Biomechanics and Modeling in Mechanobiology最新文献

This study presents a multi-scale computational framework to quantify how externally applied acoustic waves propagate through the knee joint and induce mechanotransductive strain at the level of the chondrocyte nucleus. Patient-specific knee geometries (n = 8) were used to simulate acoustic wave transmission through layered tissues, while a representative volume element modelled the coupled solid–shell–acoustic behaviour of the chondrocyte, pericellular matrix, and extracellular matrix. Modal and frequency–response analyses identified the spheroidal s₃ mode as the dominant contributor to nuclear deformation. Strain amplification was found to occur within defined frequency bands rather than at a single frequency, with healthy patients exhibiting a broader mid-frequency amplification region (50–170 kHz) and diseased patients showing a shifted low-frequency (30–85 kHz) dominance due to hypertrophy and altered stiffness. Macro-to-micro coupling demonstrated that, despite anatomical variability, consistent transmissibility trends were preserved across patients, with ideal frequencies for healthy and OA patients. Time-explicit simulations comparing linear and nonlinear acoustic formulations revealed negligible harmonic generation at the applied pressure levels, indicating that linear acoustics adequately describe propagation within the mechanotransductive strain range considered. Overall, the results demonstrate that cartilage stimulation is frequency-band dependent and disease-sensitive, and they provide a mechanistically grounded basis for optimizing ultrasound excitation parameters based on cellular-scale mechanics rather than empirical frequency selection.

Marfan syndrome, caused primarily by mutations in the fibrillin-1 (FBN1) gene, is associated with progressive dilation of the proximal aorta, with dissection and rupture representing the leading causes of early mortality. A characteristic feature of Marfan-associated aneurysm is fragmentation of elastic fibers; however, the extent to which elastin loss alone can account for the observed geometric and mechanical changes remains unclear. In this study, we use a multiscale computational growth and remodeling framework to determine which geometric and mechanical features of the Marfan aorta can be reproduced by prescribed elastin loss acting through mechanically regulated fiber remodeling and tissue growth. The model couples a discrete fiber network representation of collagen, elastin, and actomyosin with a continuum description of the tissue. It is first calibrated to reproduce experimental measurements in the healthy mouse aorta, and Marfan conditions are then introduced by prescribing graded reductions in elastin content (10–80%). The model reproduces key features of the Marfan aorta, including increased wall thickness and radius, reduced axial stress and stretch, and shifts in pressure-dependent stiffness. Quantitative comparison across multiple metrics shows strong agreement between simulations and experiments, with the lowest error occurring at 29% elastin loss. Within the scope of the model, prescribed elastin loss led to many key structural and mechanical features observed in Marfan aortas, demonstrating the predictive potential of the framework for exploring the mechanical consequences of elastin fragmentation.

The thin-walled nature of the atrial myocardium can lead to artificial stiffening when full 3D electromechanical models are discretized using standard finite elements. In this work, we propose an electromechanical model of the left atrium based on a 3D-shell formulation that overcomes these limitations. The model incorporates both passive and active components of atrial tissue mechanics, while atrioventricular interaction is described by the coupling with a 0D electromechanical model of the left ventricle. The proposed approach is assessed under physiological and pathological conditions and systematically compared with the standard full 3D formulation. The results demonstrate the superior robustness and computational efficiency of the proposed 3D-shell electromechanical model.

Pathological fractures due to metastatic bone disease frequently require palliative stabilization. While polymethylmethacrylate (PMMA) provides immediate mechanical stabilization, its limited bending and multiaxial properties raise concerns. Reinforcement strategies such as plate fixation, intramedullary nails, and metallic augmentation have been proposed, yet their mechanical behavior under physiological loading remains insufficiently characterized. This study aims to evaluate the mechanical performance of three reconstruction strategies for a proximal radial defect: PMMA alone, PMMA combined with titanium plate-and-screw construct, and PMMA reinforced with a steel K-wire. A patient-specific workflow integrated musculoskeletal multibody model and finite element analysis. Muscle forces and elbow joint reaction forces were calculated for a static 90° shoulder flexion under two loading conditions: no external load and 2 kg mass applied at the center of mass of the hand. These forces were applied in finite element analysis in reconstructed forearm, and peak von Mises stress and displacements were evaluated. In loading scenario, elbow joint reaction force reached 314.4 N, and maximum muscle force was 120.8 N. In the PMMA-only construct, peak stress increased from 4.0 MPa (no load) to 12.0 MPa (with load). Plate fixation increased peak stress to 14.9 MPa in the loading case. K-wire reinforcement resulted in lowest PMMA peak stress (23% less with respect to PMMA-only and 38% less compared to titanium plate) but produced more pronounced displacement (29%) compared to plate fixation strategy. These findings suggest complementary mechanical benefits: K-wire reinforcement most effectively reduced peak cement stress, whereas plate fixation provided superior global stiffness.

Lung injury risk from high-velocity blunt impacts is thought to depend on lung pressure. Risk is typically assessed with finite element models (FEMs), but models do not typically account for lung pressure, nor do they account for lung viscoelasticity. The objective of this study is to translate and then validate a set of lung material models that consider both tissue viscoelasticity and pressure in silico. This was completed using one set of quasi-static simulations for translation and one set of dynamic simulations for validation to compare to experimental forces, where CORA was utilized. Digital image correlation (DIC) data of strain and displacement magnitude from the quasi-static experiments were also used to ensure proper material model translation. Three simulations were run for each loading case, where the only difference was the lung material properties to account for pressure (0, 4, and 10 cmH₂O). The force–time responses for both simulations showed good agreement with experimental data with a range of 0.77–0.93 CORA scores for the dynamic loading, and a range of 0.84–0.97 CORA scores for the quasi-static simulations, with all simulations falling under “good” or “excellent” categories. The DIC-equivalent data for the quasi-static simulations were determined to be dependent on mesh size. Overall, the quasi-static simulations showed the material was translated into LS-Dyna well, and each of the lung material models were able to reproduce the global force–time responses well in the dynamic simulation set.

We created computational fluid dynamic models of murine lung vasculature to assess the quantity and quality of cell deposition for lung re-endothelialization under three cell seeding protocols. These protocols include the standard direct injection seeding, negative pressure seeding, and a novel dual boundary condition seeding protocol. Our results indicate that cell seeding efficiencies are similar between the direct injection and negative pressure seeding protocols. The dual boundary condition protocol, which utilizes the direct injection of cell media with the addition of a prescribed pressure boundary condition at the parenchyma, exhibited increased cell deposition efficiencies of up to 14% compared to the direct injection and negative pressure cases, as well as the ability to target cell deposition in specific (i.e., proximal and distal) regions of the lung vasculature. This novel dual boundary condition protocol has the potential to increase cell seeding efficiencies during scaffold recellularization, addressing a significant challenge in the field of lung bioengineering.

In a soft biological tissue with a fibrous network and interstitial fluid, osmotic pressure arises primarily from Donnan ion effects and macromolecular confinement, typically ranging from kPa to hundreds of kPa, and is mechanically balanced by stresses in the solid matrix. This study introduces a new data-driven framework based on the Virtual Fields Method (VFM) for identifying full-field material parameters and discovering constitutive models of osmotic pressure in biphasic hyperelasticity. In this framework, a two‐step VFM strategy is proposed: (1) the virtual fields with zero-trace strains are applied to eliminate the osmotic pressure contribution and identify the parameters of the solid component, and (2) when the law for osmotic pressure is known a priori, the material parameters of the fluid component are further identified. When the law for osmotic pressure is unknown a priori, the osmotic pressure is identified as an independent field variable and the constitutive law for osmotic pressure is established using a machine learning method. The effectiveness of the proposed model is verified through examples including identifications with experimentally measured data.

Although transcatheter aortic valve implantation (TAVI) has been demonstrated to be a successful treatment for aortic stenosis, it remains associated with complications, such as paravalvular leakage (PVL). To address these, TAVI devices continue to undergo iterative development. Integration of in silico trials into the regulatory validation pathway offers a promising approach to accelerate the development and clinical implementation of novel TAVI devices. This study addresses the feasibility of conducting large-scale in silico TAVI trials using a virtual cohort generator (VCG) combined with a fast-to-evaluate model. The objective is to investigate anatomical and procedural predictors of PVL in silico, as was done in an earlier clinical study. A virtual cohort of 500 synthetic aortic stenosis patients was generated, that matched anatomical and demographic characteristics of the clinical population. Using a novel fast-to-evaluate TAVI deployment model, nearly 29,000 simulations were performed across multiple model parameter combinations per patient. Shape and demographic distributions in the in silico trial, remained within the bounds of the clinical study. Among the investigated anatomical parameters, a higher angle between left ventricular outflow tract and ascending aorta was found in patients with significant PLV, in both clinical and virtual cohorts. Additionally, the relationship between PVL and implantation depth appeared highly patient-specific, which is in line with findings in clinical studies. The ability to systematically test multiple TAVI deployments scenarios per patient, which is unfeasible in clinical practice, provides valuable insights for procedure design and optimisation. Overall, the results support the feasibility of implementing large-scale in silico TAVI trials, using the VCG and a fast-to-evaluate model, into the regulatory validation chain.

Previously published 5-DOF and 21-DOF lumped-parameter models of the human lumbar spine predict displacement responses to posteroanterior (PA) forces, yet neither has been validated against in vivo frequency response function (FRF) data. This study compared model-predicted driving-point compliance spectra to in vivo experimental data and estimated patient-specific mechanical properties through inverse analysis. Triaxial bone-pin accelerometers were mounted to the L2 and L4 spinous processes of two patients undergoing lumbar decompression surgery. An Impulse iQ instrument delivered 178 controlled impulses at the L3 spinous process across six conditions. Driving-point compliance FRFs were computed using the H1 spectral estimator. Patient-specific PA stiffness and damping ratios were estimated via coherence-weighted logarithmic least-squares optimization. Both patients exhibited a dominant first compliance resonance near 49 Hz, consistent with the 5-DOF prediction of 46 Hz (<7% error). The second and third modes (89–101 Hz and 107–110 Hz) agreed with model predictions of 84 and 120 Hz. Optimized stiffness converged to (52.3 pm 3.5) kN/m (published: 50 kN/m), with damping ratios of 0.049-−0.109. Time-domain Newmark–beta simulations predicted peak L3 displacements of 1.10-−5.60 mm for a 3.2 ms impulse, consistent with cadaveric and in vivo spinal manipulation studies. These results provide the first in vivo validation of lumped-parameter spine models and demonstrate patient-specific mechanical property estimation from compliance FRF data.

We present a computational framework for patient-specific modeling of biventricular (BiV) mechanics based on standard clinical data, including electrocardiogram (ECG), cuff blood pressure, and ECG-gated computed tomography angiography (CTA) imaging. The model is coupled to a closed-loop lumped-parameter network (LPN) circulatory model and incorporates rule-based fiber architecture, as well as spatially varying epicardial boundary conditions to approximate surrounding tissue support. Model parameters are personalized through a multistep procedure that sequentially tunes circulatory dynamics, passive mechanics, and active contraction. The resulting personalized BiV model reproduces the clinical hemodynamic targets used during calibration and demonstrates reasonable agreement with image-based myocardial deformation metrics that were not directly included in the parameter-tuning process. We then use this model as a baseline to assess the impact of two commonly used anatomical simplifications: a truncated BiV (t-BiV) model cut at the basal plane and a left ventricle-only (LV) model. With all parameters held fixed, the LV model exhibits similar global pressure/volume behavior compared to the BiV model, despite moderate differences in regional deformation. In contrast, the t-BiV model produces substantial differences from the full BiV baseline in both global function and local myocardial mechanics. While drawn from a single-patient case study, these results demonstrate that anatomical simplifications can substantially affect model outputs, motivating further investigation across larger cohorts, disease states, and model complexity.