Fundamental developments in infrared spectroscopic imaging for biomedical applications

Research on a Dual-Mode Infrared Liquid-Crystal Device for Simultaneous Electrically Adjusted Filtering and Zooming

A new dual-mode liquid-crystal (LC) micro-device constructed by incorporating a Fabry⁻Perot (FP) cavity and an arrayed LC micro-lens for performing simultaneous electrically adjusted filtering and zooming in infrared wavelength range is presented in this paper. The main micro-structure is a micro-cavity consisting of two parallel zinc selenide (ZnSe) substrates that are pre-coated with ~20-nm aluminum (Al) layers which served as their high-reflection films and electrodes. In particular, the top electrode of the device is patterned by 44 × 38 circular micro-holes of 120 μm diameter, which also means a 44 × 38 micro-lens array. The micro-cavity with a typical depth of ~12 μm is fully filled by LC materials. The experimental results show that the spectral component with needed frequency or wavelength can be selected effectively from incident micro-beams, and both the transmission spectrum and the point spread function can be adjusted simultaneously by simply varying the root-mean-square value of the signal voltage applied, so as to demonstrate a closely correlated feature of filtering and zooming. In addition, the maximum transmittance is already up to ~20% according the peak-to-valley value of the spectral transmittance curves, which exhibits nearly twice the increment compared with that of the ordinary LC-FP filtering without micro-lenses.

Integrated Fourier Transform Infrared Imaging and Proteomics for Identification of a Candidate Histochemical Biomarker in Bladder Cancer

Histopathological differentiation between severe urocystitis with reactive urothelial atypia and carcinoma in situ (CIS) can be difficult, particularly after a treatment that deliberately induces an inflammatory reaction, such as intravesical instillation of Bacillus Calmette-Guèrin. However, precise grading in bladder cancer is critical for therapeutic decision making and thus requires reliable immunohistochemical biomarkers. Herein, an exemplary potential biomarker in bladder cancer was identified by the novel approach of Fourier transform infrared imaging for label-free tissue annotation of tissue thin sections. Identified regions of interest are collected by laser microdissection to provide homogeneous samples for liquid chromatography-tandem mass spectrometry-based proteomic analysis. This approach afforded label-free spatial classification with a high accuracy and without interobserver variability, along with the molecular resolution of the proteomic analysis. Cystitis and invasive high-grade urothelial carcinoma samples were analyzed. Three candidate biomarkers were identified and verified by immunohistochemistry in a small cohort, including low-grade urothelial carcinoma samples. The best-performing candidate AHNAK2 was further evaluated in a much larger independent verification cohort that also included CIS samples. Reactive urothelial atypia and CIS were distinguishable on the basis of the expression of this newly identified and verified immunohistochemical biomarker, with a sensitivity of 97% and a specificity of 69%. AHNAK2 can differentiate between reactive urothelial atypia in the setting of an acute or chronic cystitis and nonmuscle invasive-type CIS.

Deep UV dispersion and absorption spectroscopy of biomolecules

Owing to the high precision and sensitivity of optical systems, there is an increasing demand for optical methods that quantitatively characterize the physical and chemical properties of biological samples. Information extracted from such quantitative methods, through phase and/or amplitude variations of light, can be crucial in the diagnosis, treatment and study of disease. In this work we apply a recently developed quantitative method, called ultraviolet hyperspectral interferometry (UHI), to characterize the dispersion and absorbing properties of various important biomolecules. Our system consists of (1) a broadband light source that spans from the deep-UV to the visible region of the spectrum, and (2) a Mach-Zehnder interferometer to gain access to complex optical properties. We apply this method to characterize (and tabulate) the dispersive and absorptive properties of hemoglobin, beta nicotinamide adenine dinucleotide (NAD), flavin adenine dinucleotide (FAD), elastin, collagen, cytochrome c, tryptophan and DNA. Our results shed new light on the complex properties of important biomolecules.

Application of a quantum cascade laser aperture scanning near-field optical microscope to the study of a cancer cell

This work reports the first images obtained by combining an infrared aperture scanning near-field optical microscope (SNOM) with a quantum cascade laser (QCL). The future potential of this set-up is demonstrated by a preliminary study on an OE33 human oesophageal adenocarcinoma cell in which the cell is imaged at 1751 cm-1, 1651 cm-1, 1539 cm-1 and 1242 cm-1. In addition to the 1651 cm-1 image, three other images were acquired within the Amide I band (1689 cm-1, 1675 cm-1 and 1626 cm-1) chosen to correspond to secondary structures of proteins. The four images obtained within the Amide I band show distinct differences demonstrating the potential of this approach to reveal subtle changes in the chemical composition of a cell.

Template-free synthesis and metalation of hierarchical covalent organic framework spheres for photothermal therapy

Room temperature synthesized hierarchical COF spheres were metalated with Fe³⁺ and utilized for photothermal therapy.

Thermal effect on dispersive infrared spectroscopic imaging of prostate cancer tissue

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

Infrared spectral histopathology using haematoxylin and eosin (H&E) stained glass slides: a major step forward towards clinical translation

Infrared spectral histopathology has shown great promise as an important diagnostic tool, with the potential to complement current pathological methods. While promising, clinical translation has been hindered by the impracticalities of using infrared transmissive substrates which are both fragile and prohibitively very expensive. Recently, glass has been proposed as a potential replacement which, although largely opaque in the infrared, allows unrestricted access to the high wavenumber region (2500-3800 cm^-1). Recent studies using unstained tissue on glass have shown that despite utilising only the amide A band, good discrimination between histological classes could be achieved, and suggest the potential of discriminating between normal and malignant tissue. However unstained tissue on glass has the potential to disrupt the pathologist workflow, since it needs to be stained following infrared chemical imaging. In light of this, we report on the very first infrared Spectral Histopathology SHP study utilising coverslipped H&E stained tissue on glass using samples as received from the pathologist. In this paper we present a rigorous study using results obtained from an extended patient sample set consisting of 182 prostate tissue cores obtained from 100 different patients, on 18 separate H&E slides. Utilising a Random Forest classification model we demonstrate that we can rapidly classify four classes of histology of an independent test set with a high degree of accuracy (>90%). We investigate different degrees of staining using nine separate prostate serial sections, and demonstrate that we discriminate on biomarkers rather than the presence of the stain. Finally, using a four-class model we show that we can discriminate normal epithelium, malignant epithelium, normal stroma and cancer associated stroma with classification accuracies over 95%.

Digital de-waxing on FTIR images

This paper presents a procedure that digitally neutralizes the contribution of paraffin to FTIR hyperspectral images. A brief mathematical derivation of the procedure is demonstrated and applied on one normal human colon sample to exemplify the de-waxing procedure. The proposed method includes construction of a paraffin model based on PCA, EMSC normalization and application of two techniques for spectral quality control. We discuss every step in which the researcher needs to take a subjective decision during the de-waxing procedure, and we explain how to make an adequate choice of parameters involved. Application of this procedure to 71 hyperspectral images collected from 55 human colon biopsies (20 normal, 17 ulcerative colitis, and 18 adenocarcinoma) showed that paraffin was appropriately neutralized, which made the de-waxed images adequate for analysis by pattern-recognition techniques such as k-means clustering or PCA-LDA.

Surface-Enhanced Raman Scattering (SERS) in Microbiology: Illumination and Enhancement of the Microbial World

The microbial world forms a huge family of organisms that exhibit the greatest phylogenetic diversity on Earth and thus colonize virtually our entire planet. Due to this diversity and subsequent complex interactions, the vast majority of microorganisms are involved in innumerable natural bioprocesses and contribute an absolutely vital role toward the maintenance of life on Earth, whilst a small minority cause various infectious diseases. The ever-increasing demand for environmental monitoring, sustainable ecosystems, food security, and improved healthcare systems drives the continuous search for inexpensive but reproducible, automated and portable techniques for detection of microbial isolates and understanding their interactions for clinical, environmental, and industrial applications and benefits. Surface-enhanced Raman scattering (SERS) is attracting significant attention for the accurate identification, discrimination and characterization and functional assessment of microbial cells at the single cell level. In this review, we briefly discuss the technological advances in Raman and Fourier transform infrared (FT-IR) instrumentation and their application for the analysis of clinically and industrially relevant microorganisms, biofilms, and biological warfare agents. In addition, we summarize the current trends and future prospects of integrating Raman/SERS-isotopic labeling and cell sorting technologies in parallel, to link genotype-to-phenotype in order to define community function of unculturable microbial cells in mixed microbial communities which possess admirable traits such as detoxification of pollutants and recycling of essential metals.

Quantum Cascade Laser-Based Infrared Microscopy for Label-Free and Automated Cancer Classification in Tissue Sections

A feasibility study using a quantum cascade laser-based infrared microscope for the rapid and label-free classification of colorectal cancer tissues is presented. Infrared imaging is a reliable, robust, automated, and operator-independent tissue classification method that has been used for differential classification of tissue thin sections identifying tumorous regions. However, long acquisition time by the so far used FT-IR-based microscopes hampered the clinical translation of this technique. Here, the used quantum cascade laser-based microscope provides now infrared images for precise tissue classification within few minutes. We analyzed 110 patients with UICC-Stage II and III colorectal cancer, showing 96% sensitivity and 100% specificity of this label-free method as compared to histopathology, the gold standard in routine clinical diagnostics. The main hurdle for the clinical translation of IR-Imaging is overcome now by the short acquisition time for high quality diagnostic images, which is in the same time range as frozen sections by pathologists.

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.

Advantages of infrared transflection micro spectroscopy and paraffin-embedded sample preparation for biological studies

Fourier-Transform Infrared micro-spectroscopy is an excellent method for biological analyses. In this paper, series metal coating films on ITO glass were prepared by the electrochemical method and the different thicknesses of paraffin embedding rat's brain tissue on the substrates were studied by IR micro-spetroscopy in attenuated total reflection (ATR) mode and transflection mode respectively. The Co-Ni-Cu alloy coating film with low cost is good reflection substrates for the IR analysis. The infrared microscopic transflection mode needs not to touch the sample at all and can get the IR spectra with higher signal to noise ratios. The Paraffin-embedding method allows tissues to be stored for a long time for re-analysis to ensure the traceability of the sample. Also it isolates the sample from the metal and avoids the interaction of biological tissue with the metals. The best thickness of the tissues is 4 μm.

Selecting optimal features from Fourier transform infrared spectroscopy for discrete-frequency imaging

Tissue histology utilizing chemical and immunohistochemical labels plays an important role in biomedicine and disease diagnosis. Recent research suggests that mid-infrared (IR) spectroscopic imaging may augment histology by providing quantitative molecular information. One of the major barriers to this approach is long acquisition time using Fourier-transform infrared (FTIR) spectroscopy. Recent advances in discrete frequency sources, particularly quantum cascade lasers (QCLs), may mitigate this problem by allowing selective sampling of the absorption spectrum. However, DFIR imaging only provides a significant advantage when the number of spectral samples is minimized, requiring a priori knowledge of important spectral features. In this paper, we demonstrate the use of a GPU-based genetic algorithm (GA) using linear discriminant analysis (LDA) for DFIR feature selection. Our proposed method relies on pre-acquired broadband FTIR images for feature selection. Based on user-selected criteria for classification accuracy, our algorithm provides a minimal set of features that can be used with DFIR in a time-frame more practical for clinical diagnosis.

Clinical applications of infrared and Raman spectroscopy: state of play and future challenges

This review examines the state-of-the-art of clinical applications of infrared absorption and Raman spectroscopy, outstanding challenges, and progress towards translation.

Applications of mid-infrared spectroscopy in the clinical laboratory setting

Fourier transform mid-infrared (MIR-FTIR) spectroscopy is a nondestructive, label-free, highly sensitive and specific technique that provides complete information on the chemical composition of biological samples. The technique both can offer fundamental structural information and serve as a quantitative analysis tool. Therefore, it has many potential applications in different fields of clinical laboratory science. Although considerable technological progress has been made to promote biomedical applications of this powerful analytical technique, most clinical laboratory analyses are based on spectroscopic measurements in the visible or ultraviolet (UV) spectrum and the potential role of FTIR spectroscopy still remains unexplored. In this review, we present some general principles of FTIR spectroscopy as a useful method to study molecules in specimens by MIR radiation together with a short overview of methods to interpret spectral data. We aim at illustrating the wide range of potential applications of the proposed technique in the clinical laboratory setting with a focus on its advantages and limitations and discussing the future directions. The reviewed applications of MIR spectroscopy include (1) quantification of clinical parameters in body fluids, (2) diagnosis and monitoring of cancer and other diseases by analysis of body fluids, cells, and tissues, (3) classification of clinically relevant microorganisms, and (4) analysis of kidney stones, nails, and faecal fat.

Infrared reflectometry of skin: Analysis of backscattered light from different skin layers

We have recently reported infrared spectroscopy of human skin in vivo using quantum cascade laser excitation and photoacoustic or photothermal detection for non-invasive glucose measurement . Here, we analyze the IR light diffusely reflected from skin layers for spectral contributions of glucose. Excitation of human skin by an external cavity tunable quantum cascade laser in the spectral region from 1000 to 1245cm^-1, where glucose exhibits a fingerprint absorption, yields reflectance spectra with some contributions from glucose molecules. A simple three-layer model of skin was used to calculate the scattering intensities from the surface and from shallow and deeper layers using the Boltzmann radiation transfer equation. Backscattering of light at wavelengths around 10μm from the living skin occurs mostly from the Stratum corneum top layers and the shallow layers of the living epidermis. The analysis of the polarization of the backscattered light confirms this calculation. Polarization is essentially unchanged; only a very small fraction (<3%) is depolarized at 90° with respect to the laser polarization set at 0°. Based on these findings, we propose that the predominant part of the backscattered light is due to specular reflectance and to scattering from layers close to the surface. Diffusely reflected light from deeper layers undergoing one or more scattering processes would appear with significantly altered polarization. We thus conclude that a non-invasive glucose measurement based on backscattering of IR light from skin would have the drawback that only shallow layers containing some glucose at concentrations only weakly related to blood glucose are monitored.

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

Spatial and molecular resolution of diffuse malignant mesothelioma heterogeneity by integrating label-free FTIR imaging, laser capture microdissection and proteomics

Diffuse malignant mesothelioma (DMM) is a heterogeneous malignant neoplasia manifesting with three subtypes: epithelioid, sarcomatoid and biphasic. DMM exhibit a high degree of spatial heterogeneity that complicates a thorough understanding of the underlying different molecular processes in each subtype. We present a novel approach to spatially resolve the heterogeneity of a tumour in a label-free manner by integrating FTIR imaging and laser capture microdissection (LCM). Subsequent proteome analysis of the dissected homogenous samples provides in addition molecular resolution. FTIR imaging resolves tumour subtypes within tissue thin-sections in an automated and label-free manner with accuracy of about 85% for DMM subtypes. Even in highly heterogeneous tissue structures, our label-free approach can identify small regions of interest, which can be dissected as homogeneous samples using LCM. Subsequent proteome analysis provides a location specific molecular characterization. Applied to DMM subtypes, we identify 142 differentially expressed proteins, including five protein biomarkers commonly used in DMM immunohistochemistry panels. Thus, FTIR imaging resolves not only morphological alteration within tissue but it resolves even alterations at the level of single proteins in tumour subtypes. Our fully automated workflow FTIR-guided LCM opens new avenues collecting homogeneous samples for precise and predictive biomarkers from omics studies.

Hyperspectral Raman imaging of human prostatic cells: An attempt to differentiate normal and malignant cell lines by univariate and multivariate data analysis

Hyperspectral Raman images of human prostatic cells have been collected and analysed with several approaches to reveal differences among normal and tumor cell lines. The objective of the study was to test the potential of different chemometric methods in providing diagnostic responses. We focused our analysis on the ν(CH) region (2800-3100cm^-1) owing to its optimal Signal-to-Noise ratio and because the main differences between the spectra of the two cell lines were observed in this frequency range. Multivariate analysis identified two principal components, which were positively recognized as due to the protein and the lipid fractions, respectively. The tumor cells exhibited a modified distribution of the cytoplasmatic lipid fraction (mainly localized alongside the cell boundary) which may result very useful for a preliminary screening. Principal Component analysis was found to provide high contrast and to be well suited for image-processing purposes. Self-Modelling Curve Resolution made available meaningful spectra and relative-concentration values; it revealed a 97% increase of the lipid fraction in the tumor cell with respect to the control. Finally, a univariate approach confirmed significant and reproducible differences between normal and tumor cells.

Fourier-transform infrared spectroscopy for characterization of protein chain reductions in enzymatic reactions

The potential of dry-film Fourier-transform infrared (FTIR) measurements as a monitoring tool for enzymatic hydrolysis of protein-based substrates is explored in this study.

Quantum cascade lasers (QCLs) in biomedical spectroscopy

This review focuses on the recent applications of QCLs in mid-IR spectroscopy of clinically relevant samples.

Ultra-filtration of human serum for improved quantitative analysis of low molecular weight biomarkers using ATR-IR spectroscopy

Monitoring of changes in the concentrations of the low molecular weight constituents enhanced by abundant proteins depletion.

Modern trends in biophotonics for clinical diagnosis and therapy to solve unmet clinical needs

This contribution covers recent original research papers in the biophotonics field. The content is organized into main techniques such as multiphoton microscopy, Raman spectroscopy, infrared spectroscopy, optical coherence tomography and photoacoustic tomography, and their applications in the context of fluid, cell, tissue and skin diagnostics. Special attention is paid to vascular and blood flow diagnostics, photothermal and photodynamic therapy, tissue therapy, cell characterization, and biosensors for biomarker detection.

An Infrared Absorbance Sensor for the Detection of Melanoma in Skin Biopsies

An infrared (IR) absorbance sensor has been designed, realized and tested with the aim of detecting malignant melanomas in human skin biopsies. The sensor has been designed to obtain fast measurements (80 s) of a biopsy using a small light spot (0.5 mm in diameter, typically five to 10 times smaller than the biopsy size) to investigate different biopsy areas. The sensor has been equipped with a monochromator to record the whole IR spectrum in the 3330-3570 nm wavelength range (where methylene and methyl stretching vibrations occur) for a qualitative spectral investigation. From the collected spectra, the CH₂ stretch ratio values (ratio of the absorption intensities of the symmetric to asymmetric CH₂ stretching peaks) are determined and studied as a cancer indicator. Melanoma areas exhibit different spectral shapes and significantly higher CH₂ stretch ratios when compared to healthy skin. The results of the infrared investigation are compared with standard histology. This study shows that the IR sensor is a promising supportive tool to improve the diagnosis of melanoma during histopathological analysis, decreasing the risk of misdiagnosis.