Biomechanics and Modeling in Mechanobiology最新文献

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.

False lumen expansion is a major factor that determines long-term survival of uncomplicated type B aortic dissection (TBAD). The objective of this study was to investigate whether structural wall stress distributions computed from patient-specific acute TBAD geometries can be used to predict aortic growth rates. Three-dimensional (3D) computed tomography angiography (CTA) of 9 patients with acute uncomplicated TBAD was obtained at initial hospital admission and at their most recent follow-up visits. Patient-specific structural wall stress distributions were computed from the initial baseline CTA using a forward penalty method. Spatially varying blood pressure distributions, derived from computational fluid dynamics (CFD) simulations informed by patient-specific brachial blood pressure (BP) measurements, were incorporated into the forward penalty stress analysis. For 5 patients, transthoracic echocardiography (TTE) data were also available and used to prescribe patient-specific inlet flow conditions in the CFD simulations. Aortic growth rates were quantified and visualized within the 3D TBAD geometries using the initial baseline and follow-up scans. Linear mixed-effects regression analyses were performed to evaluate the spatial correlations between biomechanical markers (structural wall stress, wall shear stress, and pressure) and aortic growth rates. Utilizing initial baseline patient-specific CTA and BP data, along with TTE data when available, the forward penalty analyses revealed hemodynamic and structural mechanics insights of acute uncomplicated TBADs. The linear mixed-effects model indicated that the fixed-effect association between acute structural wall stress and estimated aortic growth rate distributions was statistically significant (p = 0.036), which demonstrated that aortic segments experiencing higher structural stress in the acute phase exhibited more rapid growth. Fixed-effect associations were not significant when predicting growth rate using wall shear stress (p = 0.88) or pressure (p = 0.65) distributions computed from the acute TBAD geometry. Significant Pearson correlation coefficients (p < 0.05) were observed between acute structural wall stress and aortic growth rate in all patients. Higher structural wall stress in the acute TBAD geometry was associated with regions of increased aortic growth rates. When modeled as a solid, false lumen thrombus was linked to lower structural wall stress and may have a protective effect against rapid aortic growth. Further studies are needed to investigate the biphasic nature of thrombus. Structural stress, which in this study was derived using the forward penalty approach, may be a novel predictor of aortic growth rate in acute TBAD.

The simulation of tissue perfusion based on highly detailed synthetic vasculature that often consists of multiple supplying and draining trees with millions of vascular segments is computationally expensive. Converting highly detailed synthetic vasculature into a homogenized continuum flow representation offers a computationally efficient alternative. In this paper, we investigate such a modeling approach that retains the essential features of potentially deforming hierarchical vascular networks. It is based on multi-compartment homogenization, where each compartment represents homogenized perfusion via a Darcy-type flow model associated with vascular segments at a specific spatial resolution in one individual tree of the network. The compartments are coupled through a pressure-dependent mass exchange, applied in a smeared manner everywhere within the perfusion domain. Key parameters, namely the permeability tensors of each compartment and the intercompartmental perfusion coefficients, are estimated directly from the vascular segments of the synthetic vasculature using averaging techniques. Our approach leverages spectral decomposition and a reduced set of representative vessel segments to balance computational efficiency with physical fidelity. For scenarios involving deformation, such as in a pumping heart or a regenerating liver, we introduce a computationally efficient parameter update based on geometric mapping, avoiding full re-homogenization in nonlinear simulations. We demonstrate the effectiveness and accuracy of the approach for several benchmark examples, including a full-scale multi-compartment liver perfusion simulation that explicitly incorporates three non-intersecting vascular trees, reflecting the hepatic artery, portal vein, and hepatic vein.

This study is focused on a critical blind spot in the soft tissue biomechanics field—spatial mechanical heterogeneity. Despite abundant experimental evidence indicating that soft biological tissues exhibit regional heterogeneity, particularly in their mechanical properties, incorporation of this heterogeneity into material descriptions of finite-element models has been limited. In this work, gradual spatial variation of mechanical properties is modeled by adopting principles of the theory of functionally graded materials. Using regional biaxial data and the Holzapfel-Gasser-Ogden constitutive model, this paper demonstrates a method to average the mechanical response from tested regions to estimate the response of untested intermediate tissue regions and the use of Fourier functions to capture continuous spatial variations of material parameters. This spatial material parameter dependency was then implemented in a finite-element model’s material description using the USDFLD subroutine in Abaqus (2022). This model is referred to as the continuous heterogeneous model and was compared with two other approaches that are used to account for spatial mechanical heterogeneity in soft biological tissues: 1) the homogeneous model that utilizes the averaged mechanical response from all tested specimens, and 2) the segmental heterogeneous model that employs distinct material descriptions for geometrically divided segments of the tissue model. All three approaches to modeling were demonstrated using two biomechanically relevant idealized geometries and boundary conditions: the human ascending aortic aneurysm simulated by a thin-walled cylinder and the back skin simulated by a planar strip. Results demonstrate that implementing spatial heterogeneity markedly affects the stress/displacement fields compared to the homogeneous model. Moreover, between the segmental and continuous heterogeneous approaches, the latter offers advantages such as mitigating stress discontinuities due to abrupt property changes. These findings highlight the impact of accounting for spatial mechanical heterogeneity in finite-element modeling of soft biological tissues and provide a foundation for future research exploring the improved material description in computational models and simulations of soft tissue biomechanics.

Pulmonary arterial hypertension (PAH) induces chronic pressure overload on the right ventricle (RV), leading to progressive remodeling and eventual failure. While PAH is more prevalent in women overall, men and postmenopausal women have worse clinical outcomes. Here, we investigated how sex and ovarian hormones influence RV remodeling during the progression of PAH. Using the sugen–hypoxia (SuHx) rat model, we assessed RV hemodynamics, tissue mechanics, and collagen composition in male, ovary-intact female, and ovariectomized (OVX) female rats across four disease stages. While all three groups experienced elevated pulmonary and ventricular pressures and rapidly responded with hypertrophy and stiffening, RV remodeling progressed differently in the absence of ovarian hormones. Male and OVX rats exhibited marked increases in end-diastolic pressure and myocardial stiffness, as well as higher chamber elastances. Ovary-intact female rats largely preserved diastolic function with milder stiffening. Collagen accumulation was observed in all groups, but only male and OVX rats exhibited significant elevations in pyridinoline cross-linking—aligning with the most severe additional mechanical changes, namely increased passive stiffness. This suggests that ovarian hormones moderate the severity of SuHx-induced RV remodeling by limiting myocardial stiffening and collagen cross-linking. These findings emphasize the need to consider sex and hormonal status in preclinical PAH research and suggest that extracellular matrix cross-linking may be a targetable contributor to maladaptive right heart remodeling.