Computational Modeling Predicts Immuno-Mechanical Mechanisms of Maladaptive Aortic Remodeling in Hypertension

Remodeling of Murine Branch Pulmonary Arteries Under Chronic Hypoxia and Short-Term Normoxic Recovery

Chronic hypoxia plays a central role in diverse pulmonary pathologies, but its effects on longitudinal changes in the biomechanical behavior of proximal pulmonary arteries remain poorly understood. Similarly, effects of normoxic recovery have not been well studied. Here, we report hypoxia-induced changes in composition, vasoactivity, and passive biaxial mechanics in the main branch pulmonary artery of male C57BL/6J mice exposed to 10% FiO2 for 1, 2, or 3 weeks. We observed significant changes in extracellular matrix, and consequently wall mechanics, as early as 1 week of hypoxia. While circumferential stress and stiffness returned toward normal values by 2-3 weeks of hypoxia, area fractions of cytoplasm and thin collagen fibers did not return toward normal until after 1 week of normoxic recovery. By contrast, elastic energy storage and overall distensibility remained reduced after 3 weeks of hypoxia as well as following 1 week of normoxic recovery. While smooth muscle and endothelial cell responses were attenuated under hypoxia, smooth muscle but not endothelial cell responses recovered following 1 week of subsequent normoxia. Collectively, these data suggest that homeostatic processes were unable to preserve or restore overall function, at least over a brief period of normoxic recovery. Longitudinal changes are critical in understanding large pulmonary artery remodeling under hypoxia, and its reversal, and will inform predictive models of vascular adaptation.

Growth and remodeling of the dissected membrane in an idealized dissected aorta model

While transitioning from the acute to chronic phase, the wall of a dissected aorta often expands in diameter and adaptations in thickness and microstructure take place in the dissected membrane. Including the mechanisms, leading to these changes, in a computational model is expected to improve the accuracy of predictions of the long-term complications and optimal treatment timing of dissection patients. An idealized dissected wall was modeled to represent the elastin and collagen production and/or degradation imposed by stress- and inflammation-mediated growth and remodeling, using the homogenized constrained mixture theory. As no optimal growth and remodeling parameters have been defined for aortic dissections, a Latin hypercube sampling with 1000 parameter combinations was assessed for four inflammation patterns, with a varying spatial extent (full/local) and temporal evolution (permanent/transient). The dissected membrane thickening and microstructure was considered together with the diameter expansion over a period of 90 days. The highest success rate was found for the transient inflammation patterns, with about 15% of the samples leading to converged solutions after 90 days. Clinically observed thickening rates were found for 2-4% of the transient inflammation samples, which represented median total diameter expansion rates of about 5 mm/year. The dissected membrane microstructure showed an elastin decrease and, in most cases, a collagen increase. In conclusion, the model with the transient inflammation pattern allowed the reproduction of clinically observed dissected membrane thickening rates, diameter expansion rates and adaptations in microstructure, thus providing guidance in reducing the parameter space in growth and remodeling models of aortic dissections.

A multiscale computational model of arterial growth and remodeling including Notch signaling

Blood vessels grow and remodel in response to mechanical stimuli. Many computational models capture this process phenomenologically, by assuming stress homeostasis, but this approach cannot unravel the underlying cellular mechanisms. Mechano-sensitive Notch signaling is well-known to be key in vascular development and homeostasis. Here, we present a multiscale framework coupling a constrained mixture model, capturing the mechanics and turnover of arterial constituents, to a cell-cell signaling model, describing Notch signaling dynamics among vascular smooth muscle cells (SMCs) as influenced by mechanical stimuli. Tissue turnover was regulated by both Notch activity, informed by in vitro data, and a phenomenological contribution, accounting for mechanisms other than Notch. This novel framework predicted changes in wall thickness and arterial composition in response to hypertension similar to previous in vivo data. The simulations suggested that Notch contributes to arterial growth in hypertension mainly by promoting SMC proliferation, while other mechanisms are needed to fully capture remodeling. The results also indicated that interventions to Notch, such as external Jagged ligands, can alter both the geometry and composition of hypertensive vessels, especially in the short term. Overall, our model enables a deeper analysis of the role of Notch and Notch interventions in arterial growth and remodeling and could be adopted to investigate therapeutic strategies and optimize vascular regeneration protocols.

Computational modeling reveals inflammation-driven dilatation of the pulmonary autograft in aortic position

The pulmonary autograft in the Ross procedure, where the aortic valve is replaced by the patient's own pulmonary valve, is prone to failure due to dilatation. This is likely caused by tissue degradation and maladaptation, triggered by the higher experienced mechanical loads in aortic position. In order to further grasp the causes of dilatation, this study presents a model for tissue growth and remodeling of the pulmonary autograft, using the homogenized constrained mixture theory and equations for immuno- and mechano-mediated mass turnover. The model outcomes, compared to experimental data from an animal model of the pulmonary autograft in aortic position, show that inflammation likely plays an important role in the mass turnover of the tissue constituents and therefore in the autograft dilatation over time. We show a better match and prediction of long-term outcomes assuming immuno-mediated mass turnover, and show that there is no linear correlation between the stress-state of the material and mass production. Therefore, not only mechanobiological homeostatic adaption should be taken into account in the development of growth and remodeling models for arterial tissue in similar applications, but also inflammatory processes.

Irregular anatomical features can alter hemodynamics in Takayasu arteritis

Objective

Takayasu arteritis (TA) is a difficult disease to deal with because there are neither reliable clinical signs, laboratory biomarkers, nor a single noninvasive imaging technique that can be used for early diagnosis and disease activity monitoring. Knowledge of aortic hemodynamics in TA is lacking. This study aimed to fill this gap by assessing hemodynamics in patients with TA using image-based computational fluid dynamics (CFD) simulations.

Methods

Eleven patients with TA were included in the present study. Patient-specific geometries were reconstructed from either clinical aortic computed tomography angiography or magnetic resonance angiography studies and coupled with physiological boundary conditions for CFD simulations. Key anatomical and hemodynamic parameters were compared with a control group consisting of 18 age- and sex-matched adults without TA who had healthy aortas.

Results

Compared with controls, patients with TA had significantly higher aortic velocities (0.9 m/s [0.7, 1.1 m/s] vs 0.6 m/s [0.5, 0.7 m/s]; P = .002), maximum time-averaged wall shear stress (14.2 Pa [9.8, 20.9 Pa] vs 8.0 Pa [6.2, 10.3 Pa]; P = .004), and maximum pressure drops between the ascending and descending aorta (36.9 mm Hg [29.0, 49.3 mm Hg] vs 28.5 mm Hg [25.8, 31.5 mm Hg]; P = .004). These significant hemodynamic alterations in patients with TA might result from abnormal anatomical features including smaller arch diameter (20.0 mm [13.8, 23.3 mm] vs 25.2 mm [23.3, 26.8 mm]; P = .003), supra-aortic branch diameters (21.9 mm [18.5, 24.6 mm] vs 25.7 mm [24.3, 28.3 mm]; P = .003) and descending aorta diameter (14.7 mm [12.2, 16.8 mm] vs 22.5 mm [19.8, 24.0 mm]; P < .001).

Conclusions

CFD analysis reveals hemodynamic changes in the aorta of patients with TA. The applicability of CFD technique coupled with standard imaging assessments in predicting disease progression of such patients will be explored in future studies. Future large cohort study with outcome correlation is also warranted.

Clinical Relevance

Based on patient-specific computational fluid dynamics simulations, the present retrospective study revealed significant difference in aortic hemodynamics between the patients with and without Takayasu arteritis (TA). To the best of our knowledge, this study is the first to evaluate hemodynamic conditions within TA, demonstrating the potential of computational flow modeling in capturing abnormal hemodynamic forces, such as high wall shear stress, resulted from irregular morphological changes. In the future, assessing the hemodynamic parameters within patients with TA during the prestenotic period, together with longitudinal computational fluid dynamics studies may allow better monitoring and management of TA.

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.

Hybrid Discrete-Continuum Multiscale Model of Tissue Growth and Remodeling

Tissue growth and remodeling (G&R) is often central to disease etiology and progression, so understanding G&R is essential for understanding disease and developing effective therapies. While the state-of-the-art in this regard is animal and cellular models, recent advances in computational tools offer another avenue to investigate G&R. A major challenge for computational models is bridging from the cellular scale (at which changes are actually occurring) to the macroscopic, geometric-scale (at which physiological consequences arise). Thus, many computational models simplify one scale or another in the name of computational tractability. In this work, we develop a discrete-continuum modeling scheme for analyzing G&R, in which we apply changes directly to the discrete cell and extracellular matrix (ECM) architecture and pass those changes up to a finite-element macroscale geometry. We demonstrate the use of the model in three case-study scenarios: the media of a thick-walled artery, and the media and adventitia of a thick-walled artery, and chronic dissection of an arterial wall. We analyze each case in terms of the new and insightful data that can be gathered from this technique, and we compare our results from this model to several others. STATEMENT OF SIGNIFICANCE: This work is significant in that it provides a framework for combining discrete, microstructural- and cellular-scale models to the growth and remodeling of large tissue structures (such as the aorta). It is a significant advance in that it couples the microscopic remodeling with an existing macroscopic finite element model, making it relatively easy to use for a wide range of conceptual models. It has the potential to improve understanding of many growth and remodeling processes, such as organ formation during development and aneurysm formation, growth, and rupture.

Computational analysis of the role of mechanosensitive Notch signaling in arterial adaptation to hypertension

Arteries grow and remodel in response to mechanical stimuli. Hypertension, for example, results in arterial wall thickening. Cell-cell Notch signaling between vascular smooth muscle cells (VSMCs) is known to be involved in this process, but the underlying mechanisms are still unclear. Here, we investigated whether Notch mechanosensitivity to strain may regulate arterial thickening in hypertension. We developed a multiscale computational framework by coupling a finite element model of arterial mechanics, including residual stress, to an agent-based model of mechanosensitive Notch signaling, to predict VSMC phenotypes as an indicator of growth and remodeling. Our simulations revealed that the sensitivity of Notch to strain at mean blood pressure may be a key mediator of arterial thickening in hypertensive arteries. Further simulations showed that loss of residual stress can have synergistic effects with hypertension, and that changes in the expression of Notch receptors, but not Jagged ligands, may be used to control arterial growth and remodeling and to intensify or counteract hypertensive thickening. Overall, we identify Notch mechanosensitivity as a potential mediator of vascular adaptation, and we present a computational framework that can facilitate the testing of new therapeutic and regenerative strategies.

Tissue engineered vascular grafts transform into autologous neovessels capable of native function and growth

Background

Tissue-engineered vascular grafts (TEVGs) have the potential to advance the surgical management of infants and children requiring congenital heart surgery by creating functional vascular conduits with growth capacity.

Methods

Herein, we used an integrative computational-experimental approach to elucidate the natural history of neovessel formation in a large animal preclinical model; combining an in vitro accelerated degradation study with mechanical testing, large animal implantation studies with in vivo imaging and histology, and data-informed computational growth and remodeling models.

Results

Our findings demonstrate that the structural integrity of the polymeric scaffold is lost over the first 26 weeks in vivo, while polymeric fragments persist for up to 52 weeks. Our models predict that early neotissue accumulation is driven primarily by inflammatory processes in response to the implanted polymeric scaffold, but that turnover becomes progressively mechano-mediated as the scaffold degrades. Using a lamb model, we confirm that early neotissue formation results primarily from the foreign body reaction induced by the scaffold, resulting in an early period of dynamic remodeling characterized by transient TEVG narrowing. As the scaffold degrades, mechano-mediated neotissue remodeling becomes dominant around 26 weeks. After the scaffold degrades completely, the resulting neovessel undergoes growth and remodeling that mimicks native vessel behavior, including biological growth capacity, further supported by fluid-structure interaction simulations providing detailed hemodynamic and wall stress information.

Conclusions

These findings provide insights into TEVG remodeling, and have important implications for clinical use and future development of TEVGs for children with congenital heart disease.

Constrained Mixture Models of Soft Tissue Growth and Remodeling - Twenty Years After

Soft biological tissues compromise diverse cell types and extracellular matrix constituents, each of which can possess individual natural configurations, material properties, and rates of turnover. For this reason, mixture-based models of growth (changes in mass) and remodeling (change in microstructure) are well-suited for studying tissue adaptations, disease progression, and responses to injury or clinical intervention. Such approaches also can be used to design improved tissue engineered constructs to repair, replace, or regenerate tissues. Focusing on blood vessels as archetypes of soft tissues, this paper reviews a constrained mixture theory introduced twenty years ago and explores its usage since by contrasting simulations of diverse vascular conditions. The discussion is framed within the concept of mechanical homeostasis, with consideration of solid-fluid interactions, inflammation, and cell signaling highlighting both past accomplishments and future opportunities as we seek to understand better the evolving composition, geometry, and material behaviors of soft tissues under complex conditions.

Vascular Mechanobiology: Homeostasis, Adaptation, and Disease

Cells of the vascular wall are exquisitely sensitive to changes in their mechanical environment. In healthy vessels, mechanical forces regulate signaling and gene expression to direct the remodeling needed for the vessel wall to maintain optimal function. Major diseases of arteries involve maladaptive remodeling with compromised or lost homeostatic mechanisms. Whereas homeostasis invokes negative feedback loops at multiple scales to mediate mechanobiological stability, disease progression often occurs via positive feedback that generates mechanobiological instabilities. In this review, we focus on the cell biology, wall mechanics, and regulatory pathways associated with arterial health and how changes in these processes lead to disease. We discuss how positive feedback loops arise via biomechanical and biochemical means. We conclude that inflammation plays a central role in overriding homeostatic pathways and suggest future directions for addressing therapeutic needs.

From Transcript to Tissue: Multiscale Modeling from Cell Signaling to Matrix Remodeling

Tissue-level biomechanical properties and function derive from underlying cell signaling, which regulates mass deposition, organization, and removal. Here, we couple two existing modeling frameworks to capture associated multiscale interactions-one for vessel-level growth and remodeling and one for cell-level signaling-and illustrate utility by simulating aortic remodeling. At the vessel level, we employ a constrained mixture model describing turnover of individual wall constituents (elastin, intramural cells, and collagen), which has proven useful in predicting diverse adaptations as well as disease progression using phenomenological constitutive relations. Nevertheless, we now seek an improved mechanistic understanding of these processes; we replace phenomenological relations in the mixture model with a logic-based signaling model, which yields a system of ordinary differential equations predicting changes in collagen synthesis, matrix metalloproteinases, and cell proliferation in response to altered intramural stress, wall shear stress, and exogenous angiotensin II. This coupled approach promises improved understanding of the role of cell signaling in achieving tissue homeostasis and allows us to model feedback between vessel mechanics and cell signaling. We verify our model predictions against data from the hypertensive murine infrarenal abdominal aorta as well as results from validated phenomenological models, and consider effects of noisy signaling and heterogeneous cell populations.

Computational models of cardiac hypertrophy

Cardiac hypertrophy, defined as an increase in mass of the heart, is a complex process driven by simultaneous changes in hemodynamics, mechanical stimuli, and hormonal inputs. It occurs not only during pre- and post-natal development but also in adults in response to exercise, pregnancy, and a range of cardiovascular diseases. One of the most exciting recent developments in the field of cardiac biomechanics is the advent of computational models that are able to accurately predict patterns of heart growth in many of these settings, particularly in cases where changes in mechanical loading of the heart play an import role. These emerging models may soon be capable of making patient-specific growth predictions that can be used to guide clinical interventions. Here, we review the history and current state of cardiac growth models and highlight three main limitations of current approaches with regard to future clinical application: their inability to predict the regression of heart growth after removal of a mechanical overload, inability to account for evolving hemodynamics, and inability to incorporate known growth effects of drugs and hormones on heart growth. Next, we outline growth mechanics approaches used in other fields of biomechanics and highlight some potential lessons for cardiac growth modeling. Finally, we propose a multiscale modeling approach for future studies that blends tissue-level growth models with cell-level signaling models to incorporate the effects of hormones in the context of pregnancy-induced heart growth.

Complementary roles of mechanotransduction and inflammation in vascular homeostasis

Arteries are exposed to relentless pulsatile haemodynamic loads, but via mechanical homeostasis they tend to maintain near optimal structure, properties and function over long periods in maturity in health. Numerous insults can compromise such homeostatic tendencies, however, resulting in maladaptations or disease. Chronic inflammation can be counted among the detrimental insults experienced by arteries, yet inflammation can also play important homeostatic roles. In this paper, we present a new theoretical model of complementary mechanobiological and immunobiological control of vascular geometry and composition, and thus properties and function. We motivate and illustrate the model using data for aortic remodelling in a common mouse model of induced hypertension. Predictions match the available data well, noting a need for increased data for further parameter refinement. The overall approach and conclusions are general, however, and help to unify two previously disparate literatures, thus leading to deeper insight into the separate and overlapping roles of mechanobiology and immunobiology in vascular health and disease.

Plasma Metabolomics Analysis Identifies Abnormal Energy, Lipid, and Amino Acid Metabolism in Abdominal Aortic Aneurysms

Background

Abdominal aortic aneurysm (AAA) is a complicated aortic dilatation disease. Metabolomics is an emerging system biology method. This aim of this study was to identify abnormal metabolites and metabolic pathways associated with AAA and to discover potential biomarkers that could affect the size of AAAs.

Material/Methods

An untargeted metabolomic method was used to analyze the plasma metabolic profiles of 39 patients with AAAs and 30 controls. Multivariate analysis methods were used to perform differential metabolite screening and metabolic pathway analysis. Cluster analysis and univariate analysis were performed to identify potential metabolites that could affect the size of an AAA.

Results

Forty-five different metabolites were identified with an orthogonal projection to latent squares-discriminant analysis model and the differences between them in the patients with AAAs and the control group were compared. A variable importance in the projection score >1 and P<0.05 were considered statistically significant. In patients with AAAs, the pathways involving metabolism of alanine, aspartate, glutamate, D-glutamine, D-glutamic acid, arginine, and proline; tricarboxylic acid cycling; and biosynthesis of arginine are abnormal. The progression of an AAA may be related to 13 metabolites: citric acid, 2-oxoglutarate, succinic acid, coenzyme Q1, pyruvic acid, sphingosine-1-phosphate, platelet-activating factor, LysoPC (16: 00), lysophosphatidylcholine (18: 2(9Z,12Z)/0: 0), arginine, D-aspartic acid, and L- and D-glutamine.

Conclusions

An untargeted metabolomic analysis using ultraperformance liquid chromatography-tandem mass spectrometry identified metabolites that indicate disordered metabolism of energy, lipids, and amino acids in AAAs.

Mechanisms of Vascular Remodeling in Hypertension

Hypertension is both a cause and a consequence of central artery stiffening, which in turn is an initiator and indicator of myriad disease conditions and thus all-cause mortality. Such stiffening results from a remodeling of the arterial wall that is driven by mechanical stimuli and mediated by inflammatory signals, which together lead to differential gene expression and concomitant changes in extracellular matrix composition and organization. This review focuses on biomechanical mechanisms by which central arteries remodel in hypertension within the context of homeostasis-what promotes it, what prevents it. It is suggested that the vasoactive capacity of the wall and inflammatory burden strongly influence the ability of homeostatic mechanisms to adapt the arterial wall to high blood pressure or not. Maladaptation, often reflected by inflammation-driven adventitial fibrosis, not just excessive intimal-medial thickening, significantly diminishes central artery function and disturbs hemodynamics, ultimately compromising end organ perfusion and thus driving the associated morbidity and mortality. It is thus suggested that there is a need for increased attention to controlling both smooth muscle phenotype and inflammation in hypertensive remodeling of central arteries, with future studies of the often adaptive response of medium-sized muscular arteries promising to provide additional guidance.

Numerical knockouts-In silico assessment of factors predisposing to thoracic aortic aneurysms

Myriad risk factors–including uncontrolled hypertension, aging, and diverse genetic mutations–contribute to the development and enlargement of thoracic aortic aneurysms. Detailed analyses of clinical data and longitudinal studies of murine models continue to provide insight into the natural history of these potentially lethal conditions. Yet, because of the co-existence of multiple risk factors in most cases, it has been difficult to isolate individual effects of the many different factors or to understand how they act in combination. In this paper, we use a data-informed computational model of the initiation and progression of thoracic aortic aneurysms to contrast key predisposing risk factors both in isolation and in combination; these factors include localized losses of elastic fiber integrity, aberrant collagen remodeling, reduced smooth muscle contractility, and dysfunctional mechanosensing or mechanoregulation of extracellular matrix along with superimposed hypertension and aortic aging. In most cases, mild-to-severe localized losses in cellular function or matrix integrity give rise to varying degrees of local dilatations of the thoracic aorta, with enlargement typically exacerbated in cases wherein predisposing risk factors co-exist. The simulations suggest, for the first time, that effects of compromised smooth muscle contractility are more important in terms of dysfunctional mechanosensing and mechanoregulation of matrix than in vessel-level control of diameter and, furthermore, that dysfunctional mechanobiological control can yield lesions comparable to those in cases of compromised elastic fiber integrity. Particularly concerning, therefore, is that loss of constituents such as fibrillin-1, as in Marfan syndrome, can compromise both elastic fiber integrity and mechanosensing.

Aneurysms are local dilatations of the arterial wall that are responsible for significant disability and death. Detailed analyses of clinical data continue to provide insight into the natural history of these potentially lethal conditions, with myriad risk factors–including uncontrolled hypertension, aging, and diverse genetic mutations–contributing to their development and enlargement. Yet, because of the co-existence of these risk factors in most cases, it has been difficult to isolate individual effects or to understand how they act in combination. In this paper, we use a computational model of the initiation and progression of thoracic aortic aneurysms to contrast key predisposing factors both in isolation and in combination as well as with superimposed hypertension and aging. The present study recovers many findings from mouse models but with new and important observations that promise to guide in vivo and ex vivo studies as we seek to understand and eventually better treat these complex, multi-factorial lesions, with data-informed patient-specific computations eventually the way forward.

Vascular adaptation in the presence of external support - A modeling study

Vascular grafts have long been used to replace damaged or diseased vessels with considerable success, but a new approach is emerging where native vessels are merely supported, not replaced. Although external supports have been evaluated in diverse situations - ranging from aneurysmal disease to vein grafts or the Ross operation - optimal supports and procedures remain wanting. In this paper, we present a novel application of a growth and remodeling model well suited for parametrically exploring multiple designs of external supports while accounting for mechanobiological and immunobiological responses of the supported native vessel. These results suggest that a load bearing external support can reduce vessel thickening in response to pressure elevation. Results also suggest that the final adaptive state of the vessel depends on the structural stiffness of the support via a mechano-driven adaptation, although luminal encroachment may be a complication in the presence of chronic inflammation. Finally, the supported vessel can stiffen (structurally and materially) along circumferential and axial directions, which could have implications on overall hemodynamics and thus subsequent vascular remodeling. The proposed framework can provide valuable insights into vascular adaptation in the presence of external support, accelerate rational design, and aid translation of this emerging approach.

Cell signaling model for arterial mechanobiology

Arterial growth and remodeling at the tissue level is driven by mechanobiological processes at cellular and sub-cellular levels. Although it is widely accepted that cells seek to promote tissue homeostasis in response to biochemical and biomechanical cues—such as increased wall stress in hypertension—the ways by which these cues translate into tissue maintenance, adaptation, or maladaptation are far from understood. In this paper, we present a logic-based computational model for cell signaling within the arterial wall, aiming to predict changes in extracellular matrix turnover and cell phenotype in response to pressure-induced wall stress, flow-induced wall shear stress, and exogenous sources of angiotensin II, with particular interest in mouse models of hypertension. We simulate a number of experiments from the literature at both the cell and tissue level, involving single or combined inputs, and achieve high qualitative agreement in most cases. Additionally, we demonstrate the utility of this modeling approach for simulating alterations (in this case knockdowns) of individual nodes within the signaling network. Continued modeling of cellular signaling will enable improved mechanistic understanding of arterial growth and remodeling in health and disease, and will be crucial when considering potential pharmacological interventions.

Biological soft tissues are characterized by continuous production and removal of material, which endows them with a remarkable ability to adapt to changes in their biochemical and biomechanical environments. For arteries, mechanical stimuli result primarily from changes in blood pressure or flow, and biochemical changes are induced by multiple factors, including pharmacological intervention. In order to understand how arterial properties are maintained in health, or how they adapt or fail to adapt in disease, we must understand better how these diverse stimuli affect material turnover. Extracellular matrix is tightly regulated by mechano-sensing and mechano-regulation, and therefore cell signaling, thus we present a computational model of relevant signaling pathways within the vascular wall, with the aim of predicting changes in wall composition and function in response to three main inputs: pressure-induced wall stress, flow-induced wall shear stress, and exogenous angiotensin II. We obtain qualitative agreement with a range of experimental studies from the literature, and provide illustrative examples demonstrating how such models can be used to further our understanding of arterial remodeling.

A Two-Dimensional Model of Hypertension-Induced Arterial Remodeling With Account for Stress Interaction Between Elastin and Collagen

We propose a novel structure-based two-dimensional (2D) mathematical model of hypertension-induced arterial remodeling. The model is built in the framework of the constrained mixture theory and global growth approach, utilizing a recently proposed structure-based constitutive model of arterial tissue that accounts for the individual natural configurations of and stress interaction between elastin and collagen. The basic novel predictive result is that provided remodeling causes a change in the elastin/collagen mass fraction ratio, it leads to a structural reorganization of collagen that manifests as an altered fiber undulation and a change in direction of the helically oriented fibers in the tissue natural state. Results obtained from the illustrative simulations for a porcine renal artery show that when remodeling is complete the collagen reorganization might have significant effects on the initial arterial geometry and mechanical properties of the arterial tissue. The proposed model has potential to describe and advance mechanistic understanding of adaptive arterial remodeling, promote the continual refinement of mathematical models of arterial remodeling, and provide motivation for new avenues of experimental investigation.

Computational Modeling Predicts Immuno-Mechanical Mechanisms of Maladaptive Aortic Remodeling in Hypertension

Uncontrolled hypertension is a major risk factor for myriad cardiovascular diseases. Among its many effects, hypertension increases central artery stiffness which in turn is both an initiator and indicator of disease. Despite extensive clinical, animal, and basic science studies, the biochemomechanical mechanisms by which hypertension drives aortic stiffening remain unclear. In this paper, we show that a new computational model of aortic growth and remodeling can capture differential effects of induced hypertension on the thoracic and abdominal aorta in a common mouse model of disease. Because the simulations treat the aortic wall as a constrained mixture of different constituents having different material properties and rates of turnover, one can gain increased insight into underlying constituent-level mechanisms of aortic remodeling. Model results suggest that the aorta can mechano-adapt locally to blood pressure elevation in the absence of marked inflammation, but large increases in inflammation drive a persistent maladaptive phenotype characterized primarily by adventitial fibrosis. Moreover, this fibrosis appears to occur via a marked increase in the rate of deposition of collagen having different material properties in the absence of a compensatory increase in the rate of matrix degradation. Controlling inflammation thus appears to be key to reducing fibrosis, but therapeutic strategies should not compromise the proteolytic activity of the wall that is essential to mechanical homeostasis.