A novel stress sensor enables accurate estimation of micro-scale tissue mechanics in quantitative micro-elastography.

Quantitative micro-elastography (QME) is a compression-based optical coherence elastography technique enabling the estimation of tissue mechanical properties on the micro-scale. QME utilizes a compliant layer as an optical stress sensor, placed between an imaging window and tissue, providing quantitative estimation of elasticity. However, the implementation of the layer is challenging and introduces unpredictable friction conditions at the contact boundaries, deteriorating the accuracy and reliability of elasticity estimation. This has largely limited the use of QME to ex vivo studies and is a barrier to clinical translation. In this work, we present a novel implementation by affixing the stress sensing layer to the imaging window and optimizing the layer thickness, enhancing the practical use of QME for in vivo applications by eliminating the requirement for manual placement of the layer, and significantly reducing variations in the friction conditions, leading to substantial improvement in the accuracy and repeatability of elasticity estimation. We performed a systematic validation of the integrated layer, demonstrating >30% improvement in sensitivity and the ability to provide mechanical contrast in a mechanically heterogeneous phantom. In addition, we demonstrate the ability to obtain accurate estimation of elasticity (<6% error compared to <14% achieved using existing QME) in homogeneous phantoms with mechanical properties ranging from 40 to 130 kPa. Furthermore, we show the integrated layer to be more robust, exhibiting increased temporal stability, as well as improved conformity to variations in sample surface topography, allowing for accurate estimation of elasticity over acquisition times 3× longer than current methods. Finally, when applied to ex vivo human breast tissue, we demonstrate the ability to distinguish between healthy and diseased tissue features, such as stroma and cancer, confirmed by co-registered histology, showcasing the potential for routine use in biomedical applications.

Multimodal three-dimensional characterization of murine skeletal muscle micro-scale elasticity, structure, and composition: Impact of dysferlinopathy, Duchenne muscular dystrophy, and age on three hind-limb muscles.

Skeletal muscle tissue function is governed by the mechanical properties and organization of its components, including myofibers, extracellular matrix, and adipose tissue, which can be modified by the onset and progression of many disorders. This study used a novel combination of quantitative micro-elastography and clearing-enhanced three-dimensional (3D) microscopy to assess 3D micro-scale elasticity and micro-architecture of muscles from two muscular dystrophies: dysferlinopathy and Duchenne muscular dystrophy, using male BLA/J and mdx mice, respectively, and their wild-type (WT) controls. We examined three muscles with varying proportions of slow- and fast-twitch myofibers: the soleus (predominantly slow), extensor digitorum longus (EDL; fast), and quadriceps (mixed), from BLA/J and WTBLA/J mice aged 3, 10, and 24 months, and mdx and WTmdx mice aged 10 months. Both dysferlin deficiency and age reduced the elasticity and variability of elasticity of the soleus and quadriceps, but not EDL. Overall, the BLA/J soleus was 20% softer than WT and less mechanically heterogeneous (-14% in standard deviation of elasticity). The BLA/J quadriceps at 24 months was 72% softer than WT and less mechanically heterogeneous (-59% in standard deviation), with substantial adipose tissue accumulation. While mdx muscles did not differ quantitatively from WT, regional heterogeneity was evident in micro-scale elasticity and micro-architecture of quadriceps (e.g., 11.2 kPa in a region with marked pathology vs 3.8 kPa in a less affected area). These results demonstrate differing biomechanical changes in hind-limb muscles of two distinct muscular dystrophies, emphasizing the potential for this novel multimodal technique to identify important differences between various myopathies.

Multimodal mechano-microscopy reveals mechanical phenotypes of breast cancer spheroids in three dimensions.

Cancer cell invasion relies on an equilibrium between cell deformability and the biophysical constraints imposed by the extracellular matrix (ECM). However, there is little consensus on the nature of the local biomechanical alterations in cancer cell dissemination in the context of three-dimensional (3D) tumor microenvironments (TMEs). While the shortcomings of two-dimensional (2D) models in replicating in situ cell behavior are well known, 3D TME models remain underutilized because contemporary mechanical quantification tools are limited to surface measurements. Here, we overcome this major challenge by quantifying local mechanics of cancer cell spheroids in 3D TMEs. We achieve this using multimodal mechano-microscopy, integrating optical coherence microscopy-based elasticity imaging with confocal fluorescence microscopy. We observe that non-metastatic cancer spheroids show no invasion while showing increased peripheral cell elasticity in both stiff and soft environments. Metastatic cancer spheroids, however, show ECM-mediated softening in a stiff microenvironment and, in a soft environment, initiate cell invasion with peripheral softening associated with early metastatic dissemination. This exemplar of live-cell 3D mechanotyping supports that invasion increases cell deformability in a 3D context, illustrating the power of multimodal mechano-microscopy for quantitative mechanobiology in situ.

Full-field optical coherence microscopy enables high-resolution label-free imaging of the dynamics of live mouse oocytes and early embryos.

High quality label-free imaging of oocytes and early embryos is essential for accurate assessment of their developmental potential, a key element of assisted reproduction procedures. To achieve this goal, we propose full-field optical coherence microscopy (FF-OCM), constructed as a compact module fully integrated with a commercial wide-field fluorescence microscope. Our system achieves optical sectioning in wide-field, high in-plane resolution of 0.5 µm, and high sensitivity to backscattered light. To demonstrate its imaging capabilities, we study live mouse oocytes and embryos at all important stages of meiotic maturation and early embryogenesis. Our system enables visualization of intracellular structures, which are not visible in common bright-field microscopy, i.e., internal structure of nuclear apparatus, cytoskeletal filaments, cellular cortex, cytoplasmic protrusions, or zona pellucida features. Additionally, we visualize and quantify intracellular dynamics like cytoplasmic stirring motion, nuclear envelope fluctuations and nucleolus mobility. Altogether, we demonstrate that FF-OCM is a powerful tool for research in developmental biology that also holds great potential for non-invasive time-lapse monitoring of oocyte and embryo quality in assisted reproduction.

Tumor spheroid elasticity estimation using mechano-microscopy combined with a conditional generative adversarial network.

BACKGROUND AND OBJECTIVES: Techniques for imaging the mechanical properties of cells are needed to study how cell mechanics influence cell function and disease progression. Mechano-microscopy (a high-resolution variant of compression optical coherence elastography) generates elasticity images of a sample undergoing compression from the phase difference between optical coherence microscopy (OCM) B-scans. However, the existing mechano-microscopy signal processing chain (referred to as the algebraic method) assumes the sample stress is uniaxial and axially uniform, such that violation of these assumptions reduces the accuracy and precision of elasticity images. Furthermore, it does not account for prior information regarding the sample geometry or mechanical property distribution. In this study, we investigate the feasibility of training a conditional generative adversarial network (cGAN) to generate elasticity images from phase difference images of samples containing a cell spheroid embedded in a hydrogel. METHODS: To construct the cGAN training and simulated test sets, we generated 30,000 artificial elasticity images using a parametric model and computed the corresponding phase difference images using finite element analysis to simulate compression applied to the artificial samples. We also imaged real MCF7 breast tumor spheroids embedded in hydrogel using mechano-microscopy to construct the experimental test set and evaluated the cGAN using the algebraic elasticity images and co-registered OCM and confocal fluorescence microscopy (CFM) images. RESULTS: Comparison with the simulated test set ground truth elasticity images shows the cGAN produces a lower root mean square error (median: 3.47 kPa, 95 % confidence interval (CI) [3.41, 3.52]) than the algebraic method (median: 4.91 kPa, 95 % CI [4.85, 4.97]). For the experimental test set, the cGAN elasticity images contain features resembling stiff nuclei at locations corresponding to nuclei seen in the algebraic elasticity, OCM, and CFM images. Furthermore, the cGAN elasticity images are higher resolution and more robust to noise than the algebraic elasticity images. CONCLUSIONS: The cGAN elasticity images exhibit better accuracy, spatial resolution, sensitivity, and robustness to noise than the algebraic elasticity images for both simulated and real experimental data.

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.

Stiffness Mediated-Mechanosensation of Airway Smooth Muscle Cells on Linear Stiffness Gradient Hydrogels.

In obstructive airway diseases such as asthma and chronic obstructive pulmonary disease (COPD), the extracellular matrix (ECM) protein amount and composition of the airway smooth muscle (ASM) is often remodelled, likely altering tissue stiffness. The underlying mechanism of how human ASM cell (hASMC) mechanosenses the aberrant microenvironment is not well understood. Physiological stiffnesses of the ASM were measured by uniaxial compression tester using porcine ASM layers under 0, 5 and 10% longitudinal stretch above in situ length. Linear stiffness gradient hydrogels (230 kPa range) were fabricated and functionalized with ECM proteins, collagen I (ColI), fibronectin (Fn) and laminin (Ln), to recapitulate the above-measured range of stiffnesses. Overall, hASMC mechanosensation exhibited a clear correlation with the underlying hydrogel stiffness. Cell size, nuclear size and contractile marker alpha-smooth muscle actin (αSMA) expression showed a strong correlation to substrate stiffness. Mechanosensation, assessed by Lamin-A intensity and nuc/cyto YAP, exhibited stiffness-mediated behaviour only on ColI and Fn-coated hydrogels. Inhibition studies using blebbistatin or Y27632 attenuated most mechanotransduction-derived cell morphological responses, αSMA and Lamin-A expression and nuc/cyto YAP (blebbistatin only). This study highlights the interplay and complexities between stiffness and ECM protein type on hASMC mechanosensation, relevant to airway remodelling in obstructive airway diseases.

Mechanical overload-induced release of extracellular mitochondrial particles from tendon cells leads to inflammation in tendinopathy.

Tendinopathy is one of the most common musculoskeletal diseases, and mechanical overload is considered its primary cause. However, the underlying mechanism through which mechanical overload induces tendinopathy has not been determined. In this study, we identified for the first time that tendon cells can release extracellular mitochondria (ExtraMito) particles, a subtype of medium extracellular particles (mEPs), into the environment through a process regulated by mechanical loading. RNA sequencing systematically revealed that oxygen-related reactions, extracellular particles, and inflammation were present in diseased human tendons, suggesting that these factors play a role in the pathogenesis of tendinopathy. We simulated the disease condition by imposing a 9% strain overload on three-dimensional mouse tendon constructs in our cyclic uniaxial stretching bioreactor. The three-dimensional mouse tendon constructs under normal loading with 6% strain exhibited an extended mitochondrial network, as observed through live-cell confocal laser scanning microscopy. In contrast, mechanical overload led to a fragmented mitochondrial network. Our microscopic and immunoblot results demonstrated that mechanical loading induced tendon cells to release ExtraMito particles. Furthermore, we showed that mEPs released from tendon cells overloaded with a 9% strain (mEP9%) induced macrophage chemotaxis and increased the production of proinflammatory cytokines, including IL-6, CXCL1, and IL-18, from macrophages compared to mEP0%, mEP3%, and mEP6%. Partial depletion of the ExtraMito particles from mEP9% by magnetic-activated cell sorting significantly reduced macrophage chemotaxis. N-acetyl-L-cysteine treatment preserved the mitochondrial network in overloaded tendon cells, diminishing overload-induced macrophage chemotaxis toward mEP9%. These findings revealed a novel mechanism of tendinopathy; in an overloaded environment, ExtraMito particles convey mechanical response signals from tendon cells to the immune microenvironment, culminating in tendinopathy.

In vivo characterisation of field pea stem wall thickness using optical coherence tomography.

BACKGROUND: Modern field pea breeding faces a significant challenge in selecting lines with strong stems that resist lodging. Traditional methods of assessing stem strength involve destructive mechanical tests on mature stems after natural senescence, such as measuring stem flexion, stem buckling or the thickness of dry stems when compressed, but these measurements may not correspond to the strength of stems in the living plant. Optical coherence tomography (OCT) can be used as a noncontact and nondestructive method to measure stem wall thickness in living plants by acquiring two- or three-dimensional images of living plant tissue. RESULTS: In this proof-of-principle study, we demonstrated in vivo characterisation of stem wall thickness using OCT, with the measurement corrected for the refractive index of the stem tissue. This in vivo characterisation was achieved through real-time imaging of stems, with an acquisition rate of 13 milliseconds per two-dimensional, cross-sectional OCT image. We also acquired OCT images of excised stems and compared the accuracy of in vivo OCT measurements of stem wall thickness with ex vivo results for 10 plants each of two field pea cultivars, Dunwa and Kaspa. In vivo OCT measurements of stem wall thickness have an average percent error of - 3.1% when compared with ex vivo measurements. Additionally, we performed in vivo measurements of both stem wall thickness and stem width at various internode positions on the two cultivars. The results revealed that Dunwa had a uniform stem wall thickness across different internode positions, while Kaspa had a significantly negative slope of [Formula: see text]0.0198 mm/node. Both cultivars exhibited an increase in stem width along the internode positions; however, Dunwa had a rate of increase of 0.1844 mm/node, which is three times higher than that of Kaspa. CONCLUSIONS: Our study has demonstrated the efficacy of OCT for accurate measurement of the stem wall thickness of live field pea. Moreover, OCT shows that the trends of stem wall thickness and stem width along the internode positions are different for the two cultivars, Dunwa and Kaspa, potentially hinting at differences in their stem strength. This rapid, in vivo imaging method provides a useful tool for characterising physical traits critical in breeding cultivars that are resistant to lodging.

Analysis of friction in quantitative micro-elastography.

Quantitative micro-elastography (QME) is a compression-based optical coherence elastography technique capable of measuring the mechanical properties of tissue on the micro-scale. As QME requires contact between the imaging window and the sample, the presence of friction affects the accuracy of the estimated elasticity. In previous implementations, a lubricant was applied at the contact surfaces, which was assumed to result in negligible friction. However, recently, errors in the estimation of elasticity caused by friction have been reported. This effect has yet to be characterized and is, therefore, not well understood. In this work, we present a systematic analysis of friction in QME using silicone phantoms. We demonstrate that friction, and, therefore, the elasticity accuracy, is influenced by several experimental factors, including the viscosity of the lubricant, the mechanical contrast between the compliant layer and the sample, and the time after the application of a compressive strain. Elasticity errors over an order of magnitude were observed in the absence of appropriate lubrication when compared to uniaxial compression testing. Using an optimized lubrication protocol, we demonstrate accurate elasticity estimation (<10% error) for nonlinear elastic samples with Young's moduli ranging from 3 kPa to 130 kPa. Finally, using a structured phantom, we demonstrate that friction can significantly reduce mechanical contrast in QME. We believe that the framework established in this study will facilitate more robust elasticity estimations in QME, as well as being readily adapted to understand the effects of friction in other contact elastography techniques.

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.

Biomechanical assessment of chronic liver injury using quantitative micro-elastography.

Hepatocellular carcinoma is one of the most lethal cancers worldwide, causing almost 700,000 deaths annually. It mainly arises from cirrhosis, which, in turn, results from chronic injury to liver cells and corresponding fibrotic changes. Although it is known that chronic liver injury increases the elasticity of liver tissue, the role of increased elasticity of the microenvironment as a possible hepatocarcinogen is yet to be investigated. One reason for this is the paucity of imaging techniques capable of mapping the micro-scale elasticity variation in liver and correlating that with cancerous mechanisms on the cellular scale. The clinical techniques of ultrasound elastography and magnetic resonance elastography typically do not provide micro-scale resolution, while atomic force microscopy can only assess the elasticity of a limited number of cells. We propose quantitative micro-elastography (QME) for mapping the micro-scale elasticity of liver tissue into images known as micro-elastograms, and therefore, as a technique capable of correlating the micro-environment elasticity of tissue with cellular scale cancerous mechanisms in liver. We performed QME on 13 freshly excised healthy and diseased mouse livers and present micro-elastograms, together with co-registered histology, in four representative cases. Our results indicate a significant increase in the mean (×6.3) and standard deviation (×6.0) of elasticity caused by chronic liver injury and demonstrate that the onset and progression of pathological features such as fibrosis, hepatocyte damage, and immune cell infiltration correlate with localized variations in micro-elastograms.

Evaluating Distribution of Foveal Avascular Zone Parameters Corrected by Lateral Magnification and Their Associations with Retinal Thickness.

Purpose: To examine the distribution of foveal avascular zone (FAZ) parameters, with and without correction for lateral magnification, in a large cohort of healthy young adults. Design: Cross-sectional, observational cohort study. Participants: A total of 504 healthy adults, 27 to 30 years of age. Methods: Participants underwent a comprehensive ophthalmic examination including axial length measurement and OCT angiography (OCTA) imaging of the macula. OCT angiography images of combined superficial and deep retinal vessel plexuses were processed via a custom software to extract foveal avascular zone area (FAZA) and foveal density-300 (FD-300), the vessel density in a 300-µm wide annulus surrounding the FAZ, with and without correction for lateral magnification. Bland-Altman analyses were performed to examine the effect of lateral magnification on FAZA and FD-300, as well as to evaluate the interocular agreement in both parameters. Linear mixed-effects models were used to examine the relationship between retinal thicknesses and OCTA parameters. Main Outcome Measures: The FAZA and FD-300, corrected for lateral magnification. Results: The mean (standard deviation [SD]) of laterally corrected FAZA and FD-300 was 0.22 mm2 (0.10 mm2) and 51.9% (3.2%), respectively. Relative to uncorrected data, 55.6% of corrected FAZA showed a relative change > 5%, whereas all FD-300 changes were within 5%. There was good interocular symmetry (mean right eye-left eye difference, 95% limits of agreement [LoA]) in both FAZA (0.006 mm2, -0.05 mm2, to 0.07 mm2) and FD-300 (-0.05%, -5.39%, to 5.30%). There were significant negative associations between central retinal thickness and FAZA (ß = -0.0029), as well as between central retinal thickness and FD-300 (ß = -0.044), with the relationships driven by inner, not outer, retina. Conclusions: We reported lateral magnification adjusted normative values for FAZA and FD-300 in a large cohort of young, healthy eyes. Clinicians should strongly consider accounting for lateral magnification when evaluating FAZA. Good interocular agreement in FAZA and FD-300 suggests the contralateral eye can be used as control data.

Quantitative Micro-Elastography Enables In Vivo Detection of Residual Cancer in the Surgical Cavity during Breast-Conserving Surgery.

Breast-conserving surgery (BCS) is commonly used for the treatment of early-stage breast cancer. Following BCS, approximately 20% to 30% of patients require reexcision because postoperative histopathology identifies cancer in the surgical margins of the excised specimen. Quantitative micro-elastography (QME) is an imaging technique that maps microscale tissue stiffness and has demonstrated a high diagnostic accuracy (96%) in detecting cancer in specimens excised during surgery. However, current QME methods, in common with most proposed intraoperative solutions, cannot image cancer directly in the patient, making their translation to clinical use challenging. In this proof-of-concept study, we aimed to determine whether a handheld QME probe, designed to interrogate the surgical cavity, can detect residual cancer directly in the breast cavity in vivo during BCS. In a first-in-human study, 21 BCS patients were scanned in vivo with the QME probe by five surgeons. For validation, protocols were developed to coregister in vivo QME with postoperative histopathology of the resected tissue to assess the capability of QME to identify residual cancer. In four cavity aspects presenting cancer and 21 cavity aspects presenting benign tissue, QME detected elevated stiffness in all four cancer cases, in contrast to low stiffness observed in 19 of the 21 benign cases. The results indicate that in vivo QME can identify residual cancer by directly imaging the surgical cavity, potentially providing a reliable intraoperative solution that can enable more complete cancer excision during BCS. SIGNIFICANCE: Optical imaging of microscale tissue stiffness enables the detection of residual breast cancer directly in the surgical cavity during breast-conserving surgery, which could potentially contribute to more complete cancer excision.

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.

Multi-class classification of breast tissue using optical coherence tomography and attenuation imaging combined via deep learning.

We demonstrate a convolutional neural network (CNN) for multi-class breast tissue classification as adipose tissue, benign dense tissue, or malignant tissue, using multi-channel optical coherence tomography (OCT) and attenuation images, and a novel Matthews correlation coefficient (MCC)-based loss function that correlates more strongly with performance metrics than the commonly used cross-entropy loss. We hypothesized that using multi-channel images would increase tumor detection performance compared to using OCT alone. 5,804 images from 29 patients were used to fine-tune a pre-trained ResNet-18 network. Adding attenuation images to OCT images yields statistically significant improvements in several performance metrics, including benign dense tissue sensitivity (68.0% versus 59.6%), malignant tissue positive predictive value (PPV) (79.4% versus 75.5%), and total accuracy (85.4% versus 83.3%), indicating that the additional contrast from attenuation imaging is most beneficial for distinguishing between benign dense tissue and malignant tissue.

Analysis of strain estimation methods in phase-sensitive compression optical coherence elastography.

In compression optical coherence elastography (OCE), deformation is quantified as the local strain at each pixel in the OCT field-of-view. A range of strain estimation methods have been demonstrated, yet it is unclear which method provides the best performance. Here, we analyze the two most prevalent strain estimation methods used in phase-sensitive compression OCE, i.e., weighted least squares (WLS) and the vector method. We introduce a framework to compare strain imaging metrics, incorporating strain sensitivity, strain signal-to-noise ratio (SNR), strain resolution, and strain accuracy. In addition, we propose a new phase unwrapping algorithm in OCE, fast phase unwrapping (FPU), and combine it with WLS, termed WLSFPU. Using the framework, we compare this new strain estimation method with both a current implementation of WLS that incorporates weighted phase unwrapping (WPU), termed WLSWPU, and the vector method. Our analysis reveals that the three methods provide similar strain sensitivity, strain SNR, and strain resolution, but that WLSFPU extends the dynamic range of accurate, measurable local strain, e.g., measuring a strain of 2.5 mɛ with ∼4% error, that is ×11 and ×15 smaller than the error measured using WLSWPU and the vector method, respectively. We also demonstrate, for the first time, the capability to detect sub-resolution contrast in compression OCE, i.e., changes in strain occurring within the strain axial resolution, and how this contrast varies between the different strain estimation methods. Lastly, we compare the performance of the three strain estimation methods on mouse skeletal muscle and human breast tissue and demonstrate that WLSFPU avoids strain imaging artifacts resulting from phase unwrapping errors in WLSWPU and provides improved contrast over the other two methods.

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.

Coherence function-encoded optical palpation.

Optical palpation maps stress at the surface of biological tissue into 2D images. It relies on measuring surface deformation of a compliant layer, which to date has been performed with optical coherence tomography (OCT). OCT-based optical palpation holds promise for improved clinical diagnostics; however, the complexity and cost hinder broad adoption. In this Letter, we introduce coherence function-encoded optical palpation (CFE-OP) using a novel optical profilometry technique that exploits the envelope of the coherence function rather than its peak position, which is typically used to retrieve depth information. CFE-OP utilizes a Fabry-Perot laser diode (bandwidth, 2.2 nm) and a single photodiode in a Michelson interferometer to detect the position along the coherence envelope as a function of path length. This technique greatly reduces complexity and cost in comparison to the OCT-based approach. We perform CFE-OP on phantom and excised human breast tissue, demonstrating comparable mechanical contrast to OCT-based optical palpation and the capability to distinguish stiff tumor from soft benign tissue.