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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.

OCT and QME of mucinous carcinoma

OCT and QME of invasive ductal carcinoma with stroma

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.

OCT and QME of benign stroma

Inadequate margins in breast-conserving surgery (BCS) are associated with an increased likelihood of local recurrence of breast cancer. Currently, approximately 20% of BCS patients require repeat surgery due to inadequate margins at the initial operation. Implementation of an accurate, intraoperative margin assessment tool may reduce this re-excision rate. This study determined, for the first time, the diagnostic accuracy of quantitative micro-elastography (QME), an optical coherence tomography (OCT)–based elastography technique that produces images of tissue microscale elasticity, for detecting tumor within 1 mm of the margins of BCS specimens. Simultaneous OCT and QME were performed on the margins of intact, freshly excised specimens from 83 patients undergoing BCS and on dissected specimens from 7 patients undergoing mastectomy. The resulting three-dimensional images (45 × 45 × 1 mm) were coregistered with postoperative histology to determine tissue types present in each scan. Data from 12 BCS patients and the 7 mastectomy patients served to build a set of images for reader training. One hundred and fifty-four subimages (10 × 10 × 1 mm) from the remaining 71 BCS patients were included in a blinded reader study, which resulted in 69.0% sensitivity and 79.0% specificity using OCT images, versus 92.9% sensitivity and 96.4% specificity using elasticity images. The quantitative nature of QME also facilitated development of an automated reader, which resulted in 100.0% sensitivity and 97.7% specificity. These results demonstrate high accuracy of QME for detecting tumor within 1 mm of the margin and the potential for this technique to improve outcomes in BCS.Significance:An optical imaging technology probes breast tissue elasticity to provide accurate assessment of tumor margin involvement in breast-conserving surgery.

OCT and QME of adipose tissue

OCT and QME of ductal carcinoma in situ

Reader stats, Read-Eng1, Read-Eng2, Read-Path, Read-Res, Read-Truth, Read-Son, Read-Surg1, Read-Surg2

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

Mechanisms of tissue deformation in OCME

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.

13 pags., 6 figs., Optical elastography is undergoing extensive development as an imaging tool to map mechanical contrast in tissue. Here, we present a new platform for optical elastography by generating sub-millimetre-scale mechanical contrast from a simple digital camera. This cost-effective, compact and easy-to-implement approach opens the possibility to greatly expand applications of optical elastography both within and beyond the field of medical imaging. Camera-based optical palpation (CBOP) utilises a digital camera to acquire photographs that quantify the light intensity transmitted through a silicone layer comprising a dense distribution of micro-pores (diameter, 30–100 µm). As the transmission of light through the micro-pores increases with compression, we deduce strain in the layer directly from intensity in the digital photograph. By pre-characterising the relationship between stress and strain of the layer, the measured strain map can be converted to an optical palpogram, a map of stress that visualises mechanical contrast in the sample. We demonstrate a spatial resolution as high as 290 µm in CBOP, comparable to that achieved using an optical coherence tomography-based implementation of optical palpation. In this paper, we describe the fabrication of the micro-porous layer and present experimental results from structured phantoms containing stiff inclusions as small as 0.5 × 0.5 × 1 mm. In each case, we demonstrate high contrast between the inclusion and the base material and validate both the contrast and spatial resolution achieved using finite element modelling. By performing CBOP on freshly excised human breast tissue, we demonstrate the capability to delineate tumour from surrounding benign tissue., Te authors acknowledge the facilities and scientifc and technical assistance of the Australian Microscopy & Microanalysis Research Facility at the Centre for Microscopy, Characterisation & Analysis, the University of Western Australia, a facility funded by the University, State and Commonwealth Governments. Tis work was supported by research grants from the Australian Research Council, the Department of Health, Western Australia and the Cancer Council, Western Australia; a research contract with OncoRes Medical; the Herta Massarik PhD Scholarship for Breast Cancer Research; and the War Widows Guild of Western Australia Top-up Scholarship for Research into Breast Cancer.

The aim of this research was to investigate the use of shear wave elastography as a novel tool to quantify and visualize scar stiffness after a burn. Increased scar stiffness is indicative of pathologic scarring which is associated with persistent pain, chronic itch and restricted range of movement. Fifty-five participants with a total of 96 scars and 69 contralateral normal skin sites were evaluated. A unique protocol was developed to enable imaging of the raised and uneven burn scars. Intra-rater and inter-rater reliability was excellent (intra-class correlation coefficient >0.97), and test–retest reliability was good (intra-class correlation coefficient >0.85). Shear wave elastography was able to differentiate between normal skin, pathologic scars and non-pathologic scars, with preliminary cutoff values identified. Significant correlations were found between shear wave velocity and subjective clinical scar assessment (r = 0.66). Shear wave elastography was able to provide unique information associated with pathologic scarring and shows promise as a clinical assessment and research tool.

Research has shown that accounting for moral sentiment in natural language can yield insight into a variety of on- and off-line phenomena such as message diffusion, protest dynamics, and social distancing. However, measuring moral sentiment in natural language is challenging, and the difficulty of this task is exacerbated by the limited availability of annotated data. To address this issue, we introduce the Moral Foundations Twitter Corpus, a collection of 35,108 tweets that have been curated from seven distinct domains of discourse and hand annotated by at least three trained annotators for 10 categories of moral sentiment. To facilitate investigations of annotator response dynamics, we also provide psychological and demographic metadata for each annotator. Finally, we report moral sentiment classification baselines for this corpus using a range of popular methodologies.

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 β-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 β-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 β-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. Postprint

Imaging probes for optical coherence elastography (OCE) are undergoing development to enable its practical implementation in a number of applications. The specific challenges posed by each application defines the technical requirements for each probe, leading to the development of a range of benchtop, handheld and endoscopic probes. In addition, a number of more compact OCE imaging probes have been proposed, including finger-mounted and needle-based probes. In this chapter, we describe each of these probes in detail within the context of the relevant applications they are proposed for. An analysis of each probe is provided, with particular focus on optical design, mechanical loading, and image acquisition protocol.

Deformation is the change in size and shape of a sample in response to an applied load. Accurately measuring deformation is critical in optical coherence elastography (OCE), as along with the validity of the mechanical model of the sample, it determines the accuracy of the measurement of mechanical properties. In this chapter, we describe prominent methods to measure deformation in OCE, including phase-sensitive detection and cross-correlation-based approaches such as speckle tracking. We describe the working principles of these methods and analyze their advantages and disadvantages in the context of performance metrics including sensitivity, accuracy, and spatial resolution. In addition, we briefly describe several less prominent methods such as morphological tracking, correlation stability, digitally shifted complex cross-correlation, and Doppler spectrum detection.

Speckle is a characteristic granular texture inherent to optical coherence tomography (OCT) images of turbid media, such as biological tissues. Speckle is a consequence of the coherent nature of OCT, and results from the interference of light scattered by sub-resolution scatterers. As deformation can rearrange these scatterers, consequently changing the realization of speckle, an understanding of speckle is required to understand elastogram formation in optical coherence elastography (OCE). In this chapter, we analyze speckle using both 1D and 3D models of OCT image formation, and we use these models to describe key concepts, including statistics of the OCT amplitude, intensity, and phase; speckle size; and speckle contrast. The chapter concludes with a description of techniques developed to reduce speckle contrast, including digital image processing, and speckle-modulation techniques.

Optical Coherence Elastography: Imaging Tissue Mechanics on the Micro-Scale provides a unique and practical overview of this important new fi eld, which has seen tremendous growth in the last decade. Using optical coherence tomography (OCT) to measure sample deformation, optical coherence elastography (OCE) provides visualization of the three-dimensional, micro-scale mechanical properties of tissues and biomaterials and has shown distinct promise for application across clinical medicine, biology, and tissue engineering. This timely book provides:Detailed coverage of the key elements required for the successful implementation of OCE techniques, particularly OCT imaging, mechanical deformation, and image processingSynthesis of theory, methodology, and applications in one resourceDetailed discussion of the historical context within which OCE has evolved, particularly regarding ultrasound elastography and magnetic resonance elastographyPerspectives on likely future developments in OCE This book is an invaluable resource for graduate students and researchers in biophotonics and tissue engineering and for professionals working with OCT and elastography.

Optical coherence tomography (OCT) is an imaging technique that uses low-coherence interferometry to construct 3D images with micrometer-scale resolution. It is the imaging modality used in optical coherence elastography (OCE) to measure sample deformation; as such, a detailed analysis of OCT is required to gain a clear understanding of OCE. This chapter provides an overview of the physical principles of OCT, including wave optics, coherence, and interferometry. This theory is then used to describe the main variants of OCT: time-domain OCT and Fourier-domain OCT; the latter of which can be further subdivided into swept-source OCT and spectral-domain OCT. The relationship between system parameters (such as resolution, field of view, and signal-to-noise ratio), and the specification of OCT system components (such as the light source, objectives lens, and scanning mirrors) is also discussed. The chapter concludes with a brief description of OCT variants, including optical coherence microscopy, full-field OCT, and line-field OCT.

In this chapter, we describe the applications proposed for optical coherence elastography (OCE), paying particular attention to applications in oncology, ophthalmology, and tissue engineering. In addition, we briefly describe proposed applications in areas such as cardiology, dermatology, and pulmonology. As well as describing the potential for OCE in each of these areas, and studies performed to date, we describe the challenges, and opportunities that may lie ahead in each area. We also describe some important considerations when commencing collaborations that are focused on applying OCE in new areas.

Compression optical coherence elastography (OCE) is a variant of OCE that maps mechanical parameters, or properties of a sample by measuring the deformation in response to quasi-static compressive loading. Relative to other OCE techniques, to date, compression OCE has provided higher acquisition speed, and the capability to scan over wider fields of view. In early compression OCE studies, it was not possible to estimate quantitative mechanical properties, such as elasticity, instead these early studies calculated qualitative mechanical parameters, typically strain. More recently, quantitative compression OCE has been developed to enable the estimation of elasticity, extending its use to broader applications. However, physical contact between the sample, and loading mechanism is typically required, which is a drawback in applications involving delicate tissues, such as ophthalmology. This chapter focuses on the technical development of compression OCE, beginning with the mechanical model used to determine elasticity. An overview of methods for estimating mechanical parameters, and properties; in particular, strain, stress, and elasticity, is provided. In addition, image quality metrics defined to characterize the imaging performance, such as spatial resolution, and sensitivity, are described.

Tissue mechanical properties determine the relationship between an applied mechanical load and the resulting deformation of the sample. In optical coherence elastography (OCE), the objective is to spatially resolve tissue mechanical properties from often incomplete and noisy measurements of the load and deformation. This is achieved by solving an inverse problem, using a model of elasticity that reasonably describes the behavior of tissue. Incorporating more parameters into the model (such as heterogeneity, anisotropy, nonlinearity, or viscoelasticity) than are needed in a given application can unnecessarily complicate the inverse problem. Also, how the load is applied can enhance certain tissue responses, and the validity of an elasticity model, and, thus, allow for the characterization of tissue in different regimes. A successful OCE technique offers a good match between the load application method, and the tissue mechanical properties of interest, and employs a reasonably complete but simplified mechanical model that provides a noise-robust inversion. OCE techniques can be classified into two broad categories: those inducing and subsequently tracking propagating mechanical waves, and those applying and assuming a uniaxial load, and tracking the deformation in response. With a brief introduction to the former, this chapter focuses on the latter group, describes the most prominent of these techniques, and presents an overview of studies that have successfully extracted mechanical properties in tissue-like media.

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.

Funding: Australian Research Council, the National Health and Medical Research Council (Australia), OncoRes Medical, Australia. 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. Postprint

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.

Understanding motivations underlying acts of hatred are essential for developing strategies to prevent such extreme behavioral expressions of prejudice (EBEPs) against marginalized groups. In this work, we investigate the motivations underlying EBEPs as a function of moral values. Specifically, we propose EBEPs may often be best understood as morally motivated behaviors grounded in people’s moral values and perceptions of moral violations. As evidence, we report five studies that integrate spatial modeling and experimental methods to investigate the relationship between moral values and EBEPs. Our results, from these U.S. based studies, suggest that moral values oriented around group preservation are predictive of the county-level prevalence of hate groups and associated with the belief that extreme behavioral expressions of prejudice against marginalized groups are justified. Additional analyses suggest that the association between group-based moral values and EBEPs against outgroups can be partly explained by the belief that these groups have done something morally wrong., Understanding motivations underlying acts of hatred are essential for developing strategies to prevent such acts against marginalized groups. Here the authors show that group-based moral values are associated with tendency to justify extreme behavioural expressions of prejudice.

Compression optical coherence elastography forms images based on the mechanical properties of tissue by mapping the local strain in response to a compressive load. Strain is described by a second-order tensor, comprising six independent components. The majority of compression elastography methods, however, measure and form their analyses from a single axial component, which relies on the assumption that the stress in tissue is uniform and uniaxial. However, in general, tissues are complex and heterogeneous, and rarely comply with this assumption. This can lead to inaccuracies and misinterpretation of image contrast in compression optical coherence elastography. Here, we image the full strain tensor and demonstrate its utility in unambiguously characterizing deformation in structured phantoms and ex vivo tissues. We derive additional parameters from the strain tensor, and map the local compressibility, anisotropy of deformation, and total equivalent strain. Such analysis is enabled by an efficient non-iterative approach to measuring the three-dimensional displacement field via a closed-form solution to a collection of the amplitude of complex correlation coefficients across multiple digitally shifted images. Strain tensor imaging is likely to lead to more accurate estimation of tissue mechanical properties, improving the utility of compression optical coherence elastography in clinical and biological applications.

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.

Funding: Australian Research Council; Department of Health, Australian Government; Cancer Council Western Australia; Oncores Medical; The William and Marlene Schrader Trust of the University of Western Australia; Royal Society. 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. Publisher PDF

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.

Due to the explosion of new sources of human language data and the rapid progression of computational methods for extracting meaning from natural language, language analysis is a promising, though complicated, category of psychological research. In this chapter, we give a modern perspective on language analysis as it applies to psychology, uniting historical context, the diverse range of domains studied in psychology via language, and the methodological rigor of natural language processing (NLP) and machine learning. Top–down methods (e.g., dictionary approaches, text annotation) are presented alongside bottom–up methods (e.g., topic modeling, word embedding, language modeling) in order to give the reader a comprehensive grounding in the tools available and the recommended practices involved in applying them. We conclude with a view of the future of language analysis, specifically the ways in which psychology and NLP will continue to co-develop.