Investigation of Pathophysiological Aspects of Aortic Growth, Remodeling, and Failure Using a Discrete-Fiber Microstructural Model

Atherosclerotic Calcifications Have a Local Effect on the Peel Behavior of Human Aortic Media

Aortic dissections, characterized by the propagation of a tear through the layers of the vessel wall, are critical, life-threatening events. Aortic calcifications are a common comorbidity in both acute and chronic dissections, yet their impact on dissection mechanics remains unclear. Using micro-computed tomography (CT) imaging, peel testing, and finite element modeling, this study examines the interplay between atherosclerotic calcifications and dissection mechanics. Samples cut from cadaveric human thoracic aortas were micro-CT imaged and subsequently peel-tested to map peel tension curves to the location of aortic calcifications. Empirical mode decomposition separated peel tension curves into high and low-frequency components, with high-frequency effects corresponding to interlamellar bonding mechanics and low-frequency effects to peel tension fluctuations. Finally, we used an idealized finite element model to examine how stiff calcifications affect aortic failure mechanics. Results showed that atherosclerosis influences dissection behavior on multiple length scales. Experimentally, atherosclerotic samples exhibited higher peel tensions and greater variance in the axial direction. The variation was driven by increased amplitudes of low-frequency tension fluctuations in diseased samples, indicating that more catastrophic propagations occur near calcifications. The simulations corroborated this finding, suggesting that the low-frequency changes resulted from the presence of a stiff calcification in the vessel wall. There were also modifications to the high-frequency peel mechanics, a response likely attributable to alterations in the microstructure and interlamellar bonding within the media. Considered collectively, these findings demonstrate that dissection mechanics are modified in aortic media nearby and adjacent to aortic calcifications.

A computational bridge between traction force microscopy and tissue contraction

Arterial wall active mechanics are driven by resident smooth muscle cells, which respond to biological, chemical, and mechanical stimuli and activate their cytoskeletal machinery to generate contractile stresses. The cellular mechanoresponse is sensitive to environmental perturbations, often leading to maladaptation and disease progression. When investigated at the single cell scale, however, these perturbations do not consistently result in phenotypes observed at the tissue scale. Here, a multiscale model is introduced that translates microscale contractility signaling into a macroscale, tissue-level response. The microscale framework incorporates a biochemical signaling network along with characterization of fiber networks that govern the anisotropic mechanics of vascular tissue. By incorporating both biochemical and mechanical components, the model is more flexible and more broadly applicable to physiological and pathological conditions. The model can be applied to both cell and tissue scale systems, allowing for the analysis of in vitro, traction force microscopy and ex vivo, isometric contraction experiments in parallel. When applied to aortic explant rings and isolated smooth muscle cells, the model predicts that active contractility is not a function of stretch at intermediate strain. The model also successfully predicts cell-scale and tissue-scale contractility and matches experimentally observed behaviors, including the hypercontractile phenotype caused by chronic hyperglycemia. The connection of the microscale framework to the macroscale through the multiscale model presents a framework that can translate the wealth of information already collected at the cell scale to tissue scale phenotypes, potentially easing the development of smooth muscle cell-targeting therapeutics.

The non-affine fiber network solver: A multiscale fiber network material model for finite-element analysis

Multiscale mechanical models in biomaterials research have largely relied on simplifying the microstructure in order to make large-scale simulations tractable. The microscale simplifications often rely on approximations of the constituent distributions and assumptions on the deformation of the constituents. Of particular interest in biomechanics are fiber embedded materials, where simplified fiber distributions and assumed affinity in the fiber deformation greatly influence the mechanical behavior. The consequences of these assumptions are problematic when dealing with microscale mechanical phenomena such as cellular mechanotransduction in growth and remodeling, and fiber-level failure events during tissue failure. In this work, we propose a technique for coupling non-affine network models to finite element solvers, allowing for simulation of discrete microstructural phenomena within macroscopically complex geometries. The developed plugin is readily available as an open-source library for use with the bio-focused finite element software FEBio, and the description of the implementation allows for the adaptation to other finite element solvers.

Beyond CFD: Emerging methodologies for predictive simulation in cardiovascular health and disease

Physics-based computational models of the cardiovascular system are increasingly used to simulate hemodynamics, tissue mechanics, and physiology in evolving healthy and diseased states. While predictive models using computational fluid dynamics (CFD) originated primarily for use in surgical planning, their application now extends well beyond this purpose. In this review, we describe an increasingly wide range of modeling applications aimed at uncovering fundamental mechanisms of disease progression and development, performing model-guided design, and generating testable hypotheses to drive targeted experiments. Increasingly, models are incorporating multiple physical processes spanning a wide range of time and length scales in the heart and vasculature. With these expanded capabilities, clinical adoption of patient-specific modeling in congenital and acquired cardiovascular disease is also increasing, impacting clinical care and treatment decisions in complex congenital heart disease, coronary artery disease, vascular surgery, pulmonary artery disease, and medical device design. In support of these efforts, we discuss recent advances in modeling methodology, which are most impactful when driven by clinical needs. We describe pivotal recent developments in image processing, fluid-structure interaction, modeling under uncertainty, and reduced order modeling to enable simulations in clinically relevant timeframes. In all these areas, we argue that traditional CFD alone is insufficient to tackle increasingly complex clinical and biological problems across scales and systems. Rather, CFD should be coupled with appropriate multiscale biological, physical, and physiological models needed to produce comprehensive, impactful models of mechanobiological systems and complex clinical scenarios. With this perspective, we finally outline open problems and future challenges in the field.

Experimental and Mouse-Specific Computational Models of the Fbln4SMKO Mouse to Identify Potential Biomarkers for Ascending Thoracic Aortic Aneurysm

PURPOSE

To use computational methods to explore geometric, mechanical, and fluidic biomarkers that could correlate with mouse lifespan in the Fbln4SMKO mouse. Mouse lifespan was used as a surrogate for risk of a severe cardiovascular event in cases of ascending thoracic aortic aneurysm.

METHODS

Image-based, mouse-specific fluid-structure-interaction models were developed for Fbln4SMKO mice (n = 10) at ages two and six months. The results of the simulations were used to quantify potential biofluidic biomarkers, complementing the geometrical biomarkers obtained directly from the images.

RESULTS

Comparing the different geometrical and biofluidic biomarkers to the mouse lifespan, it was found that mean oscillatory shear index (OSImin) and minimum time-averaged wall shear stress (TAWSSmin) at six months showed the largest correlation with lifespan (r2 = 0.70, 0.56), with both correlations being positive (i.e., mice with high OSImean and high TAWSSmin tended to live longer). When change between two and six months was considered, the change in TAWSSmin showed a much stronger correlation than OSImean (r2 = 0.75 vs. 0.24), and the correlation was negative (i.e., mice with increasing TAWSSmin over this period tended to live less long).

CONCLUSION

The results highlight potential biomarkers of ATAA outcomes that can be obtained through noninvasive imaging and computational simulations, and they illustrate the potential synergy between small-animal and computational models.

Elucidating the signal for contact guidance contained in aligned fibrils with a microstructural-mechanical model

Despite its importance in physiological processes and tissue engineering, the mechanism underlying cell contact guidance in an aligned fibrillar network has defied elucidation due to multiple interdependent signals that such a network presents to cells, namely, anisotropy of adhesion, porosity and mechanical behaviour. A microstructural-mechanical model of fibril networks was used to assess the relative magnitudes of these competing signals in networks of varied alignment strength based on idealized cylindrical pseudopods projected into the aligned and orthogonal directions and computing the anisotropy of metrics chosen for adhesion, porosity and mechanical behaviour: cylinder-fibre contact area for adhesion, persistence length of pores for porosity and total force to displace fibres from the cylindrical volume as well as network stiffness experienced upon cylinder retraction for mechanical behaviour. The signals related to mechanical anisotropy are substantially higher than adhesion and porosity anisotropy, especially at stronger network alignments, although their signal to noise (S/N) values are substantially lower. The former finding is consistent with a recent report that fibroblasts can sense fibril alignment via anisotropy of network mechanical resistance, and the model reveals this can be due to either mechanical resistance to pseudopod protrusion or retraction given their signal and S/N values are similar.

A Hybrid Microstructural-Continuum Multiscale Approach for Modeling Hyperelastic Fibrous Soft Tissue

The heterogeneous, nonlinear, anisotropic material behavior of biological tissues makes precise definition of an accurate constitutive model difficult. One possible solution to this issue would be to define microstructural elements and perform fully coupled multiscale simulation. However, for complex geometries and loading scenarios, the computational costs of such simulations can be prohibitive. Ideally then, we should seek a method that contains microstructural detail, but leverages the speed of classical continuum-based finite-element (FE) modeling. In this work, we demonstrate the use of the Holzapfel-Gasser-Ogden (HGO) model [1, 2] to fit the behavior of microstructural network models. We show that Delaunay microstructural networks can be fit to the HGO strain energy function by calculating fiber network strain energy and average fiber stretch ratio. We then use the HGO constitutive model in a FE framework to improve the speed of our hybrid model, and demonstrate that this method, combined with a material property update scheme, can match a full multiscale simulation. This method gives us flexibility in defining complex FE simulations that would be impossible, or at least prohibitively time consuming, in multiscale simulation, while still accounting for microstructural heterogeneity.

From Uniaxial Testing of Isolated Layers to a Tri-Layered Arterial Wall: A Novel Constitutive Modelling Framework

Mechanical testing and constitutive modelling of isolated arterial layers yields insight into the individual layers’ mechanical properties, but per se fails to recapitulate the in vivo loading state, neglecting layer-specific residual stresses. The aim of this study was to develop a testing/modelling framework that integrates layer-specific uniaxial testing data into a three-layered model of the arterial wall, thereby enabling study of layer-specific mechanics under realistic (patho)physiological conditions. Circumferentially and axially oriented strips of pig thoracic aortas (n = 10) were tested uniaxially. Individual arterial layers were then isolated from the wall, tested, and their mechanical behaviour modelled using a hyperelastic strain energy function. Subsequently, the three layers were computationally assembled into a single flat-walled sample, deformed into a cylindrical vessel, and subjected to physiological tension-inflation. At the in vivo axial stretch of 1.10 ± 0.03, average circumferential wall stress was 75 ± 9 kPa at 100 mmHg, which almost doubled to 138 ± 15 kPa at 160 mmHg. A ~ 200% stiffening of the adventitia over the 60 mmHg pressure increase shifted layer-specific load-bearing from the media (65 ± 10% → 61 ± 14%) to the adventitia (28 ± 9% → 32 ± 14%). Our approach provides valuable insight into the (patho)physiological mechanical roles of individual arterial layers at different loading states, and can be implemented conveniently using simple, inexpensive and widely available uniaxial testing equipment.