Computational and experimental characterization of skin mechanics: identifying current challenges and future directions

Quantification of age-related changes in the structure and mechanical function of skin with multiscale imaging

The mechanical properties of skin change during aging but the relationships between structure and mechanical function remain poorly understood. Previous work has shown that young skin exhibits a substantial decrease in tissue volume, a large macro-scale Poisson's ratio, and an increase in micro-scale collagen fiber alignment during mechanical stretch. In this study, label-free multiphoton microscopy was used to quantify how the microstructure and fiber kinematics of aged mouse skin affect its mechanical function. In an unloaded state, aged skin was found to have less collagen alignment and more non-enzymatic collagen fiber crosslinks. Skin samples were then loaded in uniaxial tension and aged skin exhibited a lower mechanical stiffness compared to young skin. Aged tissue also demonstrated less volume reduction and a lower macro-scale Poisson's ratio at 10% uniaxial strain, but not at 20% strain. The magnitude of 3D fiber realignment in the direction of loading was not different between age groups, and the amount of realignment in young and aged skin was less than expected based on theoretical fiber kinematics affine to the local deformation. These findings provide key insights on how the collagen fiber microstructure changes with age, and how those changes affect the mechanical function of skin, findings which may help guide wound healing or anti-aging treatments.

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.

Exploring uncertainty in hyper-viscoelastic properties of scalp skin through patient-specific finite element models for reconstructive surgery

Understanding skin responses to external forces is crucial for post-cutaneous flap wound healing. However, the in vivo viscoelastic behavior of scalp skin remains poorly understood. Personalized virtual surgery simulations offer a way to study tissue responses in relevant 3D geometries. Yet, anticipating wound risk remains challenging due to limited data on skin viscoelasticity, which hinders our ability to determine the interplay between wound size and stress levels. To bridge this gap, we reexamine three clinical cases involving scalp reconstruction using patient-specific geometric models and employ uncertainty quantification through a Monte Carlo simulation approach to study the effect of skin viscoelasticity on the final stress levels from reconstructive surgery. Utilizing the generalized Maxwell model via the Prony series, we can parameterize and efficiently sample a realistic range of viscoelastic response and thus shed light on the influence of viscoelastic material uncertainty in surgical scenarios. Our analysis identifies regions at risk of wound complications based on reported threshold stress values from the literature and highlights the significance of focusing on long-term responses rather than short-term ones.

Benchmarking physics-informed frameworks for data-driven hyperelasticity

Data-driven methods have changed the way we understand and model materials. However, while providing unmatched flexibility, these methods have limitations such as reduced capacity to extrapolate, overfitting, and violation of physics constraints. Recently, frameworks that automatically satisfy these requirements have been proposed. Here we review, extend, and compare three promising data-driven methods: Constitutive Artificial Neural Networks (CANN), Input Convex Neural Networks (ICNN), and Neural Ordinary Differential Equations (NODE). Our formulation expands the strain energy potentials in terms of sums of convex non-decreasing functions of invariants and linear combinations of these. The expansion of the energy is shared across all three methods and guarantees the automatic satisfaction of objectivity, material symmetries, and polyconvexity, essential within the context of hyperelasticity. To benchmark the methods, we train them against rubber and skin stress-strain data. All three approaches capture the data almost perfectly, without overfitting, and have some capacity to extrapolate. This is in contrast to unconstrained neural networks which fail to make physically meaningful predictions outside the training range. Interestingly, the methods find different energy functions even though the prediction on the stress data is nearly identical. The most notable differences are observed in the second derivatives, which could impact performance of numerical solvers. On the rich data used in these benchmarks, the models show the anticipated trade-off between number of parameters and accuracy. Overall, CANN, ICNN and NODE retain the flexibility and accuracy of other data-driven methods without compromising on the physics. These methods are ideal options to model arbitrary hyperelastic material behavior.

Characterisation of superficial corneocyte properties over category I pressure ulcers: Insights into topographical and maturation changes

BACKGROUND

Pressure ulcers (PUs) are chronic wounds that are detrimental to the quality of life of patients. Despite advances in monitoring skin changes, the structure and function of skin cells over the site of pressure ulcers are not fully understood.

OBJECTIVE

The present study aims to evaluate local changes in the properties of superficial corneocytes in category 1 PU sites sampled from a cohort of hospitalised patients.

METHODS

Cells were collected from a PU-compromised site and an adjacent control area and their topographical, maturation and mechanical properties were analysed.

RESULTS

Corneocytes at the PU-compromised site were characterised by higher levels of immature cornified envelopes (p < 0.001) and greater amounts of desmoglein-1 (corneodesmosomal protein) (p < 0.001) compared to the adjacent control area. The cells at the control site presented the typical ridges-and-valleys topographical features of sacrum corneocytes. By contrast, the PU cells presented circular nano-objects at the cell surface, and, for some patients, the cell topography was deformed. CEs at the PU site were also smaller than at the control site. Although differences were not observed in the mechanical properties of the cells, those of the elderly patients were much softer compared with young subjects.

CONCLUSION

This is the first study investigating the changes in corneocyte properties in category I pressure ulcers. Superficial cells at the PU sites showed altered topographical and maturation characteristics. Further studies are required to elucidate if these changes are a consequence of early loss of skin integrity or a result of mechanical and microclimate insults to the skin surface.

Assessing the risk of a clinically significant infection from a Microneedle Array Patch (MAP) product

Microneedle Array Patches (MAPs) are an emerging dosage form that creates transient micron-sized disruptions in the outermost physical skin barrier, the stratum corneum, to facilitate delivery of active pharmaceutical ingredients to the underlying tissue. Numerous MAP products are proposed and there is significant clinical potential in priority areas such as vaccination. However, since their inception scientists have hypothesized about the risk of a clinically significant MAP-induced infection. Safety data from two major Phase 3 clinical trials involving hundreds of participants, who in total received tens of thousands of MAP applications, does not identify any clinically significant infections. However, the incumbent data set is not extensive enough to make definitive generalizable conclusions. A comprehensive assessment of the infection risk is therefore advised for MAP products, and this should be informed by clinical and pre-clinical data, theoretical analysis and informed opinions. In this article, a group of key stakeholders identify some of the key product- and patient-specific factors that may contribute to the risk of infection from a MAP product and provide expert opinions in the context of guidance from regulatory authorities. Considerations that are particularly pertinent to the MAP dosage form include the specifications of the finished product (e.g. microbial specification), it's design features, the setting for administration, the skill of the administrator, the anatomical application site, the target population and the clinical context. These factors, and others discussed in this article, provide a platform for the development of MAP risk assessments and a stimulus for early and open dialogue between developers, regulatory authorities and other key stakeholders, to expedite and promote development of safe and effective MAP products.

The multiscale characterization and constitutive modeling of healthy and type 2 diabetes mellitus Sprague Dawley rat skin

In type 2 diabetes mellitus (T2DM), elevated glucose level impairs the biochemistry of the skin which may result in alteration of its mechanical and structural properties. The several aspects of structural and mechanical changes in skin due to T2DM remain poorly understood. To fill these research gaps, we developed a non-obese T2DM rat (Sprague Dawley (SD)) model for investigating the effect of T2DM on the in vivo strain stress state, mechanical and structural properties of skin. In vivo strain and mechanical anisotropy of healthy and T2DM skin were measured using the digital imaging correlation (DIC) technique and DIC coupled bulge experiment, respectively. Fluorescence microscopy and histology were used to assess the collagen and elastin fibers microstructure whereas nanoscale structure was captured through atomic force microscopy (AFM). Based on the microstructural observations, skin was modeled as a multilayer membrane where in and out of plane distribution of collagen fibers and planar distribution of elastin fibers were cast in constitutive model. Further, the state of in vivo stresses of healthy and T2DM were measured using model parameters and in vivo strain in the constitutive model. The results showed that T2DM causes significant loss in in vivo stresses (p < 0.01) and increase in anisotropy (p < 0.001) of skin. These changes were found in good correlation with T2DM associated alteration in skin microstructure. Statistical analysis emphasized that increase in blood glucose concentration (HbA1c) was the main cause of impaired biomechanical properties of skin. The presented data in this study can help to understand the skin pathology and to simulate the skin related clinical procedures. STATEMENT OF SIGNIFICANCE: Our study is significant as it presents findings related to the effect of T2DM on the physiologic stress strain, structural and mechanical response of SD rat skin. In this study, we developed a non-obese T2DM SD rat model which mimics the phenotype of Asian type 2 diabetics (non-obese). Several structural and mechanical characterization techniques were explored for multiscale characterization of healthy and T2DM skin. Further, based on microstructural information, we presented the constitutive models that incorporate the real microstructure of skin. The presented results can be helpful to simulate the realistic mechanical response of skin during various clinical trials.

Automated Layer Identification Method for Skin Tissue Histology Images

We present a novel automated tissue layer identification method for histology images. The method requires a single user input: the number of layers to be identified. The method incorporates a coarse boundary identification step followed by a refinement step. The coarse identification segments the image into 125 × 125 pixel sub-tiles, computes the histogram of each sub-tile, implements K-means clustering to label each sub-tile, and uses Dijkstra's algorithm to form the layer boundary. The refinement step identifies hair follicles, improves the detail and accuracy of the boundary, and segments the epidermis. The method only uses one color channel (blue). We test our proposed method using eight excised porcine tissue samples taken at different anatomical locations. The layer segmentations demonstrated that the dermis thickness increased, and the subcutaneous thickness decreased moving from breast to belly. Minimal variation in the thickness of the epidermis layer across anatomical locations was observed. Overall, these results highlight the importance of quantifying and assessing the tissue environment. Moreover, we demonstrate that our proposed method was robust across different histology stains and did not depend on color-specific information.

Development of a Vascularized Human Skin Equivalent with Hypodermis for Photoaging Studies

Photoaging is an important extrinsic aging factor leading to altered skin morphology and reduced function. Prior work has revealed a connection between photoaging and loss of subcutaneous fat. Currently, primary models for studying this are in vivo (human samples or animal models) or in vitro models, including human skin equivalents (HSEs). In vivo models are limited by accessibility and cost, while HSEs typically do not include a subcutaneous adipose component. To address this, we developed an "adipose-vascular" HSE (AVHSE) culture method, which includes both hypodermal adipose and vascular cells. Furthermore, we tested AVHSE as a potential model for hypodermal adipose aging via exposure to 0.45 ± 0.15 mW/cm² 385 nm light (UVA). One week of 2 h daily UVA exposure had limited impact on epidermal and vascular components of the AVHSE, but significantly reduced adiposity by approximately 50%. Overall, we have developed a novel method for generating HSE that include vascular and adipose components and demonstrated potential as an aging model using photoaging as an example.

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.

Dissolvable polymer microneedles for drug delivery and diagnostics

Dissolvable transdermal microneedles (μND) are promising micro-devices used to transport a wide selection of active compounds into the skin. To provide an effective therapeutic outcome, μNDs must pierce the human stratum corneum (~10 to 20 μm), without rupturing or bending during penetration, then release their cargo at the predetermined area and time. The ability of dissolvable μND arrays/patches to sufficiently pierce the skin is a crucial requirement, which depends on the material composition, μND geometry and fabrication techniques. This comprehensive review not only provides contemporary knowledge on the μND design approaches, but also the materials science facilitating these delivery systems and the opportunities these advanced materials can provide to enhance clinical outcomes.

Multiscale Computational Model Predicts Mouse Skin Kinematics Under Tensile Loading

Skin is a complex tissue whose biomechanical properties are generally understood in terms of an incompressible material whose microstructure undergoes affine deformations. A growing number of experiments, however, have demonstrated that skin has a high Poisson's ratio, substantially decreases in volume during uniaxial tensile loading, and demonstrates collagen fiber kinematics that are not affine with local deformation. In order to better understand the mechanical basis for these properties, we constructed multiscale mechanical models (MSM) of mouse skin based on microstructural multiphoton microscopy imaging of the dermal microstructure acquired during mechanical testing. Three models that spanned the cases of highly aligned, moderately aligned, and nearly random fiber networks were examined and compared to the data acquired from uniaxially stretched skin. Our results demonstrate that MSMs consisting of networks of matched fiber organization can predict the biomechanical behavior of mouse skin, including the large decrease in tissue volume and nonaffine fiber kinematics observed under uniaxial tension.

Effect of collagen fibre orientation on the Poisson's ratio and stress relaxation of skin: an ex vivo and in vivo study

During surgical treatment skin undergoes extensive deformation, hence it must be able to withstand large mechanical stresses without damage. Therefore, understanding the mechanical properties of skin becomes important. A detailed investigation on the relationship between the three-dimensional deformation response of skin and its microstructure is conducted in the current study. This study also discloses the underlying science of skin viscoelasticity. Deformation response of skin is captured using digital image correlation, whereas micro-CT, scanning electron microscopy and atomic force microscopy are used for microstructure analysis. Skin shows a large lateral contraction and expansion (auxeticity) when stretched parallel and perpendicular to the skin tension lines, respectively. Large lateral contraction is a result of fluid exudation from the tissue, while large rotation of the stiff collagen fibres in the loading direction explains the skin auxeticity. During stress relaxation, lateral contraction and fluid effluxion from skin reveal that tissue volume loss is the intrinsic science of skin viscoelasticity. Furthermore, the results obtained from in vivo study on human skin show the relevance of the ex vivo study to physiological conditions and stretching of the skin during its treatments.

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].

Effect of collagen degradation on the mechanical behavior and wrinkling of skin

Chronological skin aging is a complex process that is controlled by numerous intrinsic and extrinsic factors. One major factor is the gradual degradation of the dermal collagen fiber network. As a step toward understanding the mechanistic importance of dermal tissue in the process of aging, this study employs analytical and multiscale computational models to elucidate the effect of collagen fiber bundle disintegration on the mechanical properties and topography of skin. Here, human skin is modeled as a soft composite with an anisotropic dermal layer. The anisotropy of the tissue is governed by collagen fiber bundles with varying densities, average fiber alignments, and normalized alignment distributions. In all finite element models examined, collagen fiber bundle degradation results in progressive decreases in dermal and full-thickness composite stiffness. This reduction is more profound when collagen bundles align with the compression axis. Aged skin models with low collagen fiber bundle densities under compression exhibit notably smaller critical wrinkling strains and larger critical wavelengths than younger skin models, in agreement with in vivo wrinkling behavior with age. The propensity for skin wrinkling can be directly attributable to the degradation of collagen fiber bundles, a relationship that has previously been assumed but unsubstantiated. While linear-elastic analytical models fail to capture the postbuckling behavior in skin, nonlinear finite element models can predict the complex bifurcations of the compressed skin with different densities of collagen bundles.

Improving reconstructive surgery design using Gaussian process surrogates to capture material behavior uncertainty

To produce functional, aesthetically natural results, reconstructive surgeries must be planned to minimize stress as excessive loads near wounds have been shown to produce pathological scarring and other complications (Gurtner et al., 2011). Presently, stress cannot easily be measured in the operating room. Consequently, surgeons rely on intuition and experience (Paul et al., 2016; Buchanan et al., 2016). Predictive computational tools are ideal candidates for surgery planning. Finite element (FE) simulations have shown promise in predicting stress fields on large skin patches and in complex cases, helping to identify potential regions of complication. Unfortunately, these simulations are computationally expensive and deterministic (Lee et al., 2018a). However, running a few, well selected FE simulations allows us to create Gaussian process (GP) surrogate models of local cutaneous flaps that are computationally efficient and able to predict stress and strain for arbitrary material parameters. Here, we create GP surrogates for the advancement, rotation, and transposition flaps. We then use the predictive capability of these surrogates to perform a global sensitivity analysis, ultimately showing that fiber direction has the most significant impact on strain field variations. We then perform an optimization to determine the optimal fiber direction for each flap for three different objectives driven by clinical guidelines (Leedy et al., 2005; Rohrer and Bhatia, 2005). While material properties are not controlled by the surgeon and are actually a source of uncertainty, the surgeon can in fact control the orientation of the flap with respect to the skin's relaxed tension lines, which are associated with the underlying fiber orientation (Borges, 1984). Therefore, fiber direction is the only material parameter that can be optimized clinically. The optimization task relies on the efficiency of the GP surrogates to calculate the expected cost of different strategies when the uncertainty of other material parameters is included. We propose optimal flap orientations for the three cost functions and that can help in reducing stress resulting from the surgery and ultimately reduce complications associated with excessive mechanical loading near wounds.

Three-Dimensional Quantification of Collagen Microstructure During Tensile Mechanical Loading of Skin

Skin is a heterogeneous tissue that can undergo substantial structural and functional changes with age, disease, or following injury. Understanding how these changes impact the mechanical properties of skin requires three-dimensional (3D) quantification of the tissue microstructure and its kinematics. The goal of this study was to quantify these structure-function relationships via second harmonic generation (SHG) microscopy of mouse skin under tensile mechanical loading. Tissue deformation at the macro- and micro-scale was quantified, and a substantial decrease in tissue volume and a large Poisson’s ratio was detected with stretch, indicating the skin differs substantially from the hyperelastic material models historically used to explain its behavior. Additionally, the relative amount of measured strain did not significantly change between length scales, suggesting that the collagen fiber network is uniformly distributing applied strains. Analysis of undeformed collagen fiber organization and volume fraction revealed a length scale dependency for both metrics. 3D analysis of SHG volumes also showed that collagen fiber alignment increased in the direction of stretch, but fiber volume fraction did not change. Interestingly, 3D fiber kinematics was found to have a non-affine relationship with tissue deformation, and an affine transformation of the micro-scale fiber network overestimates the amount of fiber realignment. This result, along with the other outcomes, highlights the importance of accurate, scale-matched 3D experimental measurements when developing multi-scale models of skin mechanical function.

Engineering Microneedle Patches for Improved Penetration: Analysis, Skin Models and Factors Affecting Needle Insertion

Transdermal microneedle (MN) patches are a promising tool used to transport a wide variety of active compounds into the skin. To serve as a substitute for common hypodermic needles, MNs must pierce the human stratum corneum (~ 10 to 20 µm), without rupturing or bending during penetration. This ensures that the cargo is released at the predetermined place and time. Therefore, the ability of MN patches to sufficiently pierce the skin is a crucial requirement. In the current review, the pain signal and its management during application of MNs and typical hypodermic needles are presented and compared. This is followed by a discussion on mechanical analysis and skin models used for insertion tests before application to clinical practice. Factors that affect insertion (e.g., geometry, material composition and cross-linking of MNs), along with recent advancements in developed strategies (e.g., insertion responsive patches and 3D printed biomimetic MNs using two-photon lithography) to improve the skin penetration are highlighted to provide a backdrop for future research.

Challenges and opportunities for small volumes delivery into the skin

Each individual's skin has its own features, such as strength, elasticity, or permeability to drugs, which limits the effectiveness of one-size-fits-all approaches typically found in medical treatments. Therefore, understanding the transport mechanisms of substances across the skin is instrumental for the development of novel minimal invasive transdermal therapies. However, the large difference between transport timescales and length scales of disparate molecules needed for medical therapies makes it difficult to address fundamental questions. Thus, this lack of fundamental knowledge has limited the efficacy of bioengineering equipment and medical treatments. In this article, we provide an overview of the most important microfluidics-related transport phenomena through the skin and versatile tools to study them. Moreover, we provide a summary of challenges and opportunities faced by advanced transdermal delivery methods, such as needle-free jet injectors, microneedles, and tattooing, which could pave the way to the implementation of better therapies and new methods.

How stiff is skin?

The measurement of the mechanical properties of skin (such as stiffness, extensibility and strength) is a key step in characterisation of both dermal ageing and disease mechanisms and in the assessment of tissue-engineered skin replacements. However, the biomechanical terminology and plethora of mathematical analysis approaches can be daunting to those outside the field. As a consequence, mechanical studies are often inaccessible to a significant proportion of the intended audience. Furthermore, devices for the measurement of skin function in vivo generate relative values rather than formal mechanical measures, therefore limiting the ability to compare studies. In this viewpoint essay, we discuss key biomechanical concepts and the influence of technical and biological factors (including the nature of the testing apparatus, length scale, donor age and anatomical site) on measured mechanical properties such as stiffness. Having discussed the current state-of-the-art in macro-mechanical and micromechanical measuring techniques and in mathematical and computational modelling methods, we then make suggestions as to how these approaches, in combination with 3D X-ray imaging and mechanics methods, may be adopted into a single strategy to characterise the mechanical behaviour of skin.

Personalized Computational Models of Tissue-Rearrangement in the Scalp Predict the Mechanical Stress Signature of Rotation Flaps

OBJECTIVE

To elucidate the mechanics of scalp rotation flaps through 3D imaging and computational modeling. Excessive tension near a wound or sutured region can delay wound healing or trigger complications. Measuring tension in the operating room is challenging, instead, noninvasive methods to improve surgical planning are needed.

DESIGN

Multi-view stereo allows creation of 3D patient-specific geometries based on a set of photographs. The patient-specific 3D geometry is imported into a finite element (FE) platform to perform a virtual procedure. The simulation is compared with the clinical outcome. Additional simulations quantify the effect of individual flap parameters on the resulting tension distribution.

PARTICIPANTS

Rotation flaps for reconstruction of scalp defects following melanoma resection in 2 cases are presented. Rotation flaps were designed without preoperative FE preparation.

MAIN OUTCOME MEASURE

Tension distribution over the operated region.

RESULTS

The tension from FE shows peaks at the base and distal ends of the scalp rotation flap. The predicted geometry from the simulation aligns with postoperative photographs. Simulations exploring the flap design parameters show variation in the tension. Lower tensions were achieved when rotation was oriented with respect to skin tension lines (horizontal tissue fibers) and smaller rotation angles.

CONCLUSIONS

Tension distribution following rotation of scalp flaps can be predicted through personalized FE simulations. Flaps can be designed to reduce tension using FE, which may greatly improve the reliability of scalp reconstruction in craniofacial surgery, critical in complex cases when scalp reconstruction is essential for coverage of hardware, implants, and/or bone graft.

Toward clinical elastography of dermal tissues: A medical device to probe skin's elasticity through suction, with subsurface imaging via optical coherence tomography

The mechanical behavior of dermal tissues is unarguably recognized for its diagnostic ability and in the last decades received a steadily increasing interest in dermatology practices. Among the various methods to investigate the mechanics of skin in clinical environments, suction-based ones are especially noteworthy, thanks to their qualities of minimal invasiveness and relative simplicity of setups and data analysis. In such experiments, structural visualization of the sample is highly desirable, both in its own right and because it enables elastography. The latter is a technique that combines the knowledge of an applied mechanical stimulus and the visualization of the induced deformation to result in a spatially resolved map of the mechanical properties, which is particularly important for an inhomogeneous and layered material such as skin. We present a device, designed for clinical trials in dermatology practices, that uses a handheld probe to (1) deliver a suction-based, controlled mechanical stimulus and (2) visualize the subsurface structure via optical coherence tomography. We also present a device-agnostic data-analysis framework, consisting of a Python library, released in the public domain. We show the working principle of the setup on a polymeric model and on a volunteer's skin.

Heterochromatin-Driven Nuclear Softening Protects the Genome against Mechanical Stress-Induced Damage

Tissue homeostasis requires maintenance of functional integrity under stress. A central source of stress is mechanical force that acts on cells, their nuclei, and chromatin, but how the genome is protected against mechanical stress is unclear. We show that mechanical stretch deforms the nucleus, which cells initially counteract via a calcium-dependent nuclear softening driven by loss of H3K9me3-marked heterochromatin. The resulting changes in chromatin rheology and architecture are required to insulate genetic material from mechanical force. Failure to mount this nuclear mechanoresponse results in DNA damage. Persistent, high-amplitude stretch induces supracellular alignment of tissue to redistribute mechanical energy before it reaches the nucleus. This tissue-scale mechanoadaptation functions through a separate pathway mediated by cell-cell contacts and allows cells/tissues to switch off nuclear mechanotransduction to restore initial chromatin state. Our work identifies an unconventional role of chromatin in altering its own mechanical state to maintain genome integrity in response to deformation.

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Stretch triggers amplitude-dependent supracellular and nuclear mechanoresponses

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H3K9me3 heterochromatin mediates nuclear stiffness and membrane tension

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Nuclear deformation-triggered Ca²⁺ alters chromatin rheology to prevent DNA damage

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Supracellular alignment redistributes stress to restore chromatin state

Constitutive description of skin dermis: Through analytical continuum and coarse-grained approaches for multi-scale understanding

Although there are many successful descriptions of the mechanical response of dermis at different levels of complexity and incorporating varying degrees of the physical phenomena involved in deformation, observations indicate that the unraveling of fibers involves a complex three-dimensional process in which they interact in ways that resemble a braided pattern. Here we develop two complementary treatments to gain a better understanding of the mechanical response of dermis: a) an analytical treatment incorporating fibril stiffness, interfibrillar frictional sliding, and the effect of lateral fibers on the extension of a primary fiber; b) a coarse-grained molecular dynamics model comprised of an array of parallel curved fibrils simulating a fiber. Interfibrillar frictional sliding and stiffness are also captured. Both analytical and molecular dynamics models operate at a scale compatible with the wavelength of collagen fibers (~10 µm). The constitutive description presented here incorporates important physical processes taking place during deformation of dermis and thus represents an advance in our understanding of these phenomena. STATEMENT OF SIGNIFICANCE: Microstructural observations of the dermis of skin during tensile deformation indicate that the unraveling of fibers involves a complex three-dimensional process which replicates the effects of braiding. Two complementary constitutive modeling treatments were developed to gain a better understanding of the mechanical response of dermis: an analytical treatment incorporating fibril stiffness, interfibrillar sliding, and the effect of transverse fibers; and a coarse-grained molecular dynamics model describing the fibril bundling effect. An important novel aspect of the current contribution is the recognition that tridimensional collagen fiber arrangements play an important role in the mechanical response. The constitutive description presented here incorporates physical processes taking place during deformation of the dermis and thus represents an advance in our understanding of these phenomena.

Friction properties of in vivo human skin from visualized friction testing

Investigations on mechanical behaviors of intravital human skin are of significance in various fields. However, due to the great complexity and the individual variation of human skin, traditional experimental mechanics often fails to work in such research objects. In this study, the friction property considering the skin-uplift effect of human skin was in vivo studied experimentally and theoretically. An in situ and noninvasive friction experiment was performed in vivo on human skin, where the projected contact morphology was captured through a novel specially developed optical system. According to the contact morphology, a model taking uplift resistance into account is proposed based on Greenwood model, in which the contact area was depicted as a combination of two ellipses to better characterize the skin deformation. Moreover, since the model degrades into Greenwood model in small deformation, it can be considered as an extension from the perspective of small deformation to large deformation. Based on the model, the adhesion friction and deformation friction have been separated according to the ratio of indentation depth to probe radius. The results show that the friction property of skin varies with the indentation depth changing, and the deformation friction is positively correlated with the ratio of indentation depth to probe radius.

Propagation of uncertainty in the mechanical and biological response of growing tissues using multi-fidelity Gaussian process regression

A key feature of living tissues is their capacity to remodel and grow in response to environmental cues. Within continuum mechanics, this process can be captured with the multiplicative split of the deformation gradient into growth and elastic contributions. The mechanical and biological response during tissue adaptation is characterized by inherent variability. Accounting for this uncertainty is critical to better understand tissue mechanobiology, and, moreover, it is of practical importance if we aim to develop predictive models for clinical use. However, the current gold standard in computational models of growth and remodeling remains the use of deterministic finite element (FE) simulations. Here we focus on tissue expansion, a popular technique in which skin is stretched by a balloon-like device inducing its growth. We construct FE models of tissue expansion with various levels of detail, and show that a sufficiently broad set of FE simulations from these models can be used to train an accurate and efficient multi-fidelity Gaussian process (GP) surrogate. The approach is not limited to simulation data, rather, it can fuse different kinds of data, including from experiments. The main appeal of the framework relies on the common experience that highly detailed models (or experiments) are more accurate but also more costly, while simpler models (or experiments) can be easily evaluated but are bound to have some error. In these situations, doing uncertainty analysis tasks with the high fidelity models alone is not feasible and, conversely, relying solely on low fidelity approximations is also undesirable. We show that a multi-fidelity GP outperforms the high fidelity GP and low fidelity GP when tested against the most detailed FE model. In turn, having trained the multi-fidelity GP model, we showcase the propagation of uncertainty from the mechanical and biological response parameters to the spatio-temporal growth outcomes. We expect that the methods and applications in this paper will enable future research in parameter calibration under uncertainty and uncertainty propagation in real clinical scenarios involving tissue growth and remodeling.

A multi-layered computational model for wrinkling of human skin predicts aging effects

The development and progression of wrinkles from young to aged human skin relates to both structural and mechanical changes induced by aging. Here we aim to better understand the interaction of skin's layered morphology with dynamic wrinkles predicted in young and aged skin. First, we compare the predictions of wrinkling from 3-D finite element models of human skin including two to six distinct and anatomically motivated layers. Second, we perform parametric analyses using our six-layered model to determine how age-related changes in the architecture of human skin affect dynamic surface wrinkling. Specifically, we consider the following aging-related changes in the morphology of skin: flattening of the dermal-epidermal junction (DEJ) interface; thinning of both the viable epidermis (VE) and the reticular dermis (RD); and thickening of the papillary dermis (PD). We use skin compression to model dynamic, expressional wrinkles due to muscle contraction, and volumetric tissue loss to model effects of aging in wrinkling simulations. Our results highlight the role of skin's multi-layered structure in the modeling of wrinkling formation. Our six-layered model, consisting of all of the mechanical layers, predicts deep wrinkles with better fidelity than models including fewer layers. From our parametric study, applying our six-layered model, we conclude that: (1) the relative thicknesses of the layers in the epidermis or dermis significantly influences surface wrinkling in skin; and, (2) flattening of the DEJ with aging enhances surface wrinkling. Thinning of VE increases the relative stiffness of the epidermis and thus enhances dynamic wrinkling, while thickening of PD or thinning of RD has the same effect by reducing the equivalent stiffness of the substrate. Consequently, strategies to minimize wrinkling could maintain the undulating morphology of the DEJ, thereby delaying dynamic wrinkling and delaying the propagation of buckling into the deeper dermis or hypodermis. Additional strategies to minimize wrinkling could target preventing the VE and RD from thinning or preventing the PD from thickening.

Whole-Section Tumor Micro-Architecture Analysis by a Two-Dimensional Phasor-Based Approach Applied to Polarization-Dependent Second Harmonic Imaging

Second Harmonic Generation (SHG) microscopy has gained much interest in the histopathology field since it allows label-free imaging of tissues simultaneously providing information on their morphology and on the collagen microarchitecture, thereby highlighting the onset of pathologies and diseases. A wide request of image analysis tools is growing, with the aim to increase the reliability of the analysis of the huge amount of acquired data and to assist pathologists in a user-independent way during their diagnosis. In this light, we exploit here a set of phasor-parameters that, coupled to a 2-dimensional phasor-based approach (μMAPPS, Microscopic Multiparametric Analysis by Phasor projection of Polarization-dependent SHG signal) and a clustering algorithm, allow to automatically recover different collagen microarchitectures in the tissues extracellular matrix. The collagen fibrils microscopic parameters (orientation and anisotropy) are analyzed at a mesoscopic level by quantifying their local spatial heterogeneity in histopathology sections (few mm in size) from two cancer xenografts in mice, in order to maximally discriminate different collagen organizations, allowing in this case to identify the tumor area with respect to the surrounding skin tissue. We show that the “fibril entropy” parameter, which describes the tissue order on a selected spatial scale, is the most effective in enlightening the tumor edges, opening the possibility of their automatic segmentation. Our method, therefore, combined with tissue morphology information, has the potential to become a support to standard histopathology in diseases diagnosis.

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.

Tensile behavior and structural characterization of pig dermis

Skin, the outermost layer of the body, fulfills a broad range of functions, protecting internal organs from damage and infection, while regulating the body's temperature and water content via the exchange of heat and fluids. It must be able to withstand and recover from extensive deformation and damage that can occur during growth, movement, and potential injuries. A detailed investigation of the evolution of the collagen architecture of the dermis as a function of deformation is conducted, which reveals new aspects that help us to understand the mechanical response of skin. Juvenile pig is used as a model material because of its similarity to human skin. The dermis is found to have a tridimensional woven structure of collagen fibers, which evolves with deformation. After failure, we observe that the fibers have straightened and aligned in the direction of tension. The effects of strain-rate change, cyclic loading, stress relaxation, and orientation are quantitatively established. Digital image correlation techniques are implemented to quantify skin's anisotropy; measurements of the Poisson ratio are reported. This is coupled with transmission electron microscopy which enables obtaining quantitative strain parameters evaluated through the orientation and curvature of the collagen fibers and their changes, for the first time in all three dimensions of the tissue. A model experiment using braided human hair in tension exhibits a similar J-curve response to skin, and we propose that this fiber configuration is at least partially responsible for the monotonic increase of the tangent modulus of skin with strain. The obtained results are intended to serve as a basis for structurally-based models of skin. STATEMENT OF SIGNIFICANCE: Our study reveals a new aspect of the dermis: it is comprised of a tridimensional woven structure of collagen fibers, which evolves with deformation. This is enabled by primarily two techniques, transmission electron microscopy on three perpendicular planes and confocal images with second harmonic generation fluorescence of collagen, captured at different intervals of depth. After failure, the fibers have straightened and aligned in the direction of tension. Digital image correlation techniques are implemented to quantify skin's anisotropy; measurements of the Poisson ratio are reported. A model experiment using braided human hair in tension exhibits a similar J-curve response to skin, and we propose that this fiber configuration is at least partially responsible for the monotonic increase of the tangent modulus of skin with strain.

Mathematical and computational modelling of skin biophysics: a review

The objective of this paper is to provide a review on some aspects of the mathematical and computational modelling of skin biophysics, with special focus on constitutive theories based on nonlinear continuum mechanics from elasticity, through anelasticity, including growth, to thermoelasticity. Microstructural and phenomenological approaches combining imaging techniques are also discussed. Finally, recent research applications on skin wrinkles will be presented to highlight the potential of physics-based modelling of skin in tackling global challenges such as ageing of the population and the associated skin degradation, diseases and traumas.

Low-Cost Methodology for Skin Strain Measurement of a Flexed Biological Limb

OBJECTIVE

The purpose of this manuscript is to compute skin strain data from a flexed biological limb, using portable, inexpensive, and easily available resources.

METHODS

We apply and evaluate this approach on a person with bilateral transtibial amputations, imaging left and right residual limbs in extended and flexed knee postures. We map 3-D deformations to a flexed biological limb using freeware and a simple point-and-shoot camera. Mean principal strain, maximum shear strain, as well as lines of maximum, minimum, and nonextension are computed from 3-D digital models to inform directional mappings of the strain field for an unloaded residual limb.

RESULTS

Peak tensile strains are ∼0.3 on the anterior surface of the knee in the proximal region of the patella, whereas peak compressive strains are ∼ -0.5 on the posterior surface of the knee. Peak maximum shear strains are ∼0.3 on the posterior surface of the knee. The accuracy and precision of this methodology are assessed for a ground-truth model. The mean point location distance is found to be 0.08 cm, and the overall standard deviation for point location difference vectors is 0.05 cm.

CONCLUSION

This low-cost and mobile methodology may prove critical for applications such as the prosthetic socket interface where whole-limb skin strain data are required from patients in the field outside of traditional, large-scale clinical centers.

SIGNIFICANCE

Such data may inform the design of wearable technologies that directly interface with human skin.

Automatic Segmentation of Mechanically Inhomogeneous Tissues Based on Deformation Gradient Jump

Variations in properties, active behavior, injury, scarring, and/or disease can all cause a tissue's mechanical behavior to be heterogeneous. Advances in imaging technology allow for accurate full-field displacement tracking of both in vitro and in vivo deformation from an applied load. While detailed strain fields provide some insight into tissue behavior, material properties are usually determined by fitting stress-strain behavior with a constitutive equation. However, the determination of the mechanical behavior of heterogeneous soft tissue requires a spatially varying constitutive equation (i.e., one in which the material parameters vary with position). We present an approach that computationally dissects the sample domain into many homogeneous subdomains, wherein subdomain boundaries are formed by applying a betweenness based graphical analysis to the deformation gradient field to identify locations with large discontinuities. This novel partitioning technique successfully determined the shape, size and location of regions with locally similar material properties for: (1) a series of simulated soft tissue samples prescribed with both abrupt and gradual changes in anisotropy strength, prescribed fiber alignment, stiffness, and nonlinearity, (2) tissue analogs (PDMS and collagen gels) which were tested biaxially and speckle tracked (3) and soft tissues which exhibited a natural variation in properties (cadaveric supraspinatus tendon), a pathologic variation in properties (thoracic aorta containing transmural plaque), and active behavior (contracting cardiac sheet). The routine enables the dissection of samples computationally rather than physically, allowing for the study of small tissues specimens with unknown and irregular inhomogeneity.

The Incompatibility of Living Systems: Characterizing Growth-Induced Incompatibilities in Expanded Skin

Skin expansion is a common surgical technique to correct large cutaneous defects. Selecting a successful expansion protocol is solely based on the experience and personal preference of the operating surgeon. Skin expansion could be improved by predictive computational simulations. Towards this goal, we model skin expansion using the continuum framework of finite growth. This approach crucially relies on the concept of incompatible configurations. However, aside from the classical opening angle experiment, our current understanding of growth-induced incompatibilities remains rather vague. Here we visualize and characterize incompatibilities in living systems using skin expansion in a porcine model: We implanted and inflated two expanders, crescent, and spherical, and filled them to 225 cc throughout a period of 21 days. To quantify the residual strains developed during this period, we excised the expanded skin patches and subdivided them into smaller pieces. Skin growth averaged 1.17 times the original area for the spherical and 1.10 for the crescent expander, and displayed significant regional variations. When subdivided into smaller pieces, the grown skin patches retracted heterogeneously and confirmed the existence of incompatibilities. Understanding skin growth through mechanical stretch will allow surgeons to improve-and ultimately personalize-preoperative treatment planning in plastic and reconstructive surgery.

Collagen Fibrils in Skin Orient in the Direction of Applied Uniaxial Load in Proportion to Stress while Exhibiting Differential Strains around Hair Follicles

We determined inhomogeneity of strains around discontinuities as well as changes in orientation of collagen fibrils under applied load in skin. Second Harmonic Generation (SHG) images of collagen fibrils were obtained at different strain magnitudes. Changes in collagen orientation were analyzed using Fast Fourier Transforms (FFT) while strain inhomogeneity was determined at different distances from hair follicles using Digital Image Correlation (DIC). A parameter, defined as the Collagen Orientation Index (COI), is introduced that accounts for the increasingly ellipsoidal nature of the FFT amplitude images upon loading. We show that the COI demonstrates two distinct mechanical regimes, one at low strains (0%, 2.5%, 5% strain) in which randomly oriented collagen fibrils align in the direction of applied deformation. In the second regime, beginning at 5% strain, collagen fibrils elongate in response to applied deformation. Furthermore, the COI is also found to be linearly correlated with the applied stress indicating that collagen fibrils orient to take the applied load. DIC results indicated that major principal strains were found to increase with increased load at all locations. In contrast, minimum principal strain was dependent on distance from hair follicles. These findings are significant because global and local changes in collagen deformations are expected to be changed by disease, and could affect stem cell populations surrounding hair follicles, including mesenchymal stem cells within the outer root sheath.