Detection of breast micro-metastases in axillary lymph nodes by infrared micro-spectral imaging

We report the ability of infrared micro-spectral imaging, coupled with completely unsupervised methods of multivariate statistical analysis, to accurately reproduce the histological architecture of axillary lymph nodes and detect metastatic breast cancer cells. The acquisition of spectral data from tissue embedded in paraffin provided spectra free of dispersive artefacts that may be observed for infrared microscopic measurements using a 'reflection/absorption' methodology. As a consequence, superior tissue classification and identification of cellular abnormality unattainable for deparaffinised tissue was achieved.

Spectral detection of micro-metastases in lymph node histo-pathology

The first detection of breast cancer micrometastases in lymph nodes by infrared spectral imaging and methods of multivariate analysis is reported. Micrometastases are indicators of early spread of cancer from the organ originally affected by disease, and their detection is of prime importance for the staging and treatment of cancer. Infrared spectral imaging, at a spatial resolution of ca. 10-12 mum, can detect small metastases down to the level of a few cancerous cells. The results presented here add to a rapidly growing database of infrared spectral imaging results for cancer diagnostics.

Shedding new light on the molecular architecture of oocytes using a combination of synchrotron Fourier transform-infrared and Raman spectroscopic mapping

Synchrotron Fourier transform-infrared (FT-IR) and Raman microspectroscopy were applied to investigate changes in the molecular architecture of mouse oocytes and demonstrate the overall morphology of the maturing oocyte. Here we show that differences were identified between immature mouse oocytes at the germinal vesicle (GV) and mature metaphase II (MII) stage when using this technology, without the introduction of any extrinsic markers, labels, or dyes. GV mouse oocytes were found to have a small, centrally located lipid deposit and another larger polar deposit of similar composition. MII oocytes have very large, centrally located lipid deposits. Each lipid deposit for both cell types contains an inner and outer lipid environment that differs in composition. To assess interoocyte variability, line scans were recorded across the diameter of the oocytes and compared from three independent trials (GV, n = 91; MII, n = 172), and the data were analyzed with principal component analysis (PCA). The average spectra and PCA loading plots show distinct and reproducible changes in the CH stretching region that can be used as molecular maturation markers. The method paves the way for developing an independent assay to assess oocyte status during maturation providing new insights into lipid distribution at the single cell level.

Cytology by Infrared Micro-Spectroscopy: Automatic Distinction of Cell Types in Urinary Cytology

We report microscopically collected infrared spectra of cells found in human urine in an effort to develop automatic methods for bladder cancer screening. Unsupervised multivariate analysis of the observed spectral patterns reveals distinct spectral classes, which correlated very well with visual cytology. Therefore, we believe that spectral analysis of individual cells can aid cytology in rendering reliable diagnoses based on objective measurements and discriminant algorithms.

Infrared micro-spectral imaging: distinction of tissue types in axillary lymph node histology

Background

Histopathologic evaluation of surgical specimens is a well established technique for disease identification, and has remained relatively unchanged since its clinical introduction. Although it is essential for clinical investigation, histopathologic identification of tissues remains a time consuming and subjective technique, with unsatisfactory levels of inter- and intra-observer discrepancy. A novel approach for histological recognition is to use Fourier Transform Infrared (FT-IR) micro-spectroscopy. This non-destructive optical technique can provide a rapid measurement of sample biochemistry and identify variations that occur between healthy and diseased tissues. The advantage of this method is that it is objective and provides reproducible diagnosis, independent of fatigue, experience and inter-observer variability.

Methods

We report a method for analysing excised lymph nodes that is based on spectral pathology. In spectral pathology, an unstained (fixed or snap frozen) tissue section is interrogated by a beam of infrared light that samples pixels of 25 μm × 25 μm in size. This beam is rastered over the sample, and up to 100,000 complete infrared spectra are acquired for a given tissue sample. These spectra are subsequently analysed by a diagnostic computer algorithm that is trained by correlating spectral and histopathological features.

Results

We illustrate the ability of infrared micro-spectral imaging, coupled with completely unsupervised methods of multivariate statistical analysis, to accurately reproduce the histological architecture of axillary lymph nodes. By correlating spectral and histopathological features, a diagnostic algorithm was trained that allowed both accurate and rapid classification of benign and malignant tissues composed within different lymph nodes. This approach was successfully applied to both deparaffinised and frozen tissues and indicates that both intra-operative and more conventional surgical specimens can be diagnosed by this technique.

Conclusion

This paper provides strong evidence that automated diagnosis by means of infrared micro-spectral imaging is possible. Recent investigations within the author's laboratory upon lymph nodes have also revealed that cancers from different primary tumours provide distinctly different spectral signatures. Thus poorly differentiated and hard-to-determine cases of metastatic invasion, such as micrometastases, may additionally be identified by this technique. Finally, we differentiate benign and malignant tissues composed within axillary lymph nodes by completely automated methods of spectral analysis.

New ways of imaging uptake and intracellular fate of liposomal drug carrier systems inside individual cells, based on Raman microscopy

Recent developments, combining Raman spectroscopy with optical microscopy, provide a new noninvasive technique to assess and image cellular processes. Of particular interest are the uptake mechanisms of various cytologically active compounds. In order to distinguish the species of interest from their cellular environment spectroscopically, compounds may be labeled with deuterium. Here, we apply Raman microspectroscopy to follow the uptake of liposomal drug carrier systems that have been introduced to deliver biologically active compounds to their site of action within human breast adenocarcinoma MCF-7 cells. The distribution patterns of liposomes and liposomes surface-modified with a cell-penetrating peptide (TAT-peptide, TATp) have been imaged over time. The spectroscopic information obtained provides a clear evidence for variable rates, as well as different efficiencies of liposome uptake depending on their surface properties. Depending on the experimental setup, the technique may be applied to fixed or living cell organisms.

New ways of imaging uptake and intracellular fate of liposomal drug carrier systems inside individual cells, based on Raman microscopy

Recent developments, combining Raman spectroscopy with optical microscopy, provide a new noninvasive technique to assess and image cellular processes. Of particular interest are the uptake mechanisms of various cytologically active compounds. In order to distinguish the species of interest from their cellular environment spectroscopically, compounds may be labeled with deuterium. Here, we apply Raman microspectroscopy to follow the uptake of liposomal drug carrier systems that have been introduced to deliver biologically active compounds to their site of action within human breast adenocarcinoma MCF-7 cells. The distribution patterns of liposomes and liposomes surface-modified with a cell-penetrating peptide (TAT-peptide, TATp) have been imaged over time. The spectroscopic information obtained provides a clear evidence for variable rates, as well as different efficiencies of liposome uptake depending on their surface properties. Depending on the experimental setup, the technique may be applied to fixed or living cell organisms.

Chapter 10: Infrared and Raman microscopy in cell biology

This chapter presents novel microscopic methods to monitor cell biological processes of live or fixed cells without the use of any dye, stains, or other contrast agent. These methods are based on spectral techniques that detect inherent spectroscopic properties of biochemical constituents of cells, or parts thereof. Two different modalities have been developed for this task. One of them is infrared micro-spectroscopy, in which an average snapshot of a cell's biochemical composition is collected at a spatial resolution of typically 25 mum. This technique, which is extremely sensitive and can collect such a snapshot in fractions of a second, is particularly suited for studying gross biochemical changes. The other technique, Raman microscopy (also known as Raman micro-spectroscopy), is ideally suited to study variations of cellular composition on the scale of subcellular organelles, since its spatial resolution is as good as that of fluorescence microscopy. Both techniques exhibit the fingerprint sensitivity of vibrational spectroscopy toward biochemical composition, and can be used to follow a variety of cellular processes.

Label-free detection of mitochondrial distribution in cells by nonresonant Raman microspectroscopy

High spatial resolution Raman maps of fixed cells in an aqueous environment are reported. These maps were obtained by collecting individual Raman spectra via a Raman microspectrometer in a raster pattern on a 0.5-microm grid and assembling pseudocolor maps from the spectral hypercubes by multivariate methods. The Raman maps show the nucleus and the nucleoli of cells as well as subcellular organization in the cytoplasm. In particular, the distribution of mitochondria in the perinuclear region could be demonstrated by correlating distinct areas of the Raman maps with corresponding areas of fluorescence maps of the same cells after staining with mitochondria-specific labels. To the best of our knowledge, this is the first report of label-free detection of mitochondria inside a somatic mammalian cell using Raman microspectroscopy.

Artificial neural networks as supervised techniques for FT-IR microspectroscopic imaging

In this report the applicability of an improved method of image segmentation of infrared microspectroscopic data from histological specimens is demonstrated. Fourier transform infrared (FT-IR) microspectroscopy was used to record hyperspectral data sets from human colorectal adenocarcinomas and to build up a database of spatially resolved tissue spectra. This database of colon microspectra comprised 4120 high-quality FT-IR point spectra from 28 patient samples and 12 different histological structures. The spectral information contained in the database was employed to teach and validate multilayer perceptron artificial neural network (MLP-ANN) models. These classification models were then employed for database analysis and utilised to produce false colour images from complete tissue maps of FT-IR microspectra. An important aspect of this study was also to demonstrate how the diagnostic sensitivity and specificity can be specifically optimised. An example is given which shows that changes of the number of teaching patterns per class can be used to modify these two interrelated test parameters. The definition of ANN topology turned out to be crucial to achieve a high degree of correspondence between the gold standard of histopathology and IR spectroscopy. Particularly, a hierarchical scheme of ANN classification proved to be superior for the reliable classification of tissue spectra. It was found that unsupervised methods of clustering, specifically agglomerative hierarchical clustering (AHC), were helpful in the initial phases of model generation. Optimal classification results could be achieved if the class definitions for the ANNs were carried out by considering the classification information provided by cluster analysis.

Infrared micro-spectroscopy of human cells: Causes for the spectral variance of oral mucosa (buccal) cells

We discuss the causes contributing to the variance of the spectra of individual human epithelial cells. This aspect has largely been ignored in previous studies, but needs to be understood for diagnostic applications of infrared micro-spectroscopy. We attribute the spectral variance to Mie scattering, and to variations of nuclear contributions to the overall spectra caused by different nuclear size.

Infrared micro-spectroscopy of human cells: Causes for the spectral variance of oral mucosa (buccal) cells

We discuss the causes contributing to the variance of the spectra of individual human epithelial cells. This aspect has largely been ignored in previous studies, but needs to be understood for diagnostic applications of infrared micro-spectroscopy. We attribute the spectral variance to Mie scattering, and to variations of nuclear contributions to the overall spectra caused by different nuclear size.

Infrared micro-spectroscopic studies of epithelial cells

We report results from a study of human and canine mucosal cells, investigated by infrared micro-spectroscopy, and analyzed by methods of multivariate statistics. We demonstrate that the infrared spectra of individual cells are sensitive to the stage of maturation, and that a distinction between healthy and diseased cells will be possible. Since this report is written for an audience not familiar with infrared micro-spectroscopy, a short introduction into this field is presented along with a summary of principal component analysis.

Cell-cycle-dependent variations in FTIR micro-spectra of single proliferating HeLa cells: principal component and artificial neural network analysis

We have previously reported spectral differences for cells at different stages of the eukaryotic cell division cycle. These differences are due to the drastic biochemical and morphological changes that occur as a consequence of cell proliferation. We correlate these changes in FTIR absorption and Raman spectra of individual cells with their biochemical age (or phase in the cell cycle), determined by immunohistochemical staining to detect the appearance (and subsequent disappearance) of cell-cycle-specific cyclins, and/or the occurrence of DNA synthesis. Once spectra were correlated with their cells' staining patterns, we used methods of multivariate statistics to analyze the changes in cellular spectra as a function of cell cycle phase.

Infrared spectral imaging of lymph nodes: Strategies for analysis and artifact reduction

In this contribution, we discuss state-of-the-art methodology for the collection and analysis of hyperspectral images of tissue that will become useful in complementing classical histopathology. In particular, we discuss sampling strategies, data collection methods, and computational approaches to produce pseudo-color maps of large tissue sections of lymph nodes, up to about 100 mm(2) in size. The latter efforts include methods to reduce the presence of dispersion artifacts in IR transflection micro-spectra which can greatly impact the statistical analyzes performed on the data, such as hierarchical cluster analysis and principal components analysis.

Mie-type scattering and non-Beer-Lambert absorption behavior of human cells in infrared microspectroscopy

We report infrared microspectral features of nuclei in a completely inactive and contracted (pyknotic) state, and of nuclei of actively dividing cells. For pyknotic nuclei, the very high local concentration of DNA leads to opaqueness of the chromatin and, consequently, the absence of DNA signals in the IR spectra of very small nuclei. However, these nuclei can be detected by their scattering properties, which can be described by the Mie theory of scattering from dielectric spheres. This scattering depends on the size of the nucleus; consequently, quite different scattering cross-sections are calculated and observed for pyknotic and mitotic nuclei.

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.

Infrared microspectroscopy of individual human cervical cancer (HeLa) cells

We report infrared (IR) spectra observed for individual, cultured human cervical cancer (HeLa) cells. Spectra were collected microscopically, in reflection/absorption modes, from cells deposited and dried on microscope slides or from cells grown directly on slides. Within the spectra of the dried cells, significant spectral heterogeneity exists that was previously attributed to different stages of the cell cycle [Boydston-White. S., et al., Biospectroscopy 1999, 5, 219-227; Holman, H. Y., et al., Biopolymers Biospectrosc 2000, 57, 329-335; Tobin, M. J., et al., in First BASIE Workshop, Karlsruhe, Germany, 2003]. The results reported here confirm earlier findings and present the possibility of determining the abundance of cells within each stage of the cycle from the IR spectra. In an accompanying paper, we show that the spectra of cells in suspension exhibit spectral intensity distributions that are different from that of the dried cells. This result has far-reaching implications for the use of infrared microspectroscopy to screen dried cell preparations for the presence of abnormal cells.

Infrared microspectroscopy of individual human cervical cancer (HeLa) cells suspended in growth medium

We report for the first time the infrared spectra of individual human cervical cancer (HeLa) cells suspended in buffer or cell culture medium. Although we did not establish whether these cells were viable at the time of spectral data acquisition, we believe that the methodology used is applicable to the study of live cells. Data were collected either from entire cells, using 25- to 40-microm apertures, or via an imaging approach, where pixels measuring 6.25 x 6.25 microm were assembled to form a map of a cell in suspension. Measurements were carried out both in reflection/absorption and in transmission modes. The results reported here might have far-reaching implications for the use of infrared microspectroscopy to monitor cell proliferation, drug response, and other cell biological parameters in live cells.

Fourier transform infrared (FTIR) spectral mapping of the cervical transformation zone, and dysplastic squamous epithelium

OBJECTIVES

This paper is aimed at establishing infrared spectral patterns for the different tissue types found in, and for different stages of disease of squamous cervical epithelium. Methods for the unsupervised distinction of these tissue types are discussed.

METHODS

Fourier transform infrared (FTIR) maps of the squamous and glandular cervical epithelium, and of the cervical transformation zone, were obtained and analyzed by multivariate unsupervised hierarchical cluster methods. The resulting clusters are correlated to the corresponding stained histopathological features in the tissue sections.

RESULTS

Multivariate statistical analysis of FTIR spectra collected for tissue sections permit an unsupervised method of distinguishing tissue types, and of differentiating between normal and diseased tissue. By analyzing different spectral windows and comparing the results with histology, we found the amide I and II region (1740-1470 cm(-1)) to be very important in correlating anatomical and histopathological features in tissue to spectral clusters. Since an unsupervised, rather than a diagnostic, algorithm was used in these efforts, no statistical analysis of false-positive/false-negative results is reported at this time.

CONCLUSIONS

The combination of FTIR micro-spectroscopy and multivariate spectral processing provides important insights into the fundamental spectral signatures of individual cells and consequently shows potential as a diagnostic tool for cervical cancer.

Imaging of colorectal adenocarcinoma using FT-IR microspectroscopy and cluster analysis

In this paper, three different clustering algorithms were applied to assemble infrared (IR) spectral maps from IR microspectra of tissues. Using spectra from a colorectal adenocarcinoma section, we show how IR images can be assembled by agglomerative hierarchical (AH) clustering (Ward's technique), fuzzy C-means (FCM) clustering, and k-means (KM) clustering. We discuss practical problems of IR imaging on tissues such as the influence of spectral quality and data pretreatment on image quality. Furthermore, the applicability of cluster algorithms to the spatially resolved microspectroscopic data and the degree of correlation between distinct cluster images and histopathology are compared. The use of any of the clustering algorithms dramatically increased the information content of the IR images, as compared to univariate methods of IR imaging (functional group mapping). Among the cluster imaging methods, AH clustering (Ward's algorithm) proved to be the best method in terms of tissue structure differentiation.

IR spectroscopic studies of major cellular components. III. Hydration of protein, nucleic acid, and phospholipid films

The IR absorption spectra of protein, DNA, RNA, and phospholipid films as a function of the water content are reported. We find that the hydration of protein films affects the peak intensity of amide I and amide II bands and the shape of the amide III band. For nucleic acids, the symmetric (nu(S) PO(2) (-)) and antisymmetric (nu(AS) PO(2) (-)) stretching vibrations of the phosphate linkage are the most affected by hydration, because both intensity changes and frequency shifts are observed. The spectra of phospholipid films are also sensitive to hydration, and they exhibit changes in the peak intensities and frequencies of both nu(S) PO(2) (-) and nu(AS) PO(2) (-) vibrations. We interpret the spectral differences between water saturated and dried films both in terms of structural changes and the change in the local dielectric in the vicinity of the polar and solvent exposed groups. In addition, we observe that the most significant change in the absorption intensity, frequency, and shape of the water sensitive vibrations occurs at high hydration levels. The principal component analysis of hydration results and the kinetics of water removal from sample films are also discussed. In addition, protein spectra acquired using film and KBr pellet sampling techniques are compared.

Spatially resolved IR microspectroscopy of single cells

Fourier transform IR (FTIR) microspectroscopy at a spatial resolution of 18 microm was used to study skin fibroblasts and giant sarcoma cells. Both cell lines were derived from the same patient; they were metabolically active and in the exponentially growing phase. The IR spectra were acquired for the nuclei and cytosol of untreated cells, cells washed with ethanol, and cells treated with RNase or DNase. A comparison of the spectra of the two cell lines yielded only insignificant spectral differences, indicating that IR spectroscopy monitors the overall cell activity rather than specific signs of cancer.

IR spectra and IR spectral maps of individual normal and cancerous cells

The IR microspectra for individual normal and cancerous cells are reported at a spatial resolution that permits a distinction between the nuclear and cytoplasmic regions. The observed spectra reveal large differences in the spectral contributions of RNA, DNA, and phospholipids: metabolically inactive cells show spectral patterns of proteins only, whereas actively dividing cells also show spectral signatures of nucleic acids and phospholipids. These spectral variations are independent of the state of health of a cell.