Characterization of lipid extracts from brain tissue and tumors using Raman spectroscopy and mass spectrometry

Brain tissue is characterized by high lipid content. The amount of lipids decreases, and its composition changes in the most frequent primary brain tumor, the glioma. Scope of the current paper was to extract quantitatively lipids from porcine and human brain tissue as well as from five human gliomas using a modified protocol according to Folch. The lipid extracts were studied by Raman spectroscopy with 785 nm excitation and by mass spectrometry with electron impact ionization. Porcine and human brain tissues have similar water and lipid content and show similar Raman and mass spectra. In contrast, gliomas are characterized by increased water content and decreased lipid content. Elevated phosphatidylcholine to cholesterol ratios in lipid extracts of gliomas were indicated by Raman bands of the choline group and cholesterol. Due to its higher sensitivity, mass spectrometry detected increased levels of cholesterol ester relative to cholesterol in lipid extracts of gliomas. For comparison, thin tissue sections were prepared from the glioma specimens before lipid extraction; infrared spectroscopic images were recorded and analyzed by a supervised classification model. This study demonstrates how to improve the analysis of brain tumors and to complement the diagnosis of brain pathologies using a multimodal approach.     

Quantification of brain lipids by FTIR spectroscopy and partial least squares regression

Brain tissue is characterized by high lipid content. Its content decreases and the lipid composition changes during transformation from normal brain tissue to tumors. Therefore, the analysis of brain lipids might complement the existing diagnostic tools to determine the tumor type and tumor grade. Objective of this work is to extract lipids from gray matter and white matter of porcine brain tissue, record infrared (IR) spectra of these extracts and develop a quantification model for the main lipids based on partial least squares (PLS) regression. IR spectra of the pure lipids cholesterol, cholesterol ester, phosphatidic acid, phosphatidylcholine, phosphatidylethanolamine, phosphatidylserine, phosphatidylinositol, sphingomyelin, galactocerebroside and sulfatide were used as references. Two lipid mixtures were prepared for training and validation of the quantification model. The composition of lipid extracts that were predicted by the PLS regression of IR spectra was compared with lipid quantification by thin layer chromatography.     

Near infrared Raman spectra of human brain lipids

Human brain tissue, in particular white matter, contains high lipid content. These brain lipids can be divided into three principal classes: neutral lipids including the steroid cholesterol, phospholipids and sphingolipids. Major lipids in normal human brain tissue are phosphatidylcholine, phosphatidylethanolamine, phosphatidylserine, phosphatidylinositol, phosphatidic acid, sphingomyelin, galactocerebrosides, gangliosides, sulfatides and cholesterol. Minor lipids are cholesterolester and triacylglycerides. During transformation from normal brain tissue to tumors, composition and concentration of lipids change in a specific way. Therefore, analysis of lipids might be used as a diagnostic parameter to distinguish normal tissue from tumors and to determine the tumor type and tumor grade. Raman spectroscopy has been suggested as an analytical tool to detect these changes even under intra-operative conditions. We recorded Raman spectra of the 12 major and minor brain lipids with 785 nm excitation in order to identify their spectral fingerprints for qualitative and quantitative analyses.     

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.     

Classification of malignant gliomas by infrared spectroscopic imaging and linear discriminant analysis

Infrared (IR) spectroscopy provides a sensitive molecular fingerprint for tissue without external markers. Supervised classification models can be trained to identify the tissue type based on the spectroscopic fingerprint. Infrared imaging spectrometers equipped with multi-channel detectors combine the spectral and spatial information. Tissue areas of 4 x 4 mm(2) can be analyzed within a few minutes in the macroscopic imaging mode. An approach is described to apply this methodology to human astrocytic gliomas, which are graded according to their malignancy from one to four. Multiple IR images of three tissue sections from one patient with a malignant glioma are acquired and assigned to the six classes normal brain tissue, astrocytoma grade II, astrocytoma grade III, glioblastoma multiforme grade IV, hemorrhage, and other tissue by a linear discriminant analysis model which was trained by data from a single-channel detector. Before the model is applied here, the spectra are shown to be virtually identical. The first specimen contained approximately 95% malignant glioma regions, that means astrocytoma grade III or glioblastoma. The smaller percentage of 12-34% malignant glioma in the second specimen is consistent with its location at the tumor periphery. The detection of less than 0.2% malignant glioma in the third specimen points to a location outside the tumor. The results were correlated with the cellularity of the tissue which was obtained from the histopathologic gold standard. Potential applications of IR spectroscopic imaging as a rapid tool to complement established diagnostic methods are discussed.     

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.     

Fluorescence Lifetime Spectroscopy of Glioblastoma Multiforme¶

Fluorescence spectroscopy of the endogenous emission of brain tumors has been researched as a potentially important method for the intraoperative localization of brain tumor margins. We investigated the use of time‐resolved, laser‐induced fluorescence spectroscopy for demarcation of primary brain tumors by studying the time‐resolved spectra of gliomas. The fluorescence of human brain samples (glioblastoma multiforme, cortex and white matter: six patients, 23 sites) was induced ex vivo with a pulsed nitrogen laser (337 nm, 3 ns). The time‐resolved spectra were detected in a 360–550 nm wavelength range using a fast digitizer and gated detection. Parameters derived from both the spectral‐ (intensities from narrow spectral bands) and the time domain (average lifetime) measured at 390 and 460 nm were used for tissue characterization. We determined that high‐grade gliomas are characterized by fluorescence lifetimes that varied with the emission wavelength (>3 ns at 390 nm, <1 ns at 460 nm) and their emission is overall longer than that of normal brain tissue. Our study demonstrates that the use of fluorescence lifetime not only improves the specificity of fluorescence measurements but also allows a more robust evaluation of data collected from brain tissue. Combined information from both the spectraland the time domain can enhance the ability of fluorescencebased techniques to diagnose and detect brain tumor margins intraoperatively.     

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.     

Detection of collagens in brain tumors based on FTIR imaging and chemometrics

Fourier transform infrared (FTIR) imaging has been used as a molecular histopathology tool on brain tissue sections after intracranial implantation and development of glioma tumors. Healthy brain tissue (contralateral lobe) as well as solid and diffuse tumor tissues were compared for their collagen contents. IR spectra were extracted from IR images for determining the secondary structure of protein contents and compared to pure product spectra of collagens (types I, III, IV, V, and VI). Multivariate statistical analyses of variance and correspondence factorial analysis were performed to differentiate healthy and tumor brain tissues as well as their classification according to their secondary structure profiles. Secondary structure profiles revealed that no collagen was present in healthy tissues; they are also significantly different from solid and diffuse tumors (p < 0.05). Solid and diffuse tumors could be discriminated with respect to the secondary structure profile of fibrillar and non-fibrillar collagens, respectively. We can thus propose to develop FTIR imaging for histopathology examination of tumors on the basis of collagen contents.     

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.     

Feasibility study for diagnosis of stomach adenoma and cancer using IR spectroscopy

The feasibility of infrared (IR) spectroscopy as a biomedical analysis tool for the diagnosis of stomach malignancy including adenoma and cancer has been studied using unstained biopsy samples. Biopsy samples were acquired from 11 subjects. IR spectra were collected for these samples using a microscope (aperture: 25 μm × 25 μm). The samples were stained again and the spots where the IR spectra were collected were re-examined by a pathologist to ensure the spectra represented the correct diagnostic information. The spectral features were compared among the averaged spectra of normal and malignant tissues. The spectral contrasts could be correlated to the differences in the molecular structure of the membrane lipids of the two tissue types as well as the variation in their glycogen contents. However, the spectral features between the adenoma and cancer tissues could not be distinguished. Initially we used principal component analysis (PCA) to examine the degree of separation between tissue types. Soft independent modeling of class analogies (SIMCA) was employed to evaluate the prediction accuracy of IR spectroscopy for the diagnosis of stomach adenoma and cancer. The prediction accuracies for normal, adenoma and cancer tissues were 77%, 30% and 87%, respectively, using SIMCA. IR microscopy successfully differentiated normal and malignant tissues. However, a more sophisticated algorithm will be required in order to effectively extract relevant information for the differentiation between stomach adenoma and cancer.     

Chemical alterations to murine brain tissue induced by formalin fixation: implications for biospectroscopic imaging and mapping studies of disease pathogenesis

Understanding biochemical mechanisms and changes associated with disease conditions and, therefore, development of improved clinical treatments, is relying increasingly on various biochemical mapping and imaging techniques on tissue sections. However, it is essential to be able to ascertain whether the sampling used provides the full biochemical information relevant to the disease and is free from artefacts. A multi-modal micro-spectroscopic approach, including FTIR imaging and PIXE elemental mapping, has been used to study the molecular and elemental profile within cryofixed and formalin-fixed murine brain tissue sections. The results provide strong evidence that amino acids, carbohydrates, lipids, phosphates, proteins and ions, such as Cl(-) and K(+), leach from tissue sections into the aqueous fixative medium during formalin fixation of the sections. Large changes in the concentrations and distributions of most of these components are also observed by washing in PBS even for short periods. The most likely source of the chemical species lost during fixation is the extra-cellular and intra-cellular fluid of tissues. The results highlight that, at best, analysis of formalin-fixed tissues gives only part of the complete biochemical "picture" of a tissue sample. Further, this investigation has highlighted that significant lipid peroxidation/oxidation may occur during formalin fixation and that the use of standard histological fixation reagents can result in significant and differential metal contamination of different regions of tissue sections. While a consistent and reproducible fixation method may be suitable for diagnostic purposes, the findings of this study strongly question the use of formalin fixation prior to spectroscopic studies of the molecular and elemental composition of biological samples, if the primary purpose is mechanistic studies of disease pathogenesis.     

MALDI imaging mass spectrometry of lipids by adding lithium salts to the matrix solution

Mass spectrometry imaging of lipids using MALDI–TOF/TOF mass spectrometers is of growing interest for chemical mapping of organic compounds at the surface of tissue sections. Many efforts have been devoted to the best matrix choice and deposition technique. Nevertheless, the identification of lipid species desorbed from tissue sections remains problematic. It is now well-known that protonated, sodium- and potassium-cationized lipids are detected from biological samples, thus complicating the data analysis. A new sample preparation method is proposed, involving the use of lithium salts in the matrix solution in order to simplify the mass spectra with only lithium-cationized molecules instead of a mixture of various cationized species. Five different lithium salts were tested. Among them, lithium trifluoroacetate and lithium iodide merged the different lipid adducts into one single lithium-cationized species. An optimized sample preparation protocol demonstrated that the lithium trifluoroacetate salt slightly increased desorption of phosphatidylcholines. Mass spectrometry images acquired on rat brain tissue sections by adding lithium trifluoroacetate showed the best results in terms of image contrast. Moreover, more structurally relevant fragments were generated by tandem mass spectrometry when analyzing lithium-cationized species.     

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.     

傅里叶变换中红外光谱法检测脑胶质瘤

采用傅里叶变换衰减全反射中红外光谱法检测了19例液氮冻存的脑胶质瘤离体组织样品(星形细胞瘤10例, 少枝-星形细胞瘤9例), 对得到的红外光谱进行分析发现, 恶性程度不同的星形细胞瘤组织的红外光谱存在差异, 并且不同类型的脑胶质瘤组织的红外光谱也表现出较为明显的区别, 因此可以根据各个特征吸收峰的峰位、 峰形及谱峰强度等信息来区分脑胶质瘤, 并初步鉴别脑胶质瘤的性质. 研究结果表明, 通过某些特征吸收峰峰位的变化来鉴别星形细胞瘤和少枝-星形细胞瘤与病理诊断结果的符合率约为80%, 说明傅里叶变换衰减全反射中红外光谱法有望发展成为一种对样品无损伤、 快速的脑肿瘤诊断新方法.     

An integrated experimental and analytical approach to the chemical state imaging of iron in brain gliomas using X-ray absorption near edge structure spectroscopy

X-ray absorption near-edge structure spectroscopy is used for human neoplastic tissues in order to investigate distributions and chemical states of iron. The specimens used in this study were obtained intraoperatively from brain gliomas of different types and various grades of malignancy and from a control subject. An integrated experimental and analytical approach toward topographic and quantitative analysis in thin freeze-dried cryo-sections is presented. The full XANES spectra at the Fe absorption K edge show the presence of both chemical forms of Fe in the analyzed points of the tissues. The main goal of the work is the chemical state imaging of Fe in tissue areas. Topographic analysis of Fe speciation in the tissues investigated with the use of the XANES technique indicates the presence of microstructures where Fe²⁺ is dominant as well as those with a high abundance of the oxidized form of Fe. The quantitative analysis shows that for all cases the content of the oxidized form of Fe is significantly higher in comparison with Fe²⁺. The highest level of Fe³⁺ is found in the control sample, and the lowest one for the glioma of the highest grade of malignancy. The content of either Fe²⁺ or Fe³⁺ is increased in low grade gliomas in comparison to high-grade malignant tumors.     

中红外光纤技术用于口腔肿瘤在体原位检测的研究

肿瘤是严重威胁人类健康和生命的疾病,早期诊断和及时治疗是提高肿瘤病人存活率的重要因素,肿瘤的发生和发展一般可分为3个阶段：(1)基因突变;(2)生物分子组成和结构发生改变;(3)细胞和组织形态发生变化,目前常用的影像学方法只能检测较大的肿块,组织标本的病理诊断法需在     

The Effects of ex vivo Handling Procedures on the Near-Infrared Raman Spectra of Normal Mammalian Tissues

Recent studies in the literature have investigated the feasibility of tissue diagnostics based on Raman spectroscopy. The majority of these compare the ex vivo spectra of normal and diseased tissue. Due to the time lapse between tissue excision and spectroscopic examination, samples must be frozen or otherwise preserved to maintain their native biochemical states. In order to establish optimum procedures for ex vivo Raman spectroscopy of tissue, the effects of tissue drying, formalin fixing, snap freezing, tissue freezing in optimal cutting temperature (OCT) medium and extended post-thaw durations were studied to determine if any of these handling procedures introduced spectral artifacts. Experiments on representative tissues indicated that tissue heating due to the excitation light did not change the spectra significantly. With minor exceptions, OCT and formalin did not contaminate tissue spectra, so that samples stored for histological examination could also be studied with Raman spectroscopy. Tissue dehydration caused disruption of the protein vibrational modes, which caused spectral artifacts. It is concluded that ex vivo tissue samples should be frozen in OCT. Prior to spectral analysis, the tissue should then be acclimatized at room temperature in phosphate-buffered saline (PBS) and immersed in PBS during spectroscopic examination.     

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.     

A decade of vibrational micro-spectroscopy of human cells and tissue (1994-2004)

Instrumentation used in infrared microspectroscopy (IR-MSP) permits the acquisition of spectra from samples as small as 100 pg (10(-10) g), and as small as 1 pg for Raman microspectroscopy (RA-MSP). This, in turn, allows the acquisition of spectral data from objects as small as fractions of human cells, and of small regions of microtome tissue sections. Since vibrational spectroscopy is exquisitely sensitive to the biochemical composition of the sample, and variations therein, it is possible to monitor metabolic processes in tissue and cells, and to construct spectral maps based on thousands of IR spectra collected from pixels of tissue. These images, in turn, reveal information on tissue structure, distribution of cellular components, metabolic activity and state of health of cells and tissue.