Poroelastic Characterization and Modeling of Subcutaneous Tissue Under Confined Compression.

Subcutaneous tissue mechanics are important for drug delivery. Yet, even though this material is poroelastic, its mechanical characterization has focused on its hyperelastic response. Moreover, advancement in subcutaneous drug delivery requires effective tissue mimics such as hydrogels for which similar gaps of poroelastic data exist. Porcine subcutaneous samples and gelatin hydrogels were tested under confined compression at physiological conditions and strain rates of 0.01%/s in 5% strain steps with 2600 s of stress relaxation between loading steps. Force-time data were used in an inverse finite element approach to obtain material parameters. Tissues and gels were modeled as porous neo-Hookean materials with properties specified via shear modulus, effective solid volume fraction, initial hydraulic permeability, permeability exponent, and normalized viscous relaxation moduli. The constitutive model was implemented into an isogeometric analysis (IGA) framework to study subcutaneous injection. Subcutaneous tissue exhibited an initial spike in stress due to compression of the solid and fluid pressure buildup, with rapid relaxation explained by fluid drainage, and longer time-scale relaxation explained by viscous dissipation. The inferred parameters aligned with the ranges reported in the literature. Hydraulic permeability, the most important parameter for drug delivery, was in the range k 0 ∈ [ 0.142 , 0.203 ] mm 4 /(N s). With these parameters, IGA simulations showed peak stresses due to a 1-mL injection to reach 48.8 kPa at the site of injection, decaying after drug volume disperses into the tissue. The poro-hyper-viscoelastic neo-Hookean model captures the confined compression response of subcutaneous tissue and gelatin hydrogels. IGA implementation enables predictive simulations of drug delivery.

Acellular Dermal Matrix Cover Improves Skin Growth during Tissue Expansion by Affecting Distribution of Mechanical Forces.

BACKGROUND: Biological cover over tissue expander prostheses has been introduced to provide soft-tissue support for tissue expanders during breast reconstruction. However, its impact on mechanically induced skin growth remains unknown. This study investigates the hypothesis that covering the tissue expander with acellular dermal matrix (ADM) affects mechanotransduction without compromising the efficacy of tissue expansion. METHODS: Tissue expansion, with and without use of ADM, was performed on a porcine model. The tissue expanders were inflated twice with 45 mL of saline, and the full-thickness skin biopsy specimens were harvested from expanded and control unexpanded skin 1 week and 8 weeks after the final inflation. Histologic evaluation, immunohistochemistry staining, and gene expression analysis were performed. Skin growth and total deformation were evaluated using isogeometric analysis. RESULTS: The authors' results demonstrate that use of ADM as a biological cover during tissue expansion does not impede mechanotransduction that leads to skin growth and blood vessel formation. Isogeometric analysis revealed similar total deformation and growth of expanded skin with and without a biological cover, confirming that its use does not inhibit mechanically induced skin growth. In addition, the authors found that use of an ADM cover results in more uniform distribution of mechanical forces applied by the tissue expander. CONCLUSIONS: These results suggest that ADM improves mechanically induced skin growth during tissue expansion by facilitating a more uniform distribution of mechanical forces applied by the tissue expander. Therefore, the use of a biological cover has potential to improve outcomes in tissue expansion-based reconstruction.

The role of interface geometry and appendages on the mesoscale mechanics of the skin.

The skin is the largest organ in the human body and serves various functions, including mechanical protection and mechanosensation. Yet, even though skin's biomechanics are attributed to two main layers-epidermis and dermis-computational models have often treated this tissue as a thin homogeneous material or, when considering multiple layers, have ignored the most prominent heterogeneities of skin seen at the mesoscale. Here, we create finite element models of representative volume elements (RVEs) of skin, including the three-dimensional variation of the interface between the epidermis and dermis as well as considering the presence of hair follicles. The sinusoidal interface, which approximates the anatomical features known as Rete ridges, does not affect the homogenized mechanical response of the RVE but contributes to stress concentration, particularly at the valleys of the Rete ridges. The stress profile is three-dimensional due to the skin's anisotropy, leading to high-stress bands connecting the valleys of the Rete ridges through one type of saddle point. The peaks of the Rete ridges and the other class of saddle points of the sinusoidal surface form a second set of low-stress bands under equi-biaxial loading. Another prominent feature of the heterogeneous stress pattern is a switch in the stress jump across the interface, which becomes lower with respect to the flat interface at increasing deformations. These features are seen in both tension and shear loading. The RVE with the hair follicle showed strains concentrating at the epidermis adjacent to the hair follicle, the epithelial tissue surrounding the hair right below the epidermis, and the bulb or base region of the hair follicle. The regions of strain concentration near the hair follicle in equi-biaxial and shear loading align with the presence of distinct mechanoreceptors in the skin, except for the bulb or base region. This study highlights the importance of skin heterogeneities, particularly its potential mechanophysiological role in the sense of touch and the prevention of skin delamination.

The Role of Interface Geometry and Appendages on the Mesoscale Mechanics of the Skin.

The skin is the largest organ in the human body and serves various functions, including mechanical protection and mechanosensation. Yet, even though skin's biomechanics are attributed to two main layers - epidermis and dermis-computational models have often treated this tissue as a thin homogeneous material or, when considering multiple layers, have ignored the most prominent heterogeneities of skin seen at the mesoscale. Here we create finite element models of representative volume elements (RVEs) of skin, including the three-dimensional variation of the interface between the epidermis and dermis as well as considering the presence of hair follicles. The sinusoidal interface, which approximates the anatomical features known as Rete ridges, does not affect the homogenized mechanical response of the RVE but contributes to stress concentration, particularly at the valleys of the Rete ridges. The stress profile is three-dimensional due to the skin's anisotropy, leading to high-stress bands connecting the valleys of the Rete ridges through one type of saddle point. The peaks of the Rete ridges and the other class of saddle points of the sinusoidal surface form a second set of low-stress bands under equi-biaxial loading. Another prominent feature of the heterogeneous stress pattern is a switch in the stress jump across the interface, which becomes lower with respect to the flat interface at increasing deformations. These features are seen in both tension and shear loading. The RVE with the hair follicle showed strains concentrating at the epidermis adjacent to the hair follicle, the epithelial tissue surrounding the hair right below the epidermis, and the bulb or base region of the hair follicle. The regions of strain concentration near the hair follicle in equi-biaxial and shear loading align with the presence of distinct mechanoreceptors in the skin, except for the bulb or base region. This study highlights the importance of skin heterogeneities, particularly its potential mechanophysiological role in the sense of touch and the prevention of skin delamination.

Biological Cover Mitigates Disruption of the Dermal Structure in Mechanically Expanded Skin in a Porcine Model.

Tissue expansion is an integral procedure of the vast majority of breast reconstruction and has a significant impact on the final clinical outcomes. Therefore, technological advances leading to a fewer number of unfavorable outcomes and a decrease in complication rates are imperative. In this study, using a porcine model, we investigated an effect of acellular dermal matrix (ADM) used as a tissue expander cover on the dermal changes induced by mechanical forces during tissue expansion. After 14 days of expansion, skin samples were collected from one animal, while the second animal underwent radiation, and tissue was collected 8 weeks later. Tissue expanded without the use of ADM and unexpanded skin served as the controls. Collected skin biopsies were used for histological and immunohistochemical evaluation, and for gene expression analysis. We revealed that the biological cover incorporation into host tissue is facilitated by macrophages without inducing a broad inflammatory response. The utilization of ADM mitigated disruption in the dermal structure, excessive collagen deposition, and capsule formation in non-irradiated expanded skin. The protective effect was not fully maintained in irradiated skin. These results demonstrate that tissue expansion might be improved by using the tissue expander cover.

Anisotropic damage model for collagenous tissues and its application to model fracture and needle insertion mechanics.

The analysis of tissue mechanics in biomedical applications demands nonlinear constitutive models able to capture the energy dissipation mechanisms, such as damage, that occur during tissue deformation. Furthermore, implementation of sophisticated material models in finite element models is essential to improve medical devices and diagnostic tools. Building on previous work toward microstructure-driven models of collagenous tissue, here we show a constitutive model based on fiber orientation and waviness distributions for skin that captures not only the anisotropic strain-stiffening response of this and other collagen-based tissues, but, additionally, accounts for tissue damage directly as a function of changes in the microstructure, in particular changes in the fiber waviness distribution. The implementation of this nonlinear constitutive model as a user subroutine in the popular finite element package Abaqus enables large-scale finite element simulations for biomedical applications. We showcase the performance of the model in fracture simulations during pure shear tests, as well as simulations of needle insertion into skin relevant to auto-injector design.

Data-driven Modeling of the Mechanical Behavior of Anisotropic Soft Biological Tissue.

Closed-form constitutive models are the standard to describe soft tissue mechanical behavior. However, inherent pitfalls of an explicit functional form include poor fits to the data, non-uniqueness of fit, and sensitivity to parameters. Here we design deep neural networks (DNN) that satisfy desirable physics constraints in order to replace expert models of tissue mechanics. To guarantee stress-objectivity, the DNN takes strain (pseudo)-invariants as inputs, and outputs the strain energy and its derivatives. Polyconvexity of strain energy is enforced through the loss function. Direct prediction of both energy and derivative functions enables the computation of the elasticity tensor needed for a finite element implementation. We showcase the DNN ability to learn the anisotropic mechanical behavior of porcine and murine skin from biaxial test data. A multi-fidelity scheme that combines high fidelity experimental data with a low fidelity analytical approximation yields the best performance. Finite element simulations of tissue expansion with the DNN model illustrate the potential of this method to impact medical device design for skin therapeutics. We expect that the open data and software from this work will broaden the use of data-driven constitutive models of tissue mechanics.

Data-driven Tissue Mechanics with Polyconvex Neural Ordinary Differential Equations.

Data-driven methods are becoming an essential part of computational mechanics due to their advantages over traditional material modeling. Deep neural networks are able to learn complex material response without the constraints of closed-form models. However, data-driven approaches do not a priori satisfy physics-based mathematical requirements such as polyconvexity, a condition needed for the existence of minimizers for boundary value problems in elasticity. In this study, we use a recent class of neural networks, neural ordinary differential equations (N-ODEs), to develop data-driven material models that automatically satisfy polyconvexity of the strain energy. We take advantage of the properties of ordinary differential equations to create monotonic functions that approximate the derivatives of the strain energy with respect to deformation invariants. The monotonicity of the derivatives guarantees the convexity of the energy. The N-ODE material model is able to capture synthetic data generated from closed-form material models, and it outperforms conventional models when tested against experimental data on skin, a highly nonlinear and anisotropic material. We also showcase the use of the N-ODE material model in finite element simulations of reconstructive surgery. The framework is general and can be used to model a large class of materials, especially biological soft tissues. We therefore expect our methodology to further enable data-driven methods in computational mechanics.

Bayesian calibration of a computational model of tissue expansion based on a porcine animal model.

Tissue expansion is a technique used clinically to grow skin in situ to correct large defects. Despite its enormous potential, lack of fundamental knowledge of skin adaptation to mechanical cues, and lack of predictive computational models limit the broader adoption and efficacy of tissue expansion. In our previous work, we introduced a finite element model of tissue expansion that predicted key patterns of strain and growth which were then confirmed by our porcine animal model. Here we use the data from a new set of experiments to calibrate the computational model within a Bayesian framework. Four 10×10cm2 patches were tattooed in the dorsal skin of four 12 weeks-old minipigs and a total of six patches underwent successful tissue expander placement and inflation to 60cc for expansion times ranging from 1 h to 7 days. Six patches that did not have expanders implanted served as controls for the analysis. We find that growth can be explained based on the elastic deformation. The predicted area growth rate is k∈[0.02,0.08] [h-1]. Growth is anisotropic and reflects the anisotropic mechanical behavior of porcine dorsal skin. The rostral-caudal axis shows greater deformation than the transverse axis, and the time scale of growth in the rostral-caudal direction is given by rate parameters k1∈[0.04,0.1] [h-1] compared to k2∈[0.01,0.05] [h-1] in the transverse direction. Moreover, the calibration results underscore the high variability in biological systems, and the need to create probabilistic computational models to predict tissue adaptation in realistic settings. STATEMENT OF SIGNIFICANCE: Tissue expansion is a widely used technique in reconstructive surgery because it triggers growth of skin for the correction of large skin lesions and for breast reconstruction after mastectomy. Despite of its potential, complications and undesired outcomes persist due to our incomplete understanding of skin mechanobiology. Here we quantify the deformation and growth fields induced by an expander over 7 days in a porcine animal model and use these data to calibrate a computational model of skin growth using finite element simulations and a Bayesian framework. The calibrated model is a leap forward in our understanding skin growth, we now have quantitative understanding of this process: area growth is anisotropic and it is proportional to stretch with a characteristic rate constant of k∈[0.02,0.08] [h-1].

Changes in the three-dimensional microscale topography of human skin with aging impact its mechanical and tribological behavior.

Human skin enables interaction with diverse materials every day and at all times. The ability to grasp objects, feel textures, and perceive the environment depends on the mechanical behavior, complex structure, and microscale topography of human skin. At the same time, abrasive interactions, such as sometimes occur with prostheses or textiles, can damage the skin and impair its function. Previous theoretical and computational efforts have shown that skin's surface topography or microrelief is crucial for its tribological behavior. However, current understanding is limited to adult surface profiles and simplified two-dimensional simulations. Yet, the skin has a rich set of features in three dimensions, and the geometry of skin is known to change with aging. Here we create a numerical model of a dynamic indentation test to elucidate the effect of changes in microscale topography with aging on the skin's response under indentation and sliding contact with a spherical indenter. We create three different microrelief geometries representative of different ages based on experimental reports from the literature. We perform the indentation and sliding steps, and calculate the normal and tangential forces on the indenter as it moves in three distinct directions based on the characteristic skin lines. The model also evaluates the effect of varying the material parameters. Our results show that the microscale topography of the skin in three dimensions, together with the mechanical behavior of the skin layers, lead to distinctive trends on the stress and strain distribution. The major finding is the increasing role of anisotropy which emerges from the geometric changes seen with aging.

Modeling Tissue Expansion with Isogeometric Analysis: Skin Growth and Tissue Level Changes in the Porcine Model.

BACKGROUND: Tissue expansion relies on the ability of skin to grow in response to sustained mechanical strain. This study focuses on correlation of cellular and histologic changes with skin growth and deformation during tissue expansion. METHODS: Tissue expanders were placed underneath the skin of five Yucatan minipigs and inflated with one fill of 60 cc of saline 1 hour, 24 hours, 3 days, and 7 days before the animals were killed, or two fills of either 30 cc or 60 cc at 10 and 3 days or 14 and 7 days before the animals were killed. Skin biopsy specimens and three-dimensional photographs were used to calculate skin growth and stretch according to the authors' novel finite element analysis model. RESULTS: The mitotic index of keratinocytes in the basal layer increased 1 hour after stimulus was applied (4 percent) (p = 0.022), peaked at approximately day 3 (26 percent) (p < 0.0001), and tapered by day 7 (12.5 percent) (p = 0.012) after tissue expansion. The authors demonstrated that it is the volume per fill rather than the total volume in the expander that scales the magnitude of response. Lastly, the authors demonstrated that the ratio of deformation attributable to growth versus stretch (Fgrowth/Fstretch) after 60 cc of tissue expansion fill was 1.03 at 1 hour, 0.82 at 1 day, 0.85 at day 3, and 0.95 at 7 days. CONCLUSIONS: Peak cell proliferation occurred 3 days after tissue expansion fill and is scaled in response to stimulus magnitude. The growth component of deformation equilibrates to the stretch component at day 7, as cell proliferation has started to translate to skin growth.

The regional-dependent biaxial behavior of young and aged mouse skin: A detailed histomechanical characterization, residual strain analysis, and constitutive model.

Skin fulfills several vital functions, many of which are dependent on its mechanical properties. Therefore, as mice have become an invaluable model for skin research, determining murine skin's mechanical properties is important. Specifically, skin's mechanical properties are important for functional tests as well as for prognostic and diagnostic purposes. Additionally, computational simulations of skin behavior are becoming commonplace, rendering accurate models of murine skin's constitutive behavior necessary. To date, our knowledge of mouse skin mechanics shows significant gaps. For example, there are no comprehensive reports correlating skin's mechanical properties with region, age, and direction. Moreover, mouse skin's residual strain behavior has not been reported on. In our current work, we set out to fill these gaps. Based on histology, 2-photon microscopy, and planar biaxial testing, while accurately tracking various reference configurations, we report on differences in gross structure, microstructural organization, and constitutive response of skin, and cast those properties into a versatile Fung-type hyperelastic constitutive law for three reference configurations. Our data is the most comprehensive report contrasting the mechanical properties of young (12 weeks) and aged (52 weeks) mouse skin and will, thus, be valuable to basic science as control data, and provide accurate constitutive laws for mouse skin modeling. STATEMENT OF SIGNIFICANCE: Our findings are significant as they fill several gaps in our understanding of mouse skin mechanics. This is particularly important as mouse skin is becoming a frequent and critical model of human skin for cosmetic and medical science. Specifically, we quantified how mechanical properties of mice skin vary with age, with location, and with direction. Additionally, we cast our findings into constitutive models that can be used by others for predictive computer simulations of skin behavior.

Linking microvascular collapse to tissue hypoxia in a multiscale model of pressure ulcer initiation.

Pressure ulcers are devastating injuries that disproportionately affect the older adult population. The initiating factor of pressure ulcers is local ischemia, or lack of perfusion at the microvascular level, following tissue compression against bony prominences. In turn, lack of blood flow leads to a drop in oxygen concentration, i.e, hypoxia, that ultimately leads to cell death, tissue necrosis, and disruption of tissue continuity. Despite our qualitative understanding of the initiating mechanisms of pressure ulcers, we are lacking quantitative knowledge of the relationship between applied pressure, skin mechanical properties as well as structure, and tissue hypoxia. This gap in our understanding is, at least in part, due to the limitations of current imaging technologies that cannot simultaneously image the microvascular architecture, while quantifying tissue deformation. We overcome this limitation in our work by combining realistic microvascular geometries with appropriate mechanical constitutive models into a microscale finite element model of the skin. By solving boundary value problems on a representative volume element via the finite element method, we can predict blood volume fractions in response to physiological skin loading conditions (i.e., shear and compression). We then use blood volume fraction as a homogenized variable to couple tissue-level skin mechanics to an oxygen diffusion model. With our model, we find that moderate levels of pressure applied to the outer skin surface lead to oxygen concentration contours indicative of tissue hypoxia. For instance, we show that applying a pressure of 60 kPa at the skin surface leads to a decrease in oxygen partial pressure from a physiological value of 65 mmHg to a hypoxic level of 31 mmHg. Additionally, we explore the sensitivity of local oxygen concentration to skin thickness and tissue stiffness, two age-related skin parameters. We find that, for a given pressure, oxygen concentration decreases with decreasing skin thickness and skin stiffness. Future work will include rigorous calibration and validation of this model, which may render our work an important tool toward developing better prevention and treatment tools for pressure ulcers specifically targeted toward the older adult patient population.