Methodology for fiber-optic Raman mapping and FTIR imaging of metastases in mouse brains

The objectives of this study were to optimize the preparation of pristine brain tissue to obtain reference information, to optimize the conditions for introducing a fiber-optic probe to acquire Raman maps, and to transfer previous results obtained from human brain tumors to an animal model. Brain metastases of malignant melanomas were induced by injecting tumor cells into the carotid artery of mice. The procedure mimicked hematogenous tumor spread in one brain hemisphere while the other hemisphere remained tumor free. Three series of sections were prepared consecutively from whole mouse brains: dried, thin sections for FTIR imaging, hematoxylin and eosin-stained thin sections for histopathological assessment, and pristine, 2-mm thick sections for Raman mapping. FTIR images were recorded using a spectrometer with a multi-channel detector. Raman maps were collected serially using a spectrometer coupled to a fiber-optic probe. The FTIR images and the Raman maps were segmented by cluster analysis. The color-coded cluster memberships coincided well with the morphology of mouse brains in stained tissue sections. More details in less time were resolved in FTIR images with a nominal resolution of 25 microm than in Raman maps collected with a laser focus 60 microm in diameter. The spectral contributions of melanin in tumor cells were resonance enhanced in Raman spectra on excitation at 785 nm which enabled their sensitive detection in Raman maps. Possible reasons why metastatic cells of malignant melanomas were not identified in FTIR images are discussed.     

Multivariate data analysis for Raman imaging of a model pharmaceutical tablet

Spectroscopic imaging techniques provide spatial and spectral information about a sample simultaneously and are finding ever-increasing application in the pharmaceutical industry. Effective extraction of chemical information from imaging data sets is a crucial step during the application of imaging techniques. Multivariate imaging data analysis methods have been reported but few applications of these methods for pharmaceutical samples have been demonstrated. In this study, a bilayer model tablet consisting of avicel, lactose, sodium benzoate, magnesium stearate and red dye was prepared using custom press tooling, and Raman mapping data were collected from a 400 μm × 400 μm area of the tablet surface. Several representative multivariate methods were selected and used in the analysis of the data. Multivariate data analysis methods investigated include principal component analysis (PCA), cluster analysis, direct classical least squares (DCLS) and multivariate curve resolution (MCR). The relative merits and drawbacks of each technique for this application were evaluated. In addition, some practical issues associated with the use of these methods were addressed including data preprocessing, determination of the optimal number of clusters in cluster analysis and the optimization of window size in second derivative calculation.     

Near infrared Raman spectroscopic mapping of native brain tissue and intracranial tumors

This study assessed the diagnostic potential of Raman spectroscopic mapping by evaluating its ability to distinguish between normal brain tissue and the human intracranial tumors gliomas and meningeomas. Seven Raman maps of native specimens were collected ex vivo by a Raman spectrometer with 785 nm excitation coupled to a microscope with a motorized stage. Variations within each Raman map were analyzed by cluster analysis. The dependence of tissue composition on the tissue type in cluster averaged Raman spectra was shown by linear combinations of reference spectra. Normal brain tissue was found to contain higher levels of lipids, intracranial tumors have more hemoglobin and lower lipid to protein ratios, meningeomas contain more collagen with maximum collagen content in normal meninges. One sample was studied without freezing. Whereas tumor regions did not change significantly, spectral changes were observed in the hemoglobin component after snap freezing and thawing to room temperature. The results constitute a basis for subsequent Raman studies to develop classification models for diagnosis of brain tissue.     

Heterogeneous chemistry between PbSO4 and calcite microparticles using Raman microimaging

Currently, the smelting activities of lead and zinc are the loudest sources of local pollution by emission in the troposphere of dust of micrometer size containing PbSO(4). As the particles evolve in the troposphere, their chemical and physical properties - and hence their characteristics such as toxicity - change by accumulation of atmospheric heterogeneous reactions. Calcite (CaCO(3)) represents a large part of the mineral fraction in tropospheric aerosols with aerodynamic diameters less than 10 microm. The calcite particles are expected to react with PbSO(4) particles. In an effort to model the chemical behaviour of PbSO(4) individual particles in the troposphere, we present the in situ Raman imaging results during the course of the reactions in a water droplet of PbSO(4) particles with a calcite microcrystal surface. The computer-microcontrolled XY scanning and Z focusing of confocal Raman imaging combined with multivariate curve resolution (MCR) of Raman images have resolved the severe spectral overlaps of the Raman spectra which are not resolved by the spatial resolution of the instrument ( approximately 1 microm(3)). The results pointed out the identification and the mapping of Pb(3)(CO(3))(2)(OH)(2), PbCO(3) and CaSO(4).2H(2)O (gypsum) on the calcite surface.     

Crisp and soft multivariate methods visualize individual cell nuclei in Raman images of liver tissue sections

Raman and infrared spectroscopy have been recognized to be promising tools in clinical diagnostics because they provide molecular contrast without external stains. Here, vertex component analysis (VCA) was applied to Raman and Fourier transform infrared (FTIR) images of liver tissue sections and the results were compared with K-means cluster analysis, fuzzy C-means cluster analysis and principal component analysis. The main components of VCA from three Raman images were assigned to the central vein, periportal vein, cell nuclei, liver parenchyma and bile duct. After resonant Mie scattering correction, VCA of FTIR images identified veins, liver parenchyma, cracks, but no cell nuclei. The advantages of VCA in the context of tissue characterization by vibrational spectroscopic imaging are that the tissue architecture is visualized and the spectral information is reconstructed. Composite images were constructed that revealed a high molecular contrast and that can be interpreted in a similar way like hematoxylin and eosin stained tissue sections.     

Chemical imaging of articular cartilage sections with Raman mapping, employing uni- and multi-variate methods for data analysis

Raman mapping in combination with uni- and multi-variate methods of data analysis is applied to articular cartilage samples. Main differences in biochemical composition and collagen fibers orientation between superficial, middle and deep zone of the tissue are readily observed in the samples. Collagen, non-collagenous proteins, proteoglycans and nucleic acids can be distinguished on the basis of their different spectral characteristics, and their relative abundance can be mapped in the label-free tissue samples, at so high a resolution as to permit the analysis at the level of single cells. Differences between territorial and inter-territorial matrix, as well as inhomogeneities in the inter-territorial matrix, are properly identified. Multivariate methods of data analysis prove to be complementary to the univariate approach. In particular, our partial least squares regression model gives a semiquantitative mapping of the biochemical constituents in agreement with average composition found in the literature. The combination of hierarchical and fuzzy cluster analysis succeeds in detecting variations between different regions of the extra-cellular matrix. Because of its characteristics as an imaging technique, Raman mapping could be a promising tool for studying biochemical changes in cartilage occurring during aging or osteoarthritis.     

Unsupervised unmixing of Raman microspectroscopic images for morphochemical analysis of non-dried brain tumor specimens

Raman microspectroscopic imaging provides molecular contrast in a label-free manner with subcellular spatial resolution. These properties might complement clinical tools for diagnosis of tissue and cells in the future. Eight Raman spectroscopic images were collected with 785 nm excitation from five non-dried brain specimens immersed in aqueous buffer. The specimens were assigned to molecular and granular layers of cerebellum, cerebrum with and without scattered tumor cells of astrocytoma WHO grade III, ependymoma WHO grade II, astrocytoma WHO grade III, and glioblastoma multiforme WHO grade IV with subnecrotic and necrotic regions. In contrast with dried tissue section, these samples were not affected by drying effects such as crystallization of lipids or denaturation of proteins and nucleic acids. The combined data sets were processed by use of the hyperspectral unmixing algorithms N-FINDR and VCA. Both unsupervised approaches calculated seven endmembers that reveal the abundance plots and spectral signatures of cholesterol, cholesterol ester, nucleic acids, carotene, proteins, lipids, and buffer. The endmembers were correlated with Raman spectra of reference materials. The focus of the single mode laser near 1 μm and the step size of 2 μm were sufficiently small to resolve morphological details, for example cholesterol ester islets and cell nuclei. The results are compared for both unmixing algorithms and with previously reported supervised spectral decomposition techniques.     

Differentiation of individual human mesenchymal stem cells probed by FTIR microscopic imaging

Objective of this study is the novel application of Fourier transform infrared (FTIR) microscopic imaging to identify the differentiation state of individual human mesenchymal stem cells with or without osteogenic stimulation. IR spectra of several hundred single cells with lateral resolution of 5-10 microm were recorded using a FTIR imaging spectrometer coupled to a microscope with a focal plane array detector. A classification model based on linear discriminant analysis was trained to distinguish four cell types by their IR spectroscopic fingerprint. Without stimulation two cell types dominated, showing low or high levels of glycogen accumulation at the cell periphery. After stimulation, the protein composition in the cells changed and some cells started expressing calcium phosphate salts such as octacalciumphosphate, a precursor of the bone constituent hydroxyapatite. Few cells were identified which remained in their non-stimulated state. This study demonstrated for the first time that FTIR microscopic imaging can probe stem cell differentiation at the single cell level rapidly, non-destructively and with minimal preparation.     

Delimitation of squamous cell cervical carcinoma using infrared microspectroscopic imaging

Infrared (IR) spectroscopic imaging coupled with microscopy has been used to investigate thin sections of cervix uteri encompassing normal tissue, precancerous structures, and squamous cell carcinoma. Methods for unsupervised distinction of tissue types based on IR spectroscopy were developed. One-hundred and twenty-two images of cervical tissue were recorded by an FTIR spectrometer with a 64×64 focal plane array detector. The 499,712 IR spectra obtained were grouped by an approach which used fuzzy C-means clustering followed by hierarchical cluster analysis. The resulting false color maps were correlated with the morphological characteristics of an adjacent section of hematoxylin and eosin-stained tissue. In the first step, cervical stroma, epithelium, inflammation, blood vessels, and mucus could be distinguished in IR images by analysis of the spectral fingerprint region (950–1480 cm⁻¹). In the second step, analysis in the spectral window 1420–1480 cm⁻¹ enables, for the first time, IR spectroscopic distinction between the basal layer, dysplastic lesions and squamous cell carcinoma within a particular sample. The joint application of IR microspectroscopic imaging and multivariate spectral processing combines diffraction-limited lateral optical resolution on the single cell level with highly specific and sensitive spectral classification on the molecular level. Compared with previous reports our approach constitutes a significant progress in the development of optical molecular spectroscopic techniques toward an additional diagnostic tool for the early histopathological characterization of cervical cancer.     

Molecular composition and orientation in myelin figures characterized by coherent anti-stokes Raman scattering microscopy

The molecular organization inside myelin figures of various surfactants are studied by laser scanning coherent anti-Stokes Raman scattering (CARS) microscopy that permits three-dimension vibrational imaging. The resonant CARS signals from CH2 and H2O stretch vibrations are used to probe the surfactant and water molecules inside the myelin figures formed of C12E3, lecithin, and Aerosol OT. The polarization sensitivity of CARS is used to analyze the orientation of the CH2 groups and the H2O molecules. The CARS images suggest that the myelin figure is a concentric lamellar structure with alternating surfactant bilayers and partially ordered water layers. No sizable water core is observed in the CARS images at the lateral resolution of 0.3 microm and the axial resolution of 0.75 microm. The CARS data are verified by confocal fluorescence microscopy with FITC and DOPE-rhodamine labeling the water and bilayers, respectively. The relationship between the molecular composition and ordering inside the myelin figures and the surfactant structure has been investigated.     

Raman spectroscopic imaging for in vivo detection of cerebral brain metastases

We report for the first time a proof-of-concept experiment employing Raman spectroscopy to detect intracerebral tumors in vivo by brain surface mapping. Raman spectroscopy is a non-destructive biophotonic method which probes molecular vibrations. It provides a specific fingerprint of the biochemical composition and structure of tissue without using any labels. Here, the Raman system was coupled to a fiber-optic probe. Metastatic brain tumors were induced by injection of murine melanoma cells into the carotid artery of mice, which led to subcortical and cortical tumor growth within 14 days. Before data acquisition, the cortex was exposed by creating a bony window covered by a calcium fluoride window. Spectral contributions were assigned to proteins, lipids, blood, water, bone, and melanin. Based on the spectral information, Raman images enabled the localization of cortical and subcortical tumor cell aggregates with accuracy of roughly 250 μm. This study demonstrates the prospects of Raman spectroscopy as an intravital tool to detect cerebral pathologies and opens the field for biophotonic imaging of the living brain. Future investigations aim to reduce the exposure time from minutes to seconds and improve the lateral resolution.     

FTIR and Raman microspectroscopy of normal,benign, and malignant formalin-fixed ovarian tissues

Ovarian cancer is the sixth most common cancer among women worldwide, and mortality rates from this cancer are higher than for other gynecological cancers. This is attributed to a lack of reliable screening methods and the inadequacy of treatment modalities for the advanced stages of the disease. FTIR and Raman spectroscopic studies of formalin-fixed normal, benign, and malignant ovarian tissues have been undertaken in order to investigate and attempt to understand the underlying biochemical changes associated with the disease, and to explore the feasibility of discriminating between these different tissue types. Raman spectra of normal tissues indicate the dominance of proteins and lower contents of DNA and lipids compared to malignant tissues. Among the pathological tissues studied, spectra from benign tissues seem to contain more proteins and less DNA and lipids compared to malignant tissue spectra. FTIR studies corroborate these findings. FTIR and Raman spectra of both normal and benign tissues showed more similarities than those of malignant tissues. Cluster analysis of first-derivative Raman spectra in the 700–1700 cm⁻¹ range gave two clear groups, one corresponding to malignant and the other to normal+benign tissues. At a lower heterogeneity level, the normal+benign cluster gave three nonoverlapping subclusters, one corresponding to normal and two for benign tissues. Cluster analysis of second-derivative FTIR spectra in the combined spectral regions of 1540–1680 and 1720–1780 cm⁻¹ resulted into two clear clusters corresponding to malignant and normal+benign tissues. The cluster corresponding to normal+benign tissues produced nonoverlapping subclusters for normal and benign tissues at a lower heterogeneity level. The findings of this study demonstrate the feasibility of Raman and FTIR microspectroscopic discrimination of formalin-fixed normal, benign, and malignant ovarian tissues.     

Experimental Testing of Lateral and Depth Resolution in Imaging Methods

A polymer laminate and a PA-PTFE blend were studied by various imaging methods (FT-IR, Raman, ESEM). Different lateral and depth resolution of the methods were used to gain complementary information on the structure of the materials. Radiation damage caused by the electron beam during ESEM investigation was studied by Raman global imaging.     

Mass spectrometry imaging with high resolution in mass and space (HR<Superscript>2</Superscript> MSI) for reliable investigation of drug compound distributions on the cellular level

Mass spectrometry (MS) imaging is a versatile method to analyze the spatial distribution of analytes in tissue sections. It provides unique features for the analysis of drug compounds in pharmacokinetic studies such as label-free detection and differentiation of compounds and metabolites. We have recently introduced a MS imaging method that combines high mass resolution and high spatial resolution in a single experiment, hence termed HR² MS imaging. In the present study, we applied this method to analyze the spatial distribution of the anti-cancer drugs imatinib and ifosfamide in individual mouse organs. The whole kidney of an animal dosed with imatinib was measured at 35 μm spatial resolution. Imatinib showed a well-defined distribution in the outer stripe of the outer medulla. This area was analyzed in more detail at 10 μm step size, which constitutes a tenfold increase in effective spatial resolution compared to previous studies of drug compounds. In parallel, ion images of phospholipids and heme were used to characterize the histological features of the tissue section and showed excellent agreement with histological staining of the kidney after MS imaging. Ifosfamide was analyzed in mouse kidney at 20 μm step size and was found to be accumulated in the inner medulla region. The identity of imatinib and ifosfamide was confirmed by on-tissue MS/MS measurements. All measurements including mass spectra from 10 μm pixels featured accurate mass (≤2 ppm root mean square) and mass resolving power of R = 30,000. Selected ion images were generated with a bin size of ∆m/z = 0.01 ensuring highly specific information. The ability of the method to cover larger areas was demonstrated by imaging a compound in the intestinal tract of a rat whole-body tissue section at 200 μm step size. The described method represents a major improvement in terms of spatial resolution and specificity for the analysis of drug compounds in tissue sections.     

Spatially resolved determination of the structure and composition of diatom cell walls by Raman and FTIR imaging

Vibrational spectroscopic imaging has developed into a versatile tool to study the local composition of various materials. Here, we present for the first time that Raman mapping and Fourier transform infrared imaging are useful tools to study diatom cell walls as is demonstrated for the species Stephanopyxis turris. The unicellular diatoms exhibit intricately micro- and nano-patterned cell walls, which consist of amorphous silica as well as various organic and inorganic constituents, thus making up an extremely interesting inorganic/organic hybrid material. The structure and composition of this material as well as the biochemical and biophysical processes leading to its formation remain to be challenges for ongoing research. Whereas the lateral resolution of Fourier transform infrared imaging is limited to 5 μm by diffraction, Raman maps are shown to be capable of detecting the spatial distribution of the silica as well as an additional inorganic component and the organic material down to 330-nm resolution. Due to the spherical shape of the sample with a radius of 40 μm and the requirement to accurately focus the laser before each Raman measurement within the micrometer range, Raman maps of whole diatom cell walls were registered after an adjustment of the axial position. The results reveal local differences in the cell wall composition of the honeycomb-like structures and the bottom layer.     

Chemistry at level of individual aerosol particle using multivariate curve resolution of confocal Raman image

Airborne particles with aerodynamic diameter in the 10-1 microm range have been collected in an industrial/urban zone by impaction and have been investigated by automated confocal Raman microspectrometry. The computer-microcontrolled XY scanning and Z focusing of Raman images provided many pixel Raman spectra which are characteristics of complex mixture at level of individual particle. The large heterogeneity was not resolved by the spatial resolution of the instrument which is limited by the optical diffraction. The severe spectral overlaps generated by heterogeneity were resolved by multivariate curve resolution (MCR) methods. The purity based method (SIMPLISMAX) was used to resolve both luminescence spectra and pure Raman spectra without prior information. The MCR-alternating least square (ALS) was used as a refined method of both spectra and spectral concentrations. The reconstructing Raman images of the respective spectral contribution supply a versatile potential to characterize the chemistry of atmospheric aerosols at the level of the individual particles.     

Applications of Vibrational Spectroscopy for Analysis of Connective Tissues

Advances in vibrational spectroscopy have propelled new insights into the molecular composition and structure of biological tissues. In this review, we discuss common modalities and techniques of vibrational spectroscopy, and present key examples to illustrate how they have been applied to enrich the assessment of connective tissues. In particular, we focus on applications of Fourier transform infrared (FTIR), near infrared (NIR) and Raman spectroscopy to assess cartilage and bone properties. We present strengths and limitations of each approach and discuss how the combination of spectrometers with microscopes (hyperspectral imaging) and fiber optic probes have greatly advanced their biomedical applications. We show how these modalities may be used to evaluate virtually any type of sample (ex vivo, in situ or in vivo) and how “spectral fingerprints” can be interpreted to quantify outcomes related to tissue composition and quality. We highlight the unparalleled advantage of vibrational spectroscopy as a label-free and often nondestructive approach to assess properties of the extracellular matrix (ECM) associated with normal, developing, aging, pathological and treated tissues. We believe this review will assist readers not only in better understanding applications of FTIR, NIR and Raman spectroscopy, but also in implementing these approaches for their own research projects.     

Instrument design and characterization for high resolution MALDI-MS imaging of tissue sections

In previous work, we have reported using a MALDI imaging time-of-flight mass spectrometer for the detection of protein ions from tissue sections with spatial resolution of 25 microm. We present here imaging mass spectrometry results obtained with a high-resolution scanning MALDI time-of-flight mass spectrometer, equipped with a coaxial laser illumination ion source, capable of achieving irradiation areas as small as 40 microm(2) (ca 7 microm diameter). MALDI-generated analyte ion signals from these very small irradiation volumes can be observed in a molecular weight range up to 27,000. High-resolution imaging mass spectrometry images were successfully generated from matrix thin film samples and tissue sections with scanning resolutions at and below 10 microm. This work also provides fundamental characterization of the ion signal dependence as a function of various focus and fluence parameters that will be required for extension to tissue imaging at the subcellular level.     

Structural effects in the analysis of supported lipid bilayers by time-of-flight secondary ion mass spectrometry

We contribute to the rapidly emerging interest in the application of time-of-flight secondary ion mass spectrometry (TOF-SIMS) for chemical analysis of biological materials by presenting a careful TOF-SIMS investigation of structurally different SiO2-supported phospholipid assemblies. Freeze-dried supported 1-oleoyl-2-palmitoyl-sn-glycero-3-phosphocholine (POPC) bilayers, Langmuir-Blodgett POPC monolayers, and disordered thick POPC films were investigated. Compared with the two latter structures, the supported bilayer showed a strong (5-10 times) enhancement in the yield of both the molecular and the dimer ion peaks of POPC, suggesting that the molecular peak may be used as a sensitive indicator for changes in the membrane structure and, in particular, an indicator for the presence of bilayer structures in, e.g., cell and tissue samples. The detection efficiency and the useful lateral resolution indicate that a lateral resolution of around 100 nm can be obtained on all structures by imaging the phosphocholine ion at 184 u using Bi3+ primary ions. For the chemically specific molecular peak at 760 u, the measured detection efficiencies correspond to a useful lateral resolution of around 2 microm for the bilayer structure. The results are discussed in relation to recent dynamic SIMS (nano-SIMS) analysis of freeze-dried supported lipid bilayers, displaying similar or higher lateral resolution, but which in contrast to TOF-SIMS requires isotopic labeling of the analyzed lipids.     

Differentiation between normal and tumor vasculature of animal and human glioma by FTIR imaging

Malignant gliomas are very aggressive tumors, highly angiogenic and invading heterogeneously the surrounding brain parenchyma, making their resection very difficult. To overcome the limits of current diagnostic imaging techniques used for gliomas, we proposed using FTIR imaging, with a spatial resolution from 6 to 10 μm, to provide molecular information for their histological examination, based on discrimination between normal and tumor vasculature. Differentiation between normal and tumor blood vessel spectra by hierarchical cluster analysis was performed on tissue sections obtained from xenografted brain tumors of Rag-gamma mice 28 days after intracranial implantation of glioma cells, as well as for human brain tumors obtained in clinics. Classical pathological examination and immunohistochemistry were performed in parallel to the FTIR spectral imaging of brain tissues. First on the animal model, classification of FTIR spectra of blood vessels could be performed using spectral intervals based on fatty acyl (3050-2800 cm(-1)) and carbohydrate (1180-950 cm(-1)) absorptions, with the formation of two clusters corresponding to healthy and tumor parts of the tissue sections. Further data treatments on these two spectral intervals provided interpretable information about the molecular contents involved in the differentiation between normal and tumor blood vessels, the latter presenting a higher level of fatty acyl chain unsaturation and an unexpected loss of absorption from osidic residues. This classification method was further successfully tested on human glioma tissue sections. These findings demonstrate that FTIR imaging could highlight discriminant molecular markers to distinguish between normal and tumor vasculature, and help to delimitate areas of corresponding tissue.