Attenuated Total Reflection Fourier-Transform Infrared Spectral Discrimination in Human Tissue of Oesophageal Transformation to Adenocarcinoma

This study presents ATR-FTIR (attenuated total reflectance Fourier-transform infrared) spectral analysis of ex vivo oesophageal tissue including all classifications to oesophageal adenocarcinoma (OAC). The article adds further validation to previous human tissue studies identifying the potential for ATR-FTIR spectroscopy in differentiating among all classes of oesophageal transformation to OAC. Tissue spectral analysis used principal component analysis quadratic discriminant analysis (PCA-QDA), successive projection algorithm quadratic discriminant analysis (SPA-QDA), and genetic algorithm quadratic discriminant analysis (GA-QDA) algorithms for variable selection and classification. The variables selected by SPA-QDA and GA-QDA discriminated tissue samples from Barrett's oesophagus (BO) to OAC with 100% accuracy on the basis of unique spectral "fingerprints" of their biochemical composition. Accuracy test results including sensitivity and specificity were determined. The best results were obtained with PCA-QDA, where tissues ranging from normal to OAC were correctly classified with 90.9% overall accuracy (71.4-100% sensitivity and 89.5-100% specificity), including the discrimination between normal and inflammatory tissue, which failed in SPA-QDA and GA-QDA. All the models revealed excellent results for distinguishing among BO, low-grade dysplasia (LGD), high-grade dysplasia (HGD), and OAC tissues (100% sensitivities and specificities). This study highlights the need for further work identifying potential biochemical markers using ATR-FTIR in tissue that could be utilised as an adjunct to histopathological diagnosis for early detection of neoplastic changes in susceptible epithelium.

A one-dimensional convolutional neural network based deep learning for high accuracy classification of transformation stages in esophageal squamous cell carcinoma tissue using micro-FTIR

Among the most frequently diagnosed cancers in developing countries, esophageal squamous cell carcinoma (ESCC) ranks among the top six causes of death. It would be beneficial if a rapid, accurate, and automatic ESCC diagnostic method could be developed to reduce the workload of pathologists and improve the effectiveness of cancer treatments. Using micro-FTIR spectroscopy, this study classified the transformation stages of ESCC tissues. Based on 6,352 raw micro-FTIR spectra, a one-dimensional convolutional neural network (1D-CNN) model was constructed to classify-five stages. Based on the established model, more than 93% accuracy was achieved at each stage, and the accuracy of identifying proliferation, low grade neoplasia, and ESCC cancer groups was achieved 99% for the test dataset. In this proof-of-concept study, the developed method can be applied to other diseases in order to promote the use of FTIR spectroscopy in cancer pathology.

Rapid and sensitive detection of esophageal cancer by FTIR spectroscopy of serum and plasma

Fourier transform infrared (FTIR) spectroscopy, as a platform technology for cancer detection, must be up to the challenge of clinical transformation. To this end, detection of esophageal squamous cell carcinoma (ESCC) was hereby explored using serum and plasma scrape-coated on barium fluoride (BaF₂) disk by transmission FTIR method, and the classification model was built using six multivariate statistical analyses, including support vector machine (SVM), principal component linear discriminant analysis (PC-LDA), decision tree (DT), k-nearest neighbor (KNN) classification, ensemble algorithms (EA) and partial least squares for discriminant analysis (PLS-DA). All statistical analyses methods demonstrated that late-stage cancer could be well classified from healthy people employing either serum or plasma with different anticoagulants. Resulting PC-LDA model differentiated late-stage cancer from normal group with an accuracy of 99.26%, a sensitivity of 98.53%, and a specificity of 100%. The accuracy and sensitivity reached 97.08% and 91.43%, respectively for early-stage cancer discrimination from normal group. This pilot exploration demonstrated that transmission FTIR provided a rapid, cost effective and sensitive method for ESCC diagnosis using either serum or plasma.

Tracking the Oxygen Dynamics of Solid-Liquid Electrochemical Interfaces by Correlative In Situ Synchrotron Spectroscopies

ConspectusOxygen-involved electrocatalytic processes, including the oxygen evolution reaction (OER) and oxygen reduction reaction (ORR), are central to a series of advanced modern energy and conversion technologies, such as water electrolyzers, fuel cells, and CO₂ reduction or N₂ fixation devices. A comprehensive and in-depth understanding of the charge transfer and energy conversion process that ubiquitously occurs over solid-liquid electrochemical interfaces during oxygen electrocatalysis is crucial for understanding the key essence of oxygen-related electrochemistry. The huge challenges for dynamic studies over solid-liquid interfaces during oxygen electrocatalysis lie in the all-embracing electrochemical processes of the catalytic reactions, associated with both structural and reactive intermediates evolution on the electrode surface, and in the significant influence of the aqueous environments of electrolytes used. Hence, overcoming these challenges intrinsically calls for a great cooperation of multiple cutting-edge in situ technologies. Synchrotron radiation (SR) X-ray absorption fine structure (SR-XAFS) spectroscopy is highly sensitive to the local atomic structure of nanomaterials, and SR-based Fourier transform infrared (SR-FTIR) spectroscopy features unique molecular fingerprint identification to determine active species on the surface of electrodes. One can imagine that the correlative in situ SR-XAFS/FTIR spectroscopic investigations will potentially provide sufficient, reliable, and complementary information at the atomic/molecular level to depict vivid and comprehensive "dynamic movies" of solid-liquid electrochemical interfaces during oxygen electrocatalysis, which will help effectively promote/simplify the complicated screening process of advanced oxygen electrocatalysts for efficient high-energy-density energy systems.In this Account, starting with some fundamentals of SR-based spectroscopic technologies, tips for obtaining high-quality SR-XAFS and SR-FTIR spectroscopy results during the electrocatalytic process are comprehensively specified. Subsequently, the latest research achievements of dynamic investigations mainly from our group based on in situ SR-XAFS and/or SR-FTIR spectroscopies will be systematically scrutinized and properly emphasized in detail, where the currently attractive metal-organic-framework (MOF) nanomaterials and single-atom catalysts (SACs) are selected as the main object of research. Moreover, the vital contributions of correlative in situ SR-XAFS/FTIR studies on new discoveries of the dynamic evolution of solid-liquid interfaces during oxygen electrocatalysis are highlighted. In particular, our pioneering research found that the potential-dependent dynamically coupled oxygen formed in the precatalytic stage was a very useful promoter in SACs to promote efficient OER kinetics under acidic conditions. In addition, the in situ generated metastable Ni₁-N₂ centers with more structural degrees of freedom in SACs could potentially facilitate the fast 4e^- ORR kinetics. This Account is anticipated to stimulate broad interest in dynamic explorations in various catalytic processes of interest in the material science and electrochemistry communities using correlative SR-based technologies.

Disposable Coverslip for Rapid Throughput Screening of Malaria Using Attenuated Total Reflection Spectroscopy

Malaria is considered to be one of the most catastrophic health issues in the whole world. Vibrational spectroscopy is a rapid, robust, label-free, inexpensive, highly sensitive, nonperturbative, and nondestructive technique with high diagnostic potential for the early detection of disease agents. In particular, the fingerprinting capability of attenuated total reflection spectroscopy is promising as a point-of-care diagnostic tool in resource-limited areas. However, improvements are required to expedite the measurements of biofluids, including the drying procedure and subsequent cleaning of the internal reflection element to enable high throughput successive measurements. As an alternative, we propose using an inexpensive coverslip to reduce the sample preparation time by enabling multiple samples to be collectively dried together under the same temperature and conditions. In conjunction with partial least squares regression, attenuated total reflection spectroscopy was able to detect and quantify the parasitemia with root mean square error of cross-validation and R² values of 0.177 and 0.985, respectively. Here, we characterize an inexpensive, disposable coverslip for the high throughput screening of malaria parasitic infections and thus demonstrate an alternative approach to direct deposition of the sample onto the internal reflection element.

Translation of an esophagus histopathological FT-IR imaging model to a fast quantum cascade laser modality

The technical progress in fast quantum cascade laser (QCL) microscopy offers a platform where chemical imaging becomes feasible for clinical diagnostics. QCL systems allow the integration of previously developed FT-IR-based pathology recognition models in a faster workflow. The translation of such models requires a systematic approach, focusing only on the spectral frequencies that carry crucial information for discrimination of pathologic features. In this study, we optimize an FT-IR-based histopathological method for esophageal cancer detection to work with a QCL system. We explore whether the classifier's performance is affected by paraffin presence from tissue blocks compared to removing it chemically. Working with paraffin-embedded samples reduces preprocessing time in the lab and allows samples to be archived after analysis. Moreover, we test, whether the creation of a QCL model requires a preestablished FTIR model or can be optimized using solely QCL measurements.

Attenuated total reflection Fourier-transform infrared spectral discrimination in human bodily fluids of oesophageal transformation to adenocarcinoma

Attenuated total reflection Fourier-transform infrared spectroscopy (ATR-FTIR) of biofluids was used to detect oesophageal stages through to oesophageal adenocarcinoma.

Rapid infrared mapping for highly accurate automated histology in Barrett's oesophagus

Barrett's oesophagus (BE) is a premalignant condition that can progress to oesophageal adenocarcinoma. Endoscopic surveillance aims to identify potential progression at an early, treatable stage, but generates large numbers of tissue biopsies. Fourier transform infrared (FTIR) mapping was used to develop an automated histology tool for detection of BE and Barrett's neoplasia in tissue biopsies. 22 oesophageal tissue samples were collected from 19 patients. Contiguous frozen tissue sections were taken for pathology review and FTIR imaging. 45 mid-IR images were measured on an Agilent 620 FTIR microscope with an Agilent 670 spectrometer. Each image covering a 140 μm × 140 μm region was measured in 5 minutes, using a 1.1 μm² pixel size and 64 scans per pixel. Principal component fed linear discriminant analysis was used to build classification models based on spectral differences, which were then tested using leave-one-sample-out cross validation. Key biochemical differences were identified by their spectral signatures: high glycogen content was seen in normal squamous (NSQ) tissue, high glycoprotein content was observed in glandular BE tissue, and high DNA content in dysplasia/adenocarcinoma samples. Classification of normal squamous samples versus 'abnormal' samples (any stage of Barrett's) was performed with 100% sensitivity and specificity. Neoplastic Barrett's (dysplasia or adenocarcinoma) was identified with 95.6% sensitivity and 86.4% specificity. Highly accurate pathology classification can be achieved with FTIR measurement of frozen tissue sections in a clinically applicable timeframe.

Retinal oxidative stress at the onset of diabetes determined by synchrotron FTIR widefield imaging: towards diabetes pathogenesis

Diabetic retinopathy is a microvascular complication of diabetes that can lead to blindness. In the present study, we aimed to determine the nature of diabetes-induced, highly localized biochemical changes in the neuroretina at the onset of diabetes. High-resolution synchrotron Fourier transform infrared (s-FTIR) wide field microscopy coupled with multivariate analysis (PCA-LDA) was employed to identify biomarkers of diabetic retinopathy with spatial resolution at the cellular level. We compared the retinal tissue prepared from 6-week-old Ins2^Akita/+ heterozygous (Akita/+, N = 6; a model of diabetes) male mice with the wild-type (control, N = 6) mice. Male Akita/+ mice become diabetic at 4-weeks of age. Significant differences (P < 0.001) in the presence of biomarkers associated with diabetes and segregation of spectra were achieved. Differentiating IR bands attributed to nucleic acids (964, 1051, 1087, 1226 and 1710 cm^-1), proteins (1662 and 1608 cm^-1) and fatty acids (2854, 2923, 2956 and 3012 cm^-1) were observed between the Akita/+ and the WT samples. A comparison between distinctive layers of the retina, namely the photoreceptor retinal layer (PRL), outer plexiform layer (OPL), inner nucleus layer (INL) and inner plexiform layer (IPL) suggested that the photoreceptor layer is the most susceptible layer to oxidative stress in short-term diabetes. Spatially-resolved chemical images indicated heterogeneities and oxidative-stress induced alterations in the diabetic retina tissue morphology compared with the WT retina. In this study, the spectral biomarkers and the spatial biochemical alterations in the diabetic retina and in specific layers were identified for the first time. We believe that the conclusions drawn from these studies will help to bridge the gap in our understanding of the molecular and cellular mechanisms that contribute to the pathobiology of diabetic retinopathy.

Automated cytological detection of Barrett's neoplasia with infrared spectroscopy

BACKGROUND

Development of a nonendoscopic test for Barrett's esophagus would revolutionize population screening and surveillance for patients with Barrett's esophagus. Swallowed cell collection devices have recently been developed to obtain cytology brushings from the esophagus: automated detection of neoplasia in such samples would enable large-scale screening and surveillance.

METHODS

Fourier transform infrared (FTIR) spectroscopy was used to develop an automated tool for detection of Barrett's esophagus and Barrett's neoplasia in esophageal cell samples. Cytology brushings were collected at endoscopy, cytospun onto slides and FTIR images were measured. An automated cell recognition program was developed to identify individual cells on the slide.

RESULTS

Cytology review and contemporaneous histology was used to inform a training dataset containing 141 cells from 17 patients. A classification model was constructed by principal component analysis fed linear discriminant analysis, then tested by leave-one-sample-out cross validation. With application of this training model to whole slide samples, a threshold voting system was used to classify samples according to their constituent cells. Across the entire dataset of 115 FTIR maps from 66 patients, whole samples were classified with sensitivity and specificity respectively as follows: normal squamous cells 79.0% and 81.1%, nondysplastic Barrett's esophagus cells 31.3% and 100%, and neoplastic Barrett's esophagus cells 83.3% and 62.7%.

CONCLUSIONS

Analysis of esophageal cell samples can be performed with FTIR spectroscopy with reasonable sensitivity for Barrett's neoplasia, but with poor specificity with the current technique.

FTIR spectroscopic imaging and mapping with correcting lenses for studies of biological cells and tissues

Histopathology of tissue samples is used to determine the progression of cancer usually by staining and visual analysis. It is recognised that disease progression from healthy tissue to cancerous is accompanied by spectral signature changes in the mid-infrared range. In this work, FTIR spectroscopic imaging in transmission mode using a focal plane array (96 × 96 pixels) has been applied to the characterisation of Barrett's oesophageal adenocarcinoma. To correct optical aberrations, infrared transparent lenses were used of the same material (CaF₂) as the slide on which biopsies were fixed. The lenses acted as an immersion objective, reducing scattering and improving spatial resolution. A novel mapping approach using a sliding lens is presented where spectral images obtained with added lenses are stitched together such that the dataset contained a representative section of the oesophageal tissue. Images were also acquired in transmission mode using high-magnification optics for enhanced spatial resolution, as well as with a germanium micro-ATR objective. The reduction of scattering was assessed using k-means clustering. The same tissue section map, which contained a region of high grade dysplasia, was analysed using hierarchical clustering analysis. A reduction of the trough at 1077 cm⁻¹ in the second derivative spectra was identified as an indicator of high grade dysplasia. In addition, the spatial resolution obtained with the lens using high-magnification optics was assessed by measurements of a sharp interface of polymer laminate, which was also compared with that achieved with micro ATR-FTIR imaging. In transmission mode using the lens, it was determined to be 8.5 μm and using micro-ATR imaging, the resolution was 3 μm for the band at a wavelength of ca. 3 μm. The spatial resolution was also assessed with and without the added lens, in normal and high-magnification modes using a USAF target. Spectroscopic images of cells in transmission mode using two lenses are also presented, which are necessary for correcting chromatic aberration and refraction in both the condenser and objective. The use of lenses is shown to be necessary for obtaining high-quality spectroscopic images of cells in transmission mode and proves the applicability of the pseudo hemisphere approach for this and other microfluidic systems.

Label-free phenotyping of peripheral blood lymphocytes by infrared imaging

It is now widely accepted that the immune microenvironment of tumors and more precisely Tumor Infiltrating Lymphocytes (TIL) play an important role in cancer development and outcome. TILs are considered to be important prognostic and predictive factors based on a growing body of clinical evidence; however, their presence at the tumor site is not currently assessed routinely. FTIR (Fourier transform infrared) imaging has proven it has value in studying a range of tumors, particularly for characterizing tumor cells. Currently, very little is known about the potential for FTIR imaging to characterize TIL. The present proof of concept study investigates the ability of FTIR imaging to identify the principal lymphocyte subpopulations present in human peripheral blood (PB). A negative cell isolation method was employed to select pure, label-free, helper T cells (CD4(+)), cytotoxic T cells (CD8(+)) and B cells (CD19(+)) from six healthy donors PB by Fluorescence Activated Cell Sorting (FACS). Cells were centrifuged onto Barium Fluoride windows and ten infrared images were recorded for each lymphocyte subpopulation from all six donors. After spectral pre-treatment, statistical analyses were performed. Unsupervised Principal Component Analyses (PCA) revealed that in the absence of donor variability, CD4(+) T cells, CD8(+) T cells and B cells each display distinct IR spectral features. Supervised Partial Least Square Discriminant Analyses (PLS-DA) demonstrated that the differences between the three lymphocyte subpopulations are reflected in their IR spectra, permitting their individual identification even when significant donor variability is present. Our results also show that a distinct spectral signature is associated with antibody binding. To our knowledge this is the first study reporting that FTIR imaging can effectively identify T and B lymphocytes and differentiate helper T cells from cytotoxic T cells. This proof of concept study demonstrates that FTIR imaging is a reliable tool for the identification of lymphocyte subpopulations and has the potential for use in characterizing TIL.

Method for identification of spectral targets in discrete frequency infrared spectroscopy for clinical diagnostics

Spectroscopic imaging with discrete frequency infrared (DF-IR) has the potential to have a major impact on the clinical utility of IR imaging techniques for biochemical detection of disease. This can be achieved in real time using imaging at selected wavenumbers tuned to molecular absorptions of interest enabling tissue and disease-specific contrast to be obtained from the sample. However, selecting the appropriate wavenumbers to measure for DF-IR is critical, since vital diagnostic information could be missed. Here we demonstrate the application of partial least squares discriminant analysis (PLS-DA) and variable importance for projection (VIP) to identify key diagnostic wavenumber targets for the detection of dysplasia in human colon polyp sections. A small dataset, including 41 regions of interest (25 benign, 16 dysplastic; 5175 spectra in total), was selected from Fourier transform infrared (FT-IR) images of human colon polyp sections. PLS-DA was used to differentiate between benign and cancerous human colon polyp sections (sensitivity 95%, specificity 93% cross-validated), and VIP scores were calculated for all wavenumbers. A second PLS-DA model was then calculated using only variables that VIP identified as significant, reducing the number of wavenumbers to ~25% of the full dataset. The resulting cross-validated sensitivity and specificity (93 and 90%, respectively) indicate that the VIP method selects the key diagnostic wavenumbers for this dataset. Finally, a robust subset of variables was identified by selecting wavenumbers that exceeded the minimum VIP score in >95% of our validation iterations. A cross-validated PLS-DA model using only the robustly selected wavenumber targets (~20% of the original wavenumbers) resulted in sensitivity and specificity of 91 and 82%, respectively, indicating that PLS-DA and VIP are suitable approaches for the selection of wavenumber targets in DF-IR.

Real-time metabolic analysis of living cancer cells with correlated cellular spectro-microscopy

In recent years, major efforts have been devoted to the application of microscopy with mid-infrared light to the study of living cells and tissue. Despite this interest, infrared (IR) microscopy has not realized its full potential in the molecular characterization of living systems. This is partly due to the fact that current approaches for data mining and analysis of IR absorption spectra have not evolved comparably to measurement technology and are not up to the interpretation of the complex spectra of living systems such as cells and tissue. In this work we show that the use of two-dimensional correlation spectroscopy coupled to IR absorption spectro-microscopy allows us to extract the spectral components of individual metabolites from time-resolved IR spectra of living cells. We call this method correlated cellular spectro-microscopy, and we implement it in the study of the glycolytic metabolism of cancer cells. We show that the method can detect intermediates of the glycolytic pathway, quantify their rate of formation, and correlate this with variations in pH, all in a single measurement. We propose the method as a useful tool for the quantitative description of metabolic processes in living cells and for the validation of drug candidates aimed at suppressing glycolysis in cancer cells.

Transmission FT-IR chemical imaging on glass substrates: applications in infrared spectral histopathology

Fourier transform-infrared (FT-IR) chemical imaging in transmission mode has traditionally been performed on expensive mid-IR transparent windows such as barium/calcium fluoride, which are more fragile than glass, making preparation in the histopathology laboratories more cumbersome. A solution is presented here by using cheap glass substrates for the FT-IR chemical imaging, which has a high-wavenumber transmission window allowing measurement of the C-H, N-H, and O-H stretches occurring at ca. 2500-3800 cm(-1). The "fingerprint" region of the IR spectrum occurring below 1800 cm(-1) is not obtainable; however, we demonstrate that a wealth of information is contained in the high wavenumber range using 71 patients on a breast tissue microarray (TMA) as a model for investigation. Importantly, we demonstrate that the tissue can be classified into four basic tissue cell types and that using just the epithelial cells, reasonable discrimination of normal and malignant tissue can be found.

Breast cancer and melanoma cell line identification by FTIR imaging after formalin-fixation and paraffin-embedding

Over the past few decades, Fourier transform infrared (FTIR) spectroscopy coupled to microscopy has been recognized as an emerging and potentially powerful tool in cancer research and diagnosis. For this purpose, histological analyses performed by pathologists are mostly carried out on biopsied tissue that undergoes the formalin-fixation and paraffin-embedding (FFPE) procedure. This processing method ensures an optimal and permanent preservation of the samples, making FFPE-archived tissue an extremely valuable source for retrospective studies. Nevertheless, as highlighted by previous studies, this fixation procedure significantly changes the principal constituents of cells, resulting in important effects on their infrared (IR) spectrum. Despite the chemical and spectral influence of FFPE processing, some studies demonstrate that FTIR imaging allows precise identification of the different cell types present in biopsied tissue, indicating that the FFPE process preserves spectral differences between distinct cell types. In this study, we investigated whether this is also the case for closely related cell lines. We analyzed spectra from 8 cancerous epithelial cell lines: 4 breast cancer cell lines and 4 melanoma cell lines. For each cell line, we harvested cells at subconfluence and divided them into two sets. We first tested the "original" capability of FTIR imaging to identify these closely related cell lines on cells just dried on BaF2 slides. We then repeated the test after submitting the cells to the FFPE procedure. Our results show that the IR spectra of FFPE processed cancerous cell lines undergo small but significant changes due to the treatment. The spectral modifications were interpreted as a potential decrease in the phospholipid content and protein denaturation, in line with the scientific literature on the topic. Nevertheless, unsupervised analyses showed that spectral proximities and distances between closely related cell lines were mostly, but not entirely, conserved after FFPE processing. Finally, PLS-DA statistical analyses highlighted that closely related cell lines are still successfully identified and efficiently distinguished by FTIR spectroscopy after FFPE treatment. This last result paves the way towards identification and characterization of cellular subtypes on FFPE tissue sections by FTIR imaging, indicating that this analysis technique could become a potential useful tool in cancer research.

Substrate contributions in micro-ATR of thin samples: implications for analysis of cells, tissue and biological fluids

Low-e microscope slides are a common substrate for biological samples. Typically they are used for transflection infrared microspectroscopy but increasingly they are also being used for micro-ATR experiments since it is assumed that the FTIR-ATR absorbance spectra of cells and tissue on low-e substrates will not contain any spectral contributions from the substrate materials. This, in part, is due to the expectation that all the infrared light will be reflected at the highly reflective surface. At low sample thicknesses, however (e.g. less than 2 μm) the electric field does indeed penetrate through the substrate layers and undergoes absorption, from the glass supporting layer making up the majority of the slide. In this paper we show experimental evidence of the substrate contributions in ATR spectra and also a theoretical model giving insight into the spectral contributions of the substrate as a function of sample thickness.

The inherent problem of transflection-mode infrared spectroscopic microscopy and the ramifications for biomedical single point and imaging applications

Transflection-mode FTIR spectroscopy has become a popular method of measuring spectra from biomedical and other samples due to the relative low cost of substrates compared to transmission windows, and a higher absorbance due to a double pass through the same sample approximately doubling the effective path length. In this publication we state an optical description of samples on multilayer low-e reflective substrates. Using this model we are able to explain in detail the so-called electric-field standing wave effect and rationalise the non-linear change in absorbance with sample thickness. The ramifications of this non-linear change, for imaging and classification systems, where a model is built from tissue sectioned at a particular thickness and compared with tissue of a different thickness are discussed. We show that spectra can be distorted such that classification fails leading to inaccurate tissue segmentation which may have subsequent implications for disease diagnostics applications.

Biological applications of synchrotron radiation infrared spectromicroscopy

Extremely brilliant infrared (IR) beams provided by synchrotron radiation sources are now routinely used in many facilities with available commercial spectrometers coupled to IR microscopes. Using these intense non-thermal sources, a brilliance two or three order of magnitude higher than a conventional source is achievable through small pinholes (<10 μm) with a high signal to-noise ratio. IR spectroscopy is a powerful technique to investigate biological systems and offers many new imaging opportunities. The field of infrared biological imaging covers a wide range of fundamental issues and applied researches such as cell imaging or tissue imaging. Molecular maps with a spatial resolution down to the diffraction limit may be now obtained with a synchrotron radiation IR source also on thick samples. Moreover, changes of the protein structure are detectable in an IR spectrum and cellular molecular markers can be identified and used to recognize a pathological status of a tissue. Molecular structure and functions are strongly correlated and this aspect is particularly relevant for imaging. We will show that the brilliance of synchrotron radiation IR sources may enhance the sensitivity of a molecular signal obtained from small biosamples, e.g., a single cell, containing extremely small amounts of organic matter. We will also show that SR IR sources allow to study chemical composition and to identify the distribution of organic molecules in cells at submicron resolution is possible with a high signal-to-noise ratio. Moreover, the recent availability of two-dimensional IR detectors promises to push forward imaging capabilities in the time domain. Indeed, with a high current synchrotron radiation facility and a Focal Plane Array the chemical imaging of individual cells can be obtained in a few minutes. Within this framework important results are expected in the next years using synchrotron radiation and Free Electron Laser (FEL) sources for spectro-microscopy and spectral-imaging, alone or in combination with Scanning Near-field Optical Microscopy methods to study the molecular composition and dynamic changes in samples of biomedical interest at micrometric and submicrometric scales, respectively.