Classification of healthy and cancerous colon cells by Fourier transform infrared spectroscopy

Colorectal cancer is one of the most diagnosed types of cancer in developed countries. Current diagnostic methods are partly dependent on pathologist experience and laboratories instrumentation. In this study, we used Fourier Transform Infrared (FTIR) spectroscopy in transflection mode, combined with Principal Components Analysis followed by Linear Discriminant Analysis (PCA-LDA) and Partial Least Squares - Discriminant Analysis (PLS-DA), to build a classification algorithm to diagnose colon cancer in cell samples, based on absorption spectra measured in two spectral ranges of the mid-infrared spectrum. In particular, PCA technique highlights small biochemical differences between healthy and cancerous cells: these are related to the larger lipid content in the former compared with the latter and to the larger relative amount of protein and nucleic acid components in the cancerous cells compared with the healthy ones. Comparison of the classification accuracy of PCA-LDA and PLS-DA methods applied to FTIR spectra measured in the 1000-1800 cm-1 (low wavenumber range, LWR) and 2700-3700 cm-1 (high wavenumber range, HWR) remarks that both algorithms are able to classify hidden class FTIR spectra with excellent accuracy (100 %) in both spectral regions. This is a hopeful result for clinical translation of infrared spectroscopy: in fact, it makes reliable the predictions obtained using FTIR measurements carried out only in the HWR, in which the glass slides used in clinical laboratories are transparent to IR radiation.

Phasor Representation Approach for Rapid Exploratory Analysis of Large Infrared Spectroscopic Imaging Data Sets

Infrared (IR) spectroscopic imaging is potentially useful for digital histopathology as it provides spatially resolved molecular absorption spectra, which can subsequently yield useful information by powerful artificial intelligence methods. A typical analysis pipeline in using IR imaging data for chemical pathology often involves iterative processes of segmentation, evaluation, and analysis that necessitate rapid data exploration. Here, we present a fast, reliable, and intuitive method based on a phasor representation of spectra and discuss its unique applicability for IR imaging data. We simulate different features extant in IR spectra and discuss their influence on the phasor waveforms; similarly, we undertake IR image analysis in the transform space to understand spectral similarity and variance. We demonstrate the potential of phasor analysis for biomedical tissue imaging using a variety of samples, using fresh frozen surgical prostate resections and formalin-fixed paraffin-embedded breast cancer tissue microarray samples as model systems that span common histopathology practice. To demonstrate further generalizability of this approach, we apply the method to data from different experimental conditions─including standard (5.5 μm × 5.5 μm pixel size) and high-definition (1.1 μm × 1.1 μm pixel size) Fourier transform IR (FTIR) spectroscopic imaging using transmission and transflection modes. Quantitative segmentation results from our approach are compared to previous studies, showing good agreement and quick visualization. The presented method is rapid, easy to use, and highly capable of deciphering compositional differences, presenting a convenient tool for exploratory analysis of IR imaging data.

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.

Mid-infrared multispectral confocal microscope using off-axis parabolic mirrors to study epiretinal membranes

Mid-infrared (mid-IR) multispectral microscopy, especially operating at the wavelength of 5-11 µm, is an effective tool for detecting, identifying, and quantifying the structure and composition of biological tissues. Compared with that based on the optical lens, the mid-infrared microscope composed of off-axis parabolic (OAP) mirrors is low cost, simple, and suitable for longer range of wavelength without chromatic aberrations, while keeping the optical transmission efficiency. Here we report a compact and versatile mid-infrared multispectral confocal microscope based on off-axis parabolic mirrors. We also perform numerical calculations based on the vectorial diffraction theory on OAP mirrors and analyze the typical aberrations and misalignment of the OAP-based optical system. Finally, we perform multispectral imaging of the epiretinal membrane of the human eyes with the spectrum selected according to its resonance absorption peak. The system is designed to perform multispectral or even hyperspectral imaging to identify and predict potential disease.

Multiplexed Fourier Transform Infrared and Raman Imaging

Infrared (IR) and Raman spectroscopies are being increasingly employed for the label-free analysis of biochemical samples. Both are vibrational imaging techniques, but they provide complementary information about the chemical composition of the sample, and thus the integration of Raman and IR images leads to a comprehensive understanding of the samples. Here, we summarize the steps needed for performing multiplexed infrared and Raman imaging, identifying and overcoming the two main challenges: first, the technical difficulties caused by the incompatibilities of the techniques and, second, the necessity to extract the information from the large number of vibrational variables found in both IR and Raman spectra.

Infrared Spectroscopy of Blood

The magnitude of infectious diseases in the twenty-first century created an urgent need for point-of-care diagnostics. Critical shortages in reagents and testing kits have had a large impact on the ability to test patients with a suspected parasitic, bacteria, fungal, and viral infections. New point-of-care tests need to be highly sensitive, specific, and easy to use and provide results in rapid time. Infrared spectroscopy, coupled to multivariate and machine learning algorithms, has the potential to meet this unmet demand requiring minimal sample preparation to detect both pathogenic infectious agents and chronic disease markers in blood. This focal point article will highlight the application of Fourier transform infrared spectroscopy to detect disease markers in blood focusing principally on parasites, bacteria, viruses, cancer markers, and important analytes indicative of disease. Methodologies and state-of-the-art approaches will be reported and potential confounding variables in blood analysis identified. The article provides an up to date review of the literature on blood diagnosis using infrared spectroscopy highlighting the recent advances in this burgeoning field.

Detection of Glycine as a Model Protein in Blood Serum Using 2D-IR Spectroscopy

Glycine (Gly) is used as a model system to evaluate the ability of ultrafast two-dimensional infrared (2D-IR) spectroscopy to detect and quantify the low-molecular-weight proteinaceous components of blood serum. Combining data acquisition schemes to suppress absorption bands of H₂O that overlap with the protein amide I band with analysis of peak patterns appearing in the off-diagonal region of the 2D-IR spectrum allows separation of the Gly spectral signature from that of the dominant protein fraction of serum in a transmission-mode 2D-IR measurement without any sample manipulation, e.g., filtration or drying. 2D-IR spectra of blood serum samples supplemented with varying concentrations of Gly were obtained, and a range of data analysis methods compared, leading to a detection limit of ∼3 mg/mL for Gly. The reported methodology provides a platform for a critical assessment of the sensitivity of 2D-IR for measuring the concentrations of amino acids, peptides, and low-molecular-weight proteins present in serum samples. We conclude that, in the case of several clinically relevant diagnostic molecules and their combinations, the potential exists for 2D-IR to complement IR absorption methods as the benefits of the second frequency dimension offered by 2D-IR spectroscopy outweigh the added technical complexity of the measurement.

FT-IR Transflection Micro-Spectroscopy Study on Normal Human Breast Cells after Exposure to a Proton Beam

Fourier transform infrared micro-spectroscopy (μ-FT-IR) is nowadays considered a valuable tool for investigating the changes occurring in human cells after exposure to ionizing radiation. Recently, considerable attention has been devoted to the use of this optical technique in the study of cells exposed to proton beams, that are being increasingly adopted in cancer therapy. Different experimental configurations are used for proton irradiation and subsequent spectra acquisition. To facilitate the use of μ-FT-IR, it may be useful to investigate new experimental approaches capable of speeding up and simplifying the irradiation and measurements phases. Here, we propose the use of low-e-substrates slides for cell culture, allowing the irradiation and spectra acquisition in transflection mode in a fast and direct way. In recent years, there has been a wide debate about the validity of these supports, but many researchers agree that the artifacts due to the presence of the electromagnetic standing wave effects are negligible in many practical cases. We investigated human normal breast cells (MCF-10 cell line) fixed immediately after the irradiation with graded proton radiation doses (0, 0.5, 2, and 4 Gy). The spectra obtained in transflection geometry showed characteristics very similar to those present in the spectra acquired in transmission geometry and confirm the validity of the chosen approach. The analysis of spectra indicates the occurrence of significant changes in DNA and lipids components of cells. Modifications in protein secondary structure are also evidenced.

Multimodal Chemical Analysis of the Brain by High Mass Resolution Mass Spectrometry and Infrared Spectroscopic Imaging

The brain functions through chemical interactions between many different cell types, including neurons and glia. Acquiring comprehensive information on complex, heterogeneous systems requires multiple analytical tools, each of which have unique chemical specificity and spatial resolution. Multimodal imaging generates complementary chemical information via spatially localized molecular maps, ideally from the same sample, but requires method enhancements that span from data acquisition to interpretation. We devised a protocol for performing matrix-assisted laser desorption/ionization (MALDI)-Fourier transform ion cyclotron resonance-mass spectrometry imaging (MSI), followed by infrared (IR) spectroscopic imaging on the same specimen. Multimodal measurements from the same tissue provide precise spatial alignment between modalities, enabling more advanced image processing such as image fusion and sharpening. Performing MSI first produces higher quality data from each technique compared to performing IR imaging before MSI. The difference is likely due to fixing the tissue section during MALDI matrix removal, thereby preventing analyte degradation occurring during IR imaging from an unfixed specimen. Leveraging the unique capabilities of each modality, we utilized pan sharpening of MS (mass spectrometry) ion images with selected bands from IR spectroscopy and midlevel data fusion. In comparison to sharpening with histological images, pan sharpening can employ a plethora of IR bands, producing sharpened MS images while retaining the fidelity of the initial ion images. Using Laplacian pyramid sharpening, we determine the localization of several lipids present within the hippocampus with high mass accuracy at 5 μm pixel widths. Further, through midlevel data fusion of the imaging data sets combined with k-means clustering, the combined data set discriminates between additional anatomical structures unrecognized by the individual imaging approaches. Significant differences between molecular ion abundances are detected between relevant structures within the hippocampus, such as the CA1 and CA3 regions. Our methodology provides high quality multiplex and multimodal chemical imaging of the same tissue sample, enabling more advanced data processing and analysis routines.

Assessment of discriminant models in infrared imaging using constrained repeated random sampling - Cross validation

Infrared (IR) imaging is an emerging and powerful approach for studying the molecular composition of cells and tissues. It is a non-destructive and phenotypic technique which combines label-free molecular specific information from cells and tissues provided by IR with spatial resolution, offering great potential in biochemical and biomedical research and routine applications. The application of multivariate discriminant analysis using bilinear models such as Partial Least Squares-Discriminant Analysis (PLS-DA) to IR images requires to unfold the spatial directions in a two-way matrix, resulting in a loss of spatial information and structure. In this article, first we evidence that internal validation methods such as repeated k-fold cross-validation (CV) can be overly optimistic when the pixel size of the image is lower than the lateral spatial resolution. Secondly, we propose a new approach for the unbiased internal evaluation of the model performance named COnstrained Repeated Random Subsampling-Cross Validation (CORRS-CV). This method is based on the generation of q training and test sub-sets using a constrained random sampling of n training pixels without replacement and it circumvents overly optimistic effects due to oversampling, providing more accurate and robust images. The approach can be applied in IR microscopy for the development of discriminant models to analyse underlying biochemical differences associated to anatomical and histopathological features in cells and tissues.

FT-IR Spectroscopic Imaging of Endothelial Cells Response to Tumor Necrosis Factor-α: To Follow Markers of Inflammation Using Standard and High-Magnification Resolution

Two endothelial cell lines were selected as models to investigate an effect of incubation with cytokine tumor necrosis factor type α (TNF-α) using Fourier transform infrared (FT-IR) imaging spectroscopy. Both cell lines are often used in laboratories and are typical lung vascular endothelial cells (HMLVEC) derived from the fusion of umbilical vein endothelial cells with lung adenocarcinoma cells (EA.hy926). This study was focused on alteration of spectral changes accompanying inflammation at the cellular level by applying two resolution systems of FT-IR microscopy. The standard approach, with a pixel size of ca. 5.5 μm², determined the inflammatory state of the whole cell, while a high-magnification resolution (pixel size of ca. 1.1 μm²) provided information at the subcellular level. Importantly, the analysis of IR spectra recorded with different modes produced similar results overall and yielded unambiguous classification of inflamed cells. Generally, the most significant changes in the cells under the influence of TNF-α are related with lipids-their composition and concentration; however, segregation of cells into subcellular compartments provided an additional insight into proteins and nucleic acids related events. The observed spectral alterations are specific for the type of endothelial cell line.

Electric field standing wave effects in internal reflection and ATR spectroscopy

We investigate electric field standing wave effects in the system semiinfinite incidence medium with high index of refraction/layer/vacuum, the latter being the semiinfinite exit medium. If the layer has a lower index of refraction than the incidence medium, then very strong resonances occur between the two critical angles of the system defined by the systems incidence medium/layer and incidence medium/vacuum, as the layer is then a cavity. In particular close to the lower critical angles, the evanescent fields extend strongly into the exit medium. Based on this effect we suggest two new spectroscopic modalities, namely interference-enhanced internal reflection Raman spectroscopy and interference-enhanced attenuated total reflection infrared spectroscopy.

The electric field standing wave effect in infrared transflection spectroscopy

We show that an electric field standing wave effect is responsible for the oscillations and the non-linear dependence of the absorbance on the layer thickness in thin layers on a reflective surface. This effect is connected to the occurrence of interference inside these layers. Consequently, the absorptance undergoes a maximum electric field intensity enhancement at spectral positions close to those where corresponding non-absorbing layers on a metal show minima in the reflectance. The effect leads to changes of peak maxima ratios with layer thickness and shows the same periodicity as oscillations in the peak positions. These peculiarities are fully based on and described by Maxwell's equations but cannot be understood and described if the strongly simplifying model centered on reflectance absorbance is employed.

Removing interference-based effects from the infrared transflectance spectra of thin films on metallic substrates: a fast and wave optics conform solution

We provide a formalism that is able to correct electric field standing wave “artifacts” in infrared transflection spectra.

Spectroscopic imaging of biomaterials and biological systems with FTIR microscopy or with quantum cascade lasers

Spectroscopic imaging of biomaterials and biological systems has received increased interest within the last decade because of its potential to aid in the detection of disease using biomaterials/biopsy samples and to probe the states of live cells in a label-free manner. The factors behind this increased attention include the availability of improved infrared microscopes and systems that do not require the use of a synchrotron as a light source, as well as the decreasing costs of these systems. This article highlights the current technical challenges and future directions of mid-infrared spectroscopic imaging within this field. Specifically, these are improvements in spatial resolution and spectral quality through the use of novel added lenses and computational algorithms, as well as quantum cascade laser imaging systems, which offer advantages over traditional Fourier transform infrared systems with respect to the speed of acquisition and field of view. Overcoming these challenges will push forward spectroscopic imaging as a viable tool for disease diagnostics and medical research.

Graphical abstract

Vibrational Micro-Spectroscopy of Human Tissues Analysis: Review

Vibrational spectroscopy (Infrared (IR) and Raman) and, in particular, micro-spectroscopy and micro-spectroscopic imaging have been used to characterize developmental changes in tissues, to monitor these changes in cell cultures and to detect disease and drug-induced modifications. The conventional methods for biochemical and histophatological tissue characterization necessitate complex and "time-consuming" sample manipulations and the results are rarely quantifiable. The spectroscopy of molecular vibrations using mid-IR or Raman techniques has been applied to samples of human tissue. This article reviews the application of these vibrational spectroscopic techniques for analysis of biological tissue published between 2005 and 2015.

Development of a practical spatial-spectral analysis protocol for breast histopathology using Fourier transform infrared spectroscopic imaging

Breast cancer screening provides sensitive tumor identification, but low specificity implies that a vast majority of biopsies are not ultimately diagnosed as cancer. Automated techniques to evaluate biopsies can prevent errors, reduce pathologist workload and provide objective analysis. Fourier transform infrared (FT-IR) spectroscopic imaging provides both molecular signatures and spatial information that may be applicable for pathology. Here, we utilize both the spectral and spatial information to develop a combined classifier that provides rapid tissue assessment. First, we evaluated the potential of IR imaging to provide a diagnosis using spectral data alone. While highly accurate histologic [epithelium, stroma] recognition could be achieved, the same was not possible for disease [cancer, no-cancer] due to the diversity of spectral signals. Hence, we employed spatial data, developing and evaluating increasingly complex models, to detect cancers. Sub-mm tumors could be very confidently predicted as indicated by the quantitative measurement of accuracy via receiver operating characteristic (ROC) curve analyses. The developed protocol was validated with a small set and statistical performance used to develop a model that predicts study design for a large scale, definitive validation. The results of evaluation on different instruments, at higher noise levels, under a coarser spectral resolution and two sampling modes [transmission and transflection], indicate that the protocol is highly accurate under a variety of conditions. The study paves the way to validating IR imaging for rapid breast tumor detection, its statistical validation and potential directions for optimization of the speed and sampling for clinical deployment.