finite element analysis was performed to obtain the peak stress value over the fibrous cap and shoulder region denoted as critical plaque wall stress (CPWS). A rupture risk stratification scheme was proposed based on the CPWS value to classify three plaque groups from biomechanical perspective, and its agreement rate with morphological classification was calculated. Ruptured and vulnerable plaques exhibited significant higher CPWS values than stable ones while no significant difference was found between ruptured and vulnerable plaques. The biomechanical risk stratification scheme was formed using 150 kPa and 230 kPa as threshold values for CPWS to classify three types of plaques, and its agreement rates with morphological classification were 17/20, 5/10, and 7/10 for stable, vulnerable, and ruptured plaques, respectively. This biomechanical scheme holds the potential to accurately stratify the rupture risk of coronary plaques as demonstrated by reasonable concordance with morphological classification. Discrepancy between two classifications highlights the unique value of biomechanical scheme, when integrated with morphological classification, in preventing unnecessary interventions and detecting rupture-prone plaques.

This study applies a high-performance, fully coupled 3D–0D electromechanical model to simulate cardiac function across multiple scenarios of heart failure with reduced ejection fraction (HFrEF), including ventricular tachycardia post-myocardial infarction and acute hypertension. By integrating biomechanical deformation, electromechanical coupling, and hemodynamic feedback, the model provides a comprehensive analysis of different stages of heart failure. A physiologically detailed 3D-0D electromechanical model was used to simulate pressure-volume loops under different pathological conditions. The model incorporates hemodynamic coupling within an electromechanical framework to quantify left ventricular performance markers in virtual scenarios. Additionally, myocardial strains along the principal fiber direction were computed to assess systolic dysfunction and deformation. The simulations accurately predicted the hemodynamic impact of HFrEF according to their electrophysiological and mechanical properties. The computationally derived pressure-volume loops demonstrated a strong agreement with clinical findings, highlighting key features of HFrEF such as reduced stroke volume, impaired contractility, and decreased ejection fraction. Furthermore, scar-related conduction abnormalities were associated with an increased risk of ventricular tachycardia, with failing hearts exhibiting greater hemodynamic instability during arrhythmic episodes. The proposed computational framework provides a powerful tool for investigating HFrEF progression and electromechanical dysfunction. By accurately replicating pressure-volume loop characteristics and hemodynamic alterations commonly seen in clinical settings, this model enhances the understanding of HFrEF and may support the development of targeted therapeutic strategies.

Collagen fibers are essential to the mechanical behavior of soft tissues, including sclera. Conventional models often represent these fibers statistically, potentially missing crucial aspects of their role in tissue behavior. In this study, we expand on a direct fiber modeling approach that we recently presented based on explicitly representing the sclera long, interwoven fiber bundles. Specifically, our goal was to capture specimen-specific 3D fiber architecture and anisotropic mechanics of four ovine sclera samples (superior from Eye-1, temporal and superior from Eye-2, and temporal from Eye-3), each tested under five conditions: equi-biaxial (1:1) and four non-equi-biaxial (1:0.75, 0.75:1, 1:0.5, and 0.5:1). Fiber architecture was extracted using polarized light microscopy and reconstructed model fiber orientations agreed well with the histological information (adjusted R² > 0.89). Material parameters were determined via inverse fitting to the equi-biaxial tests. Remarkably, the parameters obtained from equi-biaxial fitting also accurately predicted the mechanical response of the same sample under all four non-equi-biaxial conditions. This indicates that the models inherently captured tissue anisotropy through its fiber structure, unlike conventional continuum models which require simultaneous multi-condition fitting. Our findings support direct fiber modeling as a promising tool approach for linking tissue fibrous structure and macroscopic mechanical behavior.

The classical Hodgkin–Huxley model describes the propagation of an action potential (AP) in unmyelinated axons. In many cases, the axons have a myelin sheath and the experimental studies have then revealed significant changes in the velocity of APs. In this paper, a theoretical model is proposed describing the AP propagation in myelinated axons. As far as the velocity of an AP is affected, the basis of the model is taken after Lieberstein, who included the possible effect of inductance that might influence velocity, into the governing equation. The proposed model includes the structural properties of the myelin sheath: the (mu)-ratio (the ratio of the length of the myelin sheath and the node of Ranvier) and g-ratio (the ratio of the inner-to-outer diameter of a myelinated axon) through parameter (gamma). The Lieberstein model can describe all the essential effects characteristic to the formation and propagation of an AP in an unmyelinated axon. Then a phenomenological model (a wave-type equation) for a myelinated axon is described including the influence of the structural properties of the myelin sheath and the radius of an axon. The numerical simulation using the physical variables demonstrates the changes in the velocity of an AP. These results match well the known effects from experimental studies.

The subject of this work is the problem of optimizing the configuration of cuts for skin grafting in order to improve the efficiency of the procedure. We consider the optimization problem in the framework of a linear elasticity model. We choose three mechanical measures that define optimality via related objective functionals: the compliance, the (L^p)-norm of the von Mises stress, and the area covered by the stretched skin. We provide a proof of the existence of the solution for each problem, but we cannot claim uniqueness. We compute the gradient of the objectives with respect to the cut configuration using concepts from shape calculus. To solve the problem numerically, we apply the gradient descent method, which performs well under uniaxial stretching. However, in more complex cases, such as multidirectional stretching, its effectiveness is limited due to the low sensitivity of the functionals under consideration.To avoid this difficulty, we use a combination of the genetic algorithm and the gradient descent method, which leads to a significant improvement in the results.