Delimitation of squamous cell cervical carcinoma using infrared microspectroscopic imaging

Cervical Squamous Cell Carcinoma Diagnosis by FTIR Microspectroscopy

Cervical cancer was considered the fourth most common cancer worldwide in 2020. In order to reduce mortality, an early diagnosis of the tumor is required. Currently, this type of cancer occurs mostly in developing countries due to the lack of vaccination and screening against the Human Papillomavirus. Thus, there is an urgent clinical need for new methods aiming at a reliable screening and an early diagnosis of precancerous and cancerous cervical lesions. Vibrational spectroscopy has provided very good results regarding the diagnosis of various tumors, particularly using Fourier transform infrared microspectroscopy, which has proved to be a promising complement to the currently used histopathological methods of cancer diagnosis. This spectroscopic technique was applied to the analysis of cryopreserved human cervical tissue samples, both squamous cell carcinoma (SCC) and non-cancer samples. A dedicated Support Vector Machine classification model was constructed in order to categorize the samples into either normal or malignant and was subsequently validated by cross-validation, with an accuracy higher than 90%.

Advances in Digital Pathology: From Artificial Intelligence to Label-Free Imaging

BACKGROUND

Digital pathology, in its primary meaning, describes the utilization of computer screens to view scanned histology slides. Digitized tissue sections can be easily shared for a second opinion. In addition, it allows tissue image analysis using specialized software to identify and measure events previously observed by a human observer. These tissue-based readouts were highly reproducible and precise. Digital pathology has developed over the years through new technologies. Currently, the most discussed development is the application of artificial intelligence to automatically analyze tissue images. However, even new label-free imaging technologies are being developed to allow imaging of tissues by means of their molecular composition.

SUMMARY

This review provides a summary of the current state-of-the-art and future digital pathologies. Developments in the last few years have been presented and discussed. In particular, the review provides an outlook on interesting new technologies (e.g., infrared imaging), which would allow for deeper understanding and analysis of tissue thin sections beyond conventional histopathology.

KEY MESSAGES

In digital pathology, mathematical methods are used to analyze images and draw conclusions about diseases and their progression. New innovative methods and techniques (e.g., label-free infrared imaging) will bring significant changes in the field in the coming years.

Automatic Identification of Paraffin Pixels on FTIR Images Acquired on FFPE Human Samples

The transfer of mid-infrared spectral histopathology to the clinic will be possible provided that its application in clinical practice is simple. Rapid analysis of formalin-fixed paraffin-embedded (FFPE) tissue section is thus a prerequisite. The chemical dewaxing of these samples before image acquisition used by the majority of studies is in contradiction with this principle. Fortunately, the in silico analysis of the images acquired on FFPE samples is possible using extended multiplicative signal correction (EMSC). However, the removal of pure paraffin pixels is essential to perform a relevant classification of tissue spectra. So far, this task was possible only if using manual and subjective histogram analysis. In this article, we thus propose a new automatic and multivariate methodology based on the analysis of optimized combinations of EMSC regression coefficients by validity indices and KMeans clustering to separate paraffin and tissue pixels. The validation of our method is performed using simulated infrared spectral images by measuring the Jaccard index between our partitions and the image model, with values always over 0.90 for diverse baseline complexity and signal-to-noise ratio. These encouraging results were also validated on real images by comparing our method with classical ones and by computing the Jaccard index between our partitions and the KMeans partitions obtained on the infrared image acquired on the same samples but after chemical dewaxing, with values always over 0.84.

Detection of macromolecular inversion-induced structural changes in osteosarcoma cells by FTIR microspectroscopy

Fourier transform infrared (FTIR) microspectroscopy provides a biochemical fingerprint of the cells. In this study, chemical changes in 143B osteosarcoma cells were investigated using FTIR analysis of cancer cells after their treatment with polymeric invertible micellar assemblies (IMAs) and curcumin-loaded IMAs and compared with untreated osteosarcoma cells. A comprehensive principal component analysis (PCA) was applied to analyze the FTIR results and confirm noticeable changes in cell surface chemical structures in the fingerprint regions of 1480-900 cm^-1. The performed clustering shows visible differences for all investigated groups of cancer cells. It is demonstrated that a combination of FTIR microspectroscopy with PCA can be an efficient approach in determining interactions of osteosarcoma cells and drug-loaded polymer micellar assemblies. Graphical abstract.

Resolving Interobserver Discrepancies in Lung Cancer Diagnoses by Spectral Histopathology

This paper reports the results of a collaborative lung cancer study between City of Hope Cancer Center (Duarte, California) and CIRECA, LLC (Cambridge, Massachusetts), comprising 328 samples from 249 patients, that used an optical technique known as spectral histopathology (SHP) for tissue classification. Because SHP is based on a physical measurement, it renders diagnoses on a more objective and reproducible basis than methods based on assessing cell morphology and tissue architecture. This report demonstrates that SHP provides distinction of adenocarcinomas from squamous cell carcinomas of the lung with an accuracy comparable to that of immunohistochemistry and highly reliable classification of adenosquamous carcinoma. Furthermore, this report shows that SHP can be used to resolve interobserver differences in lung pathology. Spectral histopathology is based on the detection of changes in biochemical composition, rather than morphologic features, and is therefore more akin to methods such as matrix-assisted laser desorption ionization time-of-flight mass spectrometry imaging. Both matrix-assisted laser desorption ionization time-of-flight mass spectrometry and SHP imaging modalities demonstrate that changes in tissue morphologic features observed in classical pathology are accompanied by, and may be correlated to, changes in the biochemical composition at the cellular level. Thus, these imaging methods provide novel insight into biochemical changes due to disease.

Thermal effect on dispersive infrared spectroscopic imaging of prostate cancer tissue

A system that combines dispersive infrared micro-spectroscopic imaging and thermography has been developed to study the effect of thermal radiation on the infrared absorption spectra of prostate biopsy samples. The system allows the distribution of thermal signal intensity as a function of emissivity to be interpreted from the integrated absorbance obtained by spectroscopic imaging. Biochemical differences between cancer and benign areas within the specimens are identified in the spectra. Side-by-side comparison of H&E stained adjacent tissue sections with infrared images constructed before and after the removal of thermal effect showed that the latter strongly support differentiation of regions within tissues. The use of spectral bands at discrete wavelengths significantly reduced spectral acquisition time, making this technique promising as a future clinical diagnostic tool. A systemic methodology was implemented to process the data, first by k-means clustering on the second derivative spectra without a priori knowledge, followed by principal component analysis (PCA). Four distinct regions within the tissue samples were successfully classified based on the antisymmetric stretching mode of the methylene functional group. Separation between data in clusters occurs when projecting spectra on a PCA score plot on a plane made by first 2 principal components. The significance of the disparity was verified with statistical test. Regulation of signal to chopper and detector enables simultaneous acquisition of infrared and thermal images of the prostate biopsy tissues.

Diversity among endothelial cell lines revealed by Raman and Fourier-transform infrared spectroscopic imaging

A methodology of examination and characterization of popular human endothelial cells lines.

Identification of Primary Tumors of Brain Metastases by Infrared Spectroscopic Imaging and Linear Discriminant Analysis

This study applies infrared (IR) spectroscopy to distinguish normal brain tissue from brain metastases and to determine the primary tumor of four frequent brain metastases such as lung cancer, colorectal cancer, breast cancer, and renal cell carcinoma. Standard methods sometimes fail to identify the origin of brain metastases. As metastatic cells contain the molecular information of the primary tissue cells and IR spectroscopy probes the molecular fingerprint of cells, IR spectroscopy based methods constitute a new approach to determine the primary tumor of a brain metastasis. IR spectroscopic images were recorded by a FTIR spectrometer equipped with a macro sample chamber and coupled to a focal plane array detector. Unsupervised cluster analysis of IR images revealed variances within each sample and between samples of the same tissue type. Cluster averaged IR spectra of tissue classes with known diagnoses were selected to develop a metric with eight variables. These data trained a supervised classification model based on linear discriminant analysis that was used to identify the origin of 20 cryosections including one brain metastasis with an unknown primary tumor.

High-resolution FTIR imaging of colon tissues for elucidation of individual cellular and histopathological features

Comparison of spectral-histopathological features of a colon tissue measured using a conventional (5.5 μm × 5.5 μm, left) and a high-magnification (1.1 μm × 1.1 μm, right) FTIR imaging system with respect to HE stained tissue (middle).

Label-free classification of colon cancer grading using infrared spectral histopathology

In recent years spectral histopathology (SHP) has been established as a label-free method to identify cancer within tissue. Herein, this approach is extended. It is not only used to identify tumour tissue with a sensitivity of 94% and a specificity of 100%, but in addition the tumour grading is determined. Grading is a measure of how much the tumour cells differ from the healthy cells. The grading ranges from G1 (well-differentiated), to G2 (moderately differentiated), G3 (poorly differentiated) and in rare cases to G4 (anaplastic). The grading is prognostic and is needed for the therapeutic decision of the clinician. The presented results show good agreement between the annotation by SHP and by pathologists. A correlation matrix is presented, and the results show that SHP provides prognostic values in colon cancer, which are obtained in a label-free and automated manner. It might become an important automated diagnostic tool at the bedside in precision medicine.

The pituitary gland under infrared light – in search of a representative spectrum for homogeneous regions

This work focuses on obtaining unique representative FTIR spectrum characteristic for one type of cells architecture. Presented idea is based on using of HCA for data evaluation to search for uniform patterns within samples from the perspective of FTIR spectra.

Evaluation of different tissue de-paraffinization procedures for infrared spectral imaging

Differential distribution of paraffin in a normal colon tissue section after various de-Waxing procedures in comparison to a paraffinized tissue.

Detection of cervical cancer based on photoacoustic imaging-the in-vitro results

In current clinical practice, the diagnosis of cervical cancer (CC) is mainly through the cervical screening followed by a necessary biopsy, but this method is labor consuming and expensive, and can only detect superficial lesions around the external cervical orifice. In contrast, photoacoustic imaging (PAI) is sensitive to the abnormal angiogenesis deep in the biological tissue, and may be capable for the intact scanning both around the external orifice and in cervical canal. In this paper, we for the first time put forward the photoacoustic diagnosis of CC. A total of 30 in-vitro experiments were carried out in this study, and the obtained depth maximum amplitude projection (DMAP) images were analyzed to evaluate the extent of the angiogenesis for different clinical stages of CC. Stronger absorption from the cervical lesions is observed relative to that of normal tissue. Paired t-test indicates that the difference in mean optical absorption (MOA) between normal tissue and cervical lesion has statistical significance with a confidential coefficient of 0.05. Statistical results also show that the MOAs of the cervical lesions are closely related to the severity of CC. These results imply that PAI may have great utility in the clinical diagnosis of CC.

Determination of phase behaviour in all protein blend materials with multivariate FTIR imaging technique

Multivariate FTIR imaging technique is introduced to analyse a silk fibroin/soy protein blend, which shows that the silk fibroin domains are dispersed in soy protein matrix.

Infrared imaging in breast cancer: automated tissue component recognition and spectral characterization of breast cancer cells as well as the tumor microenvironment

Current evaluation of histological sections of breast cancer samples remains unsatisfactory. The search for new predictive and prognostic factors is ongoing. Infrared spectroscopy and its potential to probe tissues and cells at the molecular level without requirement for contrast agents could be an attractive tool for clinical and diagnostic analysis of breast cancer. In this study, we report the successful application of FTIR (Fourier transform infrared) imaging for breast tissue component characterization. We show that specific FTIR spectral signatures can be assigned to the major tissue components of breast tumor samples. We demonstrate that a tissue component classifier can be built based on a spectral database of well-annotated tissues and successfully validated on independent breast samples. We also demonstrate that spectral features can reveal subtle differences within a tissue component, capturing for instance lymphocytic and stromal activation. By investigating in parallel lymph nodes, tonsils and wound healing tissues, we prove the uniqueness of the signature of both lymphocytic infiltrate and tumor microenvironment in the breast disease context. Finally, we demonstrate that the biochemical information reflected in the epithelial spectra might be clinically relevant for the grading purpose, suggesting potential to improve breast cancer management in the future.

Infrared and Raman imaging for characterizing complex biological materials: a comparative morpho-spectroscopic study of colon tissue

Complementary diagnostic methods to conventional histopathology are currently being investigated for developing rapid and objective molecular-level understanding of various disorders, especially cancers. Spectral histopathology using vibrational spectroscopic imaging has been put in the frontline as potentially promising in this regard as it provides a "spectral fingerprint" of the biochemical composition of cells and tissues. In order to ascertain the feasible conditions of vibrational spectroscopic methods for tissue-imaging analysis, vibrational multimodal imaging (infrared transmission, infrared-attenuated total reflection, and Raman imaging) of the same colon tissue has been implemented. The spectral images acquired were subjected to multivariate clustering analysis in order to identify on a molecular level the constituent histological organization of the colon tissue such as the epithelium, connective tissue, etc., by comparing the cluster images with the histological reference images. Based on this study, a comparative analysis of important factors involved in the vibrational multimodal imaging approaches such as image resolution, time constraints, their advantages and limitations, and their applicability to biological tissues has been carried out. Out of the three different vibrational imaging modalities tested, infrared-attenuated total reflection mode of imaging appears to provide a good compromise between the tissue histology and the time constraints in achieving similar image contrast to that of Raman imaging at an approximately 33-fold faster measurement time. The present study demonstrates the advantages, the limitations of the important parameters involved in vibrational multimodal imaging approaches, and their potential application toward imaging of biological tissues.

Infrared spectral histopathology for cancer diagnosis: a novel approach for automated pattern recognition of colon adenocarcinoma

Automated and label-free colon cancer diagnosis and identification of tumor-associated features using FTIR spectral histopathology directly on paraffinized tissue arrays.

Similarity maps and hierarchical clustering for annotating FT-IR spectral images

Background

Unsupervised segmentation of multi-spectral images plays an important role in annotating infrared microscopic images and is an essential step in label-free spectral histopathology. In this context, diverse clustering approaches have been utilized and evaluated in order to achieve segmentations of Fourier Transform Infrared (FT-IR) microscopic images that agree with histopathological characterization.

Results

We introduce so-called interactive similarity maps as an alternative annotation strategy for annotating infrared microscopic images. We demonstrate that segmentations obtained from interactive similarity maps lead to similarly accurate segmentations as segmentations obtained from conventionally used hierarchical clustering approaches. In order to perform this comparison on quantitative grounds, we provide a scheme that allows to identify non-horizontal cuts in dendrograms. This yields a validation scheme for hierarchical clustering approaches commonly used in infrared microscopy.

Conclusions

We demonstrate that interactive similarity maps may identify more accurate segmentations than hierarchical clustering based approaches, and thus are a viable and due to their interactive nature attractive alternative to hierarchical clustering. Our validation scheme furthermore shows that performance of hierarchical two-means is comparable to the traditionally used Ward’s clustering. As the former is much more efficient in time and memory, our results suggest another less resource demanding alternative for annotating large spectral images.

Progress in Fourier Transform Infrared Spectroscopic Imaging Applied to Venereal Cancer Diagnosis

Fourier transform infrared imaging spectroscopy is a powerful technique that provides molecular and spatial information at the single-cell level. We report on the progress of this technology in the field of cancer research, focusing on human cervical cancer because of the inherent difficulty in grading this type of cancer and as a model for venereal cancers in dogs. Using a suite of multivariate imaging processing techniques, we demonstrate the potential of this technique to identify histologic features in the normal epithelium and cervical intraepithelial neoplasia stages I and III. We highlight the advantages and detail the barriers that need to be overcome before implementation of this technology in the clinical environment.

Breast cancer characterization based on image classification of tissue sections visualized under low magnification

Rapid assessment of tissue biopsies is a critical issue in modern histopathology. For breast cancer diagnosis, the shape of the nuclei and the architectural pattern of the tissue are evaluated under high and low magnifications, respectively. In this study, we focus on the development of a pattern classification system for the assessment of breast cancer images captured under low magnification (×10). Sixty-five regions of interest were selected from 60 images of breast cancer tissue sections. Texture analysis provided 30 textural features per image. Three different pattern recognition algorithms were employed (kNN, SVM, and PNN) for classifying the images into three malignancy grades: I-III. The classifiers were validated with leave-one-out (training) and cross-validation (testing) modes. The average discrimination efficiency of the kNN, SVM, and PNN classifiers in the training mode was close to 97%, 95%, and 97%, respectively, whereas in the test mode, the average classification accuracy achieved was 86%, 85%, and 90%, respectively. Assessment of breast cancer tissue sections could be applied in complex large-scale images using textural features and pattern classifiers. The proposed technique provides several benefits, such as speed of analysis and automation, and could potentially replace the laborious task of visual examination.

Immunohistochemistry, histopathology and infrared spectral histopathology of colon cancer tissue sections

During the past years, many studies have shown that infrared spectral histopathology (SHP) can distinguish different tissue types and disease types independently of morphological criteria. In this manuscript, we report a comparison of immunohistochemical (IHC), histopathological and spectral histopathological results for colon cancer tissue sections. A supervised algorithm, based on the "random forest" methodology, was trained using classical histopathology, and used to automatically identify colon tissue types, and areas of colon adenocarcinoma. The SHP images subsequently were compared to IHC-based images. This comparison revealed excellent agreement between the methods, and demonstrated that label-free SHP detects compositional changes in tissue that are the basis of the sensitivity of IHC.

Elliptically polarized light for depth resolved optical imaging

It is shown that using elliptically polarized light permits selecting well-defined subsurface volumes in a turbid medium. This suggests the possibility of probing biological tissues at specific depths. First, we present the method and preliminary results obtained on an Intralipid phantom. We next report on the method's performance on a biological phantom (chicken breast) and, finally, on the exposed cortex of an anesthetized rat.

Fourier transform infrared microspectroscopy identifies protein propionylation in histone deacetylase inhibitor treated glioma cells

Histone deacetylase inhibitors (HDIs) have attracted considerable attention as potential drug molecules in tumour biology. In order to optimise chemotherapy, it is important to understand the mechanisms of regulation of histone deacetylase (HDAC) enzymes and modifications brought by various HDIs. In the present study, we have employed Fourier transform infrared microspectroscopy (FT-IRMS) to evaluate modifications in cellular macromolecules subsequent to treatment with various HDIs. In addition to CH(3) (methyl) stretching bands at 2872 and 2960 cm(-1) , which arises due to acetylation, we also found major changes in bands at 2851 and 2922 cm(-1) , which originates from stretching vibrations of CH(2) (methylene) groups, in valproic acid treated cells. We further demonstrate that the changes in CH(2) stretching are concentration-dependent and also induced by several other HDIs. Recently, HDIs have been shown to induce propionylation besides acetylation [1]. Since propionylation involves CH(2) groups, we hypothesized that CH(2) vibrational frequency changes seen in HDI treated cells could arise due to propionylation. As verification, pre-treatment of cells with propionyl CoA synthetase inhibitor resulted in loss of CH(2) vibrational changes in histones, purified from valproic acid treated cells. This was further proved by western blot using propionyl-lysine specific antibody. Thus we demonstrate for the first time that propionylation could be monitored by studying CH(2) stretching using IR spectroscopy and further provide a platform for monitoring HDI induced multiple changes in cells.

Applications of Infrared and Raman Microspectroscopy of Cells and Tissue in Medical Diagnostics: Present Status and Future Promises

This paper summarizes the progress achieved over the past fifteen years in applying vibrational (Raman and IR) spectroscopy to problems of medical diagnostics and cellular biology. During this time, a number of research groups have verified the enormous information content of vibrational spectra; in fact, genomic, proteomic, and metabolomic information can be deduced by decoding the observed vibrational spectra. This decoding process is aided enormously by the availability of high-power computer workstations and advanced algorithms for data analysis. Furthermore, commercial instrumentation for the fast collection of both Raman and infrared microspectral data has rendered practical the collection of images based solely on spectral data. The progress in the field has been manifested by a steady increase in the number and quality of publications submitted by established and new research groups in vibrational biological and biomedical arenas.

Fourier transform infrared microspectroscopy of complex biological systems: from intact cells to whole organisms

Fourier transform infrared (FTIR) microspectroscopy is a powerful tool for the study of complex biological systems. Indeed, it is employed to characterize intact cells, tissues, and whole model organisms such as nematodes, since it allows to obtain a chemical fingerprint of the sample under investigation, giving information on the molecular composition and structures. The successful application of this technique for the in situ study of biological processes requires specific sample preparations, in order to obtain reliable and reproducible results. In the present work, we illustrate the optimized procedures to prepare biological samples for IR measurements and the method to collect and analyze their FTIR spectra. In particular, we describe here the investigations on bacterial cells, intact eukaryotic cells, and whole intact nematode specimens.

Recent advances in optical imaging for cervical cancer detection

Cervical cancer is one of the most common and lethal gynecological malignancies in both developing and developed countries, and therefore, there is a considerable interest in early diagnosis and treatment of precancerous lesions. Although the current standard care mainly based on cytology and colposcopy has reduced rates of cervical cancer morbidity and mortality, many lesions are still missed or overcalled and referred for unnecessary biopsies. Optical imaging technologies, spectroscopy approaches and high-resolution imaging methods are anticipated to improve the conventional cervical cancer screening providing in vivo diagnosis with high sensitivity and specificity. Their concept is that morphologic and biochemical properties of the cervical tissue are altered in response to its malignant transformation. In addition, contrast agents that target against specific neoplastic biomarkers can enhance the effectiveness of this new technology. Due to the unprecedented growth of these optical techniques accompanied probably by favorable cost-effectiveness, the primary detection of premalignant lesions may become more accessible in both the developing and the developed countries and can offer see-to-treat workflows and early therapeutic interventions.

Vibrational spectroscopy: a clinical tool for cancer diagnostics

Vibrational spectroscopy techniques have demonstrated potential to provide non-destructive, rapid, clinically relevant diagnostic information. Early detection is the most important factor in the prevention of cancer. Raman and infrared spectroscopy enable the biochemical signatures from biological tissues to be extracted and analysed. In conjunction with advanced chemometrics such measurements can contribute to the diagnostic assessment of biological material. This paper also illustrates the complementary advantage of using Raman and FTIR spectroscopy technologies together. Clinical requirements are increasingly met by technological developments which show promise to become a clinical reality. This review summarises recent advances in vibrational spectroscopy and their impact on the diagnosis of cancer.

Disease recognition by infrared and Raman spectroscopy

Infrared (IR) and Raman spectroscopy are emerging biophotonic tools to recognize various diseases. The current review gives an overview of the experimental techniques, data-classification algorithms and applications to assess soft tissues, hard tissues and body fluids. The methodology section presents the principles to combine vibrational spectroscopy with microscopy, lateral information and fiber-optic probes. A crucial step is the classification of spectral data by a variety of algorithms. We discuss unsupervised algorithms such as cluster analysis or principal component analysis and supervised algorithms such as linear discriminant analysis, soft independent modeling of class analogies, artificial neural networks support vector machines, Bayesian classification, partial least-squares regression and ensemble methods. The selected topics include tumors of epithelial tissue, brain tumors, prion diseases, bone diseases, atherosclerosis, kidney stones and gallstones, skin tumors, diabetes and osteoarthritis.

Review: Optical Micrometer Resolution Scanning for Non-invasive Grading of Precancer in the Human Uterine Cervix

Management of cervical precancer is archetypal for other cancer prevention programmes but has to consider diagnostic and logistic challenges. Numerous optical tools are emerging for non-destructive near real-time early diagnosis of precancerous lesions of the cervix. Non-destructive, real-time imaging modalities have reached pre-commercial status, but high resolution mapping tools are not yet introduced in clinical settings. The NCBI PubMed web page was searched using the keywords ‘CIN diagnosis’ and the combinations of ‘cervix {confocal, optical coherence tomography, ftir, infrared, Raman, vibrational, spectroscopy}’. Suitable titles were identified and their relevant references followed. Challenges in precancer management are discussed. The following tools capable of non-destructive high resolution mapping in a clinical environment were selected: confocal microscopy, optical coherence tomography, IR spectroscopy, and Raman spectroscopy. Findings on the clinical performance of these techniques are put into context in order to assist the reader in judging the likely performance of these methods as diagnostic tools. Rationale for carrying out research under the prospect of the HPV vaccine is given.

Raman and FTIR microscopic imaging of colon tissue: a comparative study

Colon tissue constitutes a valid model for the comparative analysis of soft tissue by Raman and Fourier transform infrared (FTIR) imaging because it contains four major tissue types such as muscle tissue, connective tissue, epithelium and nerve cells. Raman microscopic images were recorded in the mapping mode using 785 nm laser excitation and a step size of 10 microm from three regions within a thin section that encompassed mucus, mucosa, submucosa, and longitudinal and circular muscle layers. FTIR microscopic images that were composed of 4, 8 and 9 individual images of 4096 spectra each were recorded from the same regions using a FTIR spectrometer coupled to a microscope with a focal plane array detector. Furthermore, Raman microscopic images were recorded at a step size of 2.5 microm from three ganglia that belong to the myenteric plexus. The results are discussed with respect to lateral resolution, spectral resolution, acquisition time and sensitivity of both modalities.

Early spectral changes of cellular malignant transformation using Fourier transform infrared microspectroscopy

Fourier transform infrared microspectroscopy (FTIR-MSP) is potentially a powerful analytical method for identifying the spectral properties of biological activity in cells. The goal of the present research is the implementation of FTIR-MSP to study early spectral changes accompanying malignant transformation of cells. As a model system, cells in culture are infected by the murine sarcoma virus (MuSV), which induces malignant transformation. The spectral measurements are taken at various postinfection time intervals. To follow up systematically the progress of the spectral changes at early stages of cell transformation, it is essential first to determine and validate consistent and significant spectral parameters (biomarkers), which can evidently discriminate between normal and cancerous cells. Early stages of cell transformation are classified by an array of spectral biomarkers utilizing cluster analysis and discriminant classification function techniques. The classifications indicate that the first spectral changes are detectable much earlier than the first morphological signs of cell transformation. Our results point out that the first spectral signs of malignant transformation are observed on the first and third day of postinfection (PI) (for NIH/3T3 and MEF cell cultures, respectively), while the first visible morphological alterations are observed only on the third and seventh day, respectively. These results strongly support the potential of developing FTIR microspectroscopy as a simple, reagent-free method for early detection of malignancy.

Biomolecular investigation of human substantia nigra in Parkinson’s disease by synchrotron radiation Fourier transform infrared microspectroscopy

Synchrotron radiation based-Fourier transform infrared microspectroscopy was used for preliminary investigation of the chemical composition and morphologies of the human substantia nigra of brain between normal and Parkinson's diseased tissues. The studies were carried out for thin tissue sections, focusing more particularly on nerve cell bodies, that are affected in Parkinson's disease (PD). The major spectral differences between normal (control) and PD tissues were identified at the following vibrational frequencies: 2930, 2850, 1655, 1380, 1236, 1173 and 1086 cm(-1). The infrared imaging of these biochemical markers show that for control cases the protein and nucleic acids functional groups (bands at: approximately 3300, approximately 3100, approximately 1655, approximately 1545, approximately 1240, approximately 1080 cm(-1)) are located mainly in the cell body. The spatial distribution of the band at 1740 cm(-1) (ester carbonyl stretching band) is quite dissimilar to the others, while it exhibits a minimal concentration in the cell body area. Contrarily, in PD samples, no clear evidence of variation of any of the vibrational fingerprint between cell body and the surrounding was noticed. Moreover, decrease of protein to lipid ratio as well as increase of amide I/amide II ratio were observed for PD case. The preliminary results strengthen the hypothesis that PD is a multietiological disorder. Moreover, the reported results clearly indicate that, in addition to a distinct visual observation, the diseased nerve cells exhibits change of their biochemical composition. It suggests that disturbances of normal functioning of SN neurons appear before their morphological atrophy.

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

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

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.

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.

Identification of primary tumors of brain metastases by SIMCA classification of IR spectroscopic images

Brain metastases are secondary intracranial lesions which occur more frequently than primary brain tumors. The four most abundant types of brain metastasis originate from primary tumors of lung cancer, colorectal cancer, breast cancer and renal cell carcinoma. As metastatic cells contain the molecular information of the primary tissue cells and IR spectroscopy probes the molecular fingerprint of cells, IR spectroscopy based methods constitute a new approach to determine the origin of brain metastases. IR spectroscopic images of 4 by 4 mm2 tissue areas were recorded in transmission mode by a FTIR imaging spectrometer coupled to a focal plane array detector. Unsupervised cluster analysis revealed variances within each cryosection. Selected clusters of five IR images with known diagnoses trained a supervised classification model based on the algorithm soft independent modeling of class analogies (SIMCA). This model was applied to distinguish normal brain tissue from brain metastases and to identify the primary tumor of brain metastases in 15 independent IR images. All specimens were assigned to the correct tissue class. This proof-of-concept study demonstrates that IR spectroscopy can complement established methods such as histopathology or immunohistochemistry for diagnosis.