Stimulated Raman Scattering Microscopy Research Articles

Initial experience with label-free stimulated Raman scattering microscopy for intraoperative assessment of peripheral nerves

BackgroundDuring nerve repair, an intraoperative assessment of the quality of the nerve stump is critically important for achieving a good outcome. Frozen section analysis of osmium-hematoxylin stained sections has not been adopted at many centers, including ours. This has left us with bread-loafing the nerve and visually assessing for healthy fascicles. A technique that would allow for rapid, safe, quantitative intraoperative assessment of nerve quality, including myelin quantity, would be beneficial. Stimulated Raman Scattering (SRS) microscopy is a rapid, label-free technique that images lipids well that may be uniquely suited for this purpose. ObjectiveTo describe our initial experience and lessons learned using SRS microscopy for evaluation of peripheral nerve tissue. MethodsWe present 6 cases during which SRS microscopy was used to evaluate peripheral nerve tissue, including standard histology and SRS microscopy images, where applicable. ResultsOur current technique involves OCT embedding the nerve tissue and then cutting 70 µm sections on a standard cryostat. The SRS microscope slide is modified to change the buffer depth from 100 µm to 50 µm. We analyzed the gray scale composite images, merged from the CH2 (lipid) channel and CH3 (protein) channel. This technique reliably produced cross-sectional images and showed good capability for imaging myelinated axons within fascicles. ConclusionsWe demonstrate here an innovative approach to quantifying myelin in peripheral nerve using Stimulated Raman Scattering microscopy. This should prove useful in the care and surgical treatment of patients with peripheral nerve injuries.

Direct visualization of general anesthetic propofol on neurons by stimulated Raman scattering microscopy

SummaryThe consensus for the precise mechanism of action of general anesthetics is through allosteric interactions with GABA receptors in neurons. However, it has been speculated that these anesthetics may also interact with the plasma membrane on some level. Owing to the small size of anesthetics, direct visualization of these interactions is difficult to achieve. We demonstrate the ability to directly visualize a deuterated analog of propofol in living cells using stimulated Raman scattering (SRS) microscopy. Our findings support the theory that propofol is highly concentrated and interacts primarily through non-specific binding to the plasma membrane of neurons. Additionally, we show that SRS microscopy can be used to monitor the dynamics of propofol binding using real-time, live-cell imaging. The strategy used to visualize propofol can be applied to other small molecule drugs that have been previously invisible to traditional imaging techniques

Spectral focusing in picosecond pulsed stimulated Raman scattering microscopy.

We introduce spectral focusing of picosecond laser pulses in stimulated Raman scattering (SRS) microscopy to improve spectral resolution, reduce nonlinear background signals, and decrease nonlinear photodamage. We produce a pair of 14 ps pump and Stokes laser pulses by spectral focusing of a 2 ps laser and achieve a spectral resolution of 2 cm-1. Due to instantaneous narrow-band excitation, we find that the chirped 14 ps laser pulses can be used to improve the signal-to-background ratio in SRS microscopy of various samples such as polymer particles and small molecules in HeLa cells. The lower peak powers produced by chirped picosecond laser pulses also reduce nonlinear photodamage, allowing long-term SRS imaging of living cells with higher SNR.

Stimulated Raman Scattering Microscopy and Its Applications

Stimulated Raman Scattering Microscopy and Its Applications

In vivo Imaging of Biological Tissues with Combined Two-Photon Fluorescence and Stimulated Raman Scattering Microscopy.

Stimulated Raman scattering (SRS) microscopy enables label-free imaging of the biological tissues in its natural microenvironment based on intrinsic molecular vibration, thus providing a perfect tool for in vivo study of biological processes at subcellular resolution. By integrating two-photon excited fluorescence (TPEF) imaging into the SRS microscope, the dual-modal in vivo imaging of tissues can acquire critical biochemical and biophysical information from multiple perspectives which helps understand the dynamic processes involved in cellular metabolism, immune response and tissue remodeling, etc. In this video protocol, the setup of a TPEF-SRS microscope system as well as the in vivo imaging method of the animal spinal cord is introduced. The spinal cord, as part of the central nervous system, plays a critical role in the communication between the brain and peripheral nervous system. Myelin sheath, abundant in phospholipids, surrounds and insulates the axon to permit saltatory conduction of action potentials. In vivo imaging of myelin sheaths in the spinal cord is important to study the progression of neurodegenerative diseases and spinal cord injury. The protocol also describes animal preparation and in vivo TPEF-SRS imaging methods to acquire high-resolution biological images.

Clinical Translation of Stimulated Raman Histology.

Stimulated Raman histology (SRH) images are created by the label-free, nondestructive imaging of tissue using stimulated Raman scattering (SRS) microscopy. In a matter of seconds, these images provide real-time histologic information on biopsied tissue in the operating room. SRS microscopy uses two lasers (pump beam and Stokes beam) to amplify the Raman signal of specific chemical bonds found in macromolecules (lipids, proteins, and nucleic acids) in these tissues. The concentrations of these macromolecules are used to produce image contrast. These images are acquired and displayed using an imaging system with five main components: (1) fiber coupled microscope, (2) dual-wavelength fiber-laser module, (3) laser control module, (4) microscope control module, and (5) a computer. This manuscript details how to assemble the dual-wavelength fiber-laser module and how to generate an SRH image.

Label-free skin penetration analysis using time-resolved, phase-modulated stimulated Raman scattering microscopy

Skin penetration analysis of topically applied drugs or active compounds is essential in biomedical applications. Stimulated Raman scattering (SRS) microscopy is a promising label-free skin penetration analysis tool. However, conventional SRS microcopy suffers from limited signal contrast owing to strong background signals, which prevents its use in low-concentration drug imaging. Here, we present a skin penetration analysis method of topical agents using recently developed phase-modulated SRS (PM-SRS) microscopy. PM-SRS uses phase modulation and time-resolved signal detection to suppress both nonlinear background signals and Raman background signals from a tissue. A proof-of-concept experiment with a topically applied skin moisturizing agent (ectoine) in an in vitro skin tissue model revealed that PM-SRS with 1.7-ps probe delay yields a signal contrast 40 times higher than that of conventional amplitude-modulated SRS (AM-SRS). Skin penetration measurement of a topical therapeutic drug (loxoprofen sodium) showed that the mean drug concentration at the tissue surface layer after 240 min was 47.3 ± 4.8 mM. The proposed PM-SRS microscopy can be employed to monitor the spatial and temporal pharmacokinetics of small molecules in the millimolar concentration regime.

Understanding the Correlation between Lithium Dendrite Growth and Local Material Properties by Machine Learning

Lithium metal batteries are attractive for next-generation energy storage because of their high energy density. A major obstacle to their commercialization is the uncontrollable growth of lithium dendrites, which arises from complicated but poorly understood interactions at the electrolyte/electrode interface. In this work, we use a machine learning-based artificial neural network (ANN) model to explore how the lithium growth rate is affected by local material properties, such as surface curvature, ion concentration in the electrolyte, and the lithium growth rates at previous moments. The ion concentration in the electrolyte was acquired by Stimulated Raman Scattering Microscopy, which is often missing in past experimental data-based modeling. The ANN network reached a high correlation coefficient of 0.8 between predicted and experimental values. Further sensitivity analysis based on the ANN model demonstrated that the salt concentration and concentration gradient, as well as the prior lithium growth rate, have the highest impacts on the lithium dendrite growth rate at the next moment. This work shows the potential capability of the ANN model to forecast lithium growth rate, and unveil the inner dependency of the lithium dendrite growth rate on various factors.

Automatic cell counting from stimulated Raman imaging using deep learning.

In this paper, we propose an automatic cell counting framework for stimulated Raman scattering (SRS) images, which can assist tumor tissue characteristic analysis, cancer diagnosis, and surgery planning processes. SRS microscopy has promoted tumor diagnosis and surgery by mapping lipids and proteins from fresh specimens and conducting a fast disclose of fundamental diagnostic hallmarks of tumors with a high resolution. However, cell counting from label-free SRS images has been challenging due to the limited contrast of cells and tissue, along with the heterogeneity of tissue morphology and biochemical compositions. To this end, a deep learning-based cell counting scheme is proposed by modifying and applying U-Net, an effective medical image semantic segmentation model that uses a small number of training samples. The distance transform and watershed segmentation algorithms are also implemented to yield the cell instance segmentation and cell counting results. By performing cell counting on SRS images of real human brain tumor specimens, promising cell counting results are obtained with > 98% of area under the curve (AUC) and R = 0.97 in terms of cell counting correlation between SRS and histological images with hematoxylin and eosin (H&E) staining. The proposed cell counting scheme illustrates the possibility and potential of performing cell counting automatically in near real time and encourages the study of applying deep learning techniques in biomedical and pathological image analyses.

Time-encoded stimulated Raman scattering microscopy of tumorous human pharynx tissue in the fingerprint region from 1500-1800 cm-1.

Stimulated Raman scattering (SRS) microscopy for biomedical analysis can provide a molecular localization map to infer pathological tissue changes. Compared to spontaneous Raman, SRS achieves much faster imaging speeds at reduced spectral coverage. By targeting spectral features in the information dense fingerprint region, SRS allows fast and reliable imaging. We present time-encoded (TICO) SRS microscopy of unstained head-and-neck biopsies in the fingerprint region with molecular contrast. We combine a Fourier-domain mode-locked (FDML) laser with a master oscillator power amplifier (MOPA) to cover Raman transitions from 1500-1800cm-1. Both lasers are fiber-based and electronically programmable making this fingerprint TICO system robust and reliable. The results of our TICO approach were cross-checked with a spontaneous Raman micro-spectrometer and show good agreement, paving the way toward clinical applications.

Label-Free Imaging of Lipid Storage Dynamics in Caenorhabditis elegans using Stimulated Raman Scattering Microscopy.

Lipid metabolism is a fundamental physiological process necessary for cellular and organism health. Dysregulation of lipid metabolism often elicits obesity and many associated diseases including cardiovascular disorders, type II diabetes, and cancer. To advance the current understanding of lipid metabolic regulation, quantitative methods to precisely measure in vivo lipid storage levels in time and space have become increasingly important and useful. Traditional approaches to analyze lipid storage are semi-quantitative for microscopic assessment or lacking spatio-temporal information for biochemical measurement. Stimulated Raman scattering (SRS) microscopy is a label-free chemical imaging technology that enables rapid and quantitative detection of lipids in live cells with a subcellular resolution. As the contrast is exploited from intrinsic molecular vibrations, SRS microscopy also permits four-dimensional tracking of lipids in live animals. In the last decade, SRS microscopy has been widely used for small molecule imaging in biomedical research and overcome the major limitations of conventional fluorescent staining and lipid extraction methods. In the laboratory, we have combined SRS microscopy with the genetic and biochemical tools available to the powerful model organism, Caenorhabditis elegans, to investigate the distribution and heterogeneity of lipid droplets across different cells and tissues and ultimately to discover novel conserved signaling pathways that modulate lipid metabolism. Here, we present the working principles and the detailed setup of the SRS microscope and provide methods for its use in quantifying lipid storage at distinct developmental timepoints of wild-type and insulin signaling deficient mutant C. elegans.

Label-Free Imaging of Lipid Storage Dynamics in <em>Caenorhabditis elegans</em> using Stimulated Raman Scattering Microscopy

Stimulated Raman scattering (SRS) microscopy allows selective, label-free imaging of specific chemical moieties and it has been effectively employed to image lipid molecules in vivo. Here, we provide a brief introduction to the principle of SRS microscopy and describe methods for its use in imaging lipid storage in Caenorhabditis elegans.

Fast denoising and lossless spectrum extraction in stimulated Raman scattering microscopy.

Stimulated Raman scattering (SRS) microscopy is a nonlinear optical imaging method for visualizing chemical content based on molecular vibrational bonds. However, the imaging speed and sensitivity are currently limited by the noise of the light beam probing the Raman process. In this paper, we present a fast non-average denoising and high-precision Raman shift extraction method, based on a self-reinforcing signal-to-noise ratio (SNR) enhancement algorithm, for SRS spectroscopy and microscopy. We compare the results of this method with the filtering methods and the reported experimental methods to demonstrate its high efficiency and high precision in spectral denoising, Raman peak extraction and image quality improvement. We demonstrate a maximum SNR enhancement of 10.3dB in fixed tissue imaging and 11.9dB in vivo imaging. This method reduces the cost and complexity of the SRS system and allows for high-quality SRS imaging without use of special laser, complicated system design and Raman tags.

Analysis of Pulses Bandwidth and Spectral Resolution in Femtosecond Stimulated Raman Scattering Microscopy

In the last decade, stimulated Raman scattering (SRS) imaging has been demonstrated to be a powerful method for label-free, non-invasive mapping of individual species distributions in a multicomponent system. This is due to the chemical selectivity of SRS techniques and the linear dependence of SRS signals on the individual species concentrations. However, even if significant efforts have been made to improve spectroscopic coherent Raman imaging technology, what is the best way to resolve overlapped Raman bands in biological samples is still an open question. In this framework, spectral resolution, i.e., the ability to distinguish closely lying resonances, is the crucial point. Therefore, in this paper, the interplay among pump and Stokes bandwidths, the degree of chirp-matching and the spectral resolution of femtosecond stimulated Raman scattering microscopy are experimentally investigated and the separation of protein and lipid bands in the C-H region, which are of great interest in biochemical studies, is, in principle, demonstrated.

Simulation of stimulated Raman scattering signal generation in scattering tissues excited by Bessel beams

Stimulated Raman scattering (SRS) microscopy has the ability of noninvasive imaging of specific chemical bonds and been increasingly used in biomedicine in recent years. Two pulsed Gaussian beams are used in traditional SRS microscopes, providing with high lateral and axial spatial resolution. Because of the tight focus of the Gaussian beam, such an SRS microscopy is difficult to be used for imaging deep targets in scattering tissues. The SRS microscopy based on Bessel beams can solve the imaging problem to a certain extent. Here, we establish a theoretical model to calculate the SRS signal excited by two Bessel beams by integrating the SRS signal generation theory with the fractal propagation method. The fractal model of refractive index turbulence is employed to generate the scattering tissues where the light transport is modeled by the beam propagation method. We model the scattering tissues containing chemicals, calculate the SRS signals stimulated by two Bessel beams, discuss the influence of the fractal model parameters on signal generation, and compare them with those generated by the Gaussian beams. The results show that, even though the modeling parameters have great influence on SRS signal generation, the Bessel beams-based SRS can generate signals in deeper scattering tissues.

Ultrasensitive Vibrational Imaging of Retinoids by Visible Preresonance Stimulated Raman Scattering Microscopy.

High‐sensitivity chemical imaging offers a window to decipher the molecular orchestra inside a living system. Based on vibrational fingerprint signatures, coherent Raman scattering microscopy provides a label‐free approach to map biomolecules and drug molecules inside a cell. Yet, by near‐infrared (NIR) pulse excitation, the sensitivity is limited to millimolar concentration for endogenous biomolecules. Here, the imaging sensitivity of stimulated Raman scattering (SRS) is significantly boosted for retinoid molecules to 34 micromolar via electronic preresonance in the visible wavelength regime. Retinoids play critical roles in development, immunity, stem cell differentiation, and lipid metabolism. By visible preresonance SRS (VP‐SRS) imaging, retinoid distribution in single embryonic neurons and mouse brain tissues is mapped, retinoid storage in chemoresistant pancreatic and ovarian cancers is revealed, and retinoids stored in protein network and lipid droplets of Caenorahbditis elegans are identified. These results demonstrate VP‐SRS microscopy as an ultrasensitive label‐free chemical imaging tool and collectively open new opportunities of understanding the function of retinoids in biological systems.

Mapping the Intratumoral Heterogeneity in Glioblastomas with Hyperspectral Stimulated Raman Scattering Microscopy.

Recent genomic studies on the glioblastoma (GBM) subtypes (e.g., mesenchymal, proneural, and classical) pave a way for effective clinical treatments of the recurrent brain tumor. However, identification of the GBM subtype is complicated by the intratumoral heterogeneity that results in coexistence of multiple subtypes within the tissue specimen. Here, we present the use of hyperspectral stimulated Raman scattering (SRS) microscopy for rapid, label-free molecular assessment of GBM intratumoral heterogeneity with submicron resolution. We develop a unique label-free Raman imaging diagnostic platform consisting of the spectral focusing hyperspectral SRS imaging of the large-area GBM tissue specimens, SRS images, and spectrum retrieval using the multivariate curve resolution algorithm and subtype classification based on the quadratic support vector machine model for rapid molecular subtyping of GBMs. Both the stain-free SRS histological images and 2D subtype maps can be obtained within 20-30 min which is superior to the days of the conventional single-cell RNA sequencing. While the SRS histology assesses the demyelination status as a new diagnostic feature, the SRS mapping provides a new insight into intratumoral heterogeneity across GBM tissue specimens. We find that the major proportions of the GBM tissues agree with the diagnostic results of the genomic analysis, but nontrivial portions of the remaining SRS image tiles in the specimens are found to belong to other molecular subtypes, implying the substantial degree of GBM heterogeneity. The rapid SRS imaging diagnostic platform developed has shown the ability of unveiling tumor heterogeneity in GBM tissues accurately, which would promote the improvement of the GBM-targeted therapy in near future.

Four-Channel Differential Lock-in Amplifiers With Autobalancing Network for Stimulated Raman Spectroscopy

We introduce a multi-channel integrated circuit for fast stimulated Raman scattering (SRS) microscopy on multiple simultaneous frequencies at a frame rate higher than 1 frame/s. The chip is a four-channel differential readout system, based on the lock-in technique. It is able to measure down to 10 ppm SRS signal, over a wide range of input optical powers (50-600 μW per channel), with a pixel dwell time of only 30 μs. Each acquisition channel includes two low-noise preamplifiers, two variable-gain amplifiers, a fully differential voltage subtractor, and a lock-in demodulator. The differential readout electronics rejects the power fluctuations of the laser, and it is automatically balanced by an analog feedback loop over ±30% input power mismatches. Due to the autobalancing network, the pixel dwell time is reduced by a factor up to 225 with a settling time of only 10 μs. The chip is fabricated in AMS 0.35 μm CMOS technology, and it is included in a combined electronics and optical system. Both single-pixel spectral measurements and multi-spectral imaging measurements are presented to validate the full SRS microscope.

A Spectral Resolution study in Femtosecond Stimulated Raman Scattering Microscopy

The simultaneous mapping and the specificity of different chemical species are desirable in several biological and biomedical applications. The stimulated Raman Scattering technique is a proven and well-established label-free method to map the distributions of individual species in a multi-component-based system due to the linear dependence of signals on concentration and its chemical selectivity. In this framework, spectral resolution, i.e., the ability to distinguish closely lying resonances, plays a fundamental role. Here in this work, the cross-correlation of Ti:Sa & OPO femtosecond laser beams in a stimulated Raman scattering microscope is measured. The separation between protein and lipid bands in the C-H region is important for biochemical research and is successfully classified.

Stimulated Raman Microscopy Implemented by Three Femtosecond Laser Sources

In this work, the implementation of a femtosecond Stimulated Raman Scattering microscope, equipped with three femtosecond laser sources: a Titanium-Sapphire (Ti:Sa), an optical parametric oscillator (OPO), and a second harmonic generator (SHG); is presented. Our microscope is designed so that it can cover all the regions of Raman spectra, taking advantage of two possible laser combinations. The first, Ti:Sa and OPO laser beams, which cover the C-H region (>2800 cm-1 ) in stimulated Raman gain (SRG) modality, whereas the second, Ti:Sa and SHG laser beams, covering the C-H region and the fingerprint region in stimulated Raman losses (SRL) modality. The successful realization of the microscope is demonstrated, reporting images of polystyrene beads using both SRL and SRG modalities.