In situ stress estimation in quantitative micro-elastography.

In quantitative micro-elastography (QME), a pre-characterized compliant layer with a known stress-strain curve is utilized to map stress at the sample surface. However, differences in the boundary conditions of the compliant layer when it is mechanically characterized and when it is used in QME experiments lead to inconsistent stress estimation and consequently, inaccurate elasticity measurements. Here, we propose a novel in situ stress estimation method using an optical coherence tomography (OCT)-based uniaxial compression testing system integrated with the QME experimental setup. By combining OCT-measured axial strain with axial stress determined using a load cell in the QME experiments, we can estimate in situ stress for the compliant layer, more accurately considering its boundary conditions. Our proposed method shows improved accuracy, with an error below 10%, compared to 85% using the existing QME technique with no lubrication. Furthermore, demonstrations on hydrogels and cells indicate the potential of this approach for improving the characterization of the micro-scale mechanical properties of cells and their interactions with the surrounding biomaterial, which has potential for application in cell mechanobiology.

3D Volumetric Mechanosensation of MCF7 Breast Cancer Spheroids in a Linear Stiffness Gradient GelAGE.

The tumor microenvironment presents spatiotemporal shifts in biomechanical properties with cancer progression. Hydrogel biomaterials like GelAGE offer the stiffness tuneability to recapitulate dynamic changes in tumor tissues by altering photo-energy exposures. Here, a tuneable hydrogel with spatiotemporal control of stiffness and mesh-network is developed. The volume of MCF7 spheroids encapsulated in a linear stiffness gradient demonstrates an inverse relationship with stiffness (p < 0.0001). As spheroids are exposed to increased crosslinking (stiffer) and greater mechanical confinement, spheroid stiffness increases. Protein expression (TRPV4, ß1 integrin, E-cadherin, and F-actin) decreases with increasing stiffness while showing strong correlations to spheroid volume (r2  > 0.9). To further investigate the role of volume, MCF7 spheroids are grown in a soft matrix for 5 days prior to a second polymerisation which presents a stiffness gradient to equally expanded spheroids. Despite being exposed to variable stiffness, these spheroids show even protein expression, confirming volume as a key regulator. Overall, this work showcases the versatility of GelAGE and demonstrates volume expansion as a key regulator of 3D mechanosensation in MCF7 breast cancer spheroids. This platform has the potential to further investigation into the role of stiffness and dimensionality in 3D spheroid culture for other types of cancers and diseases.

A surgically optimized intraoperative poly(I:C)-releasing hydrogel prevents cancer recurrence.

Recurrences frequently occur following surgical removal of primary tumors. In many cancers, adjuvant therapies have limited efficacy. Surgery provides access to the tumor microenvironment, creating an opportunity for local therapy, in particular immunotherapy, which can induce local and systemic anti-cancer effects. Here, we develop a surgically optimized biodegradable hyaluronic acid-based hydrogel for sustained intraoperative delivery of Toll-like receptor 3 agonist poly(I:C) and demonstrate that it significantly reduces tumor recurrence after surgery in multiple mouse models. Mechanistically, poly(I:C) induces a transient interferon alpha (IFNα) response, reshaping the tumor/wound microenvironment by attracting inflammatory monocytes and depleting regulatory T cells. We demonstrate that a pre-existing IFN signature predicts response to the poly(I:C) hydrogel, which sensitizes tumors to immune checkpoint therapy. The safety, immunogenicity, and surgical feasibility are confirmed in a veterinary trial in canine soft tissue tumors. The surgically optimized poly(I:C)-loaded hydrogel provides a safe and effective approach to prevent cancer recurrence.

Subcellular mechano-microscopy: high resolution three-dimensional elasticity mapping using optical coherence microscopy.

The importance of cellular-scale mechanical properties is well-established, yet it is challenging to map subcellular elasticity in three dimensions. We present subcellular mechano-microscopy, an optical coherence microscopy (OCM)-based variant of three-dimensional (3-D) compression optical coherence elastography (OCE) that provides an elasticity system resolution of 5 × 5 × 5 µm: a 7-fold improvement in system resolution over previous OCE studies of cells. The improved resolution is achieved through a ∼5-fold improvement in optical resolution, refinement of the strain estimation algorithm, and demonstration that mechanical deformation of subcellular features provides feature resolution far greater than that demonstrated previously on larger features with diameter >250 µm. We use mechano-microscopy to image adipose-derived stem cells encapsulated in gelatin methacryloyl. We compare our results with compression OCE and demonstrate that mechano-microscopy can provide contrast from subcellular features not visible using OCE.

Three-dimensional mechanical characterization of murine skeletal muscle using quantitative micro-elastography.

Skeletal muscle function is governed by both the mechanical and structural properties of its constituent tissues, which are both modified by disease. Characterizing the mechanical properties of skeletal muscle tissue at an intermediate scale, i.e., between that of cells and organs, can provide insight into diseases such as muscular dystrophies. In this study, we use quantitative micro-elastography (QME) to characterize the micro-scale elasticity of ex vivo murine skeletal muscle in three-dimensions in whole muscles. To address the challenge of achieving high QME image quality with samples featuring uneven surfaces and geometry, we encapsulate the muscles in transparent hydrogels with flat surfaces. Using this method, we study aging and disease in quadriceps tissue by comparing normal wild-type (C57BL/6J) mice with dysferlin-deficient BLAJ mice, a model for the muscular dystrophy dysferlinopathy, at 3, 10, and 24 months of age (sample size of three per group). We observe a 77% decrease in elasticity at 24 months in dysferlin-deficient quadriceps compared to wild-type quadriceps.

Speckle-dependent accuracy in phase-sensitive optical coherence tomography.

Phase-sensitive optical coherence tomography (OCT) is used to measure motion in a range of techniques, such as Doppler OCT and optical coherence elastography (OCE). In phase-sensitive OCT, motion is typically estimated using a model of the OCT signal derived from a single reflector. However, this approach is not representative of turbid samples, such as tissue, which exhibit speckle. In this study, for the first time, we demonstrate, through theory and experiment that speckle significantly lowers the accuracy of phase-sensitive OCT in a manner not accounted for by the OCT signal-to-noise ratio (SNR). We describe how the inaccuracy in speckle reduces phase difference sensitivity and introduce a new metric, speckle brightness, to quantify the amount of constructive interference at a given location in an OCT image. Experimental measurements show an almost three-fold degradation in sensitivity between regions of high and low speckle brightness at a constant OCT SNR. Finally, we apply these new results in compression OCE to demonstrate a ten-fold improvement in strain sensitivity, and a five-fold improvement in contrast-to-noise by incorporating independent speckle realizations. Our results show that speckle introduces a limit to the accuracy of phase-sensitive OCT and that speckle brightness should be considered to avoid erroneous interpretation of experimental data.

Analysis of sensitivity in quantitative micro-elastography.

Quantitative micro-elastography (QME), a variant of compression optical coherence elastography (OCE), is a technique to image tissue elasticity on the microscale. QME has been proposed for a range of applications, most notably tumor margin assessment in breast-conserving surgery. However, QME sensitivity, a key imaging metric, has yet to be systematically analyzed. Consequently, it is difficult to optimize imaging performance and to assess the potential of QME in new application areas. To address this, we present a framework for analyzing sensitivity that incorporates the three main steps in QME image formation: mechanical deformation, its detection using optical coherence tomography (OCT), and signal processing used to estimate elasticity. Firstly, we present an analytical model of QME sensitivity, validated by experimental data, and demonstrate that sub-kPa elasticity sensitivity can be achieved in QME. Using silicone phantoms, we demonstrate that sensitivity is dependent on friction, OCT focus depth, and averaging methods in signal processing. For the first time, we show that whilst lubrication of layer improves accuracy by reducing surface friction, it reduces sensitivity due to the time-dependent effect of lubricant exudation from the layer boundaries resulting in increased friction. Furthermore, we demonstrate how signal processing in QME provides a trade-off between sensitivity and resolution that can be used to optimize imaging performance. We believe that our framework to analyze sensitivity can help to sustain the development of QME and, also, that it can be readily adapted to other OCE techniques.

Strain and elasticity imaging in compression optical coherence elastography: The two-decade perspective and recent advances.

Quantitative mapping of deformation and elasticity in optical coherence tomography has attracted much attention of researchers during the last two decades. However, despite intense effort it took ~15 years to demonstrate optical coherence elastography (OCE) as a practically useful technique. Similarly to medical ultrasound, where elastography was first realized using the quasi-static compression principle and later shear-wave-based systems were developed, in OCE these two approaches also developed in parallel. However, although the compression OCE (C-OCE) was proposed historically earlier in the seminal paper by J. Schmitt in 1998, breakthroughs in quantitative mapping of genuine local strains and the Young's modulus in C-OCE have been reported only recently and have not yet obtained sufficient attention in reviews. In this overview, we focus on underlying principles of C-OCE; discuss various practical challenges in its realization and present examples of biomedical applications of C-OCE. The figure demonstrates OCE-visualization of complex transient strains in a corneal sample heated by an infrared laser beam.

Three-dimensional imaging of cell and extracellular matrix elasticity using quantitative micro-elastography.

Recent studies in mechanobiology have revealed the importance of cellular and extracellular mechanical properties in regulating cellular function in normal and disease states. Although it is established that cells should be investigated in a three-dimensional (3-D) environment, most techniques available to study mechanical properties on the microscopic scale are unable to do so. In this study, for the first time, we present volumetric images of cellular and extracellular elasticity in 3-D biomaterials using quantitative micro-elastography (QME). We achieve this by developing a novel strain estimation algorithm based on 3-D linear regression to improve QME system resolution. We show that QME can reveal elevated elasticity surrounding human adipose-derived stem cells (ASCs) embedded in soft hydrogels. We observe, for the first time in 3-D, further elevation of extracellular elasticity around ASCs with overexpressed TAZ; a mechanosensitive transcription factor which regulates cell volume. Our results demonstrate that QME has the potential to study the effects of extracellular mechanical properties on cellular functions in a 3-D micro-environment.

Enhancing Resistance of Silk Fibroin Material to Enzymatic Degradation by Cross-Linking Both Crystalline and Amorphous Domains.

Silk fibroin (SF) membranes are finding widespread use as biomaterial scaffolds in a range of tissue engineering applications. The control over SF scaffold degradation kinetics is usually driven by the proportion of SF crystalline domains in the formulation, but membranes with a high ß-sheet content are brittle and still contain amorphous domains, which are highly susceptible to enzymatic degradation. In this work, photo-cross-linking of SF using a ruthenium-based method, and with the addition of glycerol, was used to generate robust and flexible SF membranes for long-term tissue engineering applications requiring slow degradation of the scaffolds. The resulting mechanical properties, protein secondary structure, and degradation rate were investigated. In addition, the cytocompatibility and versatility of porous micropatterning of SF films were assessed. The photo-cross-linking reduced the enzymatic degradation of SF in vitro without interfering with the ß-sheet content of the SF material, while adding glycerol to the composition grants flexibility to the membranes. By combining these methods, the membrane resistance to protease degradation was significantly enhanced compared to either method alone, and the SF mechanical properties were not impaired. We hypothesize that photo-cross-linking protects the SF amorphous regions from enzymatic degradation and complements the natural protection offered by ß-sheets in the crystalline region. Overall, this approach presents broad utility in tissue engineering applications that require a long-term degradation profile and mechanical support.

Volume Adaptation Controls Stem Cell Mechanotransduction.

Recent studies have found discordant mechanosensitive outcomes when comparing 2D and 3D, highlighting the need for tools to study mechanotransduction in 3D across a wide spectrum of stiffness. A gelatin methacryloyl (GelMA) hydrogel with a continuous stiffness gradient ranging from 5 to 38 kPa was developed to recapitulate physiological stiffness conditions. Adipose-derived stem cells (ASCs) were encapsulated in this hydrogel, and their morphological characteristics and expression of both mechanosensitive proteins (Lamin A, YAP, and MRTFa) and differentiation markers (PPARγ and RUNX2) were analyzed. Low-stiffness regions (∼8 kPa) permitted increased cellular and nuclear volume and enhanced mechanosensitive protein localization in the nucleus. This trend was reversed in high stiffness regions (∼30 kPa), where decreased cellular and nuclear volumes and reduced mechanosensitive protein nuclear localization were observed. Interestingly, cells in soft regions exhibited enhanced osteogenic RUNX2 expression, while those in stiff regions upregulated the adipogenic regulator PPARγ, suggesting that volume, not substrate stiffness, is sufficient to drive 3D stem cell differentiation. Inhibition of myosin II (Blebbistatin) and ROCK (Y-27632), both key drivers of actomyosin contractility, resulted in reduced cell volume, especially in low-stiffness regions, causing a decorrelation between volume expansion and mechanosensitive protein localization. Constitutively active and inactive forms of the canonical downstream mechanotransduction effector TAZ were stably transfected into ASCs. Activated TAZ resulted in higher cellular volume despite increasing stiffness and a consistent, stiffness-independent translocation of YAP and MRTFa into the nucleus. Thus, volume adaptation as a function of 3D matrix stiffness can control stem cell mechanotransduction and differentiation.

Analysis of spatial resolution in phase-sensitive compression optical coherence elastography.

Optical coherence elastography (OCE) is emerging as a method to image the mechanical properties of tissue on the microscale. However, the spatial resolution, a main advantage of OCE, has not been investigated and is not trivial to evaluate. To address this, we present a framework to analyze resolution in phase-sensitive compression OCE that incorporates the three main determinants of resolution: mechanical deformation of the sample, detection of this deformation using optical coherence tomography (OCT), and signal processing to estimate local axial strain. We demonstrate for the first time, through close correspondence between experiment and simulation of structured phantoms, that resolution in compression OCE is both spatially varying and sample dependent, which we link to the discrepancies between the model of elasticity and the mechanical deformation of the sample. We demonstrate that resolution is dependent on factors such as feature size and mechanical contrast. We believe that the analysis of image formation provided by our framework can expedite the development of compression OCE.