Biochemical Monitoring of Spinal Cord Injury by FT-IR Spectroscopy—Effects of Therapeutic Alginate Implant in Rat Models

Spinal cord injury (SCI) induces complex biochemical changes, which result in inhibition of nervous tissue regeneration abilities. In this study, Fourier-transform infrared (FT-IR) spectroscopy was applied to assess the outcomes of implants made of a novel type of non-functionalized soft calcium alginate hydrogel in a rat model of spinal cord hemisection (n = 28). Using FT-IR spectroscopic imaging, we evaluated the stability of the implants and the effects on morphology and biochemistry of the injured tissue one and six months after injury. A semi-quantitative evaluation of the distribution of lipids and collagen showed that alginate significantly reduced injury-induced demyelination of the contralateral white matter and fibrotic scarring in the chronic state after SCI. The spectral information enabled to detect and localize the alginate hydrogel at the lesion site and proved its long-term persistence in vivo. These findings demonstrate a positive impact of alginate hydrogel on recovery after SCI and prove FT-IR spectroscopic imaging as alternative method to evaluate and optimize future SCI repair strategies.     

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.     

Identification of B and T cells in human spleen sections by infrared microspectroscopic imaging.

BACKGROUND: Infrared spectroscopy probes the chemical composition and molecular structure of complex systems such as tissue and cells. Infrared spectroscopic imaging combines this spectral information with lateral resolution near the single-cell level. We analyzed whether this method is competitive with classic immunohistochemical methods for immunologic tissue and cells. METHODS: We recorded infrared microspectroscopic mapping datasets with a 90- x 90-microm2 aperture from a 3- x 3-mm2 unstained tissue area of human spleen. A secondary follicle containing a germinal center and a T zone were studied in more detail by infrared microspectroscopic imaging with lateral resolution near 5 mum. The results were compared with consecutive sections stained by immunoglobulin D antibodies. T and B lymphocytes were extracted from human blood and served as independent test samples. RESULTS: Cluster analysis of infrared datasets produced images that distinguished anatomical features such as primary and secondary follicles, T zones, arteries, and spleen red pulp. The assignments could be confirmed in consecutive sections by immunohistochemical staining. Main spectral variances between T and B lymphocytes in high-resolution measurements were attributed to specific spectral contributions of DNA and cytosol. CONCLUSIONS: Sensitivity and specificity of the infrared based methods are comparable to those of standard staining procedures for identification of B and T cells. However, infrared spectroscopic imaging can offer advantages in velocity, data throughput, and standardization because of minimal sample preparation. The results emphasize the potential of infrared spectroscopy as an innovative tool for the distinction of cell types, in particular in immunologic tissue.     

Focus: A Multifaceted Battle Against Cancer: Extracting Knowledge from Chemical Imaging Data Using Computational Algorithms for Digital Cancer Diagnosis

Fourier transform infrared (FTIR) spectroscopic imaging is an emerging microscopy modality for clinical histopathologic diagnoses as well as for biomedical research. Spectral data recorded in this modality are indicative of the underlying, spatially resolved biochemical composition but need computerized algorithms to digitally recognize and transform this information to a diagnostic tool to identify cancer or other physiologic conditions. Statistical pattern recognition forms the backbone of these recognition protocols and can be used for highly accurate results. Aided by biochemical correlations with normal and diseased states and the power of modern computer-aided pattern recognition, this approach is capable of combating many standing questions of traditional histology-based diagnosis models. For example, a simple diagnostic test can be developed to determine cell types in tissue. As a more advanced application, IR spectral data can be integrated with patient information to predict risk of cancer, providing a potential road to precision medicine and personalized care in cancer treatment. The IR imaging approach can be implemented to complement conventional diagnoses, as the samples remain unperturbed and are not destroyed. Despite high potential and utility of this approach, clinical implementation has not yet been achieved due to practical hurdles like speed of data acquisition and lack of optimized computational procedures for extracting clinically actionable information rapidly. The latter problem has been addressed by developing highly efficient ways to process IR imaging data but remains one that has considerable scope for progress. Here, we summarize the major issues and provide practical considerations in implementing a modified Bayesian classification protocol for digital molecular pathology. We hope to familiarize readers with analysis methods in IR imaging data and enable researchers to develop methods that can lead to the use of this promising technique for digital diagnosis of cancer.     

Focal plane array infrared imaging: a new way to analyse leaf tissue

* Here, a new approach to macromolecular imaging of leaf tissue using a multichannel focal plane array (FPA) infrared detector was compared with the proven method of infrared mapping with a synchrotron source, using transverse sections of leaves from a species of Eucalyptus. * A new histological method was developed, ideally suited to infrared spectroscopic analysis of leaf tissue. Spatial resolution and the signal-to-noise ratio of the FPA imaging and synchrotron mapping methods were compared. * An area of tissue 350 microm(2) required approx. 8 h to map using the synchrotron technique and approx. 2 min to image using the FPA. The two methods produced similar infrared images, which differentiated all tissue types in the leaves according to their macromolecular chemistry. * The synchrotron and FPA methods produced similar results, with the synchrotron method having superior signal-to-noise ratio and potentially better spatial resolution, whereas the FPA method had the advantage in terms of data acquisition time, expense and ease of use. FPA imaging offers a convenient, laboratory-based approach to microscopic chemical imaging of leaves.     

Label-free biochemical imaging of heart tissue with high-speed spontaneous Raman microscopy

Label-free imaging is desirable for elucidating morphological and biochemical changes of heart tissue in vivo. Spontaneous Raman microscopy (SRM) provides high chemical contrast without labeling, but presents disadvantage in acquiring images due to low sensitivity and consequent long imaging time. Here, we report a novel technique for label-free imaging of rat heart tissues with high-speed SRM combined with resonance Raman effect of heme proteins. We found that individual cardiomyocytes were identified with resonance Raman signal arising mainly from reduced b- and c-type cytochromes, and that cardiomyocytes and blood vessels were imaged by distinguishing cytochromes from oxy- and deoxy-hemoglobin in intact hearts, while cardiomyocytes and fibrotic tissue were imaged by distinguishing cytochromes from collagen type-I in infarct hearts with principal component analysis. These results suggest the potential of SRM as a label-free high-contrast imaging technique, providing a new approach for studying biochemical changes, based on the molecular composition, in the heart.     

Molecular imaging in prostate cancer

Prostate cancer (PCa) is the most common non-cutaneous malignancy in men. New ways to diagnose this cancer in its early stages are needed. Unique genetic and biochemical changes in the cell pave the way for tumors to grow and metastasize. Novel imaging approaches attempt to detect pathological processes in cancer cells at the molecular level. This has led to the establishment and development of the field of molecular imaging. Positron emission tomography (PET), magnetic resonance spectroscopic imaging (MRSI), magnetic resonance imaging (MRI), and radiolabeled antibodies are a few of the modalities that can detect abnormal tumor metabolic processes in the clinical setting. Other imaging techniques are still in their early phase of development but hold promise for the future, including bioluminescence imaging (BLI), measurement of tumor oxygenation, and measurement of uptake of iodine by tumors. These techniques are non-invasive and can spare the patient undue morbidity, while potentially providing early diagnosis, accurate follow-up and, finally, valuable prognostic information.     

Portable optical fiber probe-based spectroscopic scanner for rapid cancer diagnosis: a new tool for intraoperative margin assessment

There continues to be a significant clinical need for rapid and reliable intraoperative margin assessment during cancer surgery. Here we describe a portable, quantitative, optical fiber probe-based, spectroscopic tissue scanner designed for intraoperative diagnostic imaging of surgical margins, which we tested in a proof of concept study in human tissue for breast cancer diagnosis. The tissue scanner combines both diffuse reflectance spectroscopy (DRS) and intrinsic fluorescence spectroscopy (IFS), and has hyperspectral imaging capability, acquiring full DRS and IFS spectra for each scanned image pixel. Modeling of the DRS and IFS spectra yields quantitative parameters that reflect the metabolic, biochemical and morphological state of tissue, which are translated into disease diagnosis. The tissue scanner has high spatial resolution (0.25 mm) over a wide field of view (10 cm × 10 cm), and both high spectral resolution (2 nm) and high spectral contrast, readily distinguishing tissues with widely varying optical properties (bone, skeletal muscle, fat and connective tissue). Tissue-simulating phantom experiments confirm that the tissue scanner can quantitatively measure spectral parameters, such as hemoglobin concentration, in a physiologically relevant range with a high degree of accuracy (<5% error). Finally, studies using human breast tissues showed that the tissue scanner can detect small foci of breast cancer in a background of normal breast tissue. This tissue scanner is simpler in design, images a larger field of view at higher resolution and provides a more physically meaningful tissue diagnosis than other spectroscopic imaging systems currently reported in literatures. We believe this spectroscopic tissue scanner can provide real-time, comprehensive diagnostic imaging of surgical margins in excised tissues, overcoming the sampling limitation in current histopathology margin assessment. As such it is a significant step in the development of a platform technology for intraoperative management of cancer, a clinical problem that has been inadequately addressed to date.     

Imaging of Scleral Collagen Deformation Using Combined Confocal Raman Microspectroscopy and Polarized Light Microscopy Techniques

This work presents an optospectroscopic characterization technique for soft tissue microstructure using site-matched confocal Raman microspectroscopy and polarized light microscopy. Using the technique, the microstructure of soft tissue samples is directly observed by polarized light microscopy during loading while spatially correlated spectroscopic information is extracted from the same plane, verifying the orientation and arrangement of the collagen fibers. Results show the response and orientation of the collagen fiber arrangement in its native state as well as during tensile and compressive loadings in a porcine sclera model. An example is also given showing how the data can be used with a finite element program to estimate the strain in individual collagen fibers. The measurements demonstrate features that indicate microstructural reorganization and damage of the sclera’s collagen fiber arrangement under loading. The site-matched confocal Raman microspectroscopic characterization of the tissue provides a qualitative measure to relate the change in fibrillar arrangement with possible chemical damage to the collagen microstructure. Tests and analyses presented here can potentially be used to determine the stress-strain behavior, and fiber reorganization of the collagen microstructure in soft tissue during viscoelastic response.     

皮肤组织显微共聚焦拉曼光谱成像研究

显微共聚焦拉曼光谱成像技术(Confocal Raman Microspectroscopy Imaging,CRMI)能够对样品微区进行精确无损的拉曼光谱分析和光谱图像扫描,提供生物样品的无损高分辨光学信息。本项研究工作,利用CRMI技术实验获取了正常人体离体皮肤组织的拉曼光谱特征,并结合典型特征峰的扫描图像,探讨了脂类、蛋白质等成分在皮肤真皮层的分布特点。实验发现皮肤组织真皮层内胶原蛋白的拉曼特征峰1 248 cm-1强度及其空间分布尤为突出,这一实验结果与组织学中胶原纤维占真皮结缔组织95%的事实相符。实验结果显示,CRMI技术能够全面诠释生物组织内部生化组成与分布信息,在实验描述皮肤组织病理变化的分子生物学机制方面具有广阔的应用前景。     

Optical fluorescence imaging with shortwave infrared light emitter nanomaterials for in vivo cell tracking in regenerative medicine

In vivo tracking and monitoring of adoptive cell transfer has a distinct importance in cell‐based therapy. There are many imaging modalities for in vivo monitoring of biodistribution, viability and effectiveness of transferred cells. Some of these procedures are not applicable in the human body because of low sensitivity and high possibility of tissue damages. Shortwave infrared region (SWIR) imaging is a relatively new technique by which deep biological tissues can be potentially visualized with high resolution at cellular level. Indeed, scanning of the electromagnetic spectrum (beyond 1000 nm) of SWIR has a great potential to increase sensitivity and resolution of in vivo imaging for various human tissues. In this review, molecular imaging modalities used for monitoring of biodistribution and fate of administered cells with focusing on the application of non‐invasive optical imaging at shortwave infrared region are discussed in detail.     

Hierarchical band-target entropy minimization curve resolution and Pearson VII curve-fitting analysis of cellular protein infrared imaging spectra

A soft-modeling multivariate numerical approach that combines self-modeling curve resolution (SMCR) and mixed Lorentzian-Gaussian curve fitting was successfully implemented for the first time to elucidate spatially and spectroscopically resolved spectral information from infrared imaging data of oral mucosa cells. A novel variant form of the robust band-target entropy minimization (BTEM) SMCR technique, coined as hierarchical BTEM (hBTEM), was introduced to first cluster similar cellular infrared spectra using the unsupervised hierarchical leader-follower cluster analysis (LFCA) and subsequently apply BTEM to clustered subsets of data to reconstruct three protein secondary structure (PSS) pure component spectra—α-helix, β-sheet, and ambiguous structures—that associate with spatially differentiated regions of the cell infrared image. The Pearson VII curve-fitting procedure, which approximates a mixed Lorentzian-Gaussian model for spectral band shape, was used to optimally curve fit the resolved amide I and II bands of various hBTEM reconstructed PSS pure component spectra. The optimized Pearson VII band-shape parameters and peak center positions serve as means to characterize amide bands of PSS spectra found in various cell locations and for approximating their actual amide I/II intensity ratios. The new hBTEM methodology can also be potentially applied to vibrational spectroscopic datasets with dynamic or spatial variations arising from chemical reactions, physical perturbations, pathological states, and the like.     

Cerebral Glioma Grading Using Bayesian Network with Features Extracted from Multiple Modalities of Magnetic Resonance Imaging

Many modalities of magnetic resonance imaging (MRI) have been confirmed to be of great diagnostic value in glioma grading. Contrast enhanced T1-weighted imaging allows the recognition of blood-brain barrier breakdown. Perfusion weighted imaging and MR spectroscopic imaging enable the quantitative measurement of perfusion parameters and metabolic alterations respectively. These modalities can potentially improve the grading process in glioma if combined properly. In this study, Bayesian Network, which is a powerful and flexible method for probabilistic analysis under uncertainty, is used to combine features extracted from contrast enhanced T1-weighted imaging, perfusion weighted imaging and MR spectroscopic imaging. The networks were constructed using K2 algorithm along with manual determination and distribution parameters learned using maximum likelihood estimation. The grading performance was evaluated in a leave-one-out analysis, achieving an overall grading accuracy of 92.86% and an area under the curve of 0.9577 in the receiver operating characteristic analysis given all available features observed in the total 56 patients. Results and discussions show that Bayesian Network is promising in combining features from multiple modalities of MRI for improved grading performance.     

High Definition Infrared Spectroscopic Imaging for Lymph Node Histopathology

Chemical imaging is a rapidly emerging field in which molecular information within samples can be used to predict biological function and recognize disease without the use of stains or manual identification. In Fourier transform infrared (FT-IR) spectroscopic imaging, molecular absorption contrast provides a large signal relative to noise. Due to the long mid-IR wavelengths and sub-optimal instrument design, however, pixel sizes have historically been much larger than cells. This limits both the accuracy of the technique in identifying small regions, as well as the ability to visualize single cells. Here we obtain data with micron-sized sampling using a tabletop FT-IR instrument, and demonstrate that the high-definition (HD) data lead to accurate identification of multiple cells in lymph nodes that was not previously possible. Highly accurate recognition of eight distinct classes - naïve and memory B cells, T cells, erythrocytes, connective tissue, fibrovascular network, smooth muscle, and light and dark zone activated B cells was achieved in healthy, reactive, and malignant lymph node biopsies using a random forest classifier. The results demonstrate that cells currently identifiable only through immunohistochemical stains and cumbersome manual recognition of optical microscopy images can now be distinguished to a similar level through a single IR spectroscopic image from a lymph node biopsy.     

Infrared imaging microscopy of bone: Illustrations from a mouse model of Fabry disease

Bone is a complex tissue whose composition and properties vary with age, sex, diet, tissue type, health and disease. In this review, we demonstrate how infrared spectroscopy and infrared spectroscopic imaging can be applied to the study of these variations. A specific example of mice with Fabry disease (a lipid storage disease) is presented in which it is demonstrated that the bones of these young animals, while showing typical spatial variation in mineral content, mineral crystal size, and collagen maturity, do not differ from the bones of age- and sex-matched wild type animals.     

Infrared imaging microscopy of bone: illustrations from a mouse model of Fabry disease

Bone is a complex tissue whose composition and properties vary with age, sex, diet, tissue type, health and disease. In this review, we demonstrate how infrared spectroscopy and infrared spectroscopic imaging can be applied to the study of these variations. A specific example of mice with Fabry disease (a lipid storage disease) is presented in which it is demonstrated that the bones of these young animals, while showing typical spatial variation in mineral content, mineral crystal size, and collagen maturity, do not differ from the bones of age- and sex-matched wild type animals.     

An emerging method for rapid characterization of feed structures and feed component matrix at a cellular level and relation to feed quality and nutritive value

Feed quality, feed characteristics, nutrient utilization and digestive behaviour are closely related to: (i) total feed composition, (ii) feed intrinsic structures, and (iii) biological component matrix (such as protein to starch matrix, protein to carbohydrate matrix). Conventional "wet" chemical analysis can determine total chemical composition, but fails to detect the feed intrinsic structures and biological component matrix due to destruction of feed samples during the processing for chemical analysis and the "wet" chemical analysis cannot link structural information to chemical information within intact feed tissue. Recently, advanced synchrotron-based Fourier transform infrared (FTIR) microspectroscopy has been developed as a non-destructive and non-invasive structural-chemical analytical technique. This technique can link chemical information to structural information of biological samples within intact tissue within cellular dimensions. It can provide four kinds of information simultaneously: tissue composition, tissue structure, tissue chemistry and tissue environment. However, this novel technique has been found mainly for medical science research, extremely rare for feed science and nutrition research. The objective of this review article was to illustrate synchrotron-based FTIR microspectroscopy as a novel research tool for rapid characterization of feed structures at a cellular level and for detection of chemical features and molecular chemical make-up of feed biological component matrix and nutrient interaction. The emphasis of this article was to show that feed structural-chemical features at a cellular level are closely related to feed characteristics, feed quality and nutritive value in animals. The synchrotron-based technology will provide us with a greater understanding of the plant-animal interface.     

Forensic visualization of foreign matter in human tissue by near-infrared spectral imaging: methodology and data mining strategies.

BACKGROUND: Rapidity of data acquisition, high image fidelity and large field of view are of tremendous value when looking for chemical contaminants or for the proverbial "needle in the haystack" - in this case foreign inclusions in histologic sections of biopsy or autopsy tissues. Near infrared chemical imaging is one of three chemical imaging techniques (NIR, MIR and Raman) based on vibrational spectroscopy, and provides distinct technical advantages for this application. METHODS: We have chosen to utilize and evaluate near infrared (NIR) imaging for studies of foreign materials in tissue because the experimental configuration is relatively simple, data collection is rapid, and large sample areas can be screened with high image fidelity and spatial resolution. RESULTS: We have shown that NIR imaging can readily find and identify silicone gel inclusions in biological tissue samples. Additionally, preliminary results indicate that spectral signatures in the data set are also potentially sensitive to structural changes in the surrounding tissue that may be induced by the foreign body. CONCLUSIONS: NIR chemical imaging is a powerful, non-destructive tool for localization and identifying foreign contaminants in biological tissue. Preliminary results indicate that NIR imaging is also sensitive enough to differentiate tissue types (perhaps based on collagen structural differences), and provide data on the spatial localization of these components.