Label-free pathology by spectrally sliced femtosecond stimulated Raman scattering (SRS) microscopy

Quantitative analysis of drug tablet aging by fast hyper-spectral stimulated Raman scattering microscopy

Pharmaceutical development of solid-state formulations requires testing active pharmaceutical ingredients (API) and excipients for uniformity and stability. Solid-state properties such as component distribution and grain size are crucial factors that influence the dissolution profile, which greatly affect drug efficacy and toxicity, and can only be analyzed spatially by chemical imaging (CI) techniques. Current CI techniques such as near infrared microscopy and confocal Raman spectroscopy are capable of high chemical and spatial resolution but cannot achieve the measurement speeds necessary for integration into the pharmaceutical production and quality assurance processes. To fill this gap, we demonstrate fast chemical imaging by epi-detected sparse spectral sampling stimulated Raman scattering to quantify API and excipient degradation and distribution.

How and why I fell into neuropathology

I'm going to explain how and why I fell into the Department of Neuropathology at the Pitié-Salpêtrière Hospital of Paris. I'd also like to sketch the history of French neuropathology in the years 1960-2010, as seen by a naive young student, and then by a practicing neuropathologist (often still very naive). As a matter of fact, although the history of neurosciences [1-2] and the Pitié-Salpêtrière Hospital in Paris [3-4] have been the subject of numerous publications, the history of neuropathology in this hospital has been rarely documented [5-6]. I spent more than forty years strolling along the alleys of La Salpêtrière, among its old pavilions, the Saint Louis chapel, the "Pavillon des folles", the courtyard of Manon Lescaut and the guard room. I worked full-time between the Escourolle laboratory, the "Amphithéâtre des morts" and the University. It has been a real pleasure to be part of this world. I would also like to offer young doctors in training and future neuropathologists some advice that might help them in the choice and development of their future careers.

Imaging approaches for monitoring three-dimensional cell and tissue culture systems

The past decade has seen an increasing demand for more complex, reproducible and physiologically relevant tissue cultures that can mimic the structural and biological features of living tissues. Monitoring the viability, development and responses of such tissues in real-time are challenging due to the complexities of cell culture physical characteristics and the environments in which these cultures need to be maintained in. Significant developments in optics, such as optical manipulation, improved detection and data analysis, have made optical imaging a preferred choice for many three-dimensional (3D) cell culture monitoring applications. The aim of this review is to discuss the challenges associated with imaging and monitoring 3D tissues and cell culture, and highlight topical label-free imaging tools that enable bioengineers and biophysicists to non-invasively characterise engineered living tissues.

In vivo simultaneous nonlinear absorption Raman and fluorescence (SNARF) imaging of mouse brain cortical structures

Label-free multiphoton microscopy is a powerful platform for biomedical imaging. Recent advancements have demonstrated the capabilities of transient absorption microscopy (TAM) for label-free quantification of hemoglobin and stimulated Raman scattering (SRS) microscopy for pathological assessment of label-free virtual histochemical staining. We propose the combination of TAM and SRS with two-photon excited fluorescence (TPEF) to characterize, quantify, and compare hemodynamics, vessel structure, cell density, and cell identity in vivo between age groups. In this study, we construct a simultaneous nonlinear absorption, Raman, and fluorescence (SNARF) microscope with the highest reported in vivo imaging depth for SRS and TAM at 250–280 μm to enable these multimodal measurements. Using machine learning, we predict capillary-lining cell identities with 90% accuracy based on nuclear morphology and capillary relationship. The microscope and methodology outlined herein provides an exciting route to study several research topics, including neurovascular coupling, blood-brain barrier, and neurodegenerative diseases.

In this study a microscope is constructed that carries out simultaneous nonlinear absorption, Raman, and fluorescence (SNARF). Machine learning is then used to predict capillary-lining cell identities with 90% accuracy based on nuclear morphology and capillary relationship, which in combination with the developed microscope, can provide a means to study several fields such as neurovascular coupling.

Real-Time, Two-Color Stimulated Raman Scattering Imaging of Mouse Brain for Tissue Diagnosis

Stimulated Raman scattering (SRS) microscopy has emerged as a powerful optical imaging technique for tissue diagnosis. In recent years, two-color SRS has been shown to be able to provide hematoxylin and eosin (H&E)-equivalent images that allow fast and reliable diagnosis of brain cancer. Such capability has enabled exciting intraoperative cancer diagnosis applications. Two-color SRS imaging of tissue can be done with either a picosecond or femtosecond laser source. Femtosecond lasers have the advantage of enabling flexible imaging modes, including fast hyperspectral imaging and real-time, two-color SRS imaging. A spectral-focusing approach with chirped laser pulses is typically used with femtosecond lasers to achieve high spectral resolution. Two-color SRS acquisition can be realized with orthogonal modulation and lock-in detection. The complexity of pulse chirping, modulation, and characterization is a bottleneck for the widespread adoption of this method. This article provides a detailed protocol to demonstrate the implementation and optimization of spectral-focusing SRS and real-time, two-color imaging of mouse brain tissue in the epi-mode. This protocol can be used for a broad range of SRS imaging applications that leverage the high speed and spectroscopic imaging capability of SRS.

Multi-window sparse spectral sampling stimulated Raman scattering microscopy

Stimulated Raman scattering (SRS) is a nondestructive and rapid technique for imaging of biological and clinical specimens with label-free chemical specificity. SRS spectral imaging is typically carried out either via broadband methods, or by tuning narrowband ultrafast light sources over narrow spectral ranges thus specifically targeting vibrational frequencies. We demonstrate a multi-window sparse spectral sampling SRS (S4RS) approach where a rapidly-tunable dual-output all-fiber optical parametric oscillator is tuned into specific vibrational modes across more than 1400 cm-1 during imaging. This approach is capable of collecting SRS hyperspectral images either by scanning a full spectrum or by rapidly tuning into select target frequencies, hands-free and automatically, across the fingerprint, silent, and high wavenumber windows of the Raman spectrum. We further apply computational techniques for spectral decomposition and feature selection to identify a sparse subset of Raman frequencies capable of sample discrimination. Here we have applied this novel method to monitor spatiotemporal dynamic changes of active pharmaceutical ingredients in skin, which has particular relevance to topical drug product delivery.

Coherent Raman scattering microscopy for chemical imaging of biological systems

Coherent Raman scattering (CRS) processes, including both the coherent anti-Stokes Raman scattering and stimulated Raman scattering, have been utilized in state-of-the-art microscopy platforms for chemical imaging of biological samples. The key advantage of CRS microscopy over fluorescence microscopy is label-free, which is an attractive characteristic for modern biological and medical sciences. Besides, CRS has other advantages such as higher selectivity to metabolites, no photobleaching, and narrow peak width. These features have brought fast-growing attention to CRS microscopy in biological research. In this review article, we will first briefly introduce the history of CRS microscopy, and then explain the theoretical background of the CRS processes in detail using the classical approach. Next, we will cover major instrumentation techniques of CRS microscopy. Finally, we will enumerate examples of recent applications of CRS imaging in biological and medical sciences.

Bond-selective imaging by optically sensing the mid-infrared photothermal effect

Mid-infrared (IR) spectroscopic imaging using inherent vibrational contrast has been broadly used as a powerful analytical tool for sample identification and characterization. However, the low spatial resolution and large water absorption associated with the long IR wavelengths hinder its applications to study subcellular features in living systems. Recently developed mid-infrared photothermal (MIP) microscopy overcomes these limitations by probing the IR absorption-induced photothermal effect using a visible light. MIP microscopy yields submicrometer spatial resolution with high spectral fidelity and reduced water background. In this review, we categorize different photothermal contrast mechanisms and discuss instrumentations for scanning and widefield MIP microscope configurations. We highlight a broad range of applications from life science to materials. We further provide future perspective and potential venues in MIP microscopy field.

Microcalcification-Based Tumor Malignancy Evaluation in Fresh Breast Biopsies with Hyperspectral Stimulated Raman Scattering

Precise evaluation of breast tumor malignancy based on tissue calcifications has important practical value in the disease diagnosis, as well as the understanding of tumor development. Traditional X-ray mammography provides the overall morphologies of the calcifications but lacks intrinsic chemical information. In contrast, spontaneous Raman spectroscopy offers detailed chemical analysis but lacks the spatial profiles. Here, we applied hyperspectral stimulated Raman scattering (SRS) microscopy to extract both the chemical and morphological features of the microcalcifications, based on the spectral and spatial domain analysis. A total of 211 calcification sites from 23 patients were imaged with SRS, and the results were analyzed with a support vector machine (SVM) based classification algorithm. With optimized combinations of chemical and geometrical features of microcalcifications, we were able to reach a precision of 98.21% and recall of 100.00% for classifying benign and malignant cases, significantly improved from the pure spectroscopy or imaging based methods. Our findings may provide a rapid means to accurately evaluate breast tumor malignancy based on fresh tissue biopsies.

Advances in stimulated Raman scattering imaging for tissues and animals

Stimulated Raman scattering (SRS) microscopy has emerged in the last decade as a powerful optical imaging technology with high chemical selectivity, speed, and subcellular resolution. Since the invention of SRS microscopy, it has been extensively employed in life science to study composition, structure, metabolism, development, and disease in biological systems. Applications of SRS in research and the clinic have generated new insights in many fields including neurobiology, tumor biology, developmental biology, metabolomics, pharmacokinetics, and more. Herein we review the advances and applications of SRS microscopy imaging in tissues and animals, as well as envision future applications and development of SRS imaging in life science and medicine.

Recent advances in the use of stimulated Raman scattering in histopathology

Stimulated Raman histopathology (SRH) utilises the intrinsic vibrational properties of lipids, proteins and nucleic acids to generate contrast providing rapid image acquisition that allows visualisation of histopathological features. It is currently being trialled in the intraoperative setting, where the ability to image unprocessed samples rapidly and with high resolution offers several potential advantages over the use of conventional haematoxylin and eosin stained images. Here we review recent advances in the field including new updates in instrumentation and computer aided diagnosis. We also discuss how other non-linear modalities can be used to provide additional diagnostic contrast which together pave the way for enhanced histopathology and open up possibilities for in vivo pathology.

Real-Time Microscale Temperature Imaging by Stimulated Raman Scattering

Microscale thermometry of aqueous solutions is essential to understand the dynamics of local heat generation and dissipation in chemical and biological systems. A wide variety of fluorescent probes have been developed to map temperature changes with submicrometer resolution, but they often suffer from the uncertainty associated with microenvironment-dependent fluorescent properties. In this work, we develop a label-free ratiometric stimulated Raman scattering (SRS) microscopy technique to quantify microscale temperature by monitoring the O-H Raman stretching modes of water. By tracking the ratio changes of the hydrogen-bonding O-H band and the isosbestic band, we can directly quantify the temperature of water-based environments in real time without exogenous contrast agents. We demonstrate real-time measurement of localized intracellular and extracellular temperature changes due to laser absorption. This high-speed nonlinear optical imaging technique has the potential for in situ microscale imaging of thermogenesis in both chemical and biological systems.

Direct Quantification of Single Red Blood Cell Hemoglobin Concentration with Multiphoton Microscopy

Blood disorders, diseases, and infections often affect the shape, number, and content of red blood cells (RBCs) dramatically. To combat these pathologies, many therapies target RBCs and their contents directly. Mean corpuscular hemoglobin concentration (MCHC) is an important pathological metric in both identification and treatment. However, current methods for RBC analysis and MCHC quantification rely on bulk measurements. Single RBC measurements could provide necessary insight into the heterogeneity of RBC health and improve therapeutic efficacy. In this study, we present a novel multimodal multiphoton approach for quantifying hemoglobin concentration at single RBC resolution. We achieve this by collecting two images simultaneously that allows us to excite water with stimulated Raman scattering and hemoglobin with transient absorption. This multimodal imaging is enabled by a newly designed orthogonal modulation theme for dual-channel lock-in detection. By leveraging water as an internal standard, we quantify MCHC of healthy RBCs and RBCs infected with Plasmodium yoelii, a commonly studied rodent parasite model.

Raman spectroscopy and neuroscience: from fundamental understanding to disease diagnostics and imaging

Neuroscience would directly benefit from more effective detection techniques, leading to earlier diagnosis of disease. The specificity of Raman spectroscopy is unparalleled, given that a molecular fingerprint is attained for each species. It also allows for label-free detection with relatively inexpensive instrumentation, minimal sample preparation, and rapid sample analysis. This review summarizes Raman spectroscopy-based techniques that have been used to advance the field of neuroscience in recent years.

Eicosapentaenoic acid (EPA) activates PPARγ signaling leading to cell cycle exit, lipid accumulation, and autophagy in human meibomian gland epithelial cells (hMGEC)

PURPOSE

The purpose of this study was to access the ability of the natural PPAR agonist, eicosapentaenoic acid (EPA), to activate PPAR gamma (γ) signaling leading to meibocyte differentiation in human meibomian gland epithelial cell (hMGEC).

METHODS

HMGEC were exposed to EPA, alone and in combination with the specific PPARγ antagonist, T0070907, to selectively block PPARγ signaling. Expression of PPARγ response genes were evaluated by qPCR. Effect on cell cycle was evaluated using Ki-67 labelling and western blots. During differentiation, autophagy was monitored using the Autophagy Tandem Sensor (ATS) and LysoTracker. Lipid accumulation was characterized by Stimulated Raman Scattering microscopy (SRS) and neutral lipid staining in combination with ER-Tracker, LysoTracker, and ATS. Autophagy was also investigated using western blotting. Seahorse XF analysis was performed to monitor mitochondrial function.

RESULTS

EPA specifically upregulated expression of genes related to lipid synthesis and induced cell cycle exit through reduced cyclin D1 expression and increased p21 and p27 expression. EPA also induced accumulation of lipid droplets in a time and dose dependent manner (P < 0.05) by specific PPARγ signaling. Lipid analysis identified both de novo synthesis and extracellular transport of lipid to form lipid droplets that were localized to the ER. PPARγ signaling also induced activation of AMPK-ULK1 signaling and autophagy, while inhibition of autophagy induced mitochondrial crisis with no effect on lipid accumulation.

CONCLUSIONS

EPA induces meibocyte differentiation through PPARγ activation that is characterized by cell cycle exit, de novo and transported lipid accumulation in the ER, and autophagy.

Hybrid Label-Free Molecular Microscopies for Simultaneous Visualization of Changes in Cell Wall Polysaccharides of Peach at Single- and Multiple-Cell Levels during Postharvest Storage

Softening of fruit during the postharvest storage, which is mainly associated with both compositional and spatial changes of polysaccharides within cell wall, affects the texture and quality of fruit. Current research on the fruit softening mechanism lacks an understanding of the overall softening at the cell level. The objective of this work was to investigate the change in the spatial distribution of cell wall polysaccharides in peach flesh cells at both single- and multiple-cell levels in a label-free way during the postharvest storage. Nonmelting peaches (Prunus persica L. Batsch cv."Zhonghuashoutao") at commercial maturity were stored at 0 °C and 20 °C. Firmness measurement and chemical analysis were performed at each storage time. In addition, three molecular imaging techniques, namely confocal Raman microspectroscopy (CRM), Fourier transform infrared microspectroscopy (FTIRM), and stimulated Raman scattering microscopy (SRS) were used to visualize changes in the spatial distribution of cell wall polysaccharides of peach fruit in a label-free way during the postharvest storage. The combination of CRM and FTIRM provided complementary spectral information to visualize the spatial changes of cellulose, hemicellulose, and pectin in the cell wall of peach flesh during softening at the single-cell level, and found that the cell wall polysaccharides tended to be concentrated in the cell corner of parenchymal cells at the late stage. Furthermore, SRS, which is an ultrafast Raman imaging technique (approximately three or four orders of magnitude faster than CRM), was used for high-throughput cell wall phenotypes measurement. Different degradation degrees of parenchymal cells during fruit softening were found based on the gray-scale statistical analysis of SRS data. In general, cell wall polysaccharides decreased during softening and tended to be concentrated in the cell corner for most parenchymal cells at the late stage, but there were also some cells not in line with the whole softening trends. The results show that there were differences in the content and spatial changes of cell wall polysaccharides among parenchymal cells of peach fruit during the softening process, and the hybrid use of CRM, FTIRM, and SRS is a promising method for simultaneous visualization of changes in cell wall polysaccharides of peach.

Intraoperative assessment of skull base tumors using stimulated Raman scattering microscopy

Intraoperative consultations, used to guide tumor resection, can present histopathological findings that are challenging to interpret due to artefacts from tissue cryosectioning and conventional staining. Stimulated Raman histology (SRH), a label-free imaging technique for unprocessed biospecimens, has demonstrated promise in a limited subset of tumors. Here, we target unexplored skull base tumors using a fast simultaneous two-channel stimulated Raman scattering (SRS) imaging technique and a new pseudo-hematoxylin and eosin (H&E) recoloring methodology. To quantitatively evaluate the efficacy of our approach, we use modularized assessment of diagnostic accuracy beyond cancer/non-cancer determination and neuropathologist confidence for SRH images contrasted to H&E-stained frozen and formalin-fixed paraffin-embedded (FFPE) tissue sections. Our results reveal that SRH is effective for establishing a diagnosis using fresh tissue in most cases with 87% accuracy relative to H&E-stained FFPE sections. Further analysis of discrepant case interpretation suggests that pseudo-H&E recoloring underutilizes the rich chemical information offered by SRS imaging, and an improved diagnosis can be achieved if full SRS information is used. In summary, our findings show that pseudo-H&E recolored SRS images in combination with lipid and protein chemical information can maximize the use of SRS during intraoperative pathologic consultation with implications for tissue preservation and augmented diagnostic utility.

Denoising of stimulated Raman scattering microscopy images via deep learning

Stimulated Raman scattering (SRS) microscopy is a label-free quantitative chemical imaging technique that has demonstrated great utility in biomedical imaging applications ranging from real-time stain-free histopathology to live animal imaging. However, similar to many other nonlinear optical imaging techniques, SRS images often suffer from low signal to noise ratio (SNR) due to absorption and scattering of light in tissue as well as the limitation in applicable power to minimize photodamage. We present the use of a deep learning algorithm to significantly improve the SNR of SRS images. Our algorithm is based on a U-Net convolutional neural network (CNN) and significantly outperforms existing denoising algorithms. More importantly, we demonstrate that the trained denoising algorithm is applicable to images acquired at different zoom, imaging power, imaging depth, and imaging geometries that are not included in the training. Our results identify deep learning as a powerful denoising tool for biomedical imaging at large, with potential towards in vivo applications, where imaging parameters are often variable and ground-truth images are not available to create a fully supervised learning training set.

In Vitro Quantification of Single Red Blood Cell Oxygen Saturation by Femtosecond Transient Absorption Microscopy

Hemoglobin, the oxygen carrying protein, ferries nearly all bodily oxygen from the lungs to cells and tissues in need. Blood oxygen saturation (sO₂) thus plays an important role in maintaining energy homeostasis throughout the body. Clinical and research tools have been developed to monitor sO₂ at a wide range of temporal and spatial scales. However, real-time quantification of sO₂ at single red blood cell (RBC) resolution remains challenging. Such capability is critically important to study energy metabolism in heterogeneous tissues including brain and tumor tissue. In this work, we develop a ratiometric transient absorption microscopy technique to image hemoglobin sO₂. By exploiting differences in transient lifetime kinetics between  oxyhemoglobin and deoxyhemoglobin, we directly quantified the sO₂ of single RBCs in real-time without the need for injection of exogenous agents. This simple and high-speed nonlinear optical imaging technique is well suited for in vitro and in vivo quantification of sO₂.

Three-dimensional label-free imaging throughout adipocyte differentiation by stimulated Raman microscopy

Lipid droplets are lipid-storage organelles with a key role in lipid accumulation pathologies such as diabetes, obesity and atherosclerosis. Despite their important functions many aspects of lipid droplets biology are still unknown. This is partially due to the current use of exogenous labels to monitor their formation and remodelling by invasive imaging methods. Here, we apply stimulated Raman scattering microscopy to acquire images with high spatial resolution along with resolving capabilities of lipids and proteins and three-dimensional sectioning. Our images and data analysis demonstrate an increase in the number of large (>15μm²) lipid droplets in human adipocyte cells during differentiation process. In addition, spatially-resolved maps of lipids and proteins inside cells and three dimensional reconstructions of lipids at the initial and final steps of adipocyte differentiation are reported, too.

Rapid histology of laryngeal squamous cell carcinoma with deep-learning based stimulated Raman scattering microscopy

Maximal resection of tumor while preserving the adjacent healthy tissue is particularly important for larynx surgery, hence precise and rapid intraoperative histology of laryngeal tissue is crucial for providing optimal surgical outcomes. We hypothesized that deep-learning based stimulated Raman scattering (SRS) microscopy could provide automated and accurate diagnosis of laryngeal squamous cell carcinoma on fresh, unprocessed surgical specimens without fixation, sectioning or staining. Methods: We first compared 80 pairs of adjacent frozen sections imaged with SRS and standard hematoxylin and eosin histology to evaluate their concordance. We then applied SRS imaging on fresh surgical tissues from 45 patients to reveal key diagnostic features, based on which we have constructed a deep learning based model to generate automated histologic results. 18,750 SRS fields of views were used to train and cross-validate our 34-layered residual convolutional neural network, which was used to classify 33 untrained fresh larynx surgical samples into normal and neoplasia. Furthermore, we simulated intraoperative evaluation of resection margins on totally removed larynxes. Results: We demonstrated near-perfect diagnostic concordance (Cohen's kappa, κ > 0.90) between SRS and standard histology as evaluated by three pathologists. And deep-learning based SRS correctly classified 33 independent surgical specimens with 100% accuracy. We also demonstrated that our method could identify tissue neoplasia at the simulated resection margins that appear grossly normal with naked eyes. Conclusion: Our results indicated that SRS histology integrated with deep learning algorithm provides potential for delivering rapid intraoperative diagnosis that could aid the surgical management of laryngeal cancer.

Broadband hyperspectral stimulated Raman scattering microscopy with a parabolic fiber amplifier source

Hyperspectral stimulated Raman scattering (hsSRS) microscopy has recently emerged as a powerful non-destructive technique for the label-free chemical imaging of biological samples. In most hsSRS imaging experiments, the SRS spectral range is limited by the total bandwidth of the excitation laser to ~300 cm^-1 and a spectral resolution of ~25 cm^-1. Here we present a novel approach for broadband hsSRS microscopy based on parabolic fiber amplification to provide linearly chirped broadened Stokes pulses. This novel hsSRS instrument provides >600 cm^-1 spectral coverage and ~10 cm^-1 spectral resolution. We further demonstrated broadband hsSRS imaging of the entire Raman fingerprint region for resolving the distribution of major biomolecules in fixed cells. Moreover, we applied broadband hsSRS in imaging amyloid plaques in human brain tissue with Alzheimer's disease.

Advancing Raman microspectroscopy for cellular and subcellular analysis: towards in vitro high-content spectralomic analysis

In the confocal mode, Raman microspectroscopy can profile the biochemical content of biological cells at a subcellular level, and any changes to it by exogenous agents, such as therapeutic drugs or toxicants. As an exploration of the potential of the technique as a high-content, label-free analysis technique, this report reviews work to monitor the spectroscopic signatures associated with the uptake and response pathways of commercial chemotherapeutic agents and polymeric nanoparticles by human lung cells. It is demonstrated that the signatures are reproducible and characteristic of the cellular event, and can be used, for example, to identify the mode of action of the agent as well as the subsequent cell death pathway, and even mechanisms of cellular resistance. Data mining approaches are discussed and a spectralomics approach is proposed.

Clinical applications of infrared and Raman spectroscopy: state of play and future challenges

This review examines the state-of-the-art of clinical applications of infrared absorption and Raman spectroscopy, outstanding challenges, and progress towards translation.