High-Resolution Raman Imaging of >300 Patient-Derived Cells from Nine Different Leukemia Subtypes: A Global Clustering Approach.

Leukemia comprises a diverse group of bone marrow tumors marked by cell proliferation. Current diagnosis involves identifying leukemia subtypes through visual assessment of blood and bone marrow smears, a subjective and time-consuming method. Our study introduces the characterization of different leukemia subtypes using a global clustering approach of Raman hyperspectral maps of cells. We analyzed bone marrow samples from 19 patients, each presenting one of nine distinct leukemia subtypes, by conducting high spatial resolution Raman imaging on 319 cells, generating over 1.3 million spectra in total. An automated preprocessing pipeline followed by a single-step global clustering approach performed over the entire data set identified relevant cellular components (cytoplasm, nucleus, carotenoids, myeloperoxidase (MPO), and hemoglobin (HB)) enabling the unsupervised creation of high-quality pseudostained images at the single-cell level. Furthermore, this approach provided a semiquantitative analysis of cellular component distribution, and multivariate analysis of clustering results revealed the potential of Raman imaging in leukemia research, highlighting both advantages and challenges associated with global clustering.

Estimation of biological variance in coherent Raman microscopy data of two cell lines using chemometrics.

Broadband Coherent Anti-Stokes Raman Scattering (BCARS) is a valuable spectroscopic imaging tool for visualizing cellular structures and lipid distributions in biomedical applications. However, the inevitable biological changes in the samples (cells/tissues/lipids) introduce spectral variations in BCARS data and make analysis challenging. In this work, we conducted a systematic study to estimate the biological variance in BCARS data of two commonly used cell lines (HEK293 and HepG2) in biomedical research. The BCARS data were acquired from two different experimental setups (Leibniz Institute of Photonics Technology (IPHT) in Jena and Politecnico di Milano (POLIMI) in Milano) to evaluate the reproducibility of results. Also, spontaneous Raman data were independently acquired at POLIMI to validate those results. First, Kramers-Kronig (KK) algorithm was utilized to retrieve Raman-like signals from the BCARS data, and a pre-processing pipeline was subsequently used to standardize the data. Principal component analysis - Linear discriminant analysis (PCA-LDA) was performed using two cross-validation (CV) methods: batch-out CV and 10-fold CV. Additionally, the analysis was repeated, considering different spectral regions of the data as input to the PCA-LDA. Finally, the classification accuracies of the two BCARS datasets were compared with the results of spontaneous Raman data. The results demonstrated that the CH band region (2770-3070 cm-1) and spectral data in the 1500-1800 cm-1 region have significantly contributed to the classification. A maximum of 100% balanced accuracies were obtained for the 10-fold CV for both BCARS setups. However, in the case of batch-out CV, it is 92.4% for the IPHT dataset and 98.8% for the POLIMI dataset. This study offers a comprehensive overview for estimating biological variance in biomedical applications. The insights gained from this analysis hold promise for improving the reliability of BCARS measurements in biomedical applications, paving the way for more accurate and meaningful spectroscopic analyses in the study of biological systems.

Fingerprint multiplex CARS at high speed based on supercontinuum generation in bulk media and deep learning spectral denoising.

We introduce a broadband coherent anti-Stokes Raman scattering (CARS) microscope based on a 2-MHz repetition rate ytterbium laser generating 1035-nm high-energy (≈µJ level) femtosecond pulses. These features of the driving laser allow producing broadband red-shifted Stokes pulses, covering the whole fingerprint region (400-1800 cm-1), employing supercontinuum generation in a bulk crystal. Our system reaches state-of-the-art acquisition speed (<1 ms/pixel) and unprecedented sensitivity of ≈14.1 mmol/L when detecting dimethyl sulfoxide in water. To further improve the performance of the system and to enhance the signal-to-noise ratio of the CARS spectra, we designed a convolutional neural network for spectral denoising, coupled with a post-processing pipeline to distinguish different chemical species of biological tissues.

A Bioorthogonal Probe for Multiscale Imaging by 19F-MRI and Raman Microscopy: From Whole Body to Single Cells.

Molecular imaging techniques are essential tools for better investigating biological processes and detecting disease biomarkers with improvement of both diagnosis and therapy monitoring. Often, a single imaging technique is not sufficient to obtain comprehensive information at different levels. Multimodal diagnostic probes are key tools to enable imaging across multiple scales. The direct registration of in vivo imaging markers with ex vivo imaging at the cellular level with a single probe is still challenging. Fluorinated (19F) probes have been increasingly showing promising potentialities for in vivo cell tracking by 19F-MRI. Here we present the unique features of a bioorthogonal 19F-probe that enables direct signal correlation of MRI with Raman imaging. In particular, we reveal the ability of PERFECTA, a superfluorinated molecule, to exhibit a remarkable intense Raman signal distinct from cell and tissue fingerprints. Therefore, PERFECTA combines in a single molecule excellent characteristics for both macroscopic in vivo 19F-MRI, across the whole body, and microscopic imaging at tissue and cellular levels by Raman imaging.

Surface Enhanced Raman Spectroscopy for Quantitative Analysis: Results of a Large-Scale European Multi-Instrument Interlaboratory Study.

Surface-enhanced Raman scattering (SERS) is a powerful and sensitive technique for the detection of fingerprint signals of molecules and for the investigation of a series of surface chemical reactions. Many studies introduced quantitative applications of SERS in various fields, and several SERS methods have been implemented for each specific application, ranging in performance characteristics, analytes used, instruments, and analytical matrices. In general, very few methods have been validated according to international guidelines. As a consequence, the application of SERS in highly regulated environments is still considered risky, and the perception of a poorly reproducible and insufficiently robust analytical technique has persistently retarded its routine implementation. Collaborative trials are a type of interlaboratory study (ILS) frequently performed to ascertain the quality of a single analytical method. The idea of an ILS of quantification with SERS arose within the framework of Working Group 1 (WG1) of the EU COST Action BM1401 Raman4Clinics in an effort to overcome the problematic perception of quantitative SERS methods. Here, we report the first interlaboratory SERS study ever conducted, involving 15 laboratories and 44 researchers. In this study, we tried to define a methodology to assess the reproducibility and trueness of a quantitative SERS method and to compare different methods. In our opinion, this is a first important step toward a "standardization" process of SERS protocols, not proposed by a single laboratory but by a larger community.

Chemical Perturbation of Oncogenic Protein Folding: from the Prediction of Locally Unstable Structures to the Design of Disruptors of Hsp90-Client Interactions.

Protein folding quality control in cells requires the activity of a class of proteins known as molecular chaperones. Heat shock protein-90 (Hsp90), a multidomain ATP driven molecular machine, is a prime representative of this family of proteins. Interactions between Hsp90, its co-chaperones, and client proteins have been shown to be important in facilitating the correct folding and activation of clients. Hsp90 levels and functions are elevated in tumor cells. Here, we computationally predict the regions on the native structures of clients c-Abl, c-Src, Cdk4, B-Raf and Glucocorticoid Receptor, that have the highest probability of undergoing local unfolding, despite being ordered in their native structures. Such regions represent potential ideal interaction points with the Hsp90-system. We synthesize mimics spanning these regions and confirm their interaction with partners of the Hsp90 complex (Hsp90, Cdc37 and Aha1) by Nuclear Magnetic Resonance (NMR). Designed mimics selectively disrupt the association of their respective clients with the Hsp90 machinery, leaving unrelated clients unperturbed and causing apoptosis in cancer cells. Overall, selective targeting of Hsp90 protein-protein interactions is achieved without causing indiscriminate degradation of all clients, setting the stage for the development of therapeutics based on specific chaperone:client perturbation.

Raman spectroscopy reveals biochemical differences in plasma derived extracellular vesicles from sporadic Amyotrophic Lateral Sclerosis patients.

Sporadic amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease for which there is no validated blood based biomarker. Extracellular vesicles (EVs) have the potential to solve this unmet clinical need. However, due to their heterogeneity and complex chemical composition, EVs are difficult to study. Raman spectroscopy (RS) is an optical method that seems particularly well suited to address this task. In fact, RS provides an overview of the biochemical composition of EVs quickly and virtually without any sample preparation. In this work, we studied by RS small extracellular vesicles (sEVs), large extracellular vesicles (lEVs) and blood plasma of sporadic ALS patients and of a matched cohort of healthy controls. The obtained results highlighted lEVs as a particularly promising biomarker for ALS. In fact, their Raman spectra show that sporadic ALS patients have a different lipid content and less intense bands relative to the aromatic amino acid phenylalanine.

A simple and universal enzyme-free approach for the detection of multiple microRNAs using a single nanostructured enhancer of surface plasmon resonance imaging.

Here we describe a simple approach for the simultaneous detection of multiple microRNAs (miRNAs) using a single nanostructured reagent as surface plasmon resonance imaging (SPRi) enhancer and without using enzymatic reactions, sequence specific enhancers or multiple enhancing steps as normally reported in similar studies. The strategy involves the preparation and optimisation of neutravidin-coated gold nanospheres (nGNSs) functionalised with a previously biotinylated antibody (Ab) against DNA/RNA hybrids. The Ab guarantees the recognition of any miRNA sequence adsorbed on a surface properly functionalised with different DNA probes; at the same time, gold nanoparticles permit to detect this interaction, thus producing enough SPRi signal even at a low ligand concentration. After a careful optimisation of the nanoenhancer and after its characterisation, the final assay allowed the simultaneous detection of four miRNAs with a limit of detection (LOD) of up to 0.5 pM (equal to 275 attomoles in 500 µL) by performing a single enhancing injection. The proposed strategy shows good signal specificity and permits to discriminate wild-type, single- and triple-mutated sequences much better than non-enhanced SPRi. Finally, the method works properly in complex samples (total RNA extracted from blood) as demonstrated by the detection of four miRNAs potentially related to multiple sclerosis used as case study. This proof-of-concept study confirms that the approach provides the possibility to detect a theoretically unlimited number of miRNAs using a simple protocol and an easily prepared enhancing reagent, and may further facilitate the development of affordable multiplexing miRNA screening for clinical purposes.

Nano-Strategies to Target Breast Cancer-Associated Fibroblasts: Rearranging the Tumor Microenvironment to Achieve Antitumor Efficacy.

Cancer-associated fibroblasts (CAF) are the most abundant cells of the tumor stroma and they critically influence cancer growth through control of the surrounding tumor microenvironment (TME). CAF-orchestrated reactive stroma, composed of pro-tumorigenic cytokines and growth factors, matrix components, neovessels, and deregulated immune cells, is associated with poor prognosis in multiple carcinomas, including breast cancer. Therefore, beyond cancer cells killing, researchers are currently focusing on TME as strategy to fight breast cancer. In recent years, nanomedicine has provided a number of smart delivery systems based on active targeting of breast CAF and immune-mediated overcome of chemoresistance. Many efforts have been made both to eradicate breast CAF and to reshape their identity and function. Nano-strategies for CAF targeting profoundly contribute to enhance chemosensitivity of breast tumors, enabling access of cytotoxic T-cells and reducing immunosuppressive signals. TME rearrangement also includes reorganization of the extracellular matrix to enhance permeability to chemotherapeutics, and nano-systems for smart coupling of chemo- and immune-therapy, by increasing immunogenicity and stimulating antitumor immunity. The present paper reviews the current state-of-the-art on nano-strategies to target breast CAF and TME. Finally, we consider and discuss future translational perspectives of proposed nano-strategies for clinical application in breast cancer.

Detection and Characterization of Different Brain-Derived Subpopulations of Plasma Exosomes by Surface Plasmon Resonance Imaging.

The use of exosomes for diagnostic and disease monitoring purposes is becoming particularly appealing in biomedical research because of the possibility to study directly in biological fluids some of the features related to the organs from which exosomes originate. A paradigmatic example are brain-derived exosomes that can be found in plasma and used as a direct read-out of the status of the central nervous system (CNS). Inspired by recent remarkable development of plasmonic biosensors, we have designed a surface plasmon resonance imaging (SPRi) assay that, taking advantage of the fact that exosome size perfectly fits within the surface plasmon wave depth, allows the detection of multiple exosome subpopulations of neural origin directly in blood. By use of an array of antibodies, exosomes derived from neurons and oligodendrocytes were isolated and detected with good sensitivity. Subsequently, by injecting a second antibody on the immobilized vesicles, we were able to quantify the amount of CD81 and GM1, membrane components of exosomes, on each subpopulation. In this way, we have been able to demonstrate that they are not homogeneously expressed but exhibit a variable abundance according to the exosome cellular origin. These results confirm the extreme variability of exosome composition and demonstrate how SPRi can provide an effective tool for their characterization. Besides, our work paves the road toward more precise clinical studies on the use of exosomes as potential biomarkers of neurodegenerative diseases.

H-Ferritin Enriches the Curcumin Uptake and Improves the Therapeutic Efficacy in Triple Negative Breast Cancer Cells.

Triple negative breast cancer (TNBC) is a highly aggressive, invasive, and metastatic tumor. Although it is reported to be sensitive to cytotoxic chemotherapeutics, frequent relapse and chemoresistance often result in treatment failure. In this study, we developed a biomimetic nanodrug consisting of a self-assembling variant (HFn) of human apoferritin loaded with curcumin. HFn nanocage improved the solubility, chemical stability, and bioavailability of curcumin, allowing us to reliably carry out several experiments in the attempt to establish the potential of this molecule as a therapeutic agent and elucidate the mechanism of action in TNBC. HFn biopolymer was designed to bind selectively to the TfR1 receptor overexpressed in TNBC cells. HFn-curcumin (CFn) proved to be more effective in viability assays compared to the drug alone using MDA-MB-468 and MDA-MB-231 cell lines, representative of basal and claudin-low TNBC subtypes, respectively. Cellular uptake of CFn was demonstrated by flow cytometry and label-free confocal Raman imaging. CFn could act as a chemosensitizer enhancing the cytotoxic effect of doxorubicin by interfering with the activity of multidrug resistance transporters. In addition, CFn exhibited different cell cycle effects on these two TNBC cell lines, blocking MDA-MB-231 in G0/G1 phase, whereas MDA-MB-468 accumulated in G2/M phase. CFn was able to inhibit the Akt phosphorylation, suggesting that the effect on the proliferation and cell cycle involved the alteration of PI3K/Akt pathway.

Antiproliferative effect of ASC-J9 delivered by PLGA nanoparticles against estrogen-dependent breast cancer cells.

Among polymeric nanoparticles designed for cancer therapy, PLGA nanoparticles have become one of the most popular polymeric devices for chemotherapeutic-based nanoformulations against several kinds of malignant diseases. Promising properties, including long-circulation time, enhanced tumor localization, interference with "multidrug" resistance effects, and environmental biodegradability, often result in an improvement of the drug bioavailability and effectiveness. In the present work, we have synthesized 1,7-bis(3,4-dimethoxyphenyl)-5-hydroxyhepta-1,4,6-trien-3-one (ASC-J9) and developed uniform ASC-J9-loaded PLGA nanoparticles of about 120 nm, which have been prepared by a single-emulsion process. Structural and morphological features of the nanoformulation were analyzed, followed by an accurate evaluation of the in vitro drug release kinetics, which exhibited Fickian law diffusion over 10 days. The intracellular degradation of ASC-J9-bearing nanoparticles within estrogen-dependent MCF-7 breast cancer cells was correlated to a time- and dose-dependent activity of the released drug. A cellular growth inhibition associated with a specific cell cycle G2/M blocking effect caused by ASC-J9 release inside the cytosol allowed us to put forward a hypothesis on the action mechanism of this nanosystem, which led to the final cell apoptosis. Our study was accomplished using Annexin V-based cell death analysis, MTT assessment of proliferation, radical scavenging activity, and intracellular ROS evaluation. Moreover, the intracellular localization of nanoformulated ASC-J9 was confirmed by a Raman optical imaging experiment designed ad hoc. PLGA nanoparticles and ASC-J9 proved also to be safe for a healthy embryo fibroblast cell line (3T3-L1), suggesting a possible clinical translation of this potential nanochemotherapeutic to expand the inherently poor bioavailability of hydrophobic ASC-J9 that could be proposed for the treatment of malignant breast cancer.

Label-free morpho-molecular phenotyping of living cancer cells by combined Raman spectroscopy and phase tomography.

Accurate, rapid and non-invasive cancer cell phenotyping is a pressing concern across the life sciences, as standard immuno-chemical imaging and omics require extended sample manipulation. Here we combine Raman micro-spectroscopy and phase tomography to achieve label-free morpho-molecular profiling of human colon cancer cells, following the adenoma, carcinoma, and metastasis disease progression, in living and unperturbed conditions. We describe how to decode and interpret quantitative chemical and co-registered morphological cell traits from Raman fingerprint spectra and refractive index tomograms. Our multimodal imaging strategy rapidly distinguishes cancer phenotypes, limiting observations to a low number of pristine cells in culture. This synergistic dataset allows us to study independent or correlated information in spectral and tomographic maps, and how it benefits cell type inference. This method is a valuable asset in biomedical research, particularly when biological material is in short supply, and it holds the potential for non-invasive monitoring of cancer progression in living organisms.

Birefringence-induced phase delay enables Brillouin mechanical imaging in turbid media.

Acoustic vibrations of matter convey fundamental viscoelastic information that can be optically retrieved by hyperfine spectral analysis of the inelastic Brillouin scattered light. Increasing evidence of the central role of the viscoelastic properties in biological processes has stimulated the rise of non-contact Brillouin microscopy, yet this method faces challenges in turbid samples due to overwhelming elastic background light. Here, we introduce a common-path Birefringence-Induced Phase Delay (BIPD) filter to disentangle the polarization states of the Brillouin and Rayleigh signals, enabling the rejection of the background light using a polarizer. We demonstrate a 65 dB extinction ratio in a single optical pass collecting Brillouin spectra in extremely scattering environments and across highly reflective interfaces. We further employ the BIPD filter to image bone tissues from a mouse model of osteopetrosis, highlighting altered biomechanical properties compared to the healthy control. Results herald new opportunities in mechanobiology where turbid biological samples remain poorly characterized.

Deep ensemble learning and transfer learning methods for classification of senescent cells from nonlinear optical microscopy images.

The success of chemotherapy and radiotherapy anti-cancer treatments can result in tumor suppression or senescence induction. Senescence was previously considered a favorable therapeutic outcome, until recent advancements in oncology research evidenced senescence as one of the culprits of cancer recurrence. Its detection requires multiple assays, and nonlinear optical (NLO) microscopy provides a solution for fast, non-invasive, and label-free detection of therapy-induced senescent cells. Here, we develop several deep learning architectures to perform binary classification between senescent and proliferating human cancer cells using NLO microscopy images and we compare their performances. As a result of our work, we demonstrate that the most performing approach is the one based on an ensemble classifier, that uses seven different pre-trained classification networks, taken from literature, with the addition of fully connected layers on top of their architectures. This approach achieves a classification accuracy of over 90%, showing the possibility of building an automatic, unbiased senescent cells image classifier starting from multimodal NLO microscopy data. Our results open the way to a deeper investigation of senescence classification via deep learning techniques with a potential application in clinical diagnosis.

Full-Spectrum CARS Microscopy of Cells and Tissues with Ultrashort White-Light Continuum Pulses.

Coherent anti-Stokes Raman scattering (CARS) microscopy is an emerging nonlinear vibrational imaging technique that delivers label-free chemical maps of cells and tissues. In narrowband CARS, two spatiotemporally superimposed picosecond pulses, pump and Stokes, illuminate the sample to interrogate a single vibrational mode. Broadband CARS (BCARS) combines narrowband pump pulses with broadband Stokes pulses to record broad vibrational spectra. Despite recent technological advancements, BCARS microscopes still struggle to image biological samples over the entire Raman-active region (400-3100 cm-1). Here, we demonstrate a robust BCARS platform that answers this need. Our system is based on a femtosecond ytterbium laser at a 1035 nm wavelength and a 2 MHz repetition rate, which delivers high-energy pulses used to produce broadband Stokes pulses by white-light continuum generation in a bulk YAG crystal. Combining such pulses, pre-compressed to sub-20 fs duration, with narrowband pump pulses, we generate a CARS signal with a high (<9 cm-1) spectral resolution in the whole Raman-active window, exploiting both the two-color and three-color excitation mechanisms. Aided by an innovative post-processing pipeline, our microscope allows us to perform high-speed (≈1 ms pixel dwell time) imaging over a large field of view, identifying the main chemical compounds in cancer cells and discriminating tumorous from healthy regions in liver slices of mouse models, paving the way for applications in histopathological settings.

Noninvasive morpho-molecular imaging reveals early therapy-induced senescence in human cancer cells.

Anticancer therapy screening in vitro identifies additional treatments and improves clinical outcomes. Systematically, although most tested cells respond to cues with apoptosis, an appreciable portion enters a senescent state, a critical condition potentially driving tumor resistance and relapse. Conventional screening protocols would strongly benefit from prompt identification and monitoring of therapy-induced senescent (TIS) cells in their native form. We combined complementary all-optical, label-free, and quantitative microscopy techniques, based on coherent Raman scattering, multiphoton absorption, and interferometry, to explore the early onset and progression of this phenotype, which has been understudied in unperturbed conditions. We identified TIS manifestations as early as 24 hours following treatment, consisting of substantial mitochondrial rearrangement and increase of volume and dry mass, followed by accumulation of lipid vesicles starting at 72 hours. This work holds the potential to affect anticancer treatment research, by offering a label-free, rapid, and accurate method to identify initial TIS in tumor cells.

Time domain diffuse Raman spectroscopy using single pixel detection.

Diffuse Raman spectroscopy (DIRS) extends the high chemical specificity of Raman scattering to in-depth investigation of thick biological tissues. We present here a novel approach for time-domain diffuse Raman spectroscopy (TD-DIRS) based on a single-pixel detector and a digital micromirror device (DMD) within an imaging spectrometer for wavelength encoding. This overcomes the intrinsic complexity and high cost of detection arrays with ps-resolving time capability. Unlike spatially offset Raman spectroscopy (SORS) or frequency offset Raman spectroscopy (FORS), TD-DIRS exploits the time-of-flight distribution of photons to probe the depth of the Raman signal at a single wavelength with a single source-detector separation. We validated the system using a bilayer tissue-bone mimicking phantom composed of a 1 cm thick slab of silicone overlaying a calcium carbonate specimen and demonstrated a high differentiation of the two Raman signals. We reconstructed the Raman spectra of the two layers, offering the potential for improved and quantitative material analysis. Using a bilayer phantom made of porcine muscle and calcium carbonate, we proved that our system can retrieve Raman peaks even in the presence of autofluorescence typical of biomedical tissues. Overall, our novel TD-DIRS setup proposes a cost-effective and high-performance approach for in-depth Raman spectroscopy in diffusive media.

Quantification and prospective evaluation of serum NfL and GFAP as blood-derived biomarkers of outcome in acute ischemic stroke patients.

Identification of reliable and accessible biomarkers to characterize ischemic stroke patients' prognosis remains a clinical challenge. Neurofilament light chain (NfL) and glial fibrillary acidic protein (GFAP) are markers of brain injury, detectable in blood by high-sensitive technologies. Our aim was to measure serum NfL and GFAP after stroke, and to evaluate their correlation with functional outcome and the scores in rehabilitation scales at 3-month follow-up. Stroke patients were prospectively enrolled in a longitudinal observational study within 24 hours from symptom onset (D1) and monitored after 7 (D7), 30 ± 3 (M1) and 90 ± 5 (M3) days. At each time-point serum NfL and GFAP levels were measured by Single Molecule Array and correlated with National Institute of Health Stroke Scale (NIHSS), modified Rankin scale (mRS), Trunk Control Test (TCT), Functional Ambulation Classification (FAC) and Functional Independence Measure (FIM) scores. Serum NfL and GFAP showed different temporal profiles: NfL increased after stroke with a peak value at D7; GFAP showed an earlier peak at D1. NfL and GFAP concentrations correlated with clinical/rehabilitation outcomes both longitudinally and prospectively. Multivariate analysis revealed that NfL-D7 and GFAP-D1 were independent predictors of 3-month NIHSS, TCT, FAC and FIM scores, with NfL being the biomarker with the best predictive performance.

Multiplex Chemical Imaging Based on Broadband Stimulated Raman Scattering Microscopy.

Stimulated Raman scattering (SRS) microscopy is a nonlinear optical technique for label-free chemical imaging. This analytical tool delivers chemical maps at high speed, and high spatial resolution of thin samples by directly interrogating their molecular vibrations. In its standard implementation, SRS microscopy is narrowband and forms images with only a single vibrational frequency at a time. However, this approach not only hinders the chemical specificity of SRS but also neglects the wealth of information encoded within vibrational spectra. These limitations can be overcome by broadband SRS, an implementation capable of extracting a vibrational spectrum per pixel of the image in parallel. This delivers hyperspectral data that, when coupled with chemometric analysis, maximizes the amount of information retrieved from the specimen. Thus, broadband SRS improves the chemical specificity of the system, allowing the quantitative determination of the concentration of the different constituents of a sample. Here, we report a protocol for chemical imaging with broadband SRS microscopy, based on a home-built SRS microscope operating with a custom differential multichannel-lock-in amplifier detection. It discusses the sample preparation, alignment of the SRS apparatus, and chemometric analysis. By acquiring vibrational Raman spectra, the protocol illustrates how to identify different chemical species within a mixture, determining their relative concentrations.