Optical diagnosis of peritoneal metastases by infrared microscopic imaging

Fourier transform infrared (FTIR) spectroscopy is nowadays widely accepted as a technique with high potential for diagnosis of cancerous tissues. This study presents an example of the investigation of peritoneal metastases by FTIR microimaging. Peritoneal malignancies are generally secondary localizations of primary visceral cancers such as ovarian, stomach or colon cancers. By analysing simultaneously both formalin-fixed paraffin-embedded and frozen specimens, we examined malignant and non-malignant (i.e. fibrotic and cicatricial) peritoneal lesions. Paraffin-embedded tissues were analysed without any previous dewaxing. Multivariate statistical approaches, based on the classification of infrared data by hierarchical cluster analysis, allowed the discrimination of these various samples. Microimaging also permits the revelation of the heterogeneity of the tissue: it was possible to localize precisely the cancerous areas, and to distinguish, on the basis of their spectral signatures, the peritumoral neighbouring connective tissue close to the carcinomatous areas from the connective tissue distant from the cancerous areas. These spectral differences could be useful as complementary information to study molecular changes associated with the malignancy.     

The Effects of ex vivo Handling Procedures on the Near-Infrared Raman Spectra of Normal Mammalian Tissues

Recent studies in the literature have investigated the feasibility of tissue diagnostics based on Raman spectroscopy. The majority of these compare the ex vivo spectra of normal and diseased tissue. Due to the time lapse between tissue excision and spectroscopic examination, samples must be frozen or otherwise preserved to maintain their native biochemical states. In order to establish optimum procedures for ex vivo Raman spectroscopy of tissue, the effects of tissue drying, formalin fixing, snap freezing, tissue freezing in optimal cutting temperature (OCT) medium and extended post-thaw durations were studied to determine if any of these handling procedures introduced spectral artifacts. Experiments on representative tissues indicated that tissue heating due to the excitation light did not change the spectra significantly. With minor exceptions, OCT and formalin did not contaminate tissue spectra, so that samples stored for histological examination could also be studied with Raman spectroscopy. Tissue dehydration caused disruption of the protein vibrational modes, which caused spectral artifacts. It is concluded that ex vivo tissue samples should be frozen in OCT. Prior to spectral analysis, the tissue should then be acclimatized at room temperature in phosphate-buffered saline (PBS) and immersed in PBS during spectroscopic examination.     

Imaging and SERS Study of the Au Nanoparticles Interaction with HPV and Carcinogenic Cervical Tissues

In this work, gold NPs were prepared by the Turkevich method, and their interaction with HPV and cancerous cervical tissues were studied by scanning electron microscopy, energy-dispersive x-ray spectroscopy, confocal and multiphoton microscopy and SERS. The SEM images confirmed the presence and localization of the gold NPs inside of the two kinds of tissues. The light absorption of the gold NPs was at 520 nm. However, it was possible to obtain two-photon imaging (red emission region) of the gold NPs inside of the tissue, exciting the samples at 900 nm, observing the morphology of the tissues. The infrared absorption was probably due to the aggregation of gold NPs inside the tissues. Therefore, through the interaction of gold nanoparticles with the HPV and cancerous cervical tissues, a surface enhanced Raman spectroscopy (SERS) was obtained. As preliminary studies, having an average of 1000 Raman spectra per tissue, SERS signals showed changes between the HPV-infected and the carcinogenic tissues; these spectral signatures occurred mainly in the DNA bands, potentially offering a tool for the rapid screening of cancer.     

Applications of Vibrational Spectroscopy for Analysis of Connective Tissues

Advances in vibrational spectroscopy have propelled new insights into the molecular composition and structure of biological tissues. In this review, we discuss common modalities and techniques of vibrational spectroscopy, and present key examples to illustrate how they have been applied to enrich the assessment of connective tissues. In particular, we focus on applications of Fourier transform infrared (FTIR), near infrared (NIR) and Raman spectroscopy to assess cartilage and bone properties. We present strengths and limitations of each approach and discuss how the combination of spectrometers with microscopes (hyperspectral imaging) and fiber optic probes have greatly advanced their biomedical applications. We show how these modalities may be used to evaluate virtually any type of sample (ex vivo, in situ or in vivo) and how “spectral fingerprints” can be interpreted to quantify outcomes related to tissue composition and quality. We highlight the unparalleled advantage of vibrational spectroscopy as a label-free and often nondestructive approach to assess properties of the extracellular matrix (ECM) associated with normal, developing, aging, pathological and treated tissues. We believe this review will assist readers not only in better understanding applications of FTIR, NIR and Raman spectroscopy, but also in implementing these approaches for their own research projects.     

基于稳健统计的新鲜乳腺组织拉曼光谱分析

采用便携式拉曼光谱仪对新鲜乳腺正常组织、良性组织和恶性组织进行检测,通过稳健统计方法对拉曼光谱数据进行分析处理,建立乳腺组织拉曼光谱标准图谱,根据标准图谱特征峰归纳3类组织的主要区别和特征.在3类乳腺组织中,正常组织有明显的脂类特征峰(1078,1297,1437,1653,1746 cm-1),而在良性和恶性组织中则出现了较明显的蛋白特征峰(1259,1530,1650 cm-1),正常、良性和恶性组织的主要区别集中在1340和1534 cm-1处,应归属为蛋白和类胡萝卜素,这一结果并不能由经典统计方法得出.基于稳健统计建立的新鲜乳腺组织拉曼光谱标准图谱为构建数学模型来鉴别乳腺病灶的性质奠定了基础.     

Classification of normal and malignant human gastric mucosa tissue with confocal Raman microspectroscopy and wavelet analysis

Thirty-two samples from the human gastric mucosa tissue, including 13 normal and 19 malignant tissue samples were measured by confocal Raman microspectroscopy. The low signal-to-background ratio spectra from human gastric mucosa tissues were obtained by this technique without any sample preparation. Raman spectral interferences include a broad featureless sloping background due to fluorescence and noise. They mask most Raman spectral feature and lead to problems with precision and quantitation of the original spectral information. A preprocessed algorithm based on wavelet analysis was used to reduce noise and eliminate background/baseline of Raman spectra. Comparing preprocessed spectra of malignant gastric mucosa tissues with those of counterpart normal ones, there were obvious spectral changes, including intensity increase at approximately 1156cm(-1) and intensity decrease at approximately 1587cm(-1). The quantitative criterion based upon the intensity ratio of the approximately 1156 and approximately 1587cm(-1) was extracted for classification of the normal and malignant gastric mucosa tissue samples. This could result in a new diagnostic method, which would assist the early diagnosis of gastric 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.     

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.     

A combined laser-induced breakdown and Raman spectroscopy Echelle system for elemental and molecular microanalysis

Raman and laser-induced breakdown spectroscopy is integrated into a single system for molecular and elemental microanalyses. Both analyses are performed on the same ~ 0.002 mm² sample spot allowing the assessment of sample heterogeneity on a micrometric scale through mapping and scanning. The core of the spectrometer system is a novel high resolution dual arm Echelle spectrograph utilized for both techniques. In contrast to scanning Raman spectroscopy systems, the Echelle–Raman spectrograph provides a high resolution spectrum in a broad spectral range of 200–6000 cm^? 1 without moving the dispersive element. The system displays comparable or better sensitivity and spectral resolution in comparison to a state-of-the-art scanning Raman microscope and allows short analysis times for both Raman and laser induced breakdown spectroscopy. The laser-induced breakdown spectroscopy performance of the system is characterized by ppm detection limits, high spectral resolving power (15,000), and broad spectral range (290–945 nm). The capability of the system is demonstrated with the mapping of heterogeneous mineral samples and layer by layer analysis of pigments revealing the advantages of combining the techniques in a single unified set-up.     

Comparison of near-infrared and Raman spectroscopy for the determination of the density of polyethylene pellets

In this study, we compare near-infrared (NIR) and Raman spectroscopy for the determination of the density of linear low density polyethylene (PE) (in a pellet form). As generally known, Raman spectral features are more selective than those of NIR for most chemical samples. NIR spectroscopy has been more extensively used for the quantitative analysis of polymers, but Raman spectroscopy is the better choice as long as the problem of reproducibility of Raman measurements (especially for solid samples), mostly resulting from insufficient sample representation due to probing only localized chemical information and the sensitivity of sample placement with regard to the focal plane, can be overcome. To improve sample representation and reproducibility of Raman measurements, we have employed the wide area illumination (WAI) Raman scheme, capable of illuminating a laser onto a large sample area (28.3 mm²) for Raman spectral collection (a 6-mm laser spot with a focal length of 248 mm). Diffuse reflectance NIR spectra of PE pellets were collected using a sample moving system which allowed for the scanning of large areas. The prediction error was 0.0008 g cm⁻³ for Raman spectroscopy and 0.0011 g cm⁻³ for NIR spectroscopy. The harmonization of inherently selective Raman features and a reproducible spectral collection with correct sample representations using the WAI scheme led to an accurate determination of the density of the PE pellets.     

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.     

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.     

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.     

Nature of light-absorbing pigments from Brazilian lichens identified by Raman spectroscopy

Light-absorbing pigments from different chemical classes have been identified from the lichens Usnea sp. and Crocodia aurata using Raman spectroscopy supported by quantum mechanical DFT calculations. Raman spectra were obtained directly from the lichen tissues as well as from isolated extracts. Usnic acid, a chemomarker of Usnea spp has been reported together with a minor constituent, namely stictic acid, which has been unambiguously identified by ¹H and ¹³C NMR spectral analysis. The structures of calycin and pulvinic dilactone isolated from Crocodia aurata have been confirmed by single crystal X-ray diffraction. The ubiquitous carotenoids have been characterized by FT-Raman and dispersive Raman microimaging in tissues of Usnea sp. and C. aurata, respectively. The Raman map has revealed the presence of a mixture of carotenoids heterogeneously distributed in the upper layer of C. aurata. In this work we have demonstrated that Raman spectroscopy can be used to monitor aromatic and conjugated polyenic pigments in different layers of lichen tissues.     

Raman spectroscopy study of breast disease

The aim of this study was to evaluate the vibrational modes of malignant and benign breast tissues with the following diagnosis: fibroadenoma, invasive ductal carcinoma, ductal carcinoma in situ, and fibrocystic condition. Quadratic discriminate analysis, a multivariate statistical method of analysis, showed 98.5% separation between normal and altered tissue. Significant changes were observed at the lower Raman shift for altered tissue. For a better understanding of the spectral differences, a biochemical interpretation was also performed in terms of the reduction and oxidation processes in the cell environment which could be associated with an inflammatory reaction.     

Near-Infrared Raman Spectroscopy for In Vitro Detection of Cervical Precancers

Abstract— In this study, we investigate the potential of near-infrared Raman spectroscopy to differentiate cervical precancers from normal tissues, inflammation and metaplasia and to differentially diagnose low-grade and high-grade precancers. Near infrared Raman spectra were measured from 36 biopsies from 18 patients in vitro. Detection algorithms were developed and evaluated relative to histopathologic examination. Algorithms based on empirically selected peak intensities, ratios of peak intensities and a combination of principal component analysis for data reduction and Fisher discriminant analysis for classification were investigated. Spectral peaks were tentatively identified from measured spectra of potential chromophores. Empirically selected normalized intensities can differentiate precancers from other tissues with an average sensitivity and specificity of 88 ± 4% and 92 ± 4%. Ratios of un-normalized intensities can differentiate precancers from other tissues with a sensitivity and specificity of 82% and 88% and high-grade from low-grade lesions with a sensitivity and specificity of 100%. Using multivariate methods, intensities at eight frequencies can be used to differentiate precancers from all other tissues with a sensitivity and specificity of 82% and 92% in an unbiased test. Raman algorithms can potentially separate benign abnormalities such as inflammation and metaplasia from precancers. Comparison of tissue spectra to published and measured chromophore spectra indicate that the most likely primary contributors to the tissue spectra are collagen, nucleic acids, phospholipids and glucose 1-phos-phate. These results suggest that near-infrared Raman spectroscopy can be used for cervical precancer diagnosis and may be able to accurately separate samples with inflammation and metaplasia from precancer.     

Detection of acute brain injury by Raman spectral signature

Brain injury can lead to irreversible tissue loss and functional deficit along with significant health care costs. Raman spectroscopy can be used as a non-invasive technique to provide detailed information on the molecular composition of diseased and damaged tissues. This technique was used to examine acute mouse brain injury, focusing on the motor cortex, a region directly involved in controlling execution of movement. The spectral profile obtained from the injured brain tissue revealed a markedly different signature, particularly in the amide I and amide III vibrational region when compared to that of healthy brain tissue. Most noticeably, there was a significant reduction of the amide I vibration at the acute injury site and the appearance of two distinct features at 1586 and 1618 cm(-1). Complementary immunohistochemical analysis of the injured brain tissue showed an abundant expression of Caspase 3 (a cysteine protease marker used for apoptosis), suggesting that the injury-induced specific Raman shifts may be correlated with cell death. Taken together, this study demonstrates that Raman spectroscopy can play an important role in detecting the changes that occur in the injured brain and provide a possible technology for monitoring the recovery process.     

Identification of Colorectal Cancer Using Near-Infrared Spectroscopy and Adaboost with Decision Stump

Rapid and objective detection of cancer is crucial for successful treatment. Near-infrared (NIR) spectroscopy is a vibrational technique capable of optically probing molecular changes associated with disease. The purpose of this study was to explore NIR spectroscopy for discriminating cancer from normal colorectal tissues. A total of 110 tissue samples from patients who underwent operations were characterized in this study. The popular ensemble technique AdaBoost was used to construct the diagnostic model. A decision stump was used as the weak learning algorithm. Adaboost with decision stump, an ensemble of weak classifiers, was compared with the most suitable single model, a strong classifier. Only the 20 most significant variables were selected as inputs for the model based on measured defined variable importance. Using an independent test set, the single strong classifier provided diagnostic accuracy of 89.1%, sensitivity of 100%, and specificity of 78.6%, whereas the ensemble of weak stumps provided accuracy of 96.3%, sensitivity of 96.3%, and specificity of 96.3% for distinguishing cancer from normal colorectal tissues. Therefore, NIR spectroscopy in combination with AdaBoost with decision stumps has demonstrated potential for rapid and objective diagnosis of colorectal cancer.     

Infrared microspectroscopy of Oral Squamous Cell Carcinoma: Spectral signatures of cancer grading

In the present paper, we compared the histopathological and vibrational analyses of different tissue sections of Oral Squamous Cell Carcinoma (OSCC) at various malignancy grades, in order to unambiguously identify them. To achieve reliable results, healthy and dysplastic samples were also taken into account. FT-IR microspectroscopy is considered an effective tool for studying different molecular structures occurring in tumoral tissues and offers an interesting alternative to detect biochemical changes in a non-subjective way. In particular, on an adequate number of tissue sections affected by three different grades of OSSC (well G1, moderately G2, and poorly G3 differentiated), as well as on dysplastic and healthy tissues (all obtained from surgical resection), the chemical maps were acquired on meaningful areas containing both epithelial and connective structures. The multivariate analysis (Hierarchical Cluster Analysis, HCA, and Principal Component Analysis, PCA), performed separately on epithelial and connective spectral data, afforded to a good segregation for the different morphological structures. By analysing the representative spectra of healthy, dysplastic and tumoral epithelia and connectives, modifications were pin-pointed in the position of bands and absorbance band ratios usually associated with carcinogenesis. Above all, the changes in the protein pattern (with modifications in the length of side chains and in secondary structures), and in carbohydrates and nucleic acids moieties were associated with specific spectral markers of this pathology. The vibrational investigation led to a satisfactory understanding of these lesions so contributing to an early diagnosis, when the sole morphological inspection may result troublesome.     

基于非接触式拉曼光谱分析人血与犬血的PCA-LDA鉴别方法

将拉曼光谱分析法与数理统计方法有机结合,构建人血与犬血种属判别模型,实现了不同种属血液样本的高效无损鉴别.采用拉曼光谱的无损测试模式对血液样本进行测试,考察了抗凝管管材、聚焦位置及曝光时间等对血液样本拉曼光谱的影响,在激发波长为632.8 nm,光谱扫描范围为200~1800 cm-1,功率衰减率50%,曝光时间5 s及累加次数为2次的优化条件下,获得了无损检测条件下的血液样本拉曼光谱图.针对血液样本组分复杂、拉曼光谱信号基底背景高等问题,提出了基于小波变换去噪,进行分段多项式基线校正的预处理方法,有效解决了血液样本拉曼光谱谱图的高噪音和基线漂移问题.实验选择30例正常人血和33例比格犬血为样本训练集,5例正常人血和5例比格犬血为测试集,基于主成分分析法(PCA)联合线性判别法(LDA)模型,训练集分类正确率达到95.23%,盲测集分类正确率达90.00%.这种基于非接触式血液样本拉曼光谱和PCA-LDA判断模型的测试方法在进出口检验检疫等涉及血液无损鉴别的领域具有广泛的应用价值和前景.