A multiscale mechanobiological modelling framework using agent-based models and finite element analysis: application to vascular tissue engineering

Recent advances in artificial intelligent strategies for tissue engineering and regenerative medicine

BACKGROUND

Tissue engineering and regenerative medicine (TERM) aim to repair or replace damaged or lost tissues or organs due to accidents, diseases, or aging, by applying different sciences. For this purpose, an essential part of TERM is the designing, manufacturing, and evaluating of scaffolds, cells, tissues, and organs. Artificial intelligence (AI) or the intelligence of machines or software can be effective in all areas where computers play a role.

METHODS

The "artificial intelligence," "machine learning," "tissue engineering," "clinical evaluation," and "scaffold" keywords used for searching in various databases and articles published from 2000 to 2024 were evaluated.

RESULTS

The combination of tissue engineering and AI has created a new generation of technological advancement in the biomedical industry. Experience in TERM has been refined using advanced design and manufacturing techniques. Advances in AI, particularly deep learning, offer an opportunity to improve scientific understanding and clinical outcomes in TERM.

CONCLUSION

The findings of this research show the high potential of AI, machine learning, and robots in the selection, design, and fabrication of scaffolds, cells, tissues, or organs, and their analysis, characterization, and evaluation after their implantation. AI can be a tool to accelerate the introduction of tissue engineering products to the bedside.

HIGHLIGHTS

The capabilities of artificial intelligence (AI) can be used in different ways in all the different stages of TERM and not only solve the existing limitations, but also accelerate the processes, increase efficiency and precision, reduce costs, and complications after transplantation. ML predicts which technologies have the most efficient and easiest path to enter the market and clinic. The use of AI along with these imaging techniques can lead to the improvement of diagnostic information, the reduction of operator errors when reading images, and the improvement of image analysis (such as classification, localization, regression, and segmentation).

A review of computational methodologies to predict the fractional flow reserve in coronary arteries with stenosis

Computational methodologies for predicting the fractional flow reserve (FFR) in coronary arteries with stenosis have gained significant attention due to their potential impact on healthcare outcomes. Coronary artery disease is a leading cause of mortality worldwide, prompting the need for accurate diagnostic and treatment approaches. The use of medical image-based anatomical vascular geometries in computational fluid dynamics (CFD) simulations to evaluate the hemodynamics has emerged as a promising tool in the medical field. This comprehensive review aims to explore the state-of-the-art computational methodologies focusing on the possible considerations. Key aspects include the rheology of blood, boundary conditions, fluid-structure interaction (FSI) between blood and the arterial wall, and multiscale modelling (MM) of stenosis. Through an in-depth analysis of the literature, the goal is to obtain an overview of the major achievements regarding non-invasive methods to compute FFR and to identify existing gaps and challenges that inform further advances in the field. This research has the major objective of improving the current diagnostic capabilities and enhancing patient care in the context of cardiovascular diseases.

The challenges and prospects of smooth muscle tissue engineering

Many vascular disorders arise as a result of dysfunctional smooth muscle cells. Tissue engineering strategies have evolved as key approaches to generate functional vascular smooth muscle cells for use in cell-based precision and personalized regenerative medicine approaches. This article highlights some of the challenges that exist in the field and presents some of the prospects for translating research advancements into therapeutic modalities. The article emphasizes the need for better developing synergetic intracellular and extracellular cues in the processes to generate functional vascular smooth muscle cells from different stem cell sources for use in tissue engineering strategies.

Current Advances in the Use of Tissue Engineering for Cancer Metastasis Therapeutics

Cancer is a leading cause of death worldwide and results in nearly 10 million deaths each year. The global economic burden of cancer from 2020 to 2050 is estimated to be USD 25.2 trillion. The spread of cancer to distant organs through metastasis is the leading cause of death due to cancer. However, as of today, there is no cure for metastasis. Tissue engineering is a promising field for regenerative medicine that is likely to be able to provide rehabilitation procedures to patients who have undergone surgeries, such as mastectomy and other reconstructive procedures. Another important use of tissue engineering has emerged recently that involves the development of realistic and robust in vitro models of cancer metastasis, to aid in drug discovery and new metastasis therapeutics, as well as evaluate cancer biology at metastasis. This review covers the current studies in developing tissue-engineered metastasis structures. This article reports recent developments in in vitro models for breast, prostate, colon, and pancreatic cancer. The review also identifies challenges and opportunities in the use of tissue engineering toward new, clinically relevant therapies that aim to reduce the cancer burden.

An intricate interplay between stent drug dose and release rate dictates arterial restenosis

Since the introduction of percutaneous coronary intervention (PCI) for the treatment of obstructive coronary artery disease (CAD), patient outcomes have progressively improved. Drug eluting stents (DES) that employ anti-proliferative drugs to limit excess tissue growth following stent deployment have proved revolutionary. However, restenosis and a need for repeat revascularisation still occurs after DES use. Over the last few years, computational models have emerged that detail restenosis following the deployment of a bare metal stent (BMS), focusing primarily on contributions from mechanics and fluid dynamics. However, none of the existing models adequately account for spatiotemporal delivery of drug and the influence of this on the cellular processes that drive restenosis. In an attempt to fill this void, a novel continuum restenosis model coupled with spatiotemporal drug delivery is presented. Our results indicate that the severity and time-course of restenosis is critically dependent on the drug delivery strategy. Specifically, we uncover an intricate interplay between initial drug loading, drug release rate and restenosis, indicating that it is not sufficient to simply ramp-up the drug dose or prolong the time course of drug release to improve stent efficacy. Our model also shows that the level of stent over-expansion and stent design features, such as inter-strut spacing and strut thickness, influence restenosis development, in agreement with trends observed in experimental and clinical studies. Moreover, other critical aspects of the model which dictate restenosis, including the drug binding site density are investigated, where comparisons are made between approaches which assume this to be either constant or proportional to the number of smooth muscle cells (SMCs). Taken together, our results highlight the necessity of incorporating these aspects of drug delivery in the pursuit of optimal DES design.

Implementing computational modeling in tissue engineering: where disciplines meet

In recent years, the mathematical and computational sciences have developed novel methodologies and insights that can aid in designing advanced bioreactors, microfluidic set-ups or organ-on-chip devices, in optimizing culture conditions, or predicting long-term behavior of engineered tissues in vivo. In this review, we introduce the concept of computational models and how they can be integrated in an interdisciplinary workflow for Tissue Engineering and Regenerative Medicine (TERM). We specifically aim this review of general concepts and examples at experimental scientists with little or no computational modeling experience. We also describe the contribution of computational models in understanding TERM processes and in advancing the TERM field by providing novel insights.

Multiscale Computational Modeling of Vascular Adaptation: A Systems Biology Approach Using Agent-Based Models

The widespread incidence of cardiovascular diseases and associated mortality and morbidity, along with the advent of powerful computational resources, have fostered an extensive research in computational modeling of vascular pathophysiology field and promoted in-silico models as a support for biomedical research. Given the multiscale nature of biological systems, the integration of phenomena at different spatial and temporal scales has emerged to be essential in capturing mechanobiological mechanisms underlying vascular adaptation processes. In this regard, agent-based models have demonstrated to successfully embed the systems biology principles and capture the emergent behavior of cellular systems under different pathophysiological conditions. Furthermore, through their modular structure, agent-based models are suitable to be integrated with continuum-based models within a multiscale framework that can link the molecular pathways to the cell and tissue levels. This can allow improving existing therapies and/or developing new therapeutic strategies. The present review examines the multiscale computational frameworks of vascular adaptation with an emphasis on the integration of agent-based approaches with continuum models to describe vascular pathophysiology in a systems biology perspective. The state-of-the-art highlights the current gaps and limitations in the field, thus shedding light on new areas to be explored that may become the future research focus. The inclusion of molecular intracellular pathways (e.g., genomics or proteomics) within the multiscale agent-based modeling frameworks will certainly provide a great contribution to the promising personalized medicine. Efforts will be also needed to address the challenges encountered for the verification, uncertainty quantification, calibration and validation of these multiscale frameworks.

Towards in silico Models of the Inflammatory Response in Bone Fracture Healing

In silico modeling is a powerful strategy to investigate the biological events occurring at tissue, cellular and subcellular level during bone fracture healing. However, most current models do not consider the impact of the inflammatory response on the later stages of bone repair. Indeed, as initiator of the healing process, this early phase can alter the regenerative outcome: if the inflammatory response is too strongly down- or upregulated, the fracture can result in a non-union. This review covers the fundamental information on fracture healing, in silico modeling and experimental validation. It starts with a description of the biology of fracture healing, paying particular attention to the inflammatory phase and its cellular and subcellular components. We then discuss the current state-of-the-art regarding in silico models of the immune response in different tissues as well as the bone regeneration process at the later stages of fracture healing. Combining the aforementioned biological and computational state-of-the-art, continuous, discrete and hybrid modeling technologies are discussed in light of their suitability to capture adequately the multiscale course of the inflammatory phase and its overall role in the healing outcome. Both in the establishment of models as in their validation step, experimental data is required. Hence, this review provides an overview of the different in vitro and in vivo set-ups that can be used to quantify cell- and tissue-scale properties and provide necessary input for model credibility assessment. In conclusion, this review aims to provide hands-on guidance for scientists interested in building in silico models as an additional tool to investigate the critical role of the inflammatory phase in bone regeneration.

3D Bioprinting of Engineered Tissue Flaps with Hierarchical Vessel Networks (VesselNet) for Direct Host-To-Implant Perfusion

Engineering hierarchical vasculatures is critical for creating implantable functional thick tissues. Current approaches focus on fabricating mesoscale vessels for implantation or hierarchical microvascular in vitro models, but a combined approach is yet to be achieved to create engineered tissue flaps. Here, millimetric vessel-like scaffolds and 3D bioprinted vascularized tissues interconnect, creating fully engineered hierarchical vascular constructs for implantation. Endothelial and support cells spontaneously form microvascular networks in bioprinted tissues using a human collagen bioink. Sacrificial molds are used to create polymeric vessel-like scaffolds and endothelial cells seeded in their lumen form native-like endothelia. Assembling endothelialized scaffolds within vascularizing hydrogels incites the bioprinted vasculature and endothelium to cooperatively create vessels, enabling tissue perfusion through the scaffold lumen. Using a cuffing microsurgery approach, the engineered tissue is directly anastomosed with a rat femoral artery, promoting a rich host vasculature within the implanted tissue. After two weeks in vivo, contrast microcomputer tomography imaging and lectin perfusion of explanted engineered tissues verify the host ingrowth vasculature's functionality. Furthermore, the hierarchical vessel network (VesselNet) supports in vitro functionality of cardiomyocytes. Finally, the proposed approach is expanded to mimic complex structures with native-like millimetric vessels. This work presents a novel strategy aiming to create fully-engineered patient-specific thick tissue flaps.

Mechano-chemo-biological Computational Models for Arteries in Health, Disease and Healing: From Tissue Remodelling to Drug-eluting Devices

This review aims to highlight urgent priorities for the computational biomechanics community in the framework of mechano-chemo-biological models. Recent approaches, promising directions and open challenges on the computational modelling of arterial tissues in health and disease are introduced and investigated, together with in silico approaches for the analysis of drug-eluting stents that promote pharmacological-induced healing. The paper addresses a number of chemo-biological phenomena that are generally neglected in biomechanical engineering models but are most likely instrumental for the onset and the progression of arterial diseases. An interdisciplinary effort is thus encouraged for providing the tools for an effective in silico insight into medical problems. An integrated mechano-chemo-biological perspective is believed to be a fundamental missing piece for crossing the bridge between computational engineering and life sciences, and for bringing computational biomechanics into medical research and clinical practice.

Pulsating fluid flow affects pre-osteoblast behavior and osteogenic differentiation through production of soluble factors

Bone mass increases after error-loading, even in the absence of osteocytes. Loaded osteoblasts may produce a combination of growth factors affecting adjacent osteoblast differentiation. We hypothesized that osteoblasts respond to a single load in the short-term (minutes) by changing F-actin stress fiber distribution, in the intermediate-term (hours) by signaling molecule production, and in the long-term (days) by differentiation. Furthermore, growth factors produced during and after mechanical loading by pulsating fluid flow (PFF) will affect osteogenic differentiation. MC3T3-E1 pre-osteoblasts were either/not stimulated by 60 min PFF (amplitude, 1.0 Pa; frequency, 1 Hz; peak shear stress rate, 6.5 Pa/s) followed by 0-6 h, or 21/28 days of post-incubation without PFF. Computational analysis revealed that PFF immediately changed distribution and magnitude of fluid dynamics over an adherent pre-osteoblast inside a parallel-plate flow chamber (immediate impact). Within 60 min, PFF increased nitric oxide production (5.3-fold), altered actin distribution, but did not affect cell pseudopodia length and cell orientation (initial downstream impact). PFF transiently stimulated Fgf2, Runx2, Ocn, Dmp1, and Col1⍺1 gene expression between 0 and 6 h after PFF cessation. PFF did not affect alkaline phosphatase nor collagen production after 21 days, but altered mineralization after 28 days. In conclusion, a single bout of PFF with indirect associated release of biochemical factors, stimulates osteoblast differentiation in the long-term, which may explain enhanced bone formation resulting from mechanical stimuli.

Spontaneous reversal of stenosis in tissue-engineered vascular grafts

We developed a tissue-engineered vascular graft (TEVG) for use in children and present results of a U.S. Food and Drug Administration (FDA)-approved clinical trial evaluating this graft in patients with single-ventricle cardiac anomalies. The TEVG was used as a Fontan conduit to connect the inferior vena cava and pulmonary artery, but a high incidence of graft narrowing manifested within the first 6 months, which was treated successfully with angioplasty. To elucidate mechanisms underlying this early stenosis, we used a data-informed, computational model to perform in silico parametric studies of TEVG development. The simulations predicted early stenosis as observed in our clinical trial but suggested further that such narrowing could reverse spontaneously through an inflammation-driven, mechano-mediated mechanism. We tested this unexpected, model-generated hypothesis by implanting TEVGs in an ovine inferior vena cava interposition graft model, which confirmed the prediction that TEVG stenosis resolved spontaneously and was typically well tolerated. These findings have important implications for our translational research because they suggest that angioplasty may be safely avoided in patients with asymptomatic early stenosis, although there will remain a need for appropriate medical monitoring. The simulations further predicted that the degree of reversible narrowing can be mitigated by altering the scaffold design to attenuate early inflammation and increase mechano-sensing by the synthetic cells, thus suggesting a new paradigm for optimizing next-generation TEVGs. We submit that there is considerable translational advantage to combined computational-experimental studies when designing cutting-edge technologies and their clinical management.

An in-silico Investigation Into the Role of Strain and Structure on Vascular Smooth Muscle Cell Growth

The orientation of vascular cells can greatly influence the in vivo mechanical properties and functionality of soft vascular tissues. How cell orientation mediates the growth response of cells is of critical importance in understanding the response of soft tissues to mechanical stimuli or injury. To date, considerable evidence has shown that cells align with structural cues such as collagen fibers. However, in the presence of uniaxial cyclic strain on unstructured substrates, cells generally align themselves perpendicularly to the mechanical stimulus, such as strain, a phenomenon known as “strain avoidance.” The cellular response to this interplay between structural cues and a mechanical stimulus is poorly understood. A recent in vitro experimental study in our lab has investigated both the individual and collective response of rat aortic smooth muscle cells (RASMC) to structural (collagenous aligned constructs) and mechanical (cyclic strain) cues. In this study, a 2D agent-based model (ABM) is developed to simulate the collective response of RASMC to varying amplitudes of cyclic strain (0–10%, 2–8%, 4–6%) when seeded on unstructured (PDMS) and structured (decellularized collagenous tissue) constructs. An ABM is presented that is fit to the experimental outcomes in terms of cellular alignment and cell growth on PDMS substrates, under cyclic strain amplitudes of (4–6%, 2–8%, 0–10%) at 24 and 72 h timepoints. Furthermore, the ABM can predict RASMC alignment and change in cell number on a structured construct at a cyclic strain amplitude of 0–10% after 10 days. The ABM suggests that strain avoidance behavior observed in cells is dominated by selective cell proliferation and apoptosis at these early time points, as opposed to cell re-orientation, i.e., cells perpendicular to the strain increase their rate of proliferation, whilst the rate of apoptosis simultaneously increases in cells parallel to the strain direction. The development of in-silico modeling platforms, such as that presented here, allow for further understanding of the response of cells to changes in their mechanical environment. Such models offer an efficient and robust means to design and optimize the compliance and topological structure of implantable devices and could be used to aid the design of next-generation vascular grafts and stents.

Notch in mechanotransduction - from molecular mechanosensitivity to tissue mechanostasis

Tissue development and homeostasis are controlled by mechanical cues. Perturbation of the mechanical equilibrium triggers restoration of mechanostasis through changes in cell behavior, while defects in these restorative mechanisms lead to mechanopathologies, for example, osteoporosis, myopathies, fibrosis or cardiovascular disease. Therefore, sensing mechanical cues and integrating them with the biomolecular cell fate machinery is essential for the maintenance of health. The Notch signaling pathway regulates cell and tissue fate in nearly all tissues. Notch activation is directly and indirectly mechanosensitive, and regulation of Notch signaling, and consequently cell fate, is integral to the cellular response to mechanical cues. Fully understanding the dynamic relationship between molecular signaling, tissue mechanics and tissue remodeling is challenging. To address this challenge, engineered microtissues and computational models play an increasingly large role. In this Review, we propose that Notch takes on the role of a 'mechanostat', maintaining the mechanical equilibrium of tissues. We discuss the reciprocal role of Notch in the regulation of tissue mechanics, with an emphasis on cardiovascular tissues, and the potential of computational and engineering approaches to unravel the complex dynamic relationship between mechanics and signaling in the maintenance of cell and tissue mechanostasis.

Why Are Viscosity and Nonlinearity Bound to Make an Impact in Clinical Elastographic Diagnosis?

The adoption of multiscale approaches by the biomechanical community has caused a major improvement in quality in the mechanical characterization of soft tissues. The recent developments in elastography techniques are enabling in vivo and non-invasive quantification of tissues' mechanical properties. Elastic changes in a tissue are associated with a broad spectrum of pathologies, which stems from the tissue microstructure, histology and biochemistry. This knowledge is combined with research evidence to provide a powerful diagnostic range of highly prevalent pathologies, from birth and labor disorders (prematurity, induction failures, etc.), to solid tumors (e.g., prostate, cervix, breast, melanoma) and liver fibrosis, just to name a few. This review aims to elucidate the potential of viscous and nonlinear elastic parameters as conceivable diagnostic mechanical biomarkers. First, by providing an insight into the classic role of soft tissue microstructure in linear elasticity; secondly, by understanding how viscosity and nonlinearity could enhance the current diagnosis in elastography; and finally, by compounding preliminary investigations of those elastography parameters within different technologies. In conclusion, evidence of the diagnostic capability of elastic parameters beyond linear stiffness is gaining momentum as a result of the technological and imaging developments in the field of biomechanics.

Lateral induction limits the impact of cell connectivity on Notch signaling in arterial walls

It is well known that arteries grow and remodel in response to mechanical stimuli. Vascular smooth muscle cells are the main mediators of this process, as they can switch phenotype from contractile to synthetic, and vice-versa, based on the surrounding bio-chemo-mechanical stimuli. A correct regulation of this phenotypic switch is fundamental to obtain and maintain arterial homeostasis. Notch, a mechanosensitive signaling pathway, is one of the main regulators of the vascular smooth muscle cell phenotype. Therefore, understanding Notch dynamics is key to elucidate arterial growth, remodeling, and mechanobiology. We have recently developed a one-dimensional agent-based model to investigate Notch signaling in arteries. However, due to its one-dimensional formulation, the model cannot be adopted to study complex nonsymmetrical geometries and, importantly, it cannot capture the realistic "cell connectivity" in arteries, here defined as the number of cell neighbors. Notch functions via direct cell-cell contact; thus, the number of cell neighbors could be an essential feature of Notch dynamics. Here, we extended the agent-based model to a two-dimensional formulation, to investigate the effects of cell connectivity on Notch dynamics and cell phenotypes in arteries. The computational results, supported by a sensitivity analysis, indicate that cell connectivity has marginal effects when Notch dynamics is dominated by the process of lateral induction, which induces all cells to have a uniform phenotype. When lateral induction is weaker, cells exhibit a nonuniform phenotype distribution and the percentage of synthetic cells within an artery depends on the number of neighbors.

Location-Specific Comparison Between a 3D In-Stent Restenosis Model and Micro-CT and Histology Data from Porcine In Vivo Experiments

BACKGROUND

Coronary artery restenosis is an important side effect of percutaneous coronary intervention. Computational models can be used to better understand this process. We report on an approach for validation of an in silico 3D model of in-stent restenosis in porcine coronary arteries and illustrate this approach by comparing the modelling results to in vivo data for 14 and 28 days post-stenting.

METHODS

This multiscale model includes single-scale models for stent deployment, blood flow and tissue growth in the stented vessel, including smooth muscle cell (SMC) proliferation and extracellular matrix (ECM) production. The validation procedure uses data from porcine in vivo experiments, by simulating stent deployment using stent geometry obtained from micro computed tomography (micro-CT) of the stented vessel and directly comparing the simulation results of neointimal growth to histological sections taken at the same locations.

RESULTS

Metrics for comparison are per-strut neointimal thickness and per-section neointimal area. The neointimal area predicted by the model demonstrates a good agreement with the detailed experimental data. For 14 days post-stenting the relative neointimal area, averaged over all vessel sections considered, was 20 ± 3% in vivo and 22 ± 4% in silico. For 28 days, the area was 42 ± 3% in vivo and 41 ± 3% in silico.

CONCLUSIONS

The approach presented here provides a very detailed, location-specific, validation methodology for in silico restenosis models. The model was able to closely match both histology datasets with a single set of parameters. Good agreement was obtained for both the overall amount of neointima produced and the local distribution. It should be noted that including vessel curvature and ECM production in the model was paramount to obtain a good agreement with the experimental data.

Resident multipotent vascular stem cells exhibit amplitude dependent strain avoidance similar to that of vascular smooth muscle cells

Atherosclerosis is one of the leading causes of mortality worldwide, and presents as a narrowing or occlusion of the arterial lumen. Interventions to re-open the arterial lumen can result in re-occlusion through intimal hyperplasia. Historically only de-differentiated vascular smooth muscle cells were thought to contribute to intimal hyperplasia. However recent significant evidence suggests that resident medial multipotent vascular stem cells (MVSC) may also play a role. We therefore investigated the strain response of MVSC since these resident cells are also subjected to strain within their native environment. Accordingly, we applied uniaxial 1 Hz cyclic uniaxial tensile strain at three amplitudes around a mean strain of 5%, (4-6%, 2-8% and 0-10%) to either rat MVSC or rat VSMC before their strain response was evaluated. While both cell types strain avoid, the strain avoidant response was greater for MVSC after 24 h, while VSMC strain avoid to a greater degree after 72 h. Additionally, both cell types increase strain avoidance as strain amplitude is increased. Moreover, MVSC and VSMC both demonstrate a strain-induced decrease in cell number, an effect more pronounced for MVSC. These experiments demonstrate for the first time the mechano-sensitivity of MVSC that may influence intimal thickening, and emphasizes the importance of strain amplitude in controlling the response of vascular cells in tissue engineering applications.

Computational modelling of magnesium stent mechanical performance in a remodelling artery: Effects of multiple remodelling stimuli

Significant research has been conducted in the area of coronary stents/scaffolds made from resorbable metallic and polymeric biomaterials. These next-generation bioabsorbable stents have the potential to completely revolutionise the treatment of coronary artery disease. The primary advantage of resorbable devices over permanent stents is their temporary presence which, from a theoretical point of view, means only a healed coronary artery will be left behind following degradation of the stent potentially eliminating long-term clinical problems associated with permanent stents. The healing of the artery following coronary stent/scaffold implantation is crucial for the long-term safety of these devices. Computational modelling can be used to evaluate the performance of complex stent devices in silico and assist in the design and development and understanding of the next-generation resorbable stents. What is lacking in computational modelling literature is the representation of the active response of the arterial tissue in the weeks and months following stent implantation, ie, neointimal remodelling, in particular for the case of biodegradable stents. In this paper, a computational modelling framework is developed, which accounts for two major physiological stimuli responsible for neointimal remodelling and combined with a magnesium corrosion model that is capable of simulating localised pitting (realistic) stent corrosion. The framework is used to simulate different neointimal growth patterns and to explore the effects the neointimal remodelling has on the mechanical performance (scaffolding support) of the bioabsorbable magnesium stent.

Mathematical modelling of the restenosis process after stent implantation

The stenting procedure has evolved to become a highly successful technique for the clinical treatment of advanced atherosclerotic lesions in arteries. However, the development of in-stent restenosis remains a key problem. In this work, a novel two-dimensional continuum mathematical model is proposed to describe the complex restenosis process following the insertion of a stent into a coronary artery. The biological species considered to play a key role in restenosis development are growth factors, matrix metalloproteinases, extracellular matrix, smooth muscle cells and endothelial cells. Diffusion-reaction equations are used for modelling the mass balance between species in the arterial wall. Experimental data from the literature have been used in order to estimate model parameters. Moreover, a sensitivity analysis has been performed to study the impact of varying the parameters of the model on the evolution of the biological species. The results demonstrate that this computational model qualitatively captures the key characteristics of the lesion growth and the healing process within an artery subjected to non-physiological mechanical forces. Our results suggest that the arterial wall response is driven by the damage area, smooth muscle cell proliferation and the collagen turnover among other factors.

In Silico Tissue Engineering: A Coupled Agent-Based Finite Element Approach

Over the past two decades, the increase in prevalence of cardiovascular diseases and the limited availability of autologous blood vessels and saphenous vein grafts have motivated the development of tissue-engineered vascular grafts (TEVGs). However, compliance mismatch and poor mechanical properties of the TEVGs remain as two major issues that need to be addressed. Researchers have investigated the role of various culture conditions and mechanical conditioning in deposition and orientation of collagen fibers, which are the key structural components in the vascular wall; however, the intrinsic complexity of mechanobiological interactions demands implementing new engineering approaches that allow researchers to investigate various scenarios more efficiently. In this study, we utilized a coupled agent-based finite element analysis (AB-FEA) modeling approach to study the effect of various loading modes (uniaxial, biaxial, and equibiaxial), boundary conditions, stretch magnitudes, and growth factor concentrations on growth and remodeling of smooth muscle cell-populated TEVGs, with specific focus on collagen deposition and orientation. Our simulations (12 weeks of culture) showed that biaxial cyclic loading (and not uniaxial or equibiaxial) leads to alignment of collagen fibers in the physiological directions. Moreover, axial boundary conditions of the TEVG act as determinants of fiber orientations. Decreasing the serum concentration, from 10% to 5% or 1%, significantly decreased the growth and remodeling speed, but only affected the fiber orientation in the 1% serum case. In conclusion, in silico tissue engineering has the potential to evolve the future of tissue engineering, as it will allow researchers to conceptualize various interactions and investigate numerous scenarios with great speed. In this study, we were able to predict the orientation of collagen fibers in TEVGs using a coupled AB-FEA model in less than 8 h. Impact Statement Tissue-engineered vascular grafts (TEVGs) hold potential to replace the current gold standard of vascular grafting, saphenous vein grafts. However, developing TEVGs that mimic the mechanical performance of the native tissue remains a challenging task. We developed a computational model of the grafts' remodeling processes and studied the effects of various loading mechanisms and culture conditions on collagen fiber orientation, which is a key factor in mechanical performance of the grafts. We were able to predict the fiber orientations accurately and show that biaxial loading and axial boundary conditions are important factors in collagen fiber organization.

Fabrications of small diameter compliance bypass conduit using electrospinning of clinical grade polyurethane

Objective

Compliance and viscoelastic mismatches of small diameter vascular conduits and host arteries have been the cause of conduit’s failure.

Methods

To reduce these mismatches, the aim of this study was to develop and characterize a polyurethane conduit, which mimics the viscoelastic behaviors of human arteries. Electrospinning technique was used to fabricate tubular polyurethane conduits with similar properties of the human common carotid artery. This was achieved by manipulating the fiber diameter by altering the syringe flow rate of the solution. The mechanical and viscoelastic properties of the fabricated electrospun polyurethane conduits were, then, compared with commercially available vascular conduits, expanded polytetrafluoroethylene, polyethylene terephthalate (Dacron®) and the healthy human common carotid arteries. In addition, a comprehensive constitutive model was proposed to capture the visco-hyperelastic behavior of the synthetic electrospun polyurethanes, commercial conduits and human common carotid arteries.

Results

Results showed that increasing the fiber diameter of electrospun polyurethanes from 114 to 190 nm reduced Young’s modulus from 8 to 2 MPa. Also, thicker fiber diameter yielded in higher conduits’ viscosity. Furthermore, the results revealed that proposed visco-hyperelastic model is strongly able to fit the experimental data with great precision which proofs the reliability of the proposed model to address both nonlinear elasticity and viscoelasticity of the electrospun polyurethanes, commercial conduits and human common carotid arteries.

Conclusions

In conclusion, statistical analysis revealed that the elastic and viscous properties of 190 nm fiber diameter conduit are very similar to that of human common carotid artery in comparison to the commercial expanded polytetrafluoroethylene and Dacron® that are up to nine and seven times stiffer than natural vessels. Therefore, based on our findings, from the mechanical point of view, by considering the amount of Young’s modulus, compliance, distensibility and viscoelastic behavior, the fabricated electrospun polyurethane with fiber diameter of 189.6 ± 52.89 nm is an optimum conduit with promising potential for substituting natural human vessels.

Spatial scaling in multiscale models: methods for coupling agent-based and finite-element models of wound healing

Multiscale models that couple agent-based modeling (ABM) and finite-element modeling (FEM) allow the dynamic simulation of tissue remodeling and wound healing, with mechanical environment influencing cellular behaviors even as tissue remodeling modifies mechanics. One of the challenges in coupling ABM to FEM is that these two domains typically employ grid or element sizes that differ by several orders of magnitude. Here, we develop and demonstrate an interpolation-based method for mapping between ABM and FEM domains of different resolutions that is suitable for linear and nonlinear FEM meshes and balances accuracy with computational demands. We then explore the effects of refining the FEM mesh and the ABM grid in the setting of a fully coupled model. ABM grid refinement studies showed unexpected effects of grid size whenever cells were present at a high enough density for crowding to affect proliferation and migration. In contrast to an FE-only model, refining the FE mesh in the coupled model increased strain differences between adjacent finite elements. Allowing strain-dependent feedback on collagen turnover magnified the effects of regional heterogeneity, producing highly nonlinear spatial and temporal responses. Our results suggest that the choice of both ABM grid and FEM mesh density in coupled models must be guided by experimental data and accompanied by careful grid and mesh refinement studies in the individual domains as well as the fully coupled model.

A fully coupled framework for in silico investigation of in-stent restenosis

Finite element analysis (FEA) can be implemented along with Agent-based model (ABM) to investigate the biomechanical and mechanobiological mechanisms of pathophysiological processes. However, traditional ABM-FEA approaches are often partially coupled and lack the feedback responses from biological analysis. To overcome this problem, a fully coupled ABM-FEA framework is developed in this paper by linking the macro-scale and cell-scale modules bi-directionally. Numerical studies of the in-stent restenosis process are conducted using the proposed approach and comparisons are made between the two types of frameworks. A reduction in lumen loss rate, which is possibly caused by the time-varying stresses, is observed in the fully coupled simulations. The re-endothelialisation process is also simulated under different frameworks and the simulation results show strong inhibition of endothelial cells to vascular restenosis. The proposed method is proved to be effective to explain the biomechanical-mechanobiological coupling characteristics of the restenosis problem and can be utilized for stent design and optimization.

Modelling multi-scale cell-tissue interaction of tissue-engineered muscle constructs

Expectation on engineered tissue substitute continues to grow, and for an effective development of a functional tissue and to control its quality, cellular mechanoresponse plays a key role. Although the mechanoresponse – in terms of cell–tissue interaction across scales – has been understood better in recent years, there are still technical limitations to quantitatively monitor the processes involved in the development of both native and engineered tissues. Computational (in silico) studies have been utilised to complement the experimental limitations and successfully applied to the prediction of tissue growth. We here review recent activities in the area of combined experimental and computational analyses of tissue growth, especially in the tissue engineering context, and highlight the advantages of such an approach for the future of the tissue engineering, using our own case study of predicting musculoskeletal tissue engineering construct development.

A versatile hybrid agent-based, particle and partial differential equations method to analyze vascular adaptation

Peripheral arterial occlusive disease is a chronic pathology affecting at least 8–12 million people in the USA, typically treated with a vein graft bypass or through the deployment of a stent in order to restore the physiological circulation. Failure of peripheral endovascular interventions occurs at the intersection of vascular biology, biomechanics, and clinical decision making. It is our hypothesis that the majority of endovascular treatment approaches share the same driving mechanisms and that a deep understanding of the adaptation process is pivotal in order to improve the current outcome of the procedure. The postsurgical adaptation of vein graft bypasses offers the perfect example of how the balance between intimal hyperplasia and wall remodeling determines the failure or the success of the intervention. Accordingly, this work presents a versatile computational model able to capture the feedback loop that describes the interaction between events at cellular/tissue level and mechano-environmental conditions. The work here presented is a generalization and an improvement of a previous work by our group of investigators, where an agent-based model uses a cellular automata principle on a fixed hexagonal grid to reproduce the leading events of the graft’s restenosis. The new hybrid model here presented allows a more realistic simulation both of the biological laws that drive the cellular behavior and of the active role of the membranes that separate the various layers of the vein. The novel feature is to use an immersed boundary implementation of a highly viscous flow to represent SMC motility and matrix reorganization in response to graft adaptation. Our implementation is modular, and this makes us able to choose the right compromise between closeness to the physiological reality and complexity of the model. The focus of this paper is to offer a new modular implementation that combines the best features of an agent-based model, continuum mechanics, and particle-tracking methods to cope with the multiscale nature of the adaptation phenomena. This hybrid method allows us to quickly test various hypotheses with a particular attention to cellular motility, a process that we demonstrated should be driven by mechanical homeostasis in order to maintain the right balance between cells and extracellular matrix in order to reproduce a distribution similar to histological experimental data from vein grafts.

Mechanosensitivity of Jagged-Notch signaling can induce a switch-type behavior in vascular homeostasis

Hemodynamic forces and Notch signaling are both known as key regulators of arterial remodeling and homeostasis. However, how these two factors integrate in vascular morphogenesis and homeostasis is unclear. Here, we combined experiments and modeling to evaluate the impact of the integration of mechanics and Notch signaling on vascular homeostasis. Vascular smooth muscle cells (VSMCs) were cyclically stretched on flexible membranes, as quantified via video tracking, demonstrating that the expression of Jagged1, Notch3, and target genes was down-regulated with strain. The data were incorporated in a computational framework of Notch signaling in the vascular wall, where the mechanical load was defined by the vascular geometry and blood pressure. Upon increasing wall thickness, the model predicted a switch-type behavior of the Notch signaling state with a steep transition of synthetic toward contractile VSMCs at a certain transition thickness. These thicknesses varied per investigated arterial location and were in good agreement with human anatomical data, thereby suggesting that the Notch response to hemodynamics plays an important role in the establishment of vascular homeostasis.

Mechanobiological model of arterial growth and remodeling

A coupled agent-based model (ABM) and finite element analysis (FEA) computational framework is developed to study the interplay of bio-chemo-mechanical factors in blood vessels and their role in maintaining homeostasis. The agent-based model implements the power of REPAST Simphony libraries and adapts its environment for biological simulations. Coupling a continuum-level model (FEA) to a cellular-level model (ABM) has enabled this computational framework to capture the response of blood vessels to increased or decreased levels of growth factors, proteases and other signaling molecules (on the micro scale) as well as altered blood pressure. Performance of the model is assessed by simulating porcine left anterior descending artery under normotensive conditions and transient increases in blood pressure and by analyzing sensitivity of the model to variations in the rule parameters of the ABM. These simulations proved that the model is stable under normotensive conditions and can recover from transient increases in blood pressure. Sensitivity studies revealed that the model is most sensitive to variations in the concentration of growth factors that affect cellular proliferation and regulate extracellular matrix composition (mainly collagen).

Computational Modeling of the Mechanical Performance of a Magnesium Stent Undergoing Uniform and Pitting Corrosion in a Remodeling Artery

Coronary stents made from degradable biomaterials such as magnesium alloy are an emerging technology in the treatment of coronary artery disease. Biodegradable stents provide mechanical support to the artery during the initial scaffolding period after which the artery will have remodeled. The subsequent resorption of the stent biomaterial by the body has potential to reduce the risk associated with long-term placement of these devices, such as in-stent restenosis, late stent thrombosis, and fatigue fracture. Computational modeling such as finite-element analysis has proven to be an extremely useful tool in the continued design and development of these medical devices. What is lacking in computational modeling literature is the representation of the active response of the arterial tissue in the weeks and months following stent implantation, i.e., neointimal remodeling. The phenomenon of neointimal remodeling is particularly interesting and significant in the case of biodegradable stents, when both stent degradation and neointimal remodeling can occur simultaneously, presenting the possibility of a mechanical interaction and transfer of load between the degrading stent and the remodeling artery. In this paper, a computational modeling framework is developed that combines magnesium alloy degradation and neointimal remodeling, which is capable of simulating both uniform (best case) and localized pitting (realistic) stent corrosion in a remodeling artery. The framework is used to evaluate the effects of the neointima on the mechanics of the stent, when the stent is undergoing uniform or pitting corrosion, and to assess the effects of the neointimal formation rate relative to the overall stent degradation rate (for both uniform and pitting conditions).

Patient-Specific, Multi-Scale Modeling of Neointimal Hyperplasia in Vein Grafts

Neointimal hyperplasia is amongst the major causes of failure of bypass grafts. The disease progression varies from patient to patient due to a range of different factors. In this paper, a mathematical model will be used to understand neointimal hyperplasia in individual patients, combining information from biological experiments and patient-specific data to analyze some aspects of the disease, particularly with regard to mechanical stimuli due to shear stresses on the vessel wall. By combining a biochemical model of cell growth and a patient-specific computational fluid dynamics analysis of blood flow in the lumen, remodeling of the blood vessel is studied by means of a novel computational framework. The framework was used to analyze two vein graft bypasses from one patient: a femoro-popliteal and a femoro-distal bypass. The remodeling of the vessel wall and analysis of the flow for each case was then compared to clinical data and discussed as a potential tool for a better understanding of the disease. Simulation results from this first computational approach showed an overall agreement on the locations of hyperplasia in these patients and demonstrated the potential of using new integrative modeling tools to understand disease progression.

A comparison of the material properties of natural and synthetic vascular walls

Characterization of the mechanical properties of native and synthetic vascular grafts is an essential task in the process of designing novel vascular constructs. The aim in this study was to compare the mechanical behavior of ovine left Subclavian artery with that of POSS-PCU (a commercial biomaterial which is currently under clinical investigation. ClinicalTrials.gov Identifier: NCT02301312). We used Delfino's strain energy potential within the framework of quasilinear viscoelasticity theory to capture the viscoelastic response of the considered materials. The material parameters of the quasilinear viscoelastic constitutive equation were determined through a combination of experimental and computational method. First, a uniaxial tensile testing device was used to perform a series of stress relaxation tests on ring samples. Then, the derived quasilinear viscoelastic models were implemented into finite element system. With the aid of mechanical experimentation and finite element simulation, the material parameters were obtained, modified and used for comparison of the mechanical properties of vascular walls. The results showed that the stiffness and the long term viscoelastic parameters of POSS-PCU may lead to different stress responses of the vascular walls. These two factors can be improved by modifications in manufacturing parameters of the synthetic vessel.

Integrated PK-PD and agent-based modeling in oncology

Mathematical modeling has become a valuable tool that strives to complement conventional biomedical research modalities in order to predict experimental outcome, generate new medical hypotheses, and optimize clinical therapies. Two specific approaches, pharmacokinetic-pharmacodynamic (PK-PD) modeling, and agent-based modeling (ABM), have been widely applied in cancer research. While they have made important contributions on their own (e.g., PK-PD in examining chemotherapy drug efficacy and resistance, and ABM in describing and predicting tumor growth and metastasis), only a few groups have started to combine both approaches together in an effort to gain more insights into the details of drug dynamics and the resulting impact on tumor growth. In this review, we focus our discussion on some of the most recent modeling studies building on a combined PK-PD and ABM approach that have generated experimentally testable hypotheses. Some future directions are also discussed.

From Histology and Imaging Data to Models for In-Stent Restenosis

The implantation of stents has been used to treat coronary artery stenosis for several decades. Although stenting is successful in restoring the vessel lumen and is a minimally invasive approach, the long-term outcomes are often compromised by in-stent restenosis (ISR). Animal models have provided insights into the pathophysiology of ISR and are widely used to evaluate candidate drug inhibitors of ISR. Such biological models allow the response of the vessel to stent implantation to be studied without the variation of lesion characteristics encountered in patient studies.

This paper describes the development of complementary in silico models employed to improve the understanding of the biological response to stenting using a porcine model of restenosis. This includes experimental quantification using microCT imaging and histology and the use of this data to establish numerical models of restenosis. Comparison of in silico results with histology is used to examine the relationship between spatial localization of fluid and solid mechanics stimuli immediately post-stenting. Multi-scale simulation methods are employed to study the evolution of neointimal growth over time and the variation in the extent of neointimal hyperplasia within the stented region. Interpretation of model results through direct comparison with the biological response contributes to more detailed understanding of the pathophysiology of ISR, and suggests the focus for follow-up studies.

In conclusion we outline the challenges which remain to both complete our understanding of the mechanisms responsible for restenosis and translate these models to applications in stent design and treatment planning at both population-based and patient-specific levels.

Deciphering mechanical regulation of chondrogenesis in fibrin-polyurethane composite scaffolds enriched with human mesenchymal stem cells: a dual computational and experimental approach

Fibrin-polyurethane composite scaffolds support chondrogenesis of human mesenchymal stem cells (hMSCs) derived from bone marrow and due to their robust mechanical properties allow mechanical loading in dynamic bioreactors, which has been shown to increase the chondrogenic differentiation of MSCs through the transforming growth factor beta pathway. The aim of this study was to use the finite element method, mechanical testing, and dynamic in vitro cell culture experiments on hMSC-enriched fibrin-polyurethane composite scaffolds to quantitatively decipher the mechanoregulation of chondrogenesis within these constructs. The study identified compressive principal strains as the key regulator of chondrogenesis in the constructs. Although dynamic uniaxial compression did not induce chondrogenesis, multiaxial loading by combined application of dynamic compression and interfacial shear induced significant chondrogenesis at locations where all the three principal strains were compressive and had a minimum magnitude of 10%. In contrast, no direct correlation was identified between the level of pore fluid velocity and chondrogenesis. Due to the high permeability of the constructs, the pore fluid pressures could not be increased sufficiently by mechanical loading, and instead, chondrogenesis was induced by triaxial compressive deformations of the matrix with a minimum magnitude of 10%. Thus, it can be concluded that dynamic triaxial compressive deformations of the matrix is sufficient to induce chondrogenesis in a threshold-dependent manner, even where the pore fluid pressure is negligible.

Multiscale computational models of complex biological systems

Integration of data across spatial, temporal, and functional scales is a primary focus of biomedical engineering efforts. The advent of powerful computing platforms, coupled with quantitative data from high-throughput experimental methodologies, has allowed multiscale modeling to expand as a means to more comprehensively investigate biological phenomena in experimentally relevant ways. This review aims to highlight recently published multiscale models of biological systems, using their successes to propose the best practices for future model development. We demonstrate that coupling continuous and discrete systems best captures biological information across spatial scales by selecting modeling techniques that are suited to the task. Further, we suggest how to leverage these multiscale models to gain insight into biological systems using quantitative biomedical engineering methods to analyze data in nonintuitive ways. These topics are discussed with a focus on the future of the field, current challenges encountered, and opportunities yet to be realized.

The effects of stenting on shear stress: relevance to endothelial injury and repair

Stent deployment following balloon angioplasty is used routinely to treat coronary artery disease. These interventions cause damage and loss of endothelial cells (EC), and thus promote in-stent thrombosis and restenosis. Injured arteries are repaired (intrinsically) by locally derived EC and by circulating endothelial progenitor cells which migrate and proliferate to re-populate denuded regions. However, re-endothelialization is not always complete and often dysfunctional. Moreover, the molecular and biomechanical mechanisms that control EC repair and function in stented segments are poorly understood. Here, we propose that stents modify endothelial repair processes, in part, by altering fluid shear stress, a mechanical force that influences EC migration and proliferation. A more detailed understanding of the biomechanical processes that control endothelial healing would provide a platform for the development of novel therapeutic approaches to minimize damage and promote vascular repair in stented arteries.