Raman mapping and FTIR imaging of lung tissue: congenital cystic adenomatoid malformation

Congenital cystic adenomatoid malformations (CCAMs) are benign masses of non-functional lung tissue developing from an overgrowth of the terminal bronchioles with subsequent suppressing of alveolar growth. For the first time CCAMs are studied by Raman mapping and Fourier transform infrared (FTIR) imaging. Both vibrational spectroscopic methods are able to analyze the biochemical composition of tissues and their pathological changes at the molecular level. Cryosections were prepared on calcium fluoride substrates from CCAMs and from normal lung tissue of two infant patients who underwent surgery. Raman maps were collected at a step size of 100 microm in order to assess the whole tissue section and at a smaller step size of 10 microm in order to resolve details in selected areas. FTIR images were collected in the macroscopic and microscopic modes. Data sets were segmented by cluster analysis and the mean spectra of each cluster were compared. At low lateral resolution a lower red blood cell content and higher lipid content were found in CCAMs than in normal lung tissue. At higher lateral resolution, accumulations of lipids and glycogen were identified in CCAMs. The lipid aggregates contain a high concentration of phosphatidylcholine. It is discussed how the combined application of Raman mapping and FTIR imaging might improve the differential diagnosis of lung malformations and how both modalities might be applied to other bioanalytical and biomedical problems in the future.     

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.     

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.     

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.     

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.     

Imaging mass spectrometry in biological tissues by laser ablation inductively coupled plasma mass spectrometry

Of all the inorganic mass spectrometric techniques, laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) plays a key role as a powerful and sensitive microanalytical technique enabling multi- element trace analysis and isotope ratio measurements at trace and ultratrace level. LA-ICP-MS was used to produce images of detailed regionally-specific element distribution in 20 microm thin sections of different parts of the human brain. The quantitative determination of copper, zinc, lead and uranium distribution in thin slices of human brain samples was performed using matrix-matched laboratory standards via external calibration procedures. Imaging mass spectrometry provides new information on the spatially inhomogeneous element distribution in thin sections of human tissues, for example, of different brain regions (the insular region) or brain tumor tissues. The detection limits obtained for Cu, Zn, Pb and U were in the ng g(-1) range. Possible strategies of LA-ICP-MS in brain research and life sciences include the elemental imaging of thin slices of brain tissue or applications in proteome analysis by combination with matrix-assisted laser desorption/ionization MS to study phospho- and metal- containing proteins will be discussed.     

Secondary ion images of the developing rat brain

Secondary ion images were obtained from sections of rat brain over a 21 day postnatal period, using the intensity of m/z 184, phosphocholine. When compared with corresponding optical images of similar, but stained sections from the same animal, the secondary ion images appear to reflect less developed brains. During development, myelination occurs after axon extension. Apparently, myelination obscures the source of secondary m/z 184, phosphatidylcholine, from the analyzing ion probe; absenting myelination, secondary ion images show no physiological features.     

傅里叶变换中红外光纤光谱法用于腮腺肿瘤的检测

采用红外光谱仪与中红外光纤、衰减全反射(ATR)探头联用对40例腮腺肿瘤患者的腺体体表皮肤进行了测定, 并以病人术后肿瘤标本病理观察结果为判断标准, 对良性及恶性肿瘤光谱进行了判别, 发现光谱法判别结果与病理诊断结果基本一致. 实验结果表明, 正常腮腺、良性和恶性腮腺肿瘤体表皮肤的FTIR 光谱中存在显著的差异, 用相关吸收峰的峰形、峰位和峰强可以表征这些差异. 研究进一步发现, 对于不同类型的恶性肿瘤, 其体表组织的红外光谱主要差别在于1500—1000 cm-1区域内峰形及峰位的改变. 根据这一区域的差异可以将恶性肿瘤分为两大类: 一类恶性肿瘤具有上述的光谱特征(如腺泡细胞癌、嗜酸细胞腺癌和腺样囊性癌等), 另一类恶性肿瘤因为类型的不同在1500—1000 cm-1区域内峰形及峰位发生了很大的变化, 不同于上述的光谱特征.     

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.     

Ex vivo and in vivo diagnosis of C6 glioblastoma development by Raman spectroscopy coupled to a microprobe

The potential of Raman spectroscopy for ex vivo and in vivo classification of normal and glioblastoma brain tumor development was investigated. High-quality spectra of normal and tumor tissues were obtained using a portable Raman spectrometer coupled to a microprobe with a signal integration time of 5 s. Ex vivo results demonstrated that by using the biochemical information contained in the spectra, we were able to distinguish between normal brain features (white and gray matter), invasion, and tumor tissues with a classification accuracy of 100%. Differences between these features resulted from variations in their lipid signal contributions, which probably reflect differences in the level of myelinization. This finding supports the ability of in vivo Raman spectroscopy to delineate tumor margins during surgery. After implanting C6 cells in rat brain, we monitored, in vivo, the development of glioblastoma tumor from days 0 to 20 post-implantation (PI). The classification exhibited a clear separation of the data into two clusters: one cluster was associated with normal brain tissues (cortex), and the second was related to data measured from tumor evolution. The second cluster could be divided into two subclusters, one associated with tumor tissue from 4 to 13 days PI and the second related to tumor tissue from 15 to 20 days PI. Histological analysis reveals that the differences between these two subclusters are: the presence of a massive infiltration zone in the brain tissue from 4 to 13 days PI, and; a maturation of the tumor characterized by the appearance of edematous and necrotic zones, as well as a diminution in the proliferative and invasive area, from 15 days. This work demonstrates the potential of Raman spectroscopy to provide diagnostic information for the early detection of tumors in vivo.     

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.     

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     

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.     

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.     

Fourier transform infrared imaging analysis in discrimination studies of squamous cell carcinoma

Oral squamous cell carcinoma (OSCC) of the oral cavity and oropharynx represents more than 95% of all malignant neoplasms in the oral cavity. Histomorphological evaluation of this cancer type is invasive and remains a time consuming and subjective technique. Therefore, novel approaches for histological recognition are necessary to identify malignancy at an early stage. Fourier transform infrared (FTIR) imaging has become an essential tool for the detection and characterization of the molecular components of biological processes, such as those responsible for the dynamic properties of tumor progression. FTIR imaging is a modern analytical technique enabling molecular imaging of a complex biological sample and is based on the absorption of IR radiation by vibrational transitions in covalent bonds. One major advantage of this technique is the acquisition of local molecular expression profiles, while maintaining the topographic integrity of the tissue and avoiding time-consuming extraction, purification, and separation steps. With this imaging technique, it is possible to obtain unique images of the spatial distribution of proteins, lipids, carbohydrates, cholesterols, nucleic acids, phospholipids, and small molecules with high spatial resolution. Analysis and visualization of FTIR imaging datasets are challenging and the use of chemometric tools is crucial in order to take advantage of the full measurement. Therefore, methodologies for this task based on the novel developed algorithm for multivariate image analysis (MIA) are often necessary. In the present study, FTIR imaging and data analysis methods were combined to optimize the tissue measurement mode after deparaffinization and subsequent data evaluation (univariate analysis and MIAs). We demonstrate that it is possible to collect excellent IR spectra from formalin-fixed paraffin-embedded (FFPE) tissue microarrays (TMAs) of OSCC tissue sections employing an optimised analytical protocol. The correlation of FTIR imaging to the morphological tissue features obtained by histological staining of the sections demonstrated that many histomorphological tissue patterns can be visualized in the colour images. The different algorithms used for MIAs of FTIR imaging data dramatically increased the information content of the IR images from squamous cell tissue sections. These findings indicate that intra-operative and surgical specimens of squamous cell carcinoma tissue can be characterized by FTIR imaging.     

Quantitative imaging of zinc, copper and lead in three distinct regions of the human brain by laser ablation inductively coupled plasma mass spectrometry

Laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) was used to determine the distribution of the trace elements zinc, copper and lead in insular, central and hippocampal areas of thin tissue sections (thickness 20microm) through an entire human brain hemisphere. For the investigation of the tissue samples, a commercial laser ablation system was coupled to a double-focusing sector field ICP-MS. The regions of interest of healthy brain tissue (thickness 20microm) were scanned (raster area approximately 200mm(2)) with a focused laser beam (wavelength 266nm, diameter of laser crater 200microm and laser power density 3x10(9)Wcm(-2)). The ion intensities of (64)Zn(+), (63)Cu(+) and (208)Pb(+) were measured by LA-ICP-MS within the ablated area. For quantification purposes, matrix-matched laboratory standards were prepared by means of dosing of each analyte to the pieces of brain tissue. The mass spectrometric analysis yielded inhomogeneous and largely reciprocal distributions of Zn and Cu in the selected areas of investigated brain samples. The highest concentrations of Zn and Cu with the most distinct distribution pattern were found in the hippocampus (up to 15microg g(-1)). In contrast to zinc and copper, for lead, a more homogeneous distribution throughout all regions examined was found at a low concentration (in the ngg(-1) range) level within the analytical range of LA-ICP-MS.     

傅里叶变换红外光谱体表无创探测乳腺肿瘤

利用傅里叶变换红外(FTIR)光谱仪联合衰减全反射(ATR)探头的中红外光导纤维对46名健康志愿者及113名乳腺肿物患者的体表皮肤进行无创红外光谱测定, 并从分子水平比较、分析了正常乳腺和有肿物乳腺体表皮肤的红外光谱特征. 结果表明, 健康志愿者乳房皮肤8个FTIR光谱测定部位的图谱趋于一致; 正常乳腺体表与有肿瘤乳腺体表的吸收峰差异明显, 而1080 cm^-1处核酸相关吸收峰的变化对鉴别肿瘤的良、 恶性有重要意义.     

ATR-FTIR imaging for the analysis of organic materials in paint cross sections: case studies on paint samples from the National Gallery, London

The potential of attenuated total reflection Fourier transform infrared (ATR-FTIR) imaging for the characterisation of the chemical components of paint cross sections from old master paintings was investigated. Three cross sections were chosen to cover a variety of the analytical problems encountered in samples from paintings. The binding medium and degradation products in a green paint sample from a fifteenth-century Florentine painting were imaged, as well as a thin layer within a cross-section from a fifteenth-century German painting, and multiple thin surface coatings on a painting of the 1760s by Peter Romney. The application of chemometric methods for further analysis of the large data set generated for each sample was also explored. The study demonstrated the advantages of ATR-FTIR imaging, which allowed images to be obtained with high spatial resolution (ca. 3-4 microm) without the need to microtome the sample. The gain in sensitivity in detecting trace materials and the information derived from the location of these compounds in the sample was especially valuable, improving interpretation of the FTIR analysis and extending knowledge of the sample composition beyond that obtainable with other analytical techniques.     

Fiber-optic Raman spectroscopy of joint tissues

In this study, we report adaptation of Raman spectroscopy for arthroscopy of joint tissues using a custom-built fiber-optic probe. Differentiation of healthy and damaged tissue or examination of subsurface tissue, such as subchondral bone, is a challenge in arthroscopy because visual inspection may not provide sufficient contrast. Discrimination of healthy versus damaged tissue may be improved by incorporating point spectroscopy or hyperspectral imaging into arthroscopy where the contrast is based on the molecular structure or chemical composition. Articular joint surfaces of knee cadaveric human tissue and tissue phantoms were examined using a custom-designed Raman fiber-optic probe. Fiber-optic Raman spectra were compared against reference spectra of cartilage, subchondral bone and cancellous bone collected using Raman microspectroscopy. In fiber-optic Raman spectra of the articular surface, there was an effect of cartilage thickness on recovery of signal from subchondral bone. At sites with intact cartilage, the bone mineralization ratio decreased but there was a minimal effect in the bone mineral chemistry ratios. Tissue phantoms were prepared as experimental models of the osteochondral interface. Raman spectra of tissue phantoms suggested that optical scattering of cartilage has a large effect on the relative cartilage and bone signal. Finite element analysis modeling of light fluence in the osteochondral interface confirmed experimental findings in human cadaveric tissue and tissue phantoms. These first studies demonstrate the proof of principle for Raman arthroscopic measurement of joint tissues and provide a basis for future clinical or animal model studies.     

Diagnostic potential of autofluorescence for an assisted intraoperative delineation of glioblastoma resection margins

The intrinsic autofluorescence properties of biological tissues can be affected by the occurrence of histological and biochemical alterations induced by pathological processes. In this study the potential of autofluorescence to distinguish tumor from normal tissues was investigated with the view of a real-time diagnostic application in neurosurgery to delineate glioblastoma resection margins. The autofluorescence properties of nonneoplastic and neoplastic tissues were analyzed on tissue sections and homogenates by means of a microspectrofluorometer, and directly on patients affected by glioblastoma multiforme, during surgery, with a fiber-optic probe. Scan-microspectrofluorometric analysis on tissue sections evidenced a reduction of emission intensity and a broadening of the main emission band, along with a redshift of the peak position, from peritumoral nonneoplastic to neoplastic tissues. Differences in both spectral shape and signal amplitude were found in patients when the glioblastoma lesion autofluorescence was compared with those of cortex and white matter taken as healthy tissues. Both biochemical composition and histological organization contribute to modify the autofluorescence emission of neoplastic, with respect to nonneoplastic, brain tissues. The differences found in the in vivo analysis confirm the prospects for improving the efficacy of tumor resection margin delineation in neurosurgery.