Mechanistic micro-structural theory of soft tissues growth and remodeling: tissues with unidirectional fibers

Review of the Brain's Behaviour after Injury and Disease for Its Application in an Agent-Based Model (ABM)

The brain is the most complex organ in the human body and, as such, its study entails great challenges (methodological, theoretical, etc.). Nonetheless, there is a remarkable amount of studies about the consequences of pathological conditions on its development and functioning. This bibliographic review aims to cover mostly findings related to changes in the physical distribution of neurons and their connections-the connectome-both structural and functional, as well as their modelling approaches. It does not intend to offer an extensive description of all conditions affecting the brain; rather, it presents the most common ones. Thus, here, we highlight the need for accurate brain modelling that can subsequently be used to understand brain function and be applied to diagnose, track, and simulate treatments for the most prevalent pathologies affecting the brain.

Benchtop characterization of the tricuspid valve leaflet pre-strains

The pre-strains of biological soft tissues are important when relating their in vitro and in vivo mechanical behaviors. In this study, we present the first-of-its-kind experimental characterization of the tricuspid valve leaflet pre-strains. We use 3D photogrammetry and the reproducing kernel method to calculate the pre-strains within the central 10×10 mm region of the tricuspid valve leaflets from n=8 porcine hearts. In agreement with previous pre-strain studies for heart valve leaflets, our results show that all the three tricuspid valve leaflets shrink after explant from the ex vivo heart. These calculated strains are leaflet-specific and the septal leaflet experiences the most compressive changes. Furthermore, the strains observed after dissection of the central 10×10 mm region of the leaflet are smaller than when the valve is explanted, suggesting that our computed pre-strains are mainly due to the release of in situ annulus and chordae connections. The leaflets are then mounted on a biaxial testing device and preconditioned using force-controlled equibiaxial loading. We show that the employed preconditioning protocol does not 100% restore the leaflet pre-strains as removed during tissue dissection, and future studies are warranted to explore alternative preconditioning methods. Finally, we compare the calculated biomechanically oriented metrics considering five stress-free reference configurations. Interestingly, the radial tissue stretches and material anisotropies are significantly smaller compared to the post-preconditioning configuration. Extensions of this work can further explore the role of this unique leaflet-specific leaflet pre-strains on in vivo valve behavior via high-fidelity in-silico models.

Remodeling of extracellular matrix in the urinary bladder of paraplegic rats results in increased compliance and delayed fiber recruitment 16 weeks after spinal cord injury

The ability of the urinary bladder to maintain low intravesical pressures while storing urine is key in ensuring proper organ function and highlights the key role that tissue mechanics plays in the lower urinary tract. Loss of supraspinal neuronal connections to the bladder after spinal cord injury can lead to remodeling of the structure of the bladder wall, which may alter its mechanical characteristics. In this study, we investigate if the morphology and mechanical properties of the bladder extracellular matrix are altered in rats 16 weeks after spinal cord injury as compared to animals who underwent sham surgery. We measured and quantified the changes in bladder geometry and mechanical behavior using histological analysis, tensile testing, and constitutive modeling. Our results suggest bladder compliance is increased in paraplegic animals 16 weeks post-injury. Furthermore, constitutive modeling showed that increased distensibility was driven by an increase in collagen fiber waviness, which altered the distribution of fiber recruitment during loading. STATEMENT OF SIGNIFICANCE: The ability of the urinary bladder to store urine under low pressure is key in ensuring proper organ function. This highlights the important role that mechanics plays in the lower urinary tract. Loss of control of neurologic connection to the bladder from spinal cord injury can lead to changes of the structure of the bladder wall, resulting in altered mechanical characteristics. We found that the bladder wall's microstructure in rats 16 weeks after spinal cord injury is more compliant than in healthy animals. This is significant since it is the longest time post-injury analyzed, to date. Understanding the extreme remodeling capabilities of the bladder in pathological conditions is key to inform new possible therapies.

A Direct Comparison of Node and Element-Based Finite Element Modeling Approaches to Study Tissue Growth

Finite element analysis is a useful tool to model growth of biological tissues and predict how growth can be impacted by stimuli. Previous work has simulated growth using node-based or element-based approaches, and this implementation choice may influence predicted growth, irrespective of the applied growth model. This study directly compared node-based and element-based approaches to understand the isolated impact of implementation method on growth predictions by simulating growth of a bone rudiment geometry, and determined what conditions produce similar results between the approaches. We used a previously reported node-based approach implemented via thermal expansion and an element-based approach implemented via osmotic swelling, and we derived a mathematical relationship to relate the growth resulting from these approaches. We found that material properties (modulus) affected growth in the element-based approach, with growth completely restricted for high modulus values relative to the growth stimulus, and no restriction for low modulus values. The node-based approach was unaffected by modulus. Node- and element-based approaches matched marginally better when the conversion coefficient to relate the approaches was optimized based on the results of initial simulations, rather than using the theoretically predicted conversion coefficient (median difference in node position 0.042 cm versus 0.052 cm, respectively). In summary, we illustrate here the importance of the choice of implementation approach for modeling growth, provide a framework for converting models between implementation approaches, and highlight important considerations for comparing results in prior work and developing new models of tissue growth.

Computational modeling of cardiac growth and remodeling in pressure overloaded hearts-Linking microstructure to organ phenotype

Cardiac growth and remodeling (G&R) refers to structural changes in myocardial tissue in response to chronic alterations in loading conditions. One such condition is pressure overload where elevated wall stresses stimulate the growth in cardiomyocyte thickness, associated with a phenotype of concentric hypertrophy at the organ scale, and promote fibrosis. The initial hypertrophic response can be considered adaptive and beneficial by favoring myocyte survival, but over time if pressure overload conditions persist, maladaptive mechanisms favoring cell death and fibrosis start to dominate, ultimately mediating the transition towards an overt heart failure phenotype. The underlying mechanisms linking biological factors at the myocyte level to biomechanical factors at the systemic and organ level remain poorly understood. Computational models of G&R show high promise as a unique framework for providing a quantitative link between myocardial stresses and strains at the organ scale to biological regulatory processes at the cellular level which govern the hypertrophic response. However, microstructurally motivated, rigorously validated computational models of G&R are still in their infancy. This article provides an overview of the current state-of-the-art of computational models to study cardiac G&R. The microstructure and mechanosensing/mechanotransduction within cells of the myocardium is discussed and quantitative data from previous experimental and clinical studies is summarized. We conclude with a discussion of major challenges and possible directions of future research that can advance the current state of cardiac G&R computational modeling. STATEMENT OF SIGNIFICANCE: The mechanistic links between organ-scale biomechanics and biological factors at the cellular size scale remain poorly understood as these are largely elusive to investigations using experimental methodology alone. Computational G&R models show high promise to establish quantitative links which allow more mechanistic insight into adaptation mechanisms and may be used as a tool for stratifying the state and predict the progression of disease in the clinic. This review provides a comprehensive overview of research in this domain including a summary of experimental data. Thus, this study may serve as a basis for the further development of more advanced G&R models which are suitable for making clinical predictions on disease progression or for testing hypotheses on pathogenic mechanisms using in-silico models.

Stress-Swelling Finite Element Modeling of Cervical Response With Homeostatic Collagen Fiber Distributions

During pregnancy, the cervix experiences significant mechanical property change due to tissue swelling, and to ongoing changes in the collagen content. In this paper, we model how these two effects contribute to cervical deformation as the pressure load on top of the cervix increases. The cervix and its surrounding supporting ligaments are taken into consideration in the resulting mechanical analysis. The cervix itself is treated as a multilayered tube-like structure, with layer-specific collagen orientation. The cervical tissue in each layer is treated in terms of a collagen constituent that remodels with time within a ground substance matrix that experiences swelling. The load and swelling are taken to change sufficiently slowly so that the collagen properties at any instant can be regarded as being in a state of homeostasis. Among other things, the simulations show how the luminal cross-sectional area varies along its length as a function of pressure and swelling. In general, an increase in pressure causes an overall shortening of the lumen while an increase in swelling has the opposite effect.

Evaluation of microstructurally motivated constitutive models to describe age-dependent tendon healing

Tendon injuries are common to all ages. Injured tendons typically do not recover full functionality. The amount and organization of tendon constituents dictate their mechanical properties. The impact of changes in these constituents during (patho)physiologic processes (e.g., aging and healing) are not fully understood. Toward this end, microstructurally motivated strain energy functions (SEFs) offer insight into underlying mechanisms of age-dependent healing. Several SEFs have been adapted for tendon; however, most are phenomenological. Therefore, the aims of this study are: (1) evaluate the descriptive capability of SEFs in age-dependent murine patellar tendon healing and (2) identify a SEF for implementation in a growth and remodeling (G&R) model. To accomplish these aims, models were fitted to patellar tendon tensile data from multiple age groups and post-injury timepoints. Model sensitivity to parameters and the determinability of the parameters were assessed. A two-way analysis of variance was used to identify changes in parameters and the feasibility of implementing each model into a G&R model is discussed. The evaluated SEFs exhibited adequate descriptive capability. Parameter determinability and sensitivity analysis, however, highlighted the need for additional data to inform and validate the models to increase physiologic relevance and enable G&R model formulation to determine underlying mechanisms of age-dependent healing. This work, as a first, evaluated changes in tendon mechanical properties both as functions of age and injury in an age-dependent manner using microstructurally motivated models, highlights inherent dependencies between parameters of widely used hyperelastic models, and identified unique post-injury behavior by the aging group compared to the mature and aged groups.

A computational algorithm to simulate disorganization of collagen network in injured articular cartilage

Cartilage defects are a known risk factor for osteoarthritis. Estimation of structural changes in these defects could help us to identify high risk defects and thus to identify patients that are susceptible for the onset and progression of osteoarthritis. Here, we present an algorithm combined with computational modeling to simulate the disorganization of collagen fibril network in injured cartilage. Several potential triggers for collagen disorganization were tested in the algorithm following the assumption that disorganization is dependent on the mechanical stimulus of the tissue. We found that tensile tissue stimulus alone was unable to preserve collagen architecture in intact cartilage as collagen network reoriented throughout the cartilage thickness. However, when collagen reorientation was based on both tensile tissue stimulus and tensile collagen fibril strains or stresses, the collagen network architecture was preserved in intact cartilage. Using the same approach, substantial collagen reorientation was predicted locally near the cartilage defect and particularly at the cartilage-bone interface. The developed algorithm was able to predict similar structural findings reported in the literature that are associated with experimentally observed remodeling in articular cartilage. The proposed algorithm, if further validated, could help to predict structural changes in articular cartilage following post-traumatic injury potentially advancing to impaired cartilage function.

A homeostatic-driven turnover remodelling constitutive model for healing in soft tissues

Remodelling of soft biological tissue is characterized by interacting biochemical and biomechanical events, which change the tissue's microstructure, and, consequently, its macroscopic mechanical properties. Remodelling is a well-defined stage of the healing process, and aims at recovering or repairing the injured extracellular matrix. Like other physiological processes, remodelling is thought to be driven by homeostasis, i.e. it tends to re-establish the properties of the uninjured tissue. However, homeostasis may never be reached, such that remodelling may also appear as a continuous pathological transformation of diseased tissues during aneurysm expansion, for example. A simple constitutive model for soft biological tissues that regards remodelling as homeostatic-driven turnover is developed. Specifically, the recoverable effective tissue damage, whose rate is the sum of a mechanical damage rate and a healing rate, serves as a scalar internal thermodynamic variable. In order to integrate the biochemical and biomechanical aspects of remodelling, the healing rate is, on the one hand, driven by mechanical stimuli, but, on the other hand, subjected to simple metabolic constraints. The proposed model is formulated in accordance with continuum damage mechanics within an open-system thermodynamics framework. The numerical implementation in an in-house finite-element code is described, particularized for Ogden hyperelasticity. Numerical examples illustrate the basic constitutive characteristics of the model and demonstrate its potential in representing aspects of remodelling of soft tissues. Simulation results are verified for their plausibility, but also validated against reported experimental data.

Large strain stimulation promotes extracellular matrix production and stiffness in an elastomeric scaffold model

Mechanical conditioning of engineered tissue constructs is widely recognized as one of the most relevant methods to enhance tissue accretion and microstructure, leading to improved mechanical behaviors. The understanding of the underlying mechanisms remains rather limited, restricting the development of in silico models of these phenomena, and the translation of engineered tissues into clinical application. In the present study, we examined the role of large strip-biaxial strains (up to 50%) on ECM synthesis by vascular smooth muscle cells (VSMCs) micro-integrated into electrospun polyester urethane urea (PEUU) constructs over the course of 3 weeks. Experimental results indicated that VSMC biosynthetic behavior was quite sensitive to tissue strain maximum level, and that collagen was the primary ECM component synthesized. Moreover, we found that while a 30% peak strain level achieved maximum ECM synthesis rate, further increases in strain level lead to a reduction in ECM biosynthesis. Subsequent mechanical analysis of the formed collagen fiber network was performed by removing the scaffold mechanical responses using a strain-energy based approach, showing that the denovo collagen also demonstrated mechanical behaviors substantially better than previously obtained with small strain training and comparable to mature collagenous tissues. We conclude that the application of large deformations can play a critical role not only in the quantity of ECM synthesis (i.e. the rate of mass production), but also on the modulation of the stiffness of the newly formed ECM constituents. The improved understanding of the process of growth and development of ECM in these mechano-sensitive cell-scaffold systems will lead to more rational design and manufacturing of engineered tissues operating under highly demanding mechanical environments.