Near infrared Raman spectroscopic mapping of native brain tissue and intracranial tumors

This study assessed the diagnostic potential of Raman spectroscopic mapping by evaluating its ability to distinguish between normal brain tissue and the human intracranial tumors gliomas and meningeomas. Seven Raman maps of native specimens were collected ex vivo by a Raman spectrometer with 785 nm excitation coupled to a microscope with a motorized stage. Variations within each Raman map were analyzed by cluster analysis. The dependence of tissue composition on the tissue type in cluster averaged Raman spectra was shown by linear combinations of reference spectra. Normal brain tissue was found to contain higher levels of lipids, intracranial tumors have more hemoglobin and lower lipid to protein ratios, meningeomas contain more collagen with maximum collagen content in normal meninges. One sample was studied without freezing. Whereas tumor regions did not change significantly, spectral changes were observed in the hemoglobin component after snap freezing and thawing to room temperature. The results constitute a basis for subsequent Raman studies to develop classification models for diagnosis of brain tissue.     

Selective sampling using confocal Raman spectroscopy provides enhanced specificity for urinary bladder cancer diagnosis

In recent years, Raman spectroscopy has shown substantive promise in diagnosing bladder cancer, especially due to its exquisite molecular specificity. The ability to reduce false detection rates in comparison to existing diagnostic tools such as photodynamic diagnosis makes Raman spectroscopy particularly attractive as a complementary diagnostic tool for real-time guidance of transurethral resection of bladder tumor (TURBT). Nevertheless, the state-of-the-art high-volume Raman spectroscopic probes have not reached the expected levels of specificity thereby impeding their clinical translation. To address this issue, we propose the use of a confocal Raman probe for bladder cancer diagnosis that can boost the specificity of the diagnostic algorithm based on its suppression of the out-of-focus non-analyte-specific signals emanating from the neighboring normal tissue. In this article, we engineer and apply such a probe, having depth of field of approximately 280?μm, for Raman spectral acquisition from ex vivo normal and cancerous TURBT samples. Using this clinical dataset, a diagnostic algorithm based on principal component analysis and logistic regression is developed. We demonstrate that this approach results in comparable sensitivity but significantly higher specificity in relation to high-volume Raman spectral data. The application of only two principal components is sufficient for the discrimination of the samples underlining the robustness of the algorithm. Further, no discordance between replicate spectra is observed emphasizing the reproducible nature of the current diagnostic assessment. The high levels of sensitivity and specificity achieved in this proof-of-concept study opens substantive avenues for application of a confocal Raman probe during endoscopic procedures related to diagnosis and treatment of bladder cancer.

High-wavenumber FT-Raman spectroscopy for in vivo and ex vivo measurements of breast cancer

The identification of normal and cancer breast tissue of rats was investigated using high-frequency (HF) FT-Raman spectroscopy with a near-infrared excitation source on in vivo and ex vivo measurements. Significant differences in the Raman intensities of prominent Raman bands of lipids and proteins structures (2,800?C3,100?cm^?1) as well as in the broad band of water (3,100?C3,550?cm^?1) were observed in mean normal and cancer tissue spectra. The multivariate statistical analysis methods of principal components analysis (PCA) and linear discriminant analysis (LDA) were performed on all high-frequency Raman spectra of normal and cancer tissues. LDA results with the leave-one-out cross-validation option yielded a discrimination accuracy of 77.2, 83.3, and 100% for in vivo transcutaneous, in vivo skin-removed, and ex vivo biopsy HF Raman spectra. Despite the lower discrimination value for the in vivo transcutaneous measurements, which could be explained by the breathing movement and skin influences, our results showed good accuracy in discriminating between normal and cancer breast tissue samples. To support this, the calculated integration areas from the receiver-operating characteristic (ROC) curve yielded 0.86, 0.94, and 1.0 for in vivo transcutaneous, in vivo skin-removed, and ex vivo biopsy measurements, respectively. The feasibility of using HF Raman spectroscopy as a clinical diagnostic tool for breast cancer detection and monitoring is due to no interfering contribution from the optical fiber in the HF Raman region, the shorter acquisition time due to a more intense signal in the HF Raman region, and the ability to distinguish between normal and cancerous tissues.     

Raman spectroscopic signature of blood and its potential application to forensic body fluid identification

Near-infrared (NIR) Raman spectroscopy was used to measure spectra of dried human blood samples from multiple donors. Two major questions addressed in this paper involve the influence of sample heterogeneity and potential Raman spectral variations that could arise between different donors of blood. Advanced statistical analysis of spectra obtained from multiple spots on dry samples showed that dry blood is chemically heterogeneous, and its Raman spectra could be presented very well as a linear combination of a fluorescent background and two Raman spectroscopic components that are dominated by hemoglobin and fibrin, respectively. Each sample Raman spectrum contains the same major peaks, but the relative contribution of the hemoglobin and fibrin components varies with the donor. Therefore, no single spectrum could adequately represent an experimental Raman spectrum of dry blood in a quantitative way, but rather the combination of hemoglobin and fibrin spectral components could be considered to be a spectroscopic signature for blood. This proof-of-concept approach shows the potential for Raman spectroscopy to be used in forensic analysis to identify an unknown substance such as blood.     

Study of normal colorectal tissue by FT-Raman spectroscopy

FT-Raman spectroscopy was employed to study normal human colorectal tissues in vitro with the aim of evaluating the spectral differences of the complex colon mucous in order to establish a characteristic Raman spectrum. The samples were collected from 39 patients, providing 144 spectra for the statistical analysis. The results enable one to estabilish three well-defined spectroscopic groups of non-altered coloretal tissues that were consistently checked by statistical (clustering) and biological (histopathology) analyses: group 1 is represented by samples with the presence of epithelial layer, connective tissue papillae, and smooth muscle tissue; group 2 comprises tissues with epithelial layer and connective tissue papillae; group 3 presented mostly fatty and slack conjunctive tissue. The study reveals the existence of an intrinsic spectral variability for each patient that must be considered when sampling tissues fragments to build a spectral database. This is the first step for future studies and applications of Raman spectroscopy to optical biopsy and diagnosis of colorectal cancer.     

Raman spectroscopy in combination with background near-infrared autofluorescence enhances the in vivo assessment of malignant tissues

The diagnostic ability of optical spectroscopy techniques, including near-infrared (NIR) Raman spectroscopy, NIR autofluorescence spectroscopy and the composite Raman and NIR autofluorescence spectroscopy, for in vivo detection of malignant tumors was evaluated in this study. A murine tumor model, in which BALB/c mice were implanted with Meth-A fibrosarcoma cells into the subcutaneous region of the lower back, was used for this purpose. A rapid-acquisition dispersive-type NIR Raman system was employed for tissue Raman and NIR autofluorescence spectroscopic measurements at 785-nm laser excitation. High-quality in vivo NIR Raman spectra associated with an autofluorescence background from mouse skin and tumor tissue were acquired in 5 s. Multivariate statistical techniques, including principal component analysis (PCA) and linear discriminant analysis (LDA), were used to develop diagnostic algorithms for differentiating tumors from normal tissue based on their spectral features. Spectral classification of tumor tissue was tested using a leave-one-out, cross-validation method, and the receiver operating characteristic (ROC) curves were used to further evaluate the performance of diagnostic algorithms derived. Thirty-two in vivo Raman, NIR fluorescence and composite Raman and NIR fluorescence spectra were analyzed (16 normal, 16 tumors). Classification results obtained from cross-validation of the LDA model based on the three spectral data sets showed diagnostic sensitivities of 81.3%, 93.8% and 93.8%; specificities of 100%, 87.5% and 100%; and overall diagnostic accuracies of 90.6%, 90.6% and 96.9% respectively, for tumor identification. ROC curves showed that the most effective diagnostic algorithms were from the composite Raman and NIR autofluorescence techniques.     

In and ex vivo breast disease study by Raman spectroscopy

In this work, Raman spectra in the 900?C1,800?cm^?1 wavenumber region of in vivo and ex vivo breast tissues of both healthy mice (normal) and mice with induced mammary gland tumors (abnormal) were measured. In the case of the in vivo tissues, the Raman spectra were collected for both transcutaneous (with skin) and skin-removed tissues. To identify the spectral differences between normal and cancer breast tissue, the paired t-test was carried out for each wavenumber using the whole spectral range from both groups. Quadratic discriminate analysis based on principal component analysis (PCA) was also used to determine and evaluate differences in the Raman spectra for the various samples as a basis for diagnostic purposes. The differences in the Raman spectra of the samples were due to biochemical changes at the molecular, cellular and tissue levels. The sensitivity and specificity of the classification scheme based on the differences in the Raman spectra obtained by PCA were evaluated using the receiver operating characteristic (ROC) curve. The in vivo transcutaneous normal and abnormal tissues were correctly classified based on their measured Raman spectra with a discriminant proportion of 73%, while the in vivo skin-removed normal and abnormal tissues were correctly classified again based on their measured Raman spectra with a discriminant proportion of 86%. This result reveals a strong influence due to the skin of the breast, which decreased the specificity by 11%. Finally, the results from ex vivo measurements gave the highest specificity and sensitivity: 96 and 97%, respectively, as well as a largest percentage for correct discrimination: 94%. Now that the important bands have been experimentally determined in this and other works, what remains is for first principles molecular-level simulations to determine whether the changes are simply due to conformational changes, due to aggregation, due to changes in the environment, or complex interactions of all of the above.     

Analysis of human brain tissue, brain tumors and tumor cells by infrared spectroscopic mapping

This study uses infrared (IR) spectroscopic, point detection, mapping procedures to examine tissue samples from normal brain specimens and from astrocytic gliomas, the most frequent human brain tumors. Model systems were derived from cultured glioma cell lines. IR spectra of normal tissue sections distinguished white matter from gray matter by increased spectral contributions from lipids and cholesterol. Qualitatively the same differences were found in IR spectra of low and high grade glioma tissue sections pointing to a significant reduction of brain lipids with increasing malignancy. Whereas spectral contributions of proteins and lipids were similar in IR spectra of glioma cells and tissues, nucleic acid bands were more intense for cells suggesting higher proliferative activities. For statistical analyses of IR spectroscopic maps from 71 samples, a parameter for the lipid to protein ratio was introduced involving the CH(2) symmetric stretch band with lipids as main contributors and the amide I band of proteins. As this parameter correlated with the grade of gliomas obtained from standard histopathological examination, it was applied to classify brain tissue sections based on IR spectroscopic mapping.     

Multivariate classification of pigments and inks using combined Raman spectroscopy and LIBS

The authenticity of objects and artifacts is often the focus of forensic analytic chemistry. In document fraud cases, the most important objective is to determine the origin of a particular ink. Here, we introduce a new approach which utilizes the combination of two analytical methods, namely Raman spectroscopy and laser-induced breakdown spectroscopy (LIBS). The methods provide complementary information on both molecular and elemental composition of samples. The potential of this hyphenation of spectroscopic methods is demonstrated for ten blue and black ink samples on white paper. LIBS and Raman spectra from different inks were fused into a single data matrix, and the number of different groups of inks was determined through multivariate analysis, i.e., principal component analysis, soft independent modelling of class analogy, partial least-squares discriminant analysis, and support vector machine. In all cases, the results obtained with the combined LIBS and Raman spectra were found to be superior to those obtained with the individual Raman or LIBS data sets.     

Investigation of the specificity of Raman spectroscopy in non-invasive blood glucose measurements

Although several in vivo blood glucose measurement studies have been performed by different research groups using near-infrared (NIR) absorption and Raman spectroscopic techniques, prospective prediction has proven to be a challenging problem. An important issue in this case is the demonstration of causality of glucose concentration to the spectral information, especially as the intrinsic glucose signal is smaller compared with that of the other analytes in the blood–tissue matrix. Furthermore, time-dependent physiological processes make the relation between glucose concentration and spectral data more complex. In this article, chance correlations in Raman spectroscopy-based calibration model for glucose measurements are investigated for both in vitro (physical tissue models) and in vivo (animal model and human subject) cases. Different spurious glucose concentration profiles are assigned to the Raman spectra acquired from physical tissue models, where the glucose concentration is intentionally held constant. Analogous concentration profiles, in addition to the true concentration profile, are also assigned to the datasets acquired from an animal model during a glucose clamping study as well as a human subject during an oral glucose tolerance test. We demonstrate that the spurious concentration profile-based calibration models are unable to provide prospective predictions, in contrast to those based on actual concentration profiles, especially for the physical tissue models. We also show that chance correlations incorporated by the calibration models are significantly less in Raman as compared to NIR absorption spectroscopy, even for the in vivo studies. Finally, our results suggest that the incorporation of chance correlations for in vivo cases can be largely attributed to the uncontrolled physiological sources of variations. Such uncontrolled physiological variations could either be intrinsic to the subject or stem from changes in the measurement conditions.     

In vivo near-infrared Raman spectroscopy: demonstration of feasibility during clinical gastrointestinal endoscopy

Raman spectroscopy (RS) has potential for disease classification within the gastrointestinal tract (GI). A near-infrared (NIR) fiber-optic RS system has been developed previously. This study reports the first in vivo Raman spectra of human gastrointestinal tissues measured during routine clinical endoscopy. This was achieved by using this system with a fiber-optic probe that was passed through the endoscope instrument channel and placed in contact with the tissue surface. Spectra could be obtained with good signal-to-noise ratio in 5 s. The effects on the spectra of varying the pressure of the probe tip on the tissue and of the probe-tissue angle were determined and shown to be insignificant. The limited set of spectra from normal and diseased tissues revealed only subtle differences. Therefore, powerful spectral-sorting algorithms, successfully implemented in prior ex vivo studies, are required to realize the full diagnostic potential of RS for tissue classification in the GI.     

Safety Analysis: Relative Risks of Ultraviolet Exposure from Fluorescence Spectroscopy and Colposcopy Are Comparable*

Fluorescence spectroscopy is a promising tool for use in the diagnosis of disease in human tissue. However, few published reports have evaluated the safety of this technique, despite the fact that many spectroscopic systems use UV illumination. This study determined the relative risk associated with light exposure from spectroscopic systems compared with the traditional light sources that are used to illuminate tissue and direct biopsies. We compared spectroscopic detection systems for the cervix to the colposcope, a low-power microscope routinely used to illuminate the cervix, which does not cause any known photochemical damage. We measured the average spectral irradiance (W/[cm²nm]) and the average tissue exposure time during a diagnostic colposcopy examination. To quantify the relative risks, we multiplied illumination spectra by several action spectra from the literature and compared the areas under the curves corresponding to each procedure. The risk associated with the average power colposcope served as our basis for comparison. We conclude that the risks of illumination using spectroscopic systems are lower than or comparable to those already encountered in routine diagnostic procedures such as colposcopy with an average power colposcope. Spectroscopic examination can be associated with a somewhat higher risk than a colposcopy with the lowest power colposcope or a shorter than average colposcopy. The analysis presented can be repeated to estimate the magnitude of risks associated with other spectroscopic diagnostic devices.     

Raman spectroscopic analysis of the Maya wall paintings in Ek'Balam, Mexico

Raman spectroscopy has been applied to the examination of wall painting fragments from the archaeological site of Ek'Balam (Yucatán, Mexico). Thirty-three samples have been studied, all originating from room 23 of the Acropolis, and being representative of the painting technique at Ek'Balam during the late Classic Maya period. Several pigments such as haematite, calcite, carbon, cinnabar and indigo were identified in these samples. The latter pigment was presumed to be present as 'Maya blue', which is an intercalation product of indigo and palygorskite clay. The observed Raman spectra are reported and some band assignments have been made. This survey is the first Raman spectroscopic examination of a whole set of pigments in archaeological Maya wall painting fragments.     

Monte Carlo simulation of near infrared autofluorescence measurements of in vivo skin

The autofluorescence properties of normal human skin in the near-infrared (NIR) spectral range were studied using Monte Carlo simulation. The light-tissue interactions including scattering, absorption and anisotropy propagation of the regenerated autofluorescence photons in the skin tissue were taken into account in the theoretical modeling. Skin was represented as a turbid seven-layered medium. To facilitate the simulation, ex vivo NIR autofluorescence spectra and images from different skin layers were measured from frozen skin vertical sections to define the intrinsic fluorescence properties. Monte Carlo simulation was then used to study how the intrinsic fluorescence spectra were distorted by the tissue reabsorption and scattering during in vivo measurements. We found that the reconstructed model skin spectra were in good agreement with the measured in vivo skin spectra from the same anatomical site as the ex vivo tissue sections, demonstrating the usefulness of this modeling. We also found that difference exists over the melanin fluorescent wavelength range (880-910 nm) between the simulated spectrum and the measured in vivo skin spectrum from a different anatomical site. This difference suggests that melanin contents may affect in vivo skin autofluorescence properties, which deserves further investigation.     

Intra-operative optical diagnostics with vibrational spectroscopy

Established methods for characterization of tissue and diagnostics, for example histochemistry, magnetic resonance imaging (MRI), X-ray tomography, or positron emission tomography (PET), are mostly not suitable for intra-operative use. However, there is a clear need for an intra-operative diagnostics especially to identify the borderline between normal and tumor tissue. Currently, vibrational spectroscopy techniques (both Raman and infrared) complement the standard methods for tissue diagnostics. Vibrational spectroscopy has the potential for intra-operative use, because it can provide a biochemically based profile of tissue in real time and without requiring additional contrast agents, which may perturb the tissue under investigation. In addition, no electric potential needs to be applied, and the measurements are not affected by electromagnetic fields. Currently, promising approaches include Raman fiber techniques and nonlinear Raman spectroscopy. Infrared spectroscopy is also being used to examine freshly resected tissue ex vivo in the operating theater. The immense volume of information contained in Raman and infrared spectra requires multivariate analysis to extract relevant information to distinguish different types of tissue. The promise and limitations of vibrational spectroscopy methods as intra-operative tools are surveyed in this review.     

C-H stretching vibrations of methyl, methylene and methine groups at the vapor/alcohol (N = 1-8) interfaces

In IR and Raman spectral studies, the congestion of the vibrational modes in the C-H stretching region between 2800 and 3000 cm(-1) has complicated spectral assignment, conformational analysis, and structural and dynamics studies, even with quite a few of the simplest molecules. To resolve these issues, polarized spectra measurement on a well aligned sample is generally required. Because the liquid interface is generally ordered and molecularly thin, and sum frequency generation vibrational spectroscopy (SFG-VS) is an intrinsically coherent polarization spectroscopy, SFG-VS can be used for discerning details in vibrational spectra of the interfacial molecules. Here we show that, from systematic molecular symmetry and SFG-VS polarization analysis, a set of polarization selection rules could be developed for explicit assignment of the SFG vibrational spectra of the C-H stretching modes. These polarization selection rules helped assignment of the SFG-VS spectra of vapor/alcohol (n = 1-8) interfaces with unprecedented details. Previous approach on assignment of these spectra relied on IR and Raman spectral assignment, and they were not able to give such detailed assignment of the SFG vibrational spectra. Sometimes inappropriate assignment was made, and consequently misleading conclusions on interfacial structure, conformation and even dynamics were reached. With these polarization rules in addition to knowledge from IR and Raman studies, new structural information and understanding of the molecular interactions at these interfaces were obtained, and some new spectral features for the C-H stretching modes were also identified. Generally speaking, these new features can be applied to IR and Raman spectroscopic studies in the condensed phase. Therefore, the advancement on vibrational spectra assignment may find broad applications in the related fields using IR and Raman as vibrational spectroscopic tools.     

Label‐Free Molecular Imaging of Biological Cells and Tissues by Linear and Nonlinear Raman Spectroscopic Approaches

Raman spectroscopy is an emerging technique in bioanalysis and imaging of biomaterials owing to its unique capability of generating spectroscopic fingerprints. Imaging cells and tissues by Raman microspectroscopy represents a nondestructive and label‐free approach. All components of cells or tissues contribute to the Raman signals, giving rise to complex spectral signatures. Resonance Raman scattering and surface‐enhanced Raman scattering can be used to enhance the signals and reduce the spectral complexity. Raman‐active labels can be introduced to increase specificity and multimodality. In addition, nonlinear coherent Raman scattering methods offer higher sensitivities, which enable the rapid imaging of larger sampling areas. Finally, fiber‐based imaging techniques pave the way towards in vivo applications of Raman spectroscopy. This Review summarizes the basic principles behind medical Raman imaging and its progress since 2012.     

Raman endoscopy for in vivo differentiation between benign and malignant ulcers in the stomach

The aim of this study was to evaluate the clinical utility of an image-guided Raman endoscopy technique for in vivo differential diagnosis of benign and malignant ulcerous lesions in the stomach. A rapid-acquisition image-guided Raman endoscopy system with 785 nm laser excitation has been developed to acquire in vivo gastric tissue Raman spectra within 0.5 s during clinical gastroscopic examinations. A total of 1102 in vivo Raman spectra were acquired from 71 gastric patients, in which 924 Raman spectra were from normal tissue, 111 Raman spectra were from benign ulcers whereas 67 Raman spectra were from ulcerated adenocarcinoma. There were distinctive spectral differences in Raman spectra among normal mucosa, benign ulcers and malignant ulcers, particularly in the spectral ranges of 800-900, 1000-1100, 1245-1335, 1440-1450 and 1500-1800 cm(-1), which primarily contain signals related to proteins, DNA, lipids and blood. The malignant ulcerous lesions showed Raman signals to be mainly associated with abnormal nuclear activity and decrease in lipids as compared to benign ulcers. Partial least squares-discriminant analysis (PLS-DA) was employed to generate multi-class diagnostic algorithms for classification of Raman spectra of different gastric tissue types. The PLS-DA algorithms together with leave-one tissue site-out, cross validation technique yielded diagnostic sensitivities of 90.8%, 84.7%, 82.1%, and specificities of 93.8%, 94.5%, 95.3%, respectively, for classification of normal mucosa, benign and malignant ulcerous lesions in the stomach. This work demonstrates that image-guided Raman endoscopy technique associated with PLS-DA diagnostic algorithms has for the first time promising clinical potential for rapid, in vivo diagnosis and detection of malignant ulcerous gastric lesions at the molecular level.     

Organotypic raft cultures as an effective in vitro tool for understanding Raman spectral analysis of tissue

There is a growing body of evidence showing that optical spectroscopy has the potential to be a useful in vivo diagnostic tool. Yet, so far there is no definitive cellular and biochemical understanding for the differences seen in the spectra from different tissue categories and disease states. In this study, we examine the use of organotypic raft cultures as an in vitro model of in vivo tissue conditions in an attempt to overcome some of the limitations of previously used methods. Organotypic raft cultures resembling normal and dysplastic epithelial cervical tissue were constructed and grown at an air-liquid interface for 2 weeks. Raman spectra of normal as well as dysplastic raft cultures were measured and compared with in vivo spectra from the corresponding tissue type. Histologic comparisons ensured that the raft cultures had similar structure and morphology to the corresponding intact tissue types. Raman spectra were also acquired from different layers of tissue. Spectral comparisons show that the Raman spectra of the raft cultures are similar to the spectra acquired from the cervix in vivo for both normal and dysplastic tissues. These results show that organotypic raft cultures are an effective and useful tool for the cellular and biochemical analysis of tissue spectroscopy.     

中红外光纤技术用于口腔肿瘤在体原位检测的研究

肿瘤是严重威胁人类健康和生命的疾病,早期诊断和及时治疗是提高肿瘤病人存活率的重要因素,肿瘤的发生和发展一般可分为3个阶段：(1)基因突变;(2)生物分子组成和结构发生改变;(3)细胞和组织形态发生变化,目前常用的影像学方法只能检测较大的肿块,组织标本的病理诊断法需在