Properties Of Soft Biological Tissues Research Articles

A Self-Optimized Machine Learning Approach for Constitutive Parameters Identification of Aortic Walls

The accurate identification of constitutive parameters is considered the key challenge for the study of mechanical properties of biological soft tissues. The popular machine learning (ML)-based inverse identification frameworks always require large amounts of training datasets. This work proposes an ML framework called self-optimized ML for accurate identifying the constitutive parameters of aortic walls under few training datasets conditions. The self-optimized ML includes three steps: Step 1: the forward physical FEM models first simulate the nonlinear deformation of aortic walls subject to uniaxial tension tests and are used to establish the nonlinear relationship datasets, Step 2: the carefully designed inverse random forest (RF) of the ML model can offer rapid identification by learning the established nonlinear relationship datasets, and Step 3: forward physical FEM models are recalled to evaluate the error between the identification results in Step 2 and real values, and then the accuracy are embedded into RF for guiding optimization directions to ensure that the final identification results are accurately and physically reasonable. The accuracy and robustness validation of proposed framework was conducted by constitutive parameters identification of uniaxial tension experiment samples of bovine aortic walls. The approach proposed achieves the R-squared exceeding 96.90% in longitudinal direction and 98.30% in circumferential direction, which is better than directly ML approach and gradient-based approach under the same amounts of datasets, respectively. The comparison results show that self-optimized ML can not only achieve accurate identification of the constitutive parameters of aortic walls, but also can decrease the identification results dependency of the initial number of sampling data effectively. The identification approach developed herein provides a common and convenient framework for constitutive parameters identification of biological soft tissues.

Shear wave speeds in a nearly incompressible fibrous material with two unequal fiber families.

The mechanical properties of soft biological tissues can be characterized non-invasively by magnetic resonance elastography (MRE). In MRE, shear wave fields are induced by vibration, imaged by magnetic resonance imaging, and inverted to estimate tissue properties in terms of the parameters of an underlying material model. Most MRE studies assume an isotropic material model; however, biological tissue is often anisotropic with a fibrous structure, and some tissues contain two or more families of fibers-each with different orientations and properties. Motivated by the prospect of using MRE to characterize such tissues, this paper describes the propagation of shear waves in soft fibrous material with two unequal fiber families. Shear wave speeds are expressed in terms of material parameters, and the effect of each parameter on the shear wave speeds is investigated. Analytical expressions of wave speeds are confirmed by finite element simulations of shear wave transmission with various polarization directions. This study supports the feasibility of estimating parameters of soft fibrous tissues with two unequal fiber families in vivo from local shear wave speeds and advances the prospects for the mechanical characterization of such biological tissues by MRE.

Impact of cryopreservation on elastomuscular artery mechanics

Low temperatures slow or halt undesired biological and chemical processes, protecting cells, tissues, and organs during storage. Cryopreservation techniques, including controlled media exchange and regulated freezing conditions, aim to mitigate the physical consequences of freezing. Dimethyl sulfoxide (DMSO), for example, is a penetrating cryoprotecting agent (CPA) that minimizes ice crystal growth by replacing intracellular water, while polyvinyl alcohol (PVA) is a nonpenetrating CPA that prevents recrystallization during thawing. Since proteins and ground substance dominate the passive properties of soft biological tissues, we studied how different freezing rates, storage temperatures, storage durations, and the presence of cryoprotecting agents (5% [v/v] DMSO + 1 mg/mL PVA) impact the histomechanical properties of the internal thoracic artery (ITA), a clinically relevant blood vessel with both elastic and muscular characteristics. Remarkably, biaxial mechanical analyses failed to reveal significant differences among the ten groups tested, suggesting that mechanical properties are virtually independent of the cryopreservation technique. Scanning electron microscopy revealed minor CPA-independent delamination in rapidly frozen samples, while cryoprotected ITAs had better post-thaw viability than their unprotected counterparts using methyl thiazole-tetrazolium (MTT) metabolic assays, especially when frozen at a controlled rate. These results can be used to inform ongoing and future studies in vascular engineering, physiology, and mechanics.

In situ sensing physiological properties of biological tissues using wireless miniature soft robots.

Implanted electronic sensors, compared with conventional medical imaging, allow monitoring of advanced physiological properties of soft biological tissues continuously, such as adhesion, pH, viscoelasticity, and biomarkers for disease diagnosis. However, they are typically invasive, requiring being deployed by surgery, and frequently cause inflammation. Here we propose a minimally invasive method of using wireless miniature soft robots to in situ sense the physiological properties of tissues. By controlling robot-tissue interaction using external magnetic fields, visualized by medical imaging, we can recover tissue properties precisely from the robot shape and magnetic fields. We demonstrate that the robot can traverse tissues with multimodal locomotion and sense the adhesion, pH, and viscoelasticity on porcine and mice gastrointestinal tissues ex vivo, tracked by x-ray or ultrasound imaging. With the unprecedented capability of sensing tissue physiological properties with minimal invasion and high resolution deep inside our body, this technology can potentially enable critical applications in both basic research and clinical practice.

A magnetically actuated, optically sensed tensile testing method for mechanical characterization of soft biological tissues.

Mechanical properties of soft biological tissues play a critical role in physiology and disease, affecting cell behavior and fate decisions and contributing to tissue development, maintenance, and repair. Limitations of existing tools prevent a comprehensive characterization of soft tissue biomechanics, hindering our understanding of these fundamental processes. Here, we develop an instrument for high-fidelity uniaxial tensile testing of soft biological tissues in controlled environmental conditions, which is based on the closed-loop interaction between an electromagnetic actuator and an optical strain sensor. We first validate the instrument using synthetic elastomers characterized via conventional methods; then, we leverage the proposed device to investigate the mechanical properties of murine esophageal tissue and, individually, of each of its constitutive layers, namely, the epithelial, connective, and muscle tissues. The enhanced reliability of this instrument makes it an ideal platform for future wide-ranging studies of the mechanics of soft biological tissues.

Statistical analysis of mechanical properties of biological soft tissue under quasi-static mechanical loading

The mechanical properties of biological soft tissues are inextricably linked to the field of health care, and their mechanical properties can be important indicators for diagnosing and detecting diseases; they can also be used to analyze the causes of organ diseases from a pathological point of view and thus guide the deployment of medical solutions. As an effective method to characterize the mechanical properties of materials, mechanical loading experiments have been successfully applied to the mechanical properties of materials, including tension, compression, pure shear, and so on. Under quasi-static loading, when the material is a biological soft tissue material between a solid and an ideal fluid, its viscoelastic properties strongly respond to the force stimulus, and the stress-strain-time in the elastic phase will have obvious disturbance characteristics. Therefore, the existing statistical methods are often difficult to quantitatively describe the mechanical properties of materials. Therefore, this study proposes an Interval Capture Point based on the principle of integration. The experimental data based on this method can characterize its nonlinear mechanical properties well, especially when the loading speed is extremely low and the soft materials show strong disturbance characteristics. The proposed method can still accurately characterize the hyperelastic and viscoelastic properties of the mechanical properties of biological soft tissues under quasi-static loading.

Cerebral tomoelastography based on multifrequency MR elastography in two and three dimensions.

Purpose: Magnetic resonance elastography (MRE) generates quantitative maps of the mechanical properties of biological soft tissues. However, published values obtained by brain MRE vary largely and lack detail resolution, due to either true biological effects or technical challenges. We here introduce cerebral tomoelastography in two and three dimensions for improved data consistency and detail resolution while considering aging, brain parenchymal fraction (BPF), systolic blood pressure, and body mass index (BMI). Methods: Multifrequency MRE with 2D- and 3D-tomoelastography postprocessing was applied to the brains of 31 volunteers (age range: 22-61years) for analyzing the coefficient of variation (CV) and effects of biological factors. Eleven volunteers were rescanned after 1day and 1year to determine intraclass correlation coefficient (ICC) and identify possible long-term changes. Results: White matter shear wave speed (SWS) was slightly higher in 2D-MRE (1.28 ± 0.02m/s) than 3D-MRE (1.22 ± 0.05m/s, p < 0.0001), with less variation after 1day in 2D (0.33 ± 0.32%) than in 3D (0.96 ± 0.66%, p = 0.004), which was also reflected in a slightly lower CV and higher ICC in 2D (1.84%, 0.97 [0.88-0.99]) than in 3D (3.89%, 0.95 [0.76-0.99]). Remarkably, 3D-MRE was sensitive to a decrease in white matter SWS within only 1year, whereas no change in white matter volume was observed during this follow-up period. Across volunteers, stiffness correlated with age and BPF, but not with blood pressure and BMI. Conclusion: Cerebral tomoelastography provides high-resolution viscoelasticity maps with excellent consistency. Brain MRE in 2D shows less variation across volunteers in shorter scan times than 3D-MRE, while 3D-MRE appears to be more sensitive to subtle biological effects such as aging.

Viscoelastic Characterization of Soft Tissue-Mimicking Gelatin Phantoms using Indentation and Magnetic Resonance Elastography.

Characterization of biomechanical properties of soft biological tissues is important to understand the tissue mechanics and explore the biomechanics-related mechanisms of disease, injury, and development. The mechanical testing method is the most straightforward way for tissue characterization and is considered as verification for in vivo measurement. Among the many ex vivo mechanical testing techniques, the indentation test provides a reliable way, especially for samples that are small, hard to fix, and viscoelastic such as brain tissue. Magnetic resonance elastography (MRE) is a clinically used method to measure the biomechanical properties of soft tissues. Based on shear wave propagation in soft tissues recorded using MRE, viscoelastic properties of soft tissues can be estimated in vivo based on wave equation. Here, the viscoelastic properties of gelatin phantoms with two different concentrations were measured by MRE and indentation. The protocols of phantom fabrication, testing, and modulus estimation have been presented.

An anti-freezing and strong wood-derived hydrogel for high-performance electronic skin and wearable sensing

Inspired by the highly aligned, well-ordered microstructure, and anisotropic mechanical properties of biological soft tissues, artificial electronic skins (e-skins) have been widely reported in recent years. However, challenges remain in achieving green, high mechanical properties, and multifunctionality simultaneously. In this work, we present a smart e-skin system with an anisotropic structure that couples a cellulose scaffold (CS) derived from natural wood with a polyvinyl alcohol (PVA)/MXene nanosheets (PM) network through a facile freeze-thawing process, featuring high toughness and excellent conductivity. With the addition of a biocompatible cryo-protectant, the smart e-skin exhibit ambient stability, anti-freezing properties, and moisturizing capability. The strong cross-linking and bonding between the 3D hierarchical CS and PM polymer network enhancing the mechanical strength of the e-skin in a specific direction, and the tensile strength along the longitudinal direction reached 12.01 MPa. The wood-derived hydrogel e-skin is 75 times and 23 times stronger than the isotropic cellulose hydrogel and pure PVA hydrogel. The soft PM polymer network endows the rigid cellulose skeleton with outstanding flexibility. Importantly, the e-skin with remarkable electromechanical sensing can realize the real-time monitoring of various human motions. In addition, the e-skin can also realize the private information transmission and even object recognition in aquatic environments. This study provides a facile strategy for developing next-generation wearable devices and multifunctional e-skin systems with bionic characteristics.

Improved two-point frequency shift power method for measurement of shear wave attenuation

Quantitative assessment of mechanical properties of biological soft tissues is frequently evaluated using a noninvasive modality, called ultrasound shear wave elastography (SWE). SWE typically exerts an acoustic radiation force (ARF) to produce shear waves propagating in the lateral direction for which velocities and attenuations are measured. The tissue viscoelasticity is commonly studied by investigating the shear wave phase velocity curves. Viscoelastic tissue properties can also be characterized through utilizing various shear wave attenuation techniques. In this study, we propose an improved method for measuring the shear wave attenuation, called two-point frequency shift power (2P-FSP), which is an improved version of the two-point frequency shift (2P-FS) method. The technique is fully data driven and does not use a rheological model for mathematical modeling. The 2P-FSP method utilizes the power spectra frequency shift of shear waves measured at two spatial positions, which provides robustness to noise. The conceptual basis for the 2P-FSP is provided and tested with numerical and experimental data. We investigated how the location of the first signal and the distance interval between the two locations influence the shear wave attenuation measurement in the 2P-FSP technique. We utilized the 2P-FSP method on numerical phantom data generated using a finite-difference-based method in tissue-mimicking viscoelastic media. Moreover, we tested the 2P-FSP method with data from custom-made tissue-mimicking viscoelastic phantom experiments, and ex vivo porcine liver. We compared results from the proposed technique with results from 2P-FS and analytical values in the case of simulations. The results showed that the 2P-FSP method provides improved results over the 2P-FS technique for lower signal-to-noise ratio (SNR) and locations farther from the push location considered, and can be used to measure attenuation of viscoelastic soft tissues.

Predictive constitutive modelling of arteries by deep learning

The constitutive modelling of soft biological tissues has rapidly gained attention over the last 20 years. Current constitutive models can describe the mechanical properties of arterial tissue. Predicting these properties from microstructural information, however, remains an elusive goal. To address this challenge, we are introducing a novel hybrid modelling framework that combines advanced theoretical concepts with deep learning. It uses data from mechanical tests, histological analysis and images from second-harmonic generation. In this first proof of concept study, our hybrid modelling framework is trained with data from 27 tissue samples only. Even such a small amount of data is sufficient to be able to predict the stress–stretch curves of tissue samples with a median coefficient of determination of R2 = 0.97 from microstructural information, as long as one limits the scope to tissue samples whose mechanical properties remain in the range commonly encountered. This finding suggests that deep learning could have a transformative impact on the way we model the constitutive properties of soft biological tissues.

Viscoelasticity Imaging of Biological Tissues and Single Cells Using Shear Wave Propagation

Changes in biomechanical properties of biological soft tissues are often associated with physiological dysfunctions. Since biological soft tissues are hydrated, viscoelasticity is likely suitable to represent its solid-like behavior using elasticity and fluid-like behavior using viscosity. Shear wave elastography is a non-invasive imaging technology invented for clinical applications that has shown promise to characterize various tissue viscoelasticity. It is based on measuring and analyzing velocities and attenuations of propagated shear waves. In this review, principles and technical developments of shear wave elastography for viscoelasticity characterization from organ to cellular levels are presented, and different imaging modalities used to track shear wave propagation are described. At a macroscopic scale, techniques for inducing shear waves using an external mechanical vibration, an acoustic radiation pressure or a Lorentz force are reviewed along with imaging approaches proposed to track shear wave propagation, namely ultrasound, magnetic resonance, optical, and photoacoustic means. Then, approaches for theoretical modeling and tracking of shear waves are detailed. Following it, some examples of applications to characterize the viscoelasticity of various organs are given. At a microscopic scale, a novel cellular shear wave elastography method using an external vibration and optical microscopy is illustrated. Finally, current limitations and future directions in shear wave elastography are presented.

Preparation and characterization of polyvinyl alcohol/ sodium alginate/carboxymethyl cellulose composite hydrogels with oriented structure

ABSTRACT In order to control complex motion behavior in organisms, most biological tissues have highly oriented structures and anisotropic mechanical properties, such as articular cartilage, muscle, skin and blood vessel. In this study, inspired by the directional structure and excellent mechanical properties of biological soft tissues, polyvinyl alcohol/carboxymethyl cellulose hydrogels with different contents of sodium alginate were prepared by combining freeze-thaw and prestretching methods. Compared with SEM images without pre-stretch hydrogels, there are obvious ordered pore structures in the pre-stretch samples along the tensile direction, and the network structure becomes denser. XRD and FTI R results indicate that the introduction of SA and CMC increases the number of internal hydrogen bond and forms new covalent bonds. The tensile strength of the hydrogel without annealing and stretching treatments is only 0.41MPa. After annealing and stretching treatments, the tensile strength of the hydrogel is increased to 0.93MPa. Furthermore, the creep deformation of hydrogel was reduced from 1.08 mm to 0.27 mm by annealing and stretching treatments. To sum up, these results suggested that PVA/SA/CMC composite hydrogels with oriented structure might have potential applications in soft tissue repair and other biomaterials.

Measuring the Hyperelastic Response of Porcine Liver Tissues In-Vitro Using Controlled Cavitation Rheology

Measuring the mechanical properties of soft biological tissues in-vitro by using conventional methods (e.g. tension, compression, or indentation) is prone to external testing and sample preparation factors. For example, sample slippage affects the measurement accuracy of mechanical properties of soft biological tissues. In addition, samples have to go through a complex cutting process to be prepared in specific shapes, which increases the post-mortem time spent before testing. The purpose of this study is to investigate the capability of a new technique to measure the mechanics of soft biological tissues without experiencing the conventional challenges. It measures the mechanical behavior of soft materials by introducing and expanding spherical cavity deformations within materials’ internal structure while generating two stresses simultaneously, radial and hoop stresses. Two porcine livers were tested. The experimental data were used to calibrate the material parameters of three hyperelastic models, namely: Yeoh, Arruda-Boyce, and Ogden. Numerical simulations were performed to validate the material parameters. Also, Computed Tomography (CT) imaging technology was used to verify the configuration of the cavity deformations. The outcome of the numerical simulations showed that hyperelastic models were able to predict the material response to cavity loading. In addition, CT imaging confirmed the spherical configuration of the applied deformations. From the experimental results, numerical simulations and the CT imaging, it can be concluded that the cavity expansion test is capable of measuring the mechanics of soft biological tissues without experiencing the difficulties encountered in conventional techniques.

Temperature Elevation in an Instrumented Phantom Insonated by B-Mode Imaging, Pulse Doppler and Shear Wave Elastography

Diagnostic ultrasound is the gold standard for obstetric scanning and one of the most important imaging techniques for perinatal and neonatal monitoring and diagnosis. Ultrasound provides detailed real-time anatomic information, including blood flow measurements and tissue elasticity. The latter is provided through various techniques including shear wave elastography (SWE). SWE is increasingly used in many areas of medicine, especially in detection and diagnosis of breast, thyroid and prostate cancers and liver disease. More recently, SWE has found application in gynaecology and obstetrics. This method mimics manual palpation, revealing the elastic properties of soft biological tissues. Despite its rising potential and expanding clinical interest in its use in obstetrics and gynaecology (such as for assessment of cervical ripening or organ development and structure during pregnancy), its effects on and potential risks to the developing fetus remain unknown. Risks should be evaluated by regulatory bodies before recommendations are made on the use of SWE. Because ultrasound is known to produce thermal and mechanical effects, this study measured the temperature increase caused by B-mode, pulse Doppler (PD) and SWE, using an instrumented phantom with 11 embedded thermocouples. Experiments were performed with an Aixplorer diagnostic ultrasound system (Supersonic Imagine, Aix-en-Provence, France). As expected, the greatest heating was detected by the thermocouple closest to the surface in contact with the transducer (2.9°C for SWE, 1.2°C for PD, 0.7°C for B-mode after 380-s excitation). Both conduction from the transducer face and direct heating owing to ultrasound waves contribute to temperature increase in the phantom with SWE associated with a larger temperature increase than PD and B-mode. This article offers a methodological approach and reference data for future safety studies, as well as initial recommendations about SWE safety in obstetrics and gynaecology.

Characterization of the Nonlinear Biaxial Mechanical Behavior of Human Ureter Using Constitutive Modeling and Artificial Neural Networks

Characterization of the mechanical properties of soft biological tissues is a fundamental issue in a variety of medical applications. As such, constitutive modeling of biological tissues that serves to establish a relationship between the kinematic variables has been used to formulate the tissue’s mechanical response under various loading conditions. However, the validation of the developed analytical and numerical models is accompanied by a length of computation time. Hence, the need for new advantageous methods like artificial intelligence (AI), aiming at minimizing the computation time for real-time applications such as in robotic-assisted surgery, sounds crucial. In this study, at first, the mechanical nonlinear characteristics of human ureter were obtained from planar biaxial test data, in which the examined specimens were simultaneously loaded along their circumferential and longitudinal directions. To do so, the biaxial stress-strain data was used to fit the well-known Fung and Holzapfel-Delfino hyperelastic functions using the genetic optimization algorithm. Next, the potential of Artificial Neural Networks (ANN), as an alternative method for prediction of the mechanical response of the tissue was evaluated such that, multilayer perceptron feedforward neural network with different architectures was designed and implemented and then, trained with the same experimental data. The results showed both approaches were practically able to predict the ureter nonlinearity and in particular, the ANN model can follow up the tissue nonlinearity during the entire loading phase in both low and high strain amplitudes (RMSE<0.02). Such results confirmed that neural networks can be a reliable alternative for modeling the nonlinear mechanical behavior of soft biological tissues.

Non-minimum phase viscoelastic properties of soft biological tissues

Understanding the viscoelastic properties of biological tissues is important because they can reveal tissue structure. This study analyzes the viscoelastic properties of soft biological tissues using a fractional dynamics model. We conducted a dynamic viscoelastic test on several porcine samples, i.e., liver, breast, and skeletal muscle tissues, using a plate–plate rheometer. We found that some soft biological tissues have non-minimum phase properties, i.e., the relationship between compliance and phase delay is not uniquely related to the non-integer derivative order in the fractional dynamics model. The experimental results show that the actual phase delay is larger than that estimated from compliance. We propose an empirical model to represent these non-minimum phase properties; a fractional Maxwell model with the fractional Hilbert transform term is proposed. The model and experimental results were highly correlated in terms of compliance and phase diagrams, and complex mechanical impedance. We also show that the amount of additional phase delay, defined as the increase in actual phase delay compared to that estimated from compliance, differs with tissue type.

Acoustic radiation force optical coherence elastography for evaluating mechanical properties of soft condensed matters and its biological applications.

Evaluating mechanical properties of biological soft tissues and viscous mucus is challenging because of complicated dynamic behaviors. Soft condensed matter models have been successfully used to explain a number of dynamical behaviors. Here, we reported that optical coherence elastography (OCE) is capable of quantifying mechanical properties of soft condensed matters, micellar fluids. A 7.5 MHz focused transducer was utilized to generate acoustic radiation force exerted on the surface of soft condensed matters in order to produce Rayleigh waves. The waves were recorded by optical coherence tomography (OCT). The Kelvin-Voigt model was adopted to evaluate shear modulus and loss modulus of soft condensed matters. The results reported that various concentrations of micellar fluids can provide reasonable ranges of elasticity from 65.71 to 428.78 Pa and viscosity from 0.035 to 0.283 Pa·s, which are close to ranges for actual biological samples, like mucus. OCE might be a promising tool to differentiate pathologic mucus samples from healthy cases as advanced applications in the future.

Investigating the Effects of Mechanical Stimulation on Retinal Ganglion Cell Spontaneous Spiking Activity.

Mechanical forces are increasingly recognized as major regulators of several physiological processes at both the molecular and cellular level; therefore, a deep understanding of the sensing of these forces and their conversion into electrical signals are essential for studying the mechanosensitive properties of soft biological tissues. To contribute to this field, we present a dual-purpose device able to mechanically stimulate retinal tissue and to record the spiking activity of retinal ganglion cells (RGCs). This new instrument relies on combining ferrule-top micro-indentation, which provides local measurements of viscoelasticity, with high-density multi-electrode array (HD-MEAs) to simultaneously record the spontaneous activity of the retina. In this paper, we introduce this instrument, describe its technical characteristics, and present a proof-of-concept experiment that shows how RGC spiking activity of explanted mice retinas respond to mechanical micro-stimulations of their photoreceptor layer. The data suggest that, under specific conditions of indentation, the retina perceive the mechanical stimulation as modulation of the visual input, besides the longer time-scale of activation, and the increase in spiking activity is not only localized under the indentation probe, but it propagates across the retinal tissue.

Micro-indentation and optical coherence tomography for the mechanical characterization of embryos: Experimental setup and measurements on chicken embryos

The investigation of the mechanical properties of embryos is expected to provide valuable information on the phenomenology of morphogenesis. It is thus believed that, by mapping the viscoelastic features of an embryo at different stages of growth, it may be possible to shed light on the role of mechanics in embryonic development. To contribute to this field, we present a new instrument that can determine spatiotemporal distributions of mechanical properties of embryos over a wide area and with unprecedented accuracy. The method relies on combining ferrule-top micro-indentation, which provides local measurements of viscoelasticity, with Optical Coherence Tomography, which can reveal changes in tissue morphology and help the user identify the indentation point. To prove the working principle, we have collected viscoelasticity maps of fixed and live HH11-HH12 chicken embryos. Our study shows that the instrument can reveal correlations between tissue morphology and mechanical behavior. Statement of SignificanceLocal mechanical properties of soft biological tissue play a crucial role in several biological processes, including cell differentiation, cell migration, and body formation; therefore, measuring tissue properties at high resolution is of great interest in biology and tissue engineering. To provide an efficient method for the biomechanical characterization of soft biological tissues, we introduce a new tool in which the combination of non-invasive Optical Coherence Tomography imaging and depth-controlled indentation measurements allows one to map the viscoelastic properties of biological tissue and investigate correlations between local mechanical features and tissue morphology with unprecedented resolution.