Effects of Polarizer-Analyzer Configurations for FTIR Spectroscopy: Implications for Multiple Polarization Algorithms

Polarized Fourier transform infrared (p-FTIR) spectroscopy is a widely used technique for determining orientational information in thin organic materials. Conventionally, a single polarizer is placed in the path of the incident light (termed the polarizer). Occasionally, a second polarizer is also placed after the sample (referred to as the analyzer). However, this polarizer-analyzer configuration has the potential to induce polarization-dependent variances in the final spectra beyond those that are expected, i.e., the squared-cosine relationship of absorptance with respect to polarization angle is no longer accurate. These variances are due to changes in the polarization state of the transmitted light induced by the sample and have yet to be explored in the context of p-FTIR. Consequently, this study employs both theoretical and experimental approaches to identify the effects of including a second polarizer in p-FTIR analyses of anisotropic organic samples. For thin samples, the most significant spectral variance arising from only birefringence is observed on the shoulders of the dichroic peaks. By adopting a crossed polarizer configuration, it is shown that there is potential to identify anisotropy of samples that are generally considered too thick for p-FTIR analysis by exploiting this feature. Furthermore, the squared-cosine relationship of absorptance with respect to the polarization angle is also shown to be inapplicable when a second parallel-oriented polarizer is included. Accordingly, a function that accounts for the second polarizer is proposed for multiple polarization techniques.

New Approaches to Stretched Film Sample Alignment and Data Collection for Vibrational Linear Dichroism

Rapid measurements of vibrational linear dichroism (VLD) infrared spectra are shown to be possible by using stretched polymer films and an extension of existing instrumentation designed for vibrational circular dichroism spectroscopy. Earlier techniques can be extended using additional inexpensive polymer substrates to record good-quality VLD spectra of a significantly wider range of compounds with comparatively short sample-preparation times. The polymer substrates used, polyethylene and polytetrafluoroethylene, are commonly available and inexpensive, and samples are more easily prepared than that for many earlier stretched-film and crystal studies. Data are presented for neutral hydrophobic organic molecules on hydrophobic films including acridine, anthracene, fluorene, and recently synthesized S-(4-((4-cyanophenyl)ethynyl)phenyl)ethanethioate. We extend the approach to polar or ionic species, including 2,2'-bipyridine, 1,10-phenanthroline, and sodium dodecyl sulfate, by oxidizing polyethylene films to change their wetting properties. The combination of new instrumentation and modified sample preparation methods is useful in basic spectroscopy for untangling and assigning complicated infrared spectra. Nevertheless, it is not a panacea as surface-adsorbed molecules are often not monodispersed, and higher analyte concentrations can lead to aggregation and resonance phenomena that have previously been observed for infrared spectra on surfaces. These effects can be assessed by varying the sample concentration. The focus of this paper is experimental, and detailed analysis of most of the spectra lies outside its scope, including some well-studied compounds such as acridine and anthracene that allow comparisons with earlier research.

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.

Recent advances and applications to cultural heritage using ATR-FTIR spectroscopy and ATR-FTIR spectroscopic imaging

Scientific investigation of cultural heritage objects plays a vital role in a responsible modern approach to conservation and archaeology. Recent advances in spectroscopy, such as the development of Attenuated Total Reflection Fourier Transform Infrared (ATR-FTIR) spectroscopy and ATR-FTIR spectroscopic imaging, have opened up a window of opportunities for characterisation of materials in artefacts and collections from museums. This review summarises some of the recent advances and applications of these ATR-FTIR spectroscopic analytical techniques in the area of cultural heritage studies, including examples of cross-sections of oil paintings, paper, textiles, plastic objects, potteries, glasses and mineral artefacts. Two of the major advantages of ATR mode measurements are minimal or no requirements for sample preparation and its provision for high lateral spatial resolution. In addition to conventional single point detection, two-dimensional mapping and imaging is especially beneficial for chemical visualisation of multi-layered structure cultural objects. This review also explores the implications of these advantages as well as some limitations and provides a brief outlook for the possible future developments in this area.

Advantages of External Reflection and Transflection over ATR in the Rapid Material Characterization of Negatives and Films via FTIR Spectroscopy

The identification of film support material is of utmost importance for evidence-based collection management in cultural heritage institutions, especially the identification of cellulose nitrate for fire safety reasons, as nitrate is highly flammable and deteriorates over time. Cellulose nitrate film was used by photographers and movie filmmakers from its release in the 1880s to the 1950s. Cellulose acetate, being called safety film, gradually began to replace cellulose nitrate, as it is not flammable. Despite its non-flammable properties, cellulose acetate also deteriorates in hazardous ways. Therefore, identification of cellulose nitrate and cellulose acetate in collections is imperative for preservation and risk management to collections and humans. Large photographic collections can easily contain several thousand negatives or more, so a rapid, non-invasive and reliable method is needed. Traditional identification methods, such as destructive chemical tests, are sometimes unreliable, and spectroscopic analyses are normally time-consuming. To overcome these issues, rapid material characterization was performed in transflection mode with a Fourier-transform infrared (FTIR) spectrometer equipped with an external reflectance module and an additional aluminum-foil reflector. With this newly developed method, the support material (cellulose nitrate, cellulose acetate and polyester) of about 99.8% of all films can be determined within two seconds of measuring time, without any further spectral processing. Very distinctive spectral patterns are obtained with this new method, regardless of which side of the film is being analyzed. A simple visual inspection of the raw spectrum is usually sufficient to determine the film support identity. A detailed comparison of the various FTIR techniques shows the advantages of the transflection measurement for the material characterization of film support layers. This newly developed method enables the non-invasive, rapid and unambiguous material identification of even large film collections in a short time.

Challenges in Experimental Methods

Experimental studies of amyloids encounter many challenges. There are many methods available for studying proteins, which can be applied to amyloids: from basic staining techniques, allowing visualization of fibers, to complex methods, e.g., AFM-IR used to their detailed biochemical and structural characterization in nanoscale. Which method is appropriate depends on the goal of an experiment: verification of aggregational properties of a peptide, distinguishing oligomers from mature fibers, or kinetic studies. Insolubility, rapid aggregation, and the need of using a high-purity peptide may be a limiting factor in studies involving amyloids. Moreover, the results obtained by various experimental methods often differ significantly, which may lead to misclassification of amyloid peptides. Due to ambiguity of experimental results, laborious and time-consuming analysis, bioinformatical methods become more widely used for amyloids.

Lineshape Distortions in Internal Reflection Two-Dimensional Infrared Spectroscopy: Tuning across the Critical Angle

Reflection mode two-dimensional infrared spectroscopy (R-2DIR) has recently emerged as a tool that expands the utility of ultrafast IR spectroscopy toward a broader class of materials. The impact of experimental configurations on the potential distortions of the transient reflectance (TR) spectra has not been fully explored, particularly in the vicinity of the critical angle θ_c and through the crossover from total internal reflection to partial reflection. Here we study the impact on the spectral lineshape of a dilute bulk solution as θ_c is varied across the incident angle by tuning the refractive index of the solvent. We demonstrate the significance of several distortions, including the appearance of phase twisted lineshapes and apparent changes in the spectral inhomogeneity, and show how these distortions impact the interpretation of the TR and R-2DIR spectroscopies.

Spectroscopic analysis focusing on ionic liquid/metal electrode and organic semiconductor interfaces in an electrochemical environment

The solid-liquid interface forms an electric double layer that enables the function of electronic devices and, thus, represents an important area of electrochemical research. Because ionic liquids (ILs) are becoming prominent candidates for new high-performing electrolytes, their interface with solid substrates (e.g., metal electrodes or organic semiconductors) attracts substantial attention. An example of improvement achieved using ILs as electrolytes is a decrease in the operating voltage of transistors from >10 V in traditional SiO₂-gated transistors to <1 V in IL-gated electronic double-layer organic field-effect devices. This perspective discusses the investigation of poorly accessible IL/substrate interfaces using both attenuated total reflectance ultraviolet (ATR-UV) spectroscopy and a newly developed electrochemical setup combined with ATR-UV (EC-ATR-UV), which allows analysis of the interfacial area under the application of varying electric potential. The recent EC-ATR-UV applications in interfacial analytical chemistry are overviewed and compared to other spectroscopic methods described in the recent literature. Lastly, the supplementation of experimental data with theoretical calculations (e.g., quantum chemical calculations and molecular dynamics simulations) is also addressed.

Application of Infrared Reflectance Spectroscopy on Plastics in Cultural Heritage Collections: A Comparative Assessment of Two Portable Mid-Fourier Transform Infrared Reflection Devices

Plastics have been increasingly used to create modern and contemporary art and design, and nowadays, museum collections hold numerous objects completely or partially made of plastics. However, the preservation of these materials is still a challenging task in heritage conservation, especially because some plastics show signs of degradation shortly after their production. In addition, different degradation mechanisms can often take place depending on the plastic composition and appropriate environmental and packaging conditions should be adopted. Therefore, methods for in situ and rapid characterization of plastic artifacts' composition are greatly needed to outline proper conservation strategies. Infrared (IR) spectroscopy, such as attenuated total reflection Fourier transform infrared spectroscopy (ATR FT-IR), is a well-established method for polymeric material analysis. However, ATR FT-IR requires an intimate contact with the object, which makes its application less appropriate for the in situ investigation of fragile or brittle degraded plastic objects. Mid-FT-IR reflectance spectroscopy may represent a valid alternative as it allows in situ measurements with minimum or even no contact, and IR data can be acquired rapidly. On the other hand, spectral interpretation of reflectance spectra is usually difficult as IR bands may appear distorted with significant changes in band maximum, shape, and relative intensity, depending on the optical properties and surface texture of the material analyzed. Presently, mid-FT-IR reflection devices working in external reflection (ER FT-IR) and diffuse reflection infrared Fourier transform spectroscopy (DRIFTS) modes have been used in cultural heritage research studies. As the collected vibrational information depends on the optical layout of the measuring system, differences between ER FT-IR and DRIFT spectra are thus expected when the same polymer is analyzed. So far, ER FT-IR and DRIFT spectroscopy have been individually explored for the identification of plastic objects, but comparative studies between the application of two reflectance FT-IR modes have not been presented yet. In this work, the use of two portable FT-IR spectrometers equipped with ER FT-IR and DRIFTS modes were compared for plastics identification purposes for the first time. Both references of polymeric materials and historical plastic objects (from a Portuguese private collection) were studied and the differences between ER FT-IR and DRIFT spectra were discussed. The spectra features were examined considering the two different optical geometries and analytes' properties. This new insight can support a better understanding of both vibrational information acquired and practical aspects in the application of the ER FT-IR and DRIFTS in plastic analysis.

A representation learning approach for recovering scatter-corrected spectra from Fourier-transform infrared spectra of tissue samples

Infrared spectra obtained from cell or tissue specimen have commonly been observed to involve a significant degree of scattering effects, often Mie scattering, which probably overshadows biochemically relevant spectral information by a nonlinear, nonadditive spectral component in Fourier transform infrared (FTIR) spectroscopic measurements. Correspondingly, many successful machine learning approaches for FTIR spectra have relied on preprocessing procedures that computationally remove the scattering components from an infrared spectrum. We propose an approach to approximate this complex preprocessing function using deep neural networks. As we demonstrate, the resulting model is not just several orders of magnitudes faster, which is important for real-time clinical applications, but also generalizes strongly across different tissue types. Using Bayesian machine learning approaches, our approach unveils model uncertainty that coincides with a band shift in the amide I region that occurs when scattering is removed computationally based on an established physical model. Furthermore, our proposed method overcomes the trade-off between computation time and the corrected spectrum being biased towards an artificial reference spectrum.

The effect of deformation of absorbing scatterers on Mie-type signatures in infrared microspectroscopy

Mie-type scattering features such as ripples (i.e., sharp shape-resonance peaks) and wiggles (i.e., broad oscillations), are frequently-observed scattering phenomena in infrared microspectroscopy of cells and tissues. They appear in general when the wavelength of electromagnetic radiation is of the same order as the size of the scatterer. By use of approximations to the Mie solutions for spheres, iterative algorithms have been developed to retrieve pure absorbance spectra. However, the question remains to what extent the Mie solutions, and approximations thereof, describe the extinction efficiency in practical situations where the shapes of scatterers deviate considerably from spheres. The aim of the current study is to investigate how deviations from a spherical scatterer can change the extinction properties of the scatterer in the context of chaos in wave systems. For this purpose, we investigate a chaotic scatterer and compare it with an elliptically shaped scatterer, which exhibits only regular scattering. We find that chaotic scattering has an accelerating effect on the disappearance of Mie ripples. We further show that the presence of absorption and the high numerical aperture of infrared microscopes does not explain the absence of ripples in most measurements of biological samples.

On-site contactless surface analysis of modern paintings from Galleria Nazionale (Rome) by reflectance FTIR and Raman spectroscopies

Seven artworks representing the diversity of paints used around the 1960s and created by German and Italian painters (J. Albers, A. Bonalumi, L. Boille, T. Scialoja and M. Schifano) were studied on-site at the Galleria Nazionale d'Arte Moderna (Rome) with mobile instruments. We present a methodology based on Specular Reflectance Infrared Spectroscopy (SR-FTIR) adapted to unvarnished paintings. Complementary measurements have been performed by Raman spectroscopy. Characteristic bands regarding as-recorded infrared reflectance spectra and Kramers-Kronig Transformation-converted absorbance spectra are identified according to literature and reference spectra recorded on representative commercially available paints. To distinguish the different binders by SR-FTIR, we propose spectroscopic markers as the comparison of the intensity of carbonyl band around 1730-1735 cm^-1 with bands at ~1160 (for acrylic), ~1230 (for PVAc), and 1270 cm^-1 (for alkyds). On the other hand, oil/resin binders are characterized by intense and thin νCH₂, νCH₃ IR absorption bands around 2920-2850 cm^-1, combined with an intense 1260 cm^-1 band and a characteristic concave cradle shape (between ca. 1750 and 1260 cm^-1). The results obtained establish the relevance of the implemented mobile non-invasive infrared spectroscopy analytical approach by successfully identifying acrylic, vinylic, oil media and enamel paints, with or without opacifiers, which is supplemented by Raman analyses for pigment identification.

Evaluating biochemical differences in thyroglobulin from normal and goiter tissues by infrared spectral imaging

Thyroglobulin is a glycoiodoprotein that is produced by thyroid follicular cells; it is stored in follicles in structures known as colloids. The main function of this protein is to stock the hormones triiodothyronine (T3) and thyroxine (T4) until the body requires them. This study aims to demonstrate that infrared spectral imaging with appropriate multivariate analysis can reveal biochemical changes in this glycoprotein. The results achieved herein point out biochemical differences in the colloid samples obtained from normal and goiter patients including glycosylation and changes in the secondary conformational structure. We have presented the first spectral histopathology-based method to detect biochemical differences in thyroid colloids, such as TG iodination, glycosylation, and changes in the secondary structure in normal and goiter patients. The observed changes in the colloids were mainly due to the alterations in amide I and amide II (secondary conformation of proteins) and there is a correlation with different glycosylation between normal and goiter tissues.

Prediction of wine sensory properties using mid-infrared spectra of Cabernet Sauvignon and Chardonnay grape berries and wines

The study determined optimal parameters to four preprocessing techniques for mid-infrared (MIR) spectra of wines and grape berry homogenates and tested MIR's ability to model sensory properties of research Cabernet Sauvignon and Chardonnay wines. Savitsky-Golay (SG) derivative, smoothing points, and polynomial order, and extended multiplicative signal correction (EMSC) polynomial were investigated as preprocessing techniques at 2, 2, 5, and 3 levels, respectively, all in combination. Preprocessed data were analysed with partial least squares regression (PLS) to model the wine sensory data and the regression coefficients of PLS calibration models (R²) were further analysed with multivariate analysis of variance (MANOVA). SG transformations were significant factors from the MANOVA that influenced R², while EMSC did not. Overall, PLSR models that predicted wine sensory characteristics gave a poor to moderate R². Consistently predicting wine sensory attributes within a variety and across vintages is challenging, regardless of using grape or wine spectra as predictors.

A Correction Scheme for Fano Line Shapes in Two-Dimensional Infrared Spectroscopy

The asymmetry of Fano line shapes observed for metal-adsorbate systems is reflected in two-dimensional infrared (2D IR) spectroscopy as a distorted spectrum. A phenomenological correction scheme is proposed that transforms distorted 2D IR spectra into conventional spectra. To that end, a phase correction factor is first derived from the IR absorption spectrum of the sample by symmetrizing the asymmetric line shape and subsequently applied to the distorted 2D IR spectra. The concept is illustrated for a model system consisting of an organic molecule (p-mercaptobenzonitrile) adsorbed on a sputter-coated metal layer (Au). The correction scheme reveals conventional, easily interpretable 2D IR spectra.

Infrared spectra of micro-structured samples with microPhotoacoustic spectroscopy and synchrotron radiation

Photoacoustic spectroscopy (PAS) measures the photon absorption spectrum of a sample through detection of the acoustic wave generated by the photothermal effect as one modulates the intensity of the incident radiation at each wavelength. We have recently demonstrated the implementation of PAS in a microscopy configuration with mid-infrared radiation (microPAS). In the present work, we describe the performance of microPAS using synchrotron radiation (SR) in diffraction-limited spectromicroscopy and imaging experiments. Spectra were obtained for polystyrene beads, polypropylene fibres, and single fibres of human hair. SR produced microPAS spectra of much higher intensity as compared with those obtained using conventional mid- and near-infrared sources. For hair samples, the penetration depth of mid-infrared light, even with bright SR, is significantly shorter than the probed sample thickness at very low modulation frequencies resulting in saturated PAS spectra. In contrast, microPAS spectra of polymer beads were in general of much better quality than those obtained with conventional sources. We also demonstrated the capability to collect line profiles and line spectra at diffraction limited spatial resolution. The microPAS spectra of beads appear free from appreciable bandshape distortions arising from the real part of the refractive index of the sample. This observation confirms microPAS as an absorption-only technique and establishes it as a valuable new tool in the microspectroscopic analysis of particulates and of samples with a complex topography.

Characterization of Intact Eukaryotic Cells with Subcellular Spatial Resolution by Photothermal-Induced Resonance Infrared Spectroscopy and Imaging

Photothermal-induced resonance (PTIR) spectroscopy and imaging with infrared light has seen increasing application in the molecular spectroscopy of biological samples. The appeal of the technique lies in its capability to provide information about IR light absorption at a spatial resolution better than that allowed by light diffraction, typically below 100 nm. In the present work, we tested the capability of the technique to perform measurements with subcellular resolution on intact eukaryotic cells, without drying or fixing. We demonstrate the possibility of obtaining PTIR images and spectra from the nucleus and multiple organelles with high resolution, better than that allowed by diffraction with infrared light. We obtain particularly strong signal from bands typically assigned to acyl lipids and proteins. We also show that while a stronger signal is obtained from some subcellular structures, other large subcellular components provide a weaker or undetectable PTIR response. The mechanism that underlies such variability in response is presently unclear. We propose and discuss different possibilities, addressing thermomechanical, geometrical, and electrical properties of the sample and the presence of cellular water, from which the difference in response may arise.

Recent trends in the application of Fourier Transform Infrared (FT-IR) spectroscopy in Heritage Science: from micro- to non-invasive FT-IR

The relevance of FT-IR spectroscopy in heritage science has experienced a constant grow in the last two decades owing to analytical peculiarities that make it an extremely useful tool to answer the questions posed by the study and conservation of art-historical and archaeological materials. High versatility, sensitivity and molecular specificity are, in fact, all requirements that FT-IR spectroscopy fulfils allowing for the investigation of the chemical properties of heritage materials spanning from the micro- to the macro-scale and offering a variety of approaches to minimize sample manipulation and maximize extracted information. Molecular identification and localisation at high lateral resolution of organic and inorganic components in micro-samples was, over recently, the mostly exploited use of FT-IR in heritage science; however, benefiting from technological progress and advances in optical materials and components achieved in the last decade, it now stands out also for non-invasive surface analysis of artworks by fully portable instrumentation.

Infrared Spectroscopy with a Fiber-Coupled Quantum Cascade Laser for Attenuated Total Reflection Measurements Towards Biomedical Applications

The development of rapid and accurate biomedical laser spectroscopy systems in the mid-infrared has been enabled by the commercial availability of external-cavity quantum cascade lasers (EC-QCLs). EC-QCLs are a preferable alternative to benchtop instruments such as Fourier transform infrared spectrometers for sensor development as they are small and have high spectral power density. They also allow for the investigation of multiple analytes due to their broad tuneability and through the use of multivariate analysis. This article presents an in vitro investigation with two fiber-coupled measurement setups based on attenuated total reflection spectroscopy and direct transmission spectroscopy for sensing. A pulsed EC-QCL (1200–900 cm−1) was used for measurements of glucose and albumin in aqueous solutions, with lactate and urea as interferents. This analyte composition was chosen as an example of a complex aqueous solution with relevance for biomedical sensors. Glucose concentrations were determined in both setup types with root-mean-square error of cross-validation (RMSECV) of less than 20 mg/dL using partial least-squares (PLS) regression. These results demonstrate accurate analyte measurements, and are promising for further development of fiber-coupled, miniaturised in vivo sensors based on mid-infrared spectroscopy.

Spectral histopathology of the lung: A review of two large studies

This paper summarizes results from two large lung cancer studies comprising over 700 samples that demonstrate the ability of spectral histopathology (SHP) to distinguish cancerous tissue regions from normal tissue, to differentiate benign lesions from normal tissue and cancerous lesions, and to classify lung cancer types. Furthermore, malignancy-associated changes can be identified in cancer-adjacent normal tissue. The ability to differentiate a multitude of normal cells and tissue types allow SHP to identify tumor margins and immune cell infiltration. Finally, SHP easily distinguishes small cell lung cancer (SCLC) from non-SCLC (NSCLC) and provides a further differentiation of NSCLC into adenocarcinomas and squamous cell carcinomas with an accuracy comparable of classical histopathology combined with immunohistochemistry. Case studies are presented that demonstrates that SHP can resolve interobserver discrepancies in standard histopathology.

Extended Multiplicative Signal Correction for Infrared Microspectroscopy of Heterogeneous Samples with Cylindrical Domains

Optical scattering corrections are invoked to computationally distinguish between scattering and absorption contributions to recorded data in infrared (IR) microscopy, with a goal to obtain an absorption spectrum that is relatively free of the effects of sample morphology. Here, we present a modification of the extended multiplicative signal correction (EMSC) approach that allows for spectral recovery from fibers and cylindrical domains in heterogeneous samples. The developed theoretical approach is based on exact Mie theory for infinite cylinders. Although rigorous Mie theory implies utilization of comprehensive and time-consuming calculations, we propose to change the workflow of the original EMSC algorithm to minimize extensive calculations for each recorded spectrum at each iteration step. This makes the modified EMSC approach practical for routine use. First, we tested our approach using synthetic data derived from a rigorous model of scattering from cylinders in an IR microscope. Second, we applied the approach to Fourier transform IR (FT-IR) microspectroscopy data recorded from filamentous fungal and cellulose samples with pronounced fiber-like shapes. While the corrected spectra show greatly reduced baseline offsets and consistency, strongly absorbing regions of the spectrum require further refinement. The modified EMSC algorithm broadly mitigates the effects of scattering, offering a practical approach to more consistent and accurate spectra from cylindrical objects or heterogeneous samples with cylindrical domains.

An open-source code for Mie extinction extended multiplicative signal correction for infrared microscopy spectra of cells and tissues

Infrared spectroscopy of single cells and tissue is affected by Mie scattering. During recent years, several methods have been proposed for retrieving pure absorbance spectra from such measurements, while currently no user-friendly version of the state-of-the-art algorithm is available. In this work, an open-source code for correcting highly scatter-distorted absorbance spectra of cells and tissues is presented, as well as several improvements of the latest version of the Mie correction algorithm based on extended multiplicative signal correction (EMSC) published by Konevskikh et al. In order to test the stability of the code, a set of apparent absorbance spectra was simulated. To this purpose, pure absorbance spectra based on a Matrigel spectrum are simulated. Scattering contributions where obtained by mimicking the scattering features observed in a set of experimentally obtained spectra . It can be concluded that the algorithm is not depending strongly on the reference spectrum used for initializing the algorithm and retrieves well the underlying pure absorbance spectrum. The calculation time of the algorithm is considerably improved with respect to the resonant Mie scattering EMSC algorithm used by the community today.

Deep representation learning for domain adaptable classification of infrared spectral imaging data

Motivation

Applying infrared microscopy in the context of tissue diagnostics heavily relies on computationally preprocessing the infrared pixel spectra that constitute an infrared microscopic image. Existing approaches involve physical models, which are non-linear in nature and lead to classifiers that do not generalize well, e.g. across different types of tissue preparation. Furthermore, existing preprocessing approaches involve iterative procedures that are computationally demanding, so that computation time required for preprocessing does not keep pace with recent progress in infrared microscopes which can capture whole-slide images within minutes.

Results

We investigate the application of stacked contractive autoencoders as an unsupervised approach to preprocess infrared microscopic pixel spectra, followed by supervised fine-tuning to obtain neural networks that can reliably resolve tissue structure. To validate the robustness of the resulting classifier, we demonstrate that a network trained on embedded tissue can be transferred to classify fresh frozen tissue. The features obtained from unsupervised pretraining thus generalize across the large spectral differences between embedded and fresh frozen tissue, where under previous approaches separate classifiers had to be trained from scratch.

Availability and implementation

Our implementation can be downloaded from https://github.com/arnrau/SCAE_IR_Spectral_Imaging.

Supplementary information

Supplementary data are available at Bioinformatics online.

Extracting pure absorbance spectra in infrared microspectroscopy by modeling absorption bands as Fano resonances

Midinfrared absorbance spectra obtained from spatially inhomogeneous and finite samples often contain scattering effects characterized by derivative-like bands with shifted peak positions. Such features may be interpreted and accurately modeled by Fano theory when the imaginary part of the complex dielectric function is small and Lorentzian in nature-as is the case for many biological media. Furthermore, by fitting Fano line shapes to isolated absorbance bands, recovery of the peak position and pure absorption strength can be obtained with high accuracy. Additionally, for small and optically soft spherical scatterers, recovery of one or the other of constant refractive index or radius (given approximate knowledge of the other) is possible.

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.

The Danger of Relying on Database Spectra

With the availability of easy-to-use commercial instrumentation for infrared (IR) and Raman spectroscopy, the number of users is growing very fast. Even in labs in which no personnel with experience in spectroscopy is around, spectra can be recorded and analyzed. However, for an inexperienced person it is virtually impossible to check whether a spectrum is plausible. In this Note, it is demonstrated that even comparing an experimental spectrum with data from a database may lead to significant errors. The vibrational spectrum of dimethyl sulfoxide (DMSO) is presented as an example.

Vibrational Spectroscopy as a Promising Toolbox for Analyzing Functionalized Ceramic Membranes

Ceramic materials find use in many fields including the life sciences and environmental engineering. For example, ceramic membranes have shown to be promising filters for water treatment and virus retention. The analysis of such materials, however, remains challenging. In the present study, the potential of three vibrational spectroscopic methods for characterizing functionalized ceramic membranes for water treatment is evaluated. For this purpose, Raman scattering, infrared (IR) absorption, and solvent infrared spectroscopy (SIRS) were employed. The data were analyzed with respect to spectral changes as well as using principal component analysis (PCA). The Raman spectra allow an unambiguous discrimination of the sample types. The IR spectra do not change systematically with functionalization state of the material. Solvent infrared spectroscopy allows a systematic distinction and enables studying the molecular interactions between the membrane surface and the solvent.

Infrared micro-spectroscopy of human tissue: principles and future promises

This article summarizes the methods employed, and the progress achieved over the past two decades in applying vibrational (Raman and IR) micro-spectroscopy to problems of medical diagnostics and cellular biology. During this time, several research groups have verified the enormous information contained in vibrational spectra; in fact, information on protein, lipid and metabolic composition of cells and tissues can be deduced by decoding the observed vibrational spectra. This decoding process is aided by the availability of computer workstations and advanced algorithms for data analysis. Furthermore, commercial instrumentation for the fast collection of both Raman and infrared micro-spectral data has enabled the collection of images of cells and tissues based solely on vibrational spectroscopic 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 spectroscopy in the biological and biomedical arenas.

An improved algorithm for fast resonant Mie scatter correction of infrared spectra of cells and tissues

Mie scattering effects create serious problems for the interpretation of Fourier-transform infrared spectroscopy spectra of single cells and tissues. During recent years, different techniques were proposed to retrieve pure absorbance spectra from spectra with Mie distortions. Recently, we published an iterative algorithm for correcting Mie scattering in spectra of single cells and tissues, which we called "the fast resonant Mie scatter correction algorithm." The algorithm is based on extended multiplicative signal correction (EMSC) and employs a meta-model for a parameter range of refractive index and size parameters. In the present study, we suggest several improvements of the algorithm. We demonstrate that the improved algorithm reestablishes chemical features of the measured spectra, and show that it tends away from the reference spectrum employed in the EMSC. We suggest strategies for choosing parameter ranges and other model parameters such as the number of principal components of the meta-model and the number of iterations. We demonstrate that the suggested algorithm optimizes an error function of the refractive index in a forward Mie model. We suggest a stop criterion for the iterative algorithm based on the error function of the forward model.

Facile Fabrication of Porous Conductive Thermoplastic Polyurethane Nanocomposite Films via Solution Casting

Porous conductive polymers are one of important materials, featuring lightweight, large specific surface area and high porosity. Non-solvent induced phase separation is widely employed to prepare porous polymer sheet materials. Through utilizing water vapor in ambient environment as the non-solvent, a facile approach was developed to produce porous conductive polymer nanocomposites using the conventional solution-casting method. Without using any non-solvent liquids, porous carbon nanofiber/thermoplastic polyurethane (CNF/TPU) nanocomposites were prepared directly by solution casting of their dimethylformamide (DMF) solutions under ambient conditions. The strength of the CNF framework played a key role in preventing the collapse of pores during DMF evaporation. The dependence of porous structures on CNF loading was studied by scanning electron microscopy and porosity measurement. The influence of CNF loading on the mechanical properties, electrical conductivity and piezoresistive behavior was explored.

Molecular Interactions and Hydration States of Ultrathin Functional Films at the Solid-Liquid Interface

We significantly improve the infrared analysis of ultrathin films in aqueous environments by employing in situ infrared ellipsometry. Combining it with rigorous optical modeling avoids otherwise typical misinterpretations of spectral features and enables the simultaneous quantification of chemical composition, hydration states, structure, and molecular interactions. We apply this approach to study covalently end-grafted, nanometer-thin brushes of poly(N-isopropylacrylamide), a thermoresponsive model polymer for proteins at solid-liquid interfaces. Quantitative analyses are based on a dielectric layer model that accounts for film swelling and deswelling, hydration of hydrophilic amide and hydrophobic isopropyl side groups, as well as molecular interactions of the polymer's amide moieties. We thereby quantify the hydration and structure dependence of intra- and intermolecular C═O···H-N and C═O···H₂O hydrogen bonds, elucidating their role in the brush's temperature-induced phase separation. The presented method is directly applicable to functional and biorelated films like polymer and polypeptide layers, which is of topical interest for interface studies, such as membrane processes and protein unfolding.

Cancer screening via infrared spectral cytopathology (SCP): results for the upper respiratory and digestive tracts

Instrumental advances in infrared micro-spectroscopy have made possible the observation of individual human cells and even subcellular structures. The observed spectra represent a snapshot of the biochemical composition of a cell; this composition varies subtly but reproducibly with cellular effects such as progression through the cell cycle, cell maturation and differentiation, and disease. The aim of this summary is to provide a synopsis of the progress achieved in infrared spectral cytopathology (SCP) - the combination of infrared micro-spectroscopy and multivariate methods of analysis - for the detection of abnormalities in exfoliated human cells of the upper respiratory and digestive tract, namely the oral and nasopharyngeal cavities, and the esophagus.

Fundamental developments in infrared spectroscopic imaging for biomedical applications

Infrared chemical imaging is a rapidly emerging field with new advances in instrumentation, data acquisition and data analysis. These developments have had significant impact in biomedical applications and numerous studies have now shown that this technology offers great promise for the improved diagnosis of the diseased state. Relying on purely biochemical signatures rather than contrast from exogenous dyes and stains, infrared chemical imaging has the potential to revolutionise histopathology for improved disease diagnosis. In this review we discuss the recent advances in infrared spectroscopic imaging specifically related to spectral histopathology (SHP) and consider the current state of the field. Finally we consider the practical application of SHP for disease diagnosis and consider potential barriers to clinical translation highlighting current directions and the future outlook.

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.

Marker-free automated histopathological annotation of lung tumour subtypes by FTIR imaging

By integration of FTIR imaging and a novel trained random forest classifier, lung tumour classes and subtypes of adenocarcinoma are identified in fresh-frozen tissue slides automated and marker-free. The tissue slices are collected under standard operation procedures within our consortium and characterized by current gold standards in histopathology. In addition, meta data of the patients are taken. The improved standards on sample collection and characterization results in higher accuracy and reproducibility as compared to former studies and allows here for the first time the identification of adenocarcinoma subtypes by this approach. The differentiation of subtypes is especially important for prognosis and therapeutic decision.

A method for the comparison of multi-platform spectral histopathology (SHP) data sets

Results of a study comparing infrared imaging data sets collected on different instruments or instrument platforms are reported, along with detailed methods developed to permit such comparisons. It was found that different instrument platforms, although employing different detector technologies and pixel sizes, produce highly similar and reproducible spectral results. However, differences in the absolute intensity values of the reflectance data sets were observed that were caused by heterogeneity of the sample substrate in terms of reflectivity and planarity.

Detection of highly energetic materials on non-reflective substrates using quantum cascade laser spectroscopy

A quantum cascade laser spectrometer was used to obtain the reflection spectra of highly energetic materials (HEMs) deposited on nonideal, low-reflectivity substrates, such as travel-bag fabric (polyester), cardboard, and wood. Various deposition methods were used to prepare the standards and samples in the study. The HEMs used were the nitroaromatic explosive 2,4,6-trinitrotoluene (TNT), the aliphatic nitrate ester pentaerythritol tetranitrate (PETN), and the aliphatic nitramine 1,3,5-trinitroperhydro-1,3,5-triazine (RDX). Chemometrics algorithms were applied to analyze the recorded spectra. Partial least squares (PLS) regression analysis was used to find the best correlation between the infrared signals and the surface concentrations of the samples, and PLS combined with discriminant analysis (PLS-DA) was used to discriminate, classify, and identity similarities in the spectral datasets. Several preprocessing steps were applied to prepare the mid-infrared spectra of HEMs deposited on the target substrates. The results demonstrate that the infrared vibrational method described in this study is well suited for the rapid screening analysis of HEMs on low-reflectivity substrates when a supervised model has been previously constructed or when a reference spectrum of the clean substrate can be acquired to be subtracted from the HEM-substrate spectrum.

Classification of malignant and benign tumors of the lung by infrared spectral histopathology (SHP)

We report results of a study utilizing a novel tissue classification method, based on label-free spectral techniques, for the classification of lung cancer histopathological samples on a tissue microarray. The spectral diagnostic method allows reproducible and objective classification of unstained tissue sections. This is accomplished by acquiring infrared data sets containing thousands of spectra, each collected from tissue pixels ∼6 μm on edge; these pixel spectra contain an encoded snapshot of the entire biochemical composition of the pixel area. The hyperspectral data sets are subsequently decoded by methods of multivariate analysis that reveal changes in the biochemical composition between tissue types, and between various stages and states of disease. In this study, a detailed comparison between classical and spectral histopathology is presented, suggesting that spectral histopathology can achieve levels of diagnostic accuracy that is comparable to that of multipanel immunohistochemistry.

Recovery of absorbance spectra of micrometer-sized biological and inanimate particles

In this paper, we first provide an overview of the Mie type scattering at absorbing materials and existing correction methods, followed by a new method to obtain the pure absorbance spectra of biological systems with spherical symmetry. This method is a further development of the recently described iterative algorithm of van Dijk et al. The method is tested on FTIR synchrotron spectra of polymethyl methacrylate (PMMA) microspheres and pollen grains with approximately spherical shape. The imaginary part of the refractive index was successfully recovered for both systems. Good agreement was obtained between the pure absorbance spectra obtained by this method and the measured spectra.

High-definition Fourier Transform Infrared (FT-IR) spectroscopic imaging of human tissue sections towards improving pathology

High-definition Fourier Transform Infrared (FT-IR) spectroscopic imaging is an emerging approach to obtain detailed images that have associated biochemical information. FT-IR imaging of tissue is based on the principle that different regions of the mid-infrared are absorbed by different chemical bonds (e.g., C=O, C-H, N-H) within cells or tissue that can then be related to the presence and composition of biomolecules (e.g., lipids, DNA, glycogen, protein, collagen). In an FT-IR image, every pixel within the image comprises an entire Infrared (IR) spectrum that can give information on the biochemical status of the cells that can then be exploited for cell-type or disease-type classification. In this paper, we show: how to obtain IR images from human tissues using an FT-IR system, how to modify existing instrumentation to allow for high-definition imaging capabilities, and how to visualize FT-IR images. We then present some applications of FT-IR for pathology using the liver and kidney as examples. FT-IR imaging holds exciting applications in providing a novel route to obtain biochemical information from cells and tissue in an entirely label-free non-perturbing route towards giving new insight into biomolecular changes as part of disease processes. Additionally, this biochemical information can potentially allow for objective and automated analysis of certain aspects of disease diagnosis.

Statistical analysis of a lung cancer spectral histopathology (SHP) data set

We report results on a statistical analysis of an infrared spectral dataset comprising a total of 388 lung biopsies from 374 patients.

Molecular pathology via IR and Raman spectral imaging

During the last 15 years, vibrational spectroscopic methods have been developed that can be viewed as molecular pathology methods that depend on sampling the entire genome, proteome and metabolome of cells and tissues, rather than probing for the presence of selected markers. First, this review introduces the background and fundamentals of the spectroscopies underlying the new methodologies, namely infrared and Raman spectroscopy. Then, results are presented in the context of spectral histopathology of tissues for detection of metastases in lymph nodes, squamous cell carcinoma, adenocarcinomas, brain tumors and brain metastases. Results from spectral cytopathology of cells are discussed for screening of oral and cervical mucosa, and circulating tumor cells. It is concluded that infrared and Raman spectroscopy can complement histopathology and reveal information that is available in classical methods only by costly and time-consuming steps such as immunohistochemistry, polymerase chain reaction or gene arrays. Due to the inherent sensitivity toward changes in the bio-molecular composition of different cell and tissue types, vibrational spectroscopy can even provide information that is in some cases superior to that of any one of the conventional techniques.

FTIR spectroscopy of biofluids revisited: an automated approach to spectral biomarker identification

The extraction of disease specific information from Fourier transform infrared (FTIR) spectra of human body fluids demands the highest standards of accuracy and reproducibility of measurements because the expected spectral differences between healthy and diseased subjects are very small in relation to a large background absorbance of the whole sample. Here, we demonstrate that with the increased sensitivity of modern FTIR spectrometers, automatisation of sample preparation and modern bioinformatics, it is possible to identify and validate spectral biomarker candidates for distinguishing between urinary bladder cancer (UBC) and inflammation in suspected bladder cancer patients. The current dataset contains spectra of blood serum and plasma samples of 135 patients. All patients underwent cytology and pathological biopsy characterization to distinguish between patients without UBC (46) and confirmed UBC cases (89). A minimally invasive blood test could spare control patients a repeated cystoscopy including a transurethral biopsy, and three-day stationary hospitalisation. Blood serum, EDTA and citrate plasma were collected from each patient and processed following predefined strict standard operating procedures. Highly reproducible dry films were obtained by spotting sub-nanoliter biofluid droplets in defined patterns, which were compared and optimized. Particular attention was paid to the automatisation of sample preparation and spectral preprocessing to exclude errors by manual handling. Spectral biomarker candidates were identified from absorbance spectra and their 1(st) and 2(nd) derivative spectra using an advanced Random Forest (RF) approach. It turned out that the 2(nd) derivative spectra were most useful for classification. Repeat validation on 21% of the dataset not included in predictor training with Linear Discriminant Analysis (LDA) classifiers and Random Forests (RFs) yielded a sensitivity of 93 ± 10% and a specificity of 46 ± 18% for bladder cancer. The low specificity can be most likely attributed to the unbalanced and small number of control samples. Using this approach, spectral biomarker candidates in blood-derived biofluids were identified, which allow us to distinguish between cancer and inflammation, but the observed differences were tiny. Obviously, a much larger sample number has to be investigated to reliably validate such candidates.