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.     

Suitability of infrared spectroscopic imaging as an intraoperative tool in cerebral glioma surgery

Infrared spectroscopic imaging is a promising intraoperative tool which enables rapid, on-site diagnosis of brain tumors during neurosurgery. A classification model was recently developed using infrared spectroscopic images from thin tissue sections to grade malignant gliomas, the most frequent class of primary brain tumor. In this study the model was applied to 54 specimens from six patients with inhomogeneous gliomas composed of regions with different tumor density and morphology. The resection was controlled using neuronavigation which transfers the findings obtained by preoperative magnetic resonance imaging (MRI) into the operating field. For comparison, all specimens were independently evaluated by histopathology after hematoxylin and eosin staining. The infrared-derived grading agreed with histopathology and MRI findings for almost all specimens. With regard to histopathological assessment, sensitivities of 100% (22/22) and 93.1% (27/29) and specificities of 96.9% (31/32) and 88.0% (22/25) were achieved, depending on whether the classification was based on the predominant or maximal tumor grade, respectively, in the specimen. Altogether, in 98% (53/54) of all specimens the decision to continue or not continue tumor resection could have been made according to the infrared spectroscopic classification. This retrospective study clearly demonstrates that infrared spectroscopic imaging may help to define tumor margins intraoperatively and to detect high-grade tumor residues for achieving more radical tumor resection. MRT-guided tumor resection (left) is combined with infrared spectroscopy-based tissue classification (middle, right). With regard to histopathological assessment, sensitivities of 100% and 93.1% and specificities of 96.9% and 88.0% were achieved for 54 specimens. (TIF 47.1 KB)     

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.     

Detection of illicit substances in fingerprints by infrared spectral imaging

FTIR and Raman spectral imaging can be used to simultaneously image a latent fingerprint and detect exogenous substances deposited within it. These substances might include drugs of abuse or traces of explosives or gunshot residue. In this work, spectral searching algorithms were tested for their efficacy in finding targeted substances deposited within fingerprints. “Reverse” library searching, where a large number of possibly poor-quality spectra from a spectral image are searched against a small number of high-quality reference spectra, poses problems for common search algorithms as they are usually implemented. Out of a range of algorithms which included conventional Euclidean distance searching, the spectral angle mapper (SAM) and correlation algorithms gave the best results when used with second-derivative image and reference spectra. All methods tested gave poorer performances with first derivative and undifferentiated spectra. In a search against a caffeine reference, the SAM and correlation methods were able to correctly rank a set of 40 confirmed but poor-quality caffeine spectra at the top of a dataset which also contained 4,096 spectra from an image of an uncontaminated latent fingerprint. These methods also successfully and individually detected aspirin, diazepam and caffeine that had been deposited together in another fingerprint, and they did not indicate any of these substances as a match in a search for another substance which was known not to be present. The SAM was used to successfully locate explosive components in fingerprints deposited on silicon windows. The potential of other spectral searching algorithms used in the field of remote sensing is considered, and the applicability of the methods tested in this work to other modes of spectral imaging is discussed.     

Non-invasive detection of superimposed latent fingerprints and inter-ridge trace evidence by infrared spectroscopic imaging

Current latent print and trace evidence collecting technologies are usually invasive and can be destructive to the original deposits. We describe a non-invasive vibrational spectroscopic approach that yields latent fingerprints that are overlaid on top of one another or that may contain trace evidence that needs to be distinguished from the print. Because of the variation in the chemical composition distribution within the fingerprint, we demonstrate that linear unmixing applied to the spectral content of the data can be used to provide images that reveal superimposed fingerprints. In addition, we demonstrate that the chemical composition of the trace evidence located in the region of the print can potentially be identified by its infrared spectrum. Thus, trace evidence found at a crime scene that previously could not be directly related to an individual, now has the potential to be directly related by its presence in the individual-identifying fingerprints. A portion of this work was presented at the 16th Meeting of the International Association of Forensic Sciences, Montpellier, France September 2–7, 2002.     

The continuous infrared spectroscopic analysis of reversed phase liquid chromatography separations

A method for HPLC/FTIR is discussed in which the effluent from a microbore HPLC is continuously deposited onto and eliminated from the surface of a circular rotating germanium crystal that has been aluminum coated on its opposite side. After deposition, the germanium disk is again rotated, this time in the sample compartment of an FTIR spectrometer while reflectance-absorbance infrared spectra are continuously collected. The novel germanium-aluminum deposition surface allows collection of reflectance-absorbance spectra that are free of the degrading effects of superposition phenomena characteristic of reflectance-absorbance spectra obtained on metal surfaces. Furthermore, germanium is impervious to aqueous solvent mixtures and, therefore, allows for the direct deposition of reversed phase separations, including those requiring acid modified mobile phases.     

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.     

Combined Fourier-transform infrared imaging and desorption electrospray-ionization linear ion-trap mass spectrometry for analysis of counterfeit antimalarial tablets

This paper reports use of a combination of Fourier-transform infrared (FTIR) spectroscopic imaging and desorption electrospray ionization linear ion-trap mass spectrometry (DESI MS) for characterization of counterfeit pharmaceutical tablets. The counterfeit artesunate antimalarial tablets were analyzed by both techniques. The results obtained revealed the ability of FTIR imaging in non-destructive micro-attenuated total reflection (ATR) mode to detect the distribution of all components in the tablet, the identities of which were confirmed by DESI MS. Chemical images of the tablets were obtained with high spatial resolution. The FTIR spectroscopic imaging method affords inherent chemical specificity with rapid acquisition of data. DESI MS enables high-sensitivity detection of trace organic compounds. Combination of these two orthogonal surface-characterization methods has great potential for detection and analysis of counterfeit tablets in the open air and without sample preparation.     

Development of single-beam wide-field infrared imaging to study sub-cellular neuron biochemistry

Multi-beam wide-field imaging using synchrotron mid-infrared light sources coupled with focal plane array detectors has provided a major breakthrough to the field of bio-spectroscopic imaging. The ability to collect sub-cellular molecular images in minutes has opened the door to a new era of biochemical studies. Although a multi-beam approach is the superior method to this form of imaging, it requires a specialized set of beamline optics, which may not be compatible with existing mid-infrared microscopy beamlines, or research programs/applications currently in place (some of which do not require an imaging component). In this investigation we demonstrate that a single-beam approach can be utilized in a similar manner to multi-beam imaging, to collect sub-cellular biochemical images of brain neurons in a rapid time frame, without extensive modification of an existing beamline configuration. This study uses an applied example, imaging the same neuron in situ within a brain tissue section, with both synchrotron and thermal sources. The results highlight the advantage of improved spatial resolution/image quality and spectral quality (signal to noise ratio) that is obtained when a high magnification and high numerical aperture objective (52×, 0.65) is coupled to a synchrotron mid-infrared lightsource with a focal plane array detector. The approach we report may prove to be particularly appealing to numerous existing mid-infrared beamlines, allowing straightforward integration of sub-cellular biochemical imaging with existing non-imaging research applications.     

Classification of spectroscopically encoded resins by Raman mapping and infrared hyperspectral imaging

Barcoded resins (BCRs) were recently introduced as a potential platform for pre-encoded multiplexed synthesis, screening, and biomedical diagnostics. A key step toward the development of this strategy is the ability to rapidly interrogate and classify the BCRs in a high-throughput, noninvasive manner. Here, we describe a one-step strategy based on Raman mapping and Fourier transform infrared imaging to classify and spatially resolve randomly distributed BCRs. To illustrate this methodology, mixtures of up to 25 different BCRs were imaged and classified with 100% confidence. This strategy can be readily extended to a larger pool of resins, provided each BCR features a unique vibrational fingerprint (spectroscopic barcode). We have also established that reliable single-bead Raman spectra can be recorded in 10 ms, thus confirming that Raman mapping, in particular, could be a very fast method to classify the BCRs.     

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.     

Coal analysis by diffuse reflectance near-infrared spectroscopy: Hierarchical cluster and linear discriminant analysis

An extensive study was carried out in coal samples coming from several origins trying to establish a relationship between nine coal properties (moisture (%), ash (%), volatile matter (%), fixed carbon (%), heating value (kcal/kg), carbon (%), hydrogen (%), nitrogen (%) and sulphur (%)) and the corresponding near-infrared spectral data. This research was developed by applying both quantitative (partial least squares regression, PLS) and qualitative multivariate analysis techniques (hierarchical cluster analysis, HCA; linear discriminant analysis, LDA), to determine a methodology able to estimate property values for a new coal sample. For that, it was necessary to define homogeneous clusters, whose calibration equations could be obtained with accuracy and precision levels comparable to those provided by commercial online analysers and, study the discrimination level between these groups of samples attending only to the instrumental variables. These two steps were performed in three different situations depending on the variables used for the pattern recognition: property values, spectral data (principal component analysis, PCA) or a combination of both. The results indicated that it was the last situation what offered the best results in both two steps previously described, with the added benefit of outlier detection and removal.     

Forensic classification of ballpoint pen inks using high performance liquid chromatography and infrared spectroscopy with principal components analysis and linear discriminant analysis

Several varieties of blue ballpoint pen inks were analyzed by high performance liquid chromatography (HPLC) and infrared spectroscopy (IR). The chromatographic data extracted at four wavelengths (254, 279, 370 and 400 nm) was analyzed individually and at a combination of these wavelengths by the soft independent modeling of class analogies (SIMCA) technique using principal components analysis (PCA) to estimate the separation between the pen samples. Linear discriminant analysis (LDA) measured the probability with which an observation could be assigned to a pen class. The best resolution was obtained by HPLC using data from all four wavelengths together, differentiating 96.4% pen pairs successfully using PCA and 97.9% pen samples by LDA. PCA separated 60.7% of the pen pairs and LDA provided a correct classification of 62.5% of the pens analyzed by IR. The results of this study indicate that HPLC coupled with chemometrics provided a better discrimination of ballpoint pen inks compared to IR. The need to develop a suitable IR method for analysing blue ballpoint pen inks has been emphasized and it is hoped that the development of such a method would indeed provide a valuable tool for the non-destructive analysis of blue ballpoint pen ink samples for forensic purposes.     

An infrared spectroscopic study of changes in unsaturation resulting from irradiation of isotropic and uniaxially oriented polyethylene films in the presence of acetylene

Interchain bridges of unsaturated double bonds have been proposed to form in amorphous regions, when polyethylene is irradiated in the presence of acetylene. We have corroborated the formation of these bridges by infrared spectroscopic studies. The double bonds are composed mainly of trans-olefin and vinyl end groups, formed as a result of competing radical-radical termination and hydrogen atom abstraction reactions. The hydrogen atom abstraction reaction becomes insignificant in uniaxially oriented high-density polyethylene having a draw ratio of 7.5, because of the alignment and positioning of the initiating radical pairs. During in vacuo irradiation and annealing only in-chain trans-olefins are usually formed. © 1994 John Wiley & Sons, Inc.     

Fourier-transform Raman and infrared spectroscopic analysis of dipyrrinones and mesobilirubins

The Fourier-transform Raman (FT-Raman), infrared (FT-IR), and UV-visible absorption spectra of four dipyrrinones and two mesobilirubins have been investigated in the solid state and in CH2Cl2 solutions. A detailed spectral analysis, assignment and discussion of these spectra are presented. The bands at 1735-1738, 1691-1707 and 1359-1377 cm(-1) which were assigned to the stretching vibrations of the C-O-C and C-O-H and symmetric deformation of C-H bonds, respectively, can act as a marker to distinguish the compounds of this class. The striking differences between the spectra of the compounds suggest that mesobilirubin XIIIalpha is tending to adopt as ridge-tile conformation, rather than linear conformation.     

Characterisation and Classification of Foodborne Bacteria Using Reflectance FTIR Microscopic Imaging

This work investigates the application of reflectance Fourier transform infrared (FTIR) microscopic imaging for rapid, and non-invasive detection and classification between Bacillus subtilis and Escherichia coli cell suspensions dried onto metallic substrates (stainless steel (STS) and aluminium (Al) slides) in the optical density (OD) concentration range of 0.001 to 10. Results showed that reflectance FTIR of samples with OD lower than 0.1 did not present an acceptable spectral signal to enable classification. Two modelling strategies were devised to evaluate model performance, transferability and consistency among concentration levels. Modelling strategy 1 involves training the model with half of the sample set, consisting of all concentrations, and applying it to the remaining half. Using this approach, for the STS substrate, the best model was achieved using support vector machine (SVM) classification, providing an accuracy of 96% and Matthews correlation coefficient (MCC) of 0.93 for the independent test set. For the Al substrate, the best SVM model produced an accuracy and MCC of 91% and 0.82, respectively. Furthermore, the aforementioned best model built from one substrate was transferred to predict the bacterial samples deposited on the other substrate. Results revealed an acceptable predictive ability when transferring the STS model to samples on Al (accuracy = 82%). However, the Al model could not be adapted to bacterial samples deposited on STS (accuracy = 57%). For modelling strategy 2, models were developed using one concentration level and tested on the other concentrations for each substrate. Results proved that models built from samples with moderate (1 OD) concentration can be adapted to other concentrations with good model generalization. Prediction maps revealed the heterogeneous distribution of biomolecules due to the coffee ring effect. This work demonstrated the feasibility of applying FTIR to characterise spectroscopic fingerprints of dry bacterial cells on substrates of relevance for food processing.     

Characterization of Japanese color sticks by energy dispersive X-ray fluorescence,X-ray diffraction and Fourier transform infrared analysis

This work comprises the use of energy dispersive X-ray fluorescence (EDXRF), X-ray diffraction (XRD) and Fourier transformed infrared (FTIR) techniques for the study of the composition of twentieth century traditional Japanese color sticks. By using the combination of analytical techniques it was possible to obtain information on inorganic and organic pigments, binders and fillers present in the sticks. The colorant materials identified in the sticks were zinc and titanium white, chrome yellow, yellow and red ochre, vermillion, alizarin, indigo, Prussian and synthetic ultramarine blue. The results also showed that calcite and barite were used as inorganic mineral fillers while Arabic gum was the medium used. EDXRF offered great potential for such investigations since it allowed the identification of the elements present in the sample preserving its integrity. However, this information alone was not enough to clearly identify some of the materials in study and therefore it was necessary to use XRD and FTIR techniques.     

Maize kernel hardness classification by near infrared (NIR) hyperspectral imaging and multivariate data analysis

The use of near infrared (NIR) hyperspectral imaging and hyperspectral image analysis for distinguishing between hard, intermediate and soft maize kernels from inbred lines was evaluated. NIR hyperspectral images of two sets (12 and 24 kernels) of whole maize kernels were acquired using a Spectral Dimensions MatrixNIR camera with a spectral range of 960-1662 nm and a sisuChema SWIR (short wave infrared) hyperspectral pushbroom imaging system with a spectral range of 1000-2498 nm. Exploratory principal component analysis (PCA) was used on absorbance images to remove background, bad pixels and shading. On the cleaned images, PCA could be used effectively to find histological classes including glassy (hard) and floury (soft) endosperm. PCA illustrated a distinct difference between glassy and floury endosperm along principal component (PC) three on the MatrixNIR and PC two on the sisuChema with two distinguishable clusters. Subsequently partial least squares discriminant analysis (PLS-DA) was applied to build a classification model. The PLS-DA model from the MatrixNIR image (12 kernels) resulted in root mean square error of prediction (RMSEP) value of 0.18. This was repeated on the MatrixNIR image of the 24 kernels which resulted in RMSEP of 0.18. The sisuChema image yielded RMSEP value of 0.29. The reproducible results obtained with the different data sets indicate that the method proposed in this paper has a real potential for future classification uses.     

Back‐propagation artificial neural network and attenuated total reflectance‐Fourier transform infrared spectroscopy for diagnosis of basal cell carcinoma by blood sample analysis

A diagnostic method for the cancer, based on investigation of infrared spectra of blood samples, has been developed. The two‐layer modified principal component feed forward back‐propagation artificial neural network (BP‐ANN) was used to classify the attenuated total reflectance‐Fourier transform infrared (ATR‐FTIR) spectra of blood samples obtained from healthy people and those with basal cell carcinoma (BCC). Results showed 98.33% of accuracy, in comparison with the current clinical methods. In the first step, 20 blood samples (10 normal and 10 cancer cases) were applied to construct the calibration model. Spectroscopic studies were performed in 900–1800 cm⁻¹ spectral region with 3.85 cm⁻¹ data space. In order to modify the capability of ANN in prediction of test samples, two different algorithms were applied. The obtained results confirmed the compatibility of the proposed network with the architecture of 20‐8‐2 (input‐hidden‐output) with the pattern model. It was concluded that analysis of blood samples by ATR‐FTIR spectroscopy and ANN chemometric technique would be a reliable approach for detection of BCC. Copyright © 2009 John Wiley & Sons, Ltd.