Assessing the impact of extracellular matrix fiber orientation on breast cancer cellular metabolism.

The extracellular matrix (ECM) is a dynamic and complex microenvironment that modulates cell behavior and cell fate. Changes in ECM composition and architecture have been correlated with development, differentiation, and disease progression in various pathologies, including breast cancer [1]. Studies have shown that aligned fibers drive a pro-metastatic microenvironment, promoting the transformation of mammary epithelial cells into invasive ductal carcinoma via the epithelial-to-mesenchymal transition (EMT) [2]. The impact of ECM orientation on breast cancer metabolism, however, is largely unknown. Here, we employ two non-invasive imaging techniques, fluorescence-lifetime imaging microscopy (FLIM) and intensity-based multiphoton microscopy, to assess the metabolic states of cancer cells cultured on ECM-mimicking nanofibers in a random and aligned orientation. By tracking the changes in the intrinsic fluorescence of nicotinamide adenine dinucleotide and flavin adenine dinucleotide, as well as expression levels of metastatic markers, we reveal how ECM fiber orientation alters cancer metabolism and EMT progression. Our study indicates that aligned cellular microenvironments play a key role in promoting metastatic phenotypes of breast cancer as evidenced by a more glycolytic metabolic signature on nanofiber scaffolds of aligned orientation compared to scaffolds of random orientation. This finding is particularly relevant for subsets of breast cancer marked by high levels of collagen remodeling (e.g. pregnancy associated breast cancer), and may serve as a platform for predicting clinical outcomes within these subsets [3-6].

Differential gene expression of leaflet tissue in chronic ovine functional tricuspid regurgitation.

OBJECTIVES: Severe functional tricuspid regurgitation (FTR) is associated with subvalvular remodelling, but leaflet tissue alterations may also contribute. We set out to investigate molecular mechanisms driving leaflet remodelling in chronic ovine FTR. METHODS: Thirteen adult sheep (55 ± 4kg) underwent left thoracotomy, epicardial echocardiography, and pulmonary artery banding (PAB) to induce right heart failure and FTR. After 16 weeks, 13 banded (FTR) and 12 control (CTL) animals underwent median sternotomy for epicardial echocardiography and were subsequently sacrificed with each tricuspid leaflet tissue harvested for RNA-seq and histology. RESULTS: After 16 weeks, 7 animals developed severe, 2 moderate, and 4 mild tricuspid regurgitation (TR). Relative to CTL, FTR animals had increased PAP, TR, tricuspid annular diameter, and right atrial volume, while tricuspid annular plane systolic excursion (TAPSE) and RV fractional area change decreased. FTR leaflets exhibited altered constituents and an increase in cellularity. RNA-seq identified 85 significantly differentially expressed genes (DEG) with 17, 53, and 127 within the anterior, posterior, and septal leaflets respectively. RRM2, PRG4, and CXCL8 (IL-8) were identified as DEGs across all leaflets and CXCL8 was differentially expressed between FTR severity grades. RRM2, PRG4, and CXCL8 significantly correlated with TAPSE, and this correlation was consistent regardless of the anatomical location of the leaflet. CONCLUSIONS: PAB in our ovine model resulted in RV failure and FTR. Leaflet RNA-seq identified several DEGs, specifically RRM2, PRG4, and CXCL8, with known roles in tissue remodelling. These data along with an overall increase in leaflet cellularity suggest tricuspid leaflets actively remodel in FTR.

"What makes blood clots break off?" A Back-of-the-Envelope Computation Toward Explaining Clot Embolization.

PURPOSE: One in four deaths worldwide is due to thromboembolic disease; that is, one in four people die from blood clots first forming and then breaking off or embolizing. Once broken off, clots travel downstream, where they occlude vital blood vessels such as those of the brain, heart, or lungs, leading to strokes, heart attacks, or pulmonary embolisms, respectively. Despite clots' obvious importance, much remains to be understood about clotting and clot embolization. In our work, we take a first step toward untangling the mystery behind clot embolization and try to answer the simple question: "What makes blood clots break off?" METHODS: To this end, we conducted experimentally-informed, back-of-the-envelope computations combining fracture mechanics and phase-field modeling. We also focused on deep venous clots as our model problem. RESULTS: Here, we show that of the three general forces that act on venous blood clots-shear stress, blood pressure, and wall stretch-induced interfacial forces-the latter may be a critical embolization force in occlusive and non-occlusive clots, while blood pressure appears to play a determinant role only for occlusive clots. Contrary to intuition and prior reports, shear stress, even when severely elevated, appears unlikely to cause embolization. CONCLUSION: This first approach to understanding the source of blood clot bulk fracture may be a critical starting point for understanding blood clot embolization. We hope to inspire future work that will build on ours and overcome the limitations of these back-of-the-envelope computations.

Mechanical properties of clot made from human and bovine whole blood differ significantly.

Thromboembolism - that is, clot formation and the subsequent fragmentation of clot - is a leading cause of death worldwide. Clots' mechanical properties are critical determinants of both the embolization process and the pathophysiological consequences thereof. Thus, understanding and quantifying the mechanical properties of clots is important to our ability to treat and prevent thromboembolic disease. However, assessing these properties from in vivo clots is experimentally challenging. Therefore, we and others have turned to studying in vitro clot mimics instead. Unfortunately, there are significant discrepancies in the reported properties of these clot mimics, which have been hypothesized to arise from differences in experimental techniques and blood sources. The goal of our current work is therefore to compare the mechanical behavior of clots made from the two most common sources, human and bovine blood, using the same experimental techniques. To this end, we tested clots under pure shear with and without initial cracks, under cyclic loading, and under stress relaxation. Based on these data, we computed and compared stiffness, strength, work-to-rupture, fracture toughness, relaxation time constants, and prestrain. While clots from both sources behaved qualitatively similarly, they differed quantitatively in almost every metric. We also correlated each mechanical metric to measures of blood composition. Thereby, we traced this inter-species variability in clot mechanics back to significant differences in hematocrit, but not platelet count. Thus, our work suggests that the results of past studies that have used bovine blood to make in vitro mimics - without adjusting blood composition - should be interpreted carefully. Future studies about the mechanical properties of blood clots should focus on human blood alone.

Leaflet remodeling reduces tricuspid valve function in a computational model.

Tricuspid valve leaflets have historically been considered "passive flaps". However, we have recently shown that tricuspid leaflets actively remodel in sheep with functional tricuspid regurgitation. We hypothesize that these remodeling-induced changes reduce leaflet coaptation and, therefore, contribute to valvular dysfunction. To test this, we simulated the impact of remodeling-induced changes on valve mechanics in a reverse-engineered computer model of the human tricuspid valve. To this end, we combined right-heart pressures and tricuspid annular dynamics recorded in an ex vivo beating heart, with subject-matched in vitro measurements of valve geometry and material properties, to build a subject-specific finite element model. Next, we modified the annular geometry and boundary conditions to mimic changes seen in patients with pulmonary hypertension. In this model, we then increased leaflet thickness and stiffness and reduced the stretch at which leaflets stiffen, which we call "transition-λ." Subsequently, we quantified mean leaflet stresses, leaflet systolic angles, and coaptation area as measures of valve function. We found that leaflet stresses, leaflet systolic angle, and coaptation area are sensitive to independent changes in stiffness, thickness, and transition-λ. When combining thickening, stiffening, and changes in transition-λ, we found that anterior and posterior leaflet stresses decreased by 26% and 28%, respectively. Furthermore, systolic angles increased by 43%, and coaptation area decreased by 66%; thereby impeding valve function. While only a computational study, we provide the first evidence that remodeling-induced leaflet thickening and stiffening may contribute to valvular dysfunction. Targeted suppression of such changes in diseased valves could restore normal valve mechanics and promote leaflet coaptation.

Geometric data of commercially available tricuspid valve annuloplasty devices.

Tricuspid valve annuloplasty is the gold standard surgical treatment for functional tricuspid valve regurgitation. During this procedure, ring-like devices are implanted to reshape the diseased tricuspid valve annulus and to restore function. For the procedure, surgeons can choose from multiple available device options varying in shape and size. In this article, we provide the three-dimensional (3D) scanned geometry (*.stl) and reduced midline (*.vtk) of five different annuloplasty devices of all commercially available sizes. Three-dimensional images were captured using a 3D scanner. After extracting the surface geometry from these images, the images were converted to 3D point clouds and skeletonized to generate a 3D midline of each device. In total, we provide 30 data sets comprising the Edwards Classic, Edwards MC3, Edwards Physio, Medtronic TriAd, and Medtronic Contour 3D of sizes 26-36. This dataset can be used in computational models of tricuspid valve annuloplasty repair to inform accurate repair geometry and boundary conditions. Additionally, others can use these data to compare and inspire new device shapes and sizes.

Impact of tricuspid annuloplasty device shape and size on valve mechanics-a computational study.

Background: Tricuspid valve disease significantly affects 1.6 million Americans. The gold standard treatment for tricuspid disease is the implantation of annuloplasty devices. These ring-like devices come in various shapes and sizes. Choices for both shape and size are most often made by surgical intuition rather than scientific rationale. Methods: To understand the impact of shape and size on valve mechanics and to provide a rational basis for their selection, we used a subject-specific finite element model to conduct a virtual case study. That is, we implanted 4 different annuloplasty devices of 6 different sizes in our virtual patient. After each virtual surgery, we computed the coaptation area, leaflet end-systolic angles, leaflet stress, and chordal forces. Results: We found that contoured devices are better at normalizing end-systolic angles, whereas the one flat device, the Edwards Classic, maximized the coaptation area and minimized leaflet stress and chordal forces. We further found that reducing device size led to increased coaptation area but also negatively impacted end-systolic angles, stress, and chordal forces. Conclusions: Based on our analyses of the coaptation area, leaflet motion, leaflet stress, and chordal forces, we found that device shape and size have a significant impact on valve mechanics. Thereby, our study also demonstrates the value of simulation tools and device tests in "virtual patients." Expanding our study to many more valves may, in the future, allow for universal recommendations.

Sex- and age-dependent skin mechanics-A detailed look in mice.

Skin aging is of immense societal and, thus, scientific interest. Because mechanics play a critical role in skin's function, a plethora of studies have investigated age-induced changes in skin mechanics. Nonetheless, much remains to be learned about the mechanics of aging skin. This is especially true when considering sex as a biological variable. In our work, we set out to answer some of these questions using mice as a model system. Specifically, we combined mechanical testing, histology, collagen assays, and two-photon microscopy to identify age- and sex-dependent changes in skin mechanics and to relate them to structural, microstructural, and compositional factors. Our work revealed that skin stiffness, thickness, and collagen content all decreased with age and were sex dependent. Interestingly, sex differences in stiffness were age induced. We hope our findings not only further our fundamental understanding of skin aging but also highlight both age and sex as important variables when conducting studies on skin mechanics. STATEMENT OF SIGNIFICANCE: Our work addresses the question, "How do sex and age affect the mechanics of skin?" Answering this question is of both scientific and societal importance. We do so in mice as a model system. Thereby, we hope to add clarity to a body of literature that appears divided on the effect of both factors. Our findings have important implications for those studying age and sex differences, especially in mice as a model system.

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.

Untangling the mechanisms of pulmonary arterial hypertension-induced right ventricular stiffening in a large animal model.

Pulmonary hypertension (PHT) is a devastating disease with low survival rates. In PHT, chronic pressure overload leads to right ventricle (RV) stiffening; thus, impeding diastolic filling. Multiple mechanisms may contribute to RV stiffening, including wall thickening, microstructural disorganization, and myocardial stiffening. The relative importance of each mechanism is unclear. Our objective is to use a large animal model to untangle these mechanisms. Thus, we induced pulmonary arterial hypertension (PAH) in sheep via pulmonary artery banding. After eight weeks, the hearts underwent anatomic and diffusion tensor MRI to characterize wall thickening and microstructural disorganization. Additionally, myocardial samples underwent histological and gene expression analyses to quantify compositional changes and mechanical testing to quantify myocardial stiffening. Finally, we used finite element modeling to disentangle the relative importance of each stiffening mechanism. We found that the RVs of PAH animals thickened most at the base and the free wall and that PAH induced excessive collagen synthesis, increased cardiomyocyte cross-sectional area, and led to microstructural disorganization, consistent with increased expression of fibrotic genes. We also found that the myocardium itself stiffened significantly. Importantly, myocardial stiffening correlated significantly with collagen synthesis. Finally, our computational models predicted that myocardial stiffness contributes to RV stiffening significantly more than other mechanisms. Thus, myocardial stiffening may be the most important predictor for PAH progression. Given the correlation between myocardial stiffness and collagen synthesis, collagen-sensitive imaging modalities may be useful for estimating myocardial stiffness and predicting PAH outcomes. STATEMENT OF SIGNIFICANCE: Ventricular stiffening is a significant contributor to pulmonary hypertension-induced right heart failure. However, the mechanisms that lead to ventricular stiffening are not fully understood. The novelty of our work lies in answering this question through the use of a large animal model in combination with spatially- and directionally sensitive experimental techniques. We find that myocardial stiffness is the primary mechanism that leads to ventricular stiffening. Clinically, this knowledge may be used to improve diagnostic, prognostic, and therapeutic strategies for patients with pulmonary hypertension.

AI-dente: an open machine learning based tool to interpret nano-indentation data of soft tissues and materials.

Nano-indentation is a promising method to identify the constitutive parameters of soft materials, including soft tissues. Especially when materials are very small and heterogeneous, nano-indentation allows mechanical interrogation where traditional methods may fail. However, because nano-indentation does not yield a homogeneous deformation field, interpreting the resulting load-displacement curves is non-trivial and most investigators resort to simplified approaches based on the Hertzian solution. Unfortunately, for small samples and large indentation depths, these solutions are inaccurate. We set out to use machine learning to provide an alternative strategy. We first used the finite element method to create a large synthetic data set. We then used these data to train neural networks to inversely identify material parameters from load-displacement curves. To this end, we took two different approaches. First, we learned the indentation forward problem, which we then applied within an iterative framework to identify material parameters. Second, we learned the inverse problem of directly identifying material parameters. We show that both approaches are effective at identifying the parameters of the neo-Hookean and Gent models. Specifically, when applied to synthetic data, our approaches are accurate even for small sample sizes and at deep indentation. Additionally, our approaches are fast, especially compared to the inverse finite element approach. Finally, our approaches worked on unseen experimental data from thin mouse brain samples. Here, our approaches proved robust to experimental noise across over 1000 samples. By providing open access to our data and code, we hope to support others that conduct nano-indentation on soft materials.

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.

A Brief Note on Building Augmented Reality Models for Scientific Visualization.

Augmented reality (AR) has revolutionized the video game industry by providing interactive, three-dimensional visualization. Interestingly, AR technology has only been sparsely used in scientific visualization. This is, at least in part, due to the significant technical challenges previously associated with creating and accessing such models. To ease access to AR for the scientific community, we introduce a novel visualization pipeline with which they can create and render AR models. We demonstrate our pipeline by means of finite element results, but note that our pipeline is generally applicable to data that may be represented through meshed surfaces. Specifically, we use two open-source software packages, ParaView and Blender. The models are then rendered through the platform, which we access through Android and iOS smartphones. To demonstrate our pipeline, we build AR models from static and time-series results of finite element simulations discretized with continuum, shell, and beam elements. Moreover, we openly provide python scripts to automate this process. Thus, others may use our framework to create and render AR models for their own research and teaching activities.

Elasticity of whole blood clots measured via Volume Controlled Cavity Expansion.

Measuring and understanding the mechanical properties of blood clots can provide insights into disease progression and the effectiveness of potential treatments. However, several limitations hinder the use of standard mechanical testing methods to measure the response of soft biological tissues, like blood clots. These tissues can be difficult to mount, and are inhomogeneous, irregular in shape, scarce, and valuable. To remedy this, we employ in this work Volume Controlled Cavity Expansion (VCCE), a technique that was recently developed, to measure local mechanical properties of soft materials in their natural environment. Through highly controlled volume expansion of a water bubble at the tip of an injection needle, paired with simultaneous measurement of the resisting pressure, we obtain a local signature of whole blood clot mechanical response. Comparing this data with predictive theoretical models, we find that a 1-term Ogden model is sufficient to capture the nonlinear elastic response observed in our experiments and produces shear modulus values that are comparable to values reported in the literature. Moreover, we find that bovine whole blood stored at 4 °C for greater than 2 days exhibits a statistically significant shift in the shear modulus from 2.53 ± 0.44 kPa on day 2 (N = 13) to 1.23 ± 0.18 kPa on day 3 (N = 14). In contrast to previously reported results, our samples did not exhibit viscoelastic rate sensitivity within strain rates ranging from 0.22 - 21.1 s-1. By surveying existing data on whole blood clots for comparison, we show that this technique provides highly repeatable and reliable results, hence we propose the more widespread adoption of VCCE as a path forward to building a better understanding of the mechanics of soft biological materials.

Untangling the mechanisms of pulmonary hypertension-induced right ventricular stiffening in a large animal model.

Background: Pulmonary arterial hypertension (PHT) is a devastating disease with low survival rates. In PHT, chronic pressure overload leads to right ventricle (RV) remodeling and stiffening; thus, impeding diastolic filling and ventricular function. Multiple mechanisms contribute to RV stiffening, including wall thickening, microstructural disorganization, and myocardial stiffening. The relative importance of each mechanism is unclear. Our objective is to use a large animal model as well as imaging, experimental, and computational approaches to untangle these mechanisms. Methods: We induced PHT in eight sheep via pulmonary artery banding. After eight weeks, the hearts underwent anatomic and diffusion tensor MRI to characterize wall thickening and microstructural disorganization. Additionally, myocardial samples underwent histological and gene expression analyses to quantify compositional changes and mechanical testing to quantify myocardial stiffening. All findings were compared to 12 control animals. Finally, we used computational modeling to disentangle the relative importance of each stiffening mechanism. Results: First, we found that the RVs of PHT animals thickened most at the base and the free wall. Additionally, we found that PHT induced excessive collagen synthesis and microstructural disorganization, consistent with increased expression of fibrotic genes. We also found that the myocardium itself stiffened significantly. Importantly, myocardial stiffening correlated significantly with excess collagen synthesis. Finally, our model of normalized RV pressure-volume relationships predicted that myocardial stiffness contributes to RV stiffening significantly more than other mechanisms. Conclusions: In summary, we found that PHT induces wall thickening, microstructural disorganization, and myocardial stiffening. These remodeling mechanisms were both spatially and directionally dependent. Using modeling, we show that myocardial stiffness is the primary contributor to RV stiffening. Thus, myocardial stiffening may be an important predictor for PHT progression. Given the significant correlation between myocardial stiffness and collagen synthesis, collagen-sensitive imaging modalities may be useful for non-invasively estimating myocardial stiffness and predicting PHT outcomes.

Septal annular dilation in chronic ovine functional tricuspid regurgitation.

INTRODUCTION: Annular reduction with prosthetic rings represents the current surgical treatment of functional tricuspid regurgitation (FTR). However, alterations of annular geometry and dynamics associated with FTR are not well characterized. METHODS: FTR was induced in 29 adult sheep with either 8 weeks of pulmonary artery banding (PAB, n = 15) or 3 weeks of tachycardia-induced cardiomyopathy (TIC, n = 14). Eight healthy sheep served as controls (CTL). At the terminal procedure, all animals underwent sternotomy, epicardial echocardiography, and implantation of sonomicrometry crystals on the tricuspid annulus (TA) and right ventricular free wall while on cardiopulmonary bypass. Simultaneous hemodynamic, sonomicrometry, and echocardiographic data were acquired after weaning from cardiopulmonary bypass and stabilization. Annular geometry and dynamics were calculated from 3-dimensional crystal coordinates. RESULTS: Mean FTR grade (0-4) was 3.2 ± 1.2 and 3.2 ± 0.5 for PAB and TIC, respectively, with both models of FTR associated with similar degree of right ventricular dysfunction (right ventricular fractional area contraction 38 ± 7% and 37 ± 9% for PAB and TIC, respectively). Left ventricular ejection fraction was significantly reduced in TIC versus baseline (33 ± 9%, vs 58 ± 4%, P = .0001). TA area was 651 ± 109 mm2, 881 ± 242 mm2, and 995 ± 232 mm2 for CTL, FTR, and TIC, respectively (P = .006) with TA area contraction of 16.6 ± 4.2%, 11.5 ± 8.0%, and 6.0 ± 4.0%, respectively (P = .003). Septal annulus increased from 33.8 ± 3.1 mm to 39.7 ± 6.4 mm and 43.1 ± 3.2 mm for CTL, PAB, and TIC, respectively (P < .0001). CONCLUSIONS: Ovine FTR was associated with annular dilation and reduced annular area contraction. Significant dilation of septal annulus was observed in both models of FTR. As tricuspid rings do not completely stabilize the septal annulus, continued remodeling may contribute to recurrent FTR after repair.

Sex- and Age-dependent Skin Mechanics - A Detailed Look in Mice.

Skin aging is of immense societal and, thus, scientific interest. Because mechanics play a critical role in skin's function, a plethora of studies have investigated age-induced changes in skin mechanics. Nonetheless, much remains to be learned about the mechanics of aging skin. This is especially true when considering sex as a biological variable. In our work, we set out to answer some of these questions using mice as a model system. Specifically, we combined mechanical testing, histology, collagen assays, and two-photon microscopy to identify age- and sex-dependent changes in skin mechanics and to relate them to structural, microstructural, and compositional factors. Our work revealed that skin stiffness, thickness, and collagen content all decreased with age and were sex dependent. Interestingly, sex differences in stiffness were age induced. We hope our findings not only further our fundamental understanding of skin aging but also highlight both age and sex as important variables when conducting studies on skin mechanics.

The impact of thickness heterogeneity on soft tissue biomechanics: a novel measurement technique and a demonstration on heart valve tissue.

The mechanical properties of soft tissues are driven by their complex, heterogeneous composition and structure. Interestingly, studies of soft tissue biomechanics often ignore spatial heterogeneity. In our work, we are therefore interested in exploring the impact of tissue heterogeneity on the mechanical properties of soft tissues. Therein, we specifically focus on soft tissue heterogeneity arising from spatially varying thickness. To this end, our first goal is to develop a non-destructive measurement technique that has a high spatial resolution, provides continuous thickness maps, and is fast. Our secondary goal is to demonstrate that including spatial variation in thickness is important to the accuracy of biomechanical analyses. To this end, we use mitral valve leaflet tissue as our model system. To attain our first goal, we identify a soft tissue-specific contrast protocol that enables thickness measurements using a Keyence profilometer. We also show that this protocol does not affect our tissues' mechanical properties. To attain our second goal, we conduct virtual biaxial, bending, and buckling tests on our model tissue both ignoring and considering spatial variation in thickness. Thereby, we show that the assumption of average, homogeneous thickness distributions significantly alters the results of biomechanical analyses when compared to including true, spatially varying thickness distributions. In conclusion, our work provides a novel measurement technique that can capture continuous thickness maps non-invasively, at high resolution, and in a short time. Our work also demonstrates the importance of including heterogeneous thickness in biomechanical analyses of soft tissues.

Can machine learning accelerate soft material parameter identification from complex mechanical test data?

Identifying the constitutive parameters of soft materials often requires heterogeneous mechanical test modes, such as simple shear. In turn, interpreting the resulting complex deformations necessitates the use of inverse strategies that iteratively call forward finite element solutions. In the past, we have found that the cost of repeatedly solving non-trivial boundary value problems can be prohibitively expensive. In this current work, we leverage our prior experimentally derived mechanical test data to explore an alternative approach. Specifically, we investigate whether a machine learning-based approach can accelerate the process of identifying material parameters based on our mechanical test data. Toward this end, we pursue two different strategies. In the first strategy, we replace the forward finite element simulations within an iterative optimization framework with a machine learning-based metamodel. Here, we explore both Gaussian process regression and neural network metamodels. In the second strategy, we forgo the iterative optimization framework and use a stand alone neural network to predict the entire material parameter set directly from experimental results. We first evaluate both approaches with simple shear experiments on blood clot, an isotropic, homogeneous material. Next, we evaluate both approaches against simple shear and uniaxial loading experiments on right ventricular myocardium, an anisotropic, heterogeneous material. We find that replacing the forward finite element simulations with metamodels significantly accelerates the parameter identification process with excellent results in the case of blood clot, and with satisfying results in the case of right ventricular myocardium. On the other hand, we find that replacing the entire optimization framework with a neural network yielded unsatisfying results, especially for right ventricular myocardium. Overall, the importance of our work stems from providing a baseline example showing how machine learning can accelerate the process of material parameter identification for soft materials from complex mechanical data, and from providing an open access experimental and simulation dataset that may serve as a benchmark dataset for others interested in applying machine learning techniques to soft tissue biomechanics.