Biomechanics and Modeling in Mechanobiology最新文献

Accurate modeling of cardiovascular tissues is crucial for understanding and predicting their behavior in various physiological and pathological conditions. In this study, we specifically focus on the pulmonary artery in the context of the Ross procedure, using neural networks to discover the most suitable material model. The Ross procedure is a complex cardiac surgery where the patient's own pulmonary valve is used to replace the diseased aortic valve. Ensuring the successful long-term outcomes of this intervention requires a detailed understanding of the mechanical properties of pulmonary tissue. Constitutive artificial neural networks offer a novel approach to capture such complex stress-strain relationships. Here, we design and train different constitutive neural networks to characterize the hyperelastic, anisotropic behavior of the main pulmonary artery. Informed by experimental biaxial testing data under various axial-circumferential loading ratios, these networks autonomously discover the inherent material behavior, without the limitations of predefined mathematical models. We regularize the model discovery using cross-sample feature selection and explore its sensitivity to the collagen fiber distribution. Strikingly, we uniformly discover an isotropic exponential first-invariant term and an anisotropic quadratic fifth-invariant term. We show that constitutive models with both these terms can reliably predict arterial responses under diverse loading conditions. Our results provide crucial improvements in experimental data agreement, and enhance our understanding into the biomechanical properties of pulmonary tissue. The model outcomes can be used in a variety of computational frameworks of autograft adaptation, ultimately improving the surgical outcomes after the Ross procedure.

Laser ablation techniques employ fast hyperthermia mechanisms for diseased-tissue removal, characterized by high selectivity, thus preserving the surrounding healthy tissue. The associated modeling approaches are based on classical Fourier-type laws, though a limited predictivity is observed, particularly at fast time scales. Moreover, limited knowledge is available for cardiac tissue compared to radiofrequency approaches. The present work proposes a comprehensive modeling approach for the computational investigation of the key factors involved in laser-based techniques and assessing the outcomes of induced cellular thermal damage in the cardiac context. The study encompasses a comparative finite element study involving various thermal and cellular damage models incorporating optical-thermal couplings, three-state cellular death dynamics, and a second-order heat transfer formulation generalizing the classical Fourier-based heat equation. A parametric investigation of the thermal profiles shows that higher-order models accurately capture temperature dynamics and lesion formation compared with the classical Fourier-based model. The results highlight the critical role of cardiac anisotropy, influencing the shape and extent of thermal damage, while the three-state cell death model effectively describes the transition from reversible to irreversible damage. These findings demonstrate the reliability of higher-order thermal formulations, laying the basis for future investigations of arrhythmia management via in silico approaches.

The arterial wall is a structurally complex material, exhibiting both nonlinearity and anisotropy in its mechanics, with the compelling consequence that the end plate force in a pressure-stretch experiment can increase or decrease with pressure depending on the axial stretch of the vessel. Furthermore, it has long been observed that the axial stretch at which the ex vivo pressure-force curve is flat is close to the in vivo axial stretch, but the mechanism driving this phenomenon has remained unclear. By employing and modifying a custom plugin that represents tissue components as networks, we computationally tested the hypothesis that tensional homeostasis at the microscopic scale could lead to the macroscopic pressure-invariant axial force effect observed at in vivo axial stretch. Our findings suggest that remodeling events for individual fibers to achieve a target stress can, acting in aggregate, cause the vessel to exhibit a pressure-invariant axial force in the pressure-force experiment without any explicit sensing of the pressure-force behavior during remodeling. Computational isolation of tissue components suggested that remodeling of collagen fibers is a primary driver of this result. Further as long seen experimentally, the pressure-force curve plateau occurred at stretches close to the in vivo remodeling stretch.

Drug treatments against osteoporosis are commonly divided into anti-catabolic and anabolic. Anti-catabolic drugs reduce bone turnover and increase bone mass mainly through mineralization of the existing bone matrix. Anabolic drugs, on the other hand, enhance osteoblastic activity, resulting in new bone formation. Treatments are often limited to a few years due to reported side effects, which increases fracture risk upon discontinuation. Switching to a different drug is a common strategy. However, it is not clear what is the best combination of a dual-drug therapy, the lapse between treatments and other parameters defining the combination. In this study, we conducted in silico trials to assess the efficacy of two drugs: denosumab (anti-catabolic) and romosozumab (anabolic and anti-catabolic). Our simulations indicate that starting treatment with romosozumab leads to greater bone mass gain. This is because anti-catabolic treatments reduce bone rate and, due to osteoblast-osteoclast coupling, the number of osteoblast precursors. Romosozumab increases the proliferation of these precursors, so their population should be maximised for optimal efficacy. Therefore, prior administration of an anti-catabolic drug may be counterproductive to the effectiveness of romosozumab. We also found that a rest period between treatments does not benefit bone mass gain. Furthermore, concurrent administration of romosozumab and denosumab results in greater bone mass gain and might be worth investigating in future clinical trials. Finally, we showed that reduction of fracture risk in patients undergoing sequential treatments is dose dependent and consequently, dosage could be optimised in a patient-specific manner.

Mild traumatic brain injury (mTBI) represents a significant public health challenge in modern society. An in-depth analysis of the injury mechanisms, pathological forms, and assessment criteria of mTBI has underscored the pivotal role of craniocerebral models in comprehending and addressing mTBI. Research indicates that although existing finite element craniocerebral models have made strides in simulating the macroscopic biomechanical responses of the brain, they still fall short in accurately depicting the complexity of mTBI. Consequently, this paper emphasizes the necessity of integrating biomechanics, neuropathology, and neuroimaging to develop multiscale and multiphysics craniocerebral models, which are crucial for precisely capturing microscopic injuries, establishing pathological mechanical indicators, and simulating secondary and long-term brain functional impairments. The comprehensive analysis and in-depth discussion presented in this paper offer new perspectives and approaches for understanding, diagnosing, and preventing mTBI, potentially contributing to alleviating the global burden of mTBI.

This study aimed to investigate the relationship between regional elastic modulus and corresponding hemodynamic indices of healthy aortic arch. Porcine aortic arches (n=18) were obtained from a local abattoir and divided into 24 regions along axial and circumferential directions. Regional elastic modulus was measured by indentation tests, and elastic fiber content was assessed using Elastica van Gieson (EVG) staining. Additionally, a porcine aortic model was reconstructed based on computed tomography angiography (CTA) images, and local hemodynamic indices were calculated by the two-way fluid-structure interaction (FSI) method. The elastic modulus and elastic fiber content were inclined to be lower on the outer curvature of the aortic arch, particularly showing significant differences at the distal end. A negative correlation was found between elastic modulus and time-averaged wall shear stress (TAWSS) $(r_s=-0.762,p=0.028$ ) at the proximal end of the porcine aortic arch. There was a significant positive correlation between elastic modulus and oscillatory shear index (OSI) $(r_s=0.714,p=0.047)$ at the middle of the aortic arch. The regional elastic modulus of healthy porcine aortic arch is associated with local TAWSS and OSI. The hemodynamic environment could be a contributing factor influencing the distribution of the mechanical properties on the arch.

Recently, the present authors proposed a three-dimensional computational model for the transit of suspended cancer cells through a microchannel (Wang et al. in Biomech Model Mechanobiol 22: 1129-1143, 2023). The cell model takes into account the three major subcellular components: A viscoelastic membrane that represents the lipid bilayer supported by the underlying cell cortex, a viscous cytoplasm, and a nucleus modelled as a smaller microcapsule. The cell deformation and its interaction with the surrounding fluid were solved by an immersed boundary-lattice Boltzmann method. The computational model accurately recovered the transient flow-induced deformation of the human leukaemia HL-60 cells in a constricted channel. However, as a general modelling framework, its applicability to other cell types in different flow geometries remains unknown, due to the lack of quantitative experimental data. In this study, we conduct experiments of the transit of human prostate cancer (PC-3) and leukaemia (K-562) cells, which represent solid and liquid tumour cell lines, respectively, through two distinct microchannel geometries, each dominated by shear and extension flow. We find that the two cell lines have qualitatively similar flow-induced dynamics. Comparisons between experiments and numerical simulations suggest that our model can accurately predict the transient cell deformation in both geometries, and that it can serve as a general modelling framework for the dynamics of suspended cancer cells in microchannels.

Percutaneous coronary interventions in highly calcified atherosclerotic lesions are challenging due to the high mechanical stiffness that significantly restricts stent expansion. Intravascular lithotripsy (IVL) is a novel vessel preparation technique with the potential to improve interventional outcomes by inducing microscopic and macroscopic cracks to enhance stent expansion. However, the exact mechanism of action for IVL is poorly understood, and it remains unclear whether the improvement in-stent expansion is caused by either the macro-cracks allowing the vessel to open or the micro-cracks altering the bulk material properties. In silico models offer a robust means to examine (a) diverse lesion morphologies, (b) a range of lesion modifications to address these deficiencies, and (c) the correlation between calcium morphology alteration and improved stenting outcomes. These models also help identify which lesions would benefit the most from IVL. In this study, we develop an in silico model of stent expansion to study the effect of macro-crack morphology on interventional outcomes in clinically inspired geometries. Larger IVL-induced defects promote more post-stent lumen gain. IVL seems to induce better stenting outcomes for large calcified lesions. IVL defects that split calcified plaque in two parts are the most beneficial for stenting angioplasty, regardless of the calcified plaque size. Location of the IVL defect does not seem to matter with respect to lumen gain. These findings underscore the potential of IVL to enhance lesion compliance and improve clinical outcomes in PCI. The macroscopic defects induced by IVL seem to have a substantial impact on post-stent outcomes.

This research demonstrates a systematic curve fitting approach for acquiring parametric values of hyperelastic constitutive models for both healthy and enzymatically mediated degenerated cartilage to facilitate finite element modeling of cartilage. Several widely used phenomenological hyperelastic constitutive models were tested to adequately capture the changes in cartilage mechanics that vary with the differential/unequal abundance of matrix metalloproteinases (MMPs). Trauma and physiological conditions result in an increased production of collagenases (MMP-1) and gelatinases (MMP-9), which impacts the load-bearing ability of cartilage by significantly deteriorating its extracellular matrix (ECM). The material parameters in the constitutive equation of each hyperelastic model are significant for developing a comprehensive computational interpretation of MMP mediated degenerated cartilage. Stress-strain responses obtained from indentation test were fitted with selected Ogden, polynomial, reduced polynomial, and van der Waals hyperelastic constitutive models by optimizing their adjustable parameters (material constants). The goodness of fit of the 2^nd order reduced polynomial and van der Waals model exhibited the closest data fitting with the experimental stress-strain distributions of healthy and degraded articular cartilage. The coefficient of the shear modulus for the 2^nd order reduced polynomial decreased gradually by 21.9% to 80.1% with more enzymatic degradation of collagen fibril due to the relative abundance of MMP-1 (collagenases), and 28.5% to 69.2% for the van der Waals model. Our findings showed that the major materials coefficients of the models were reduced in the degenerated cartilages, and the reduction varied differentially with the relative abundance of MMPs-1 and 9, correlating the severity of degeneration. This work advances the understanding of cartilage mechanics and offers insights into the impact of biochemical (enzymatic) effects on cartilage degradation.