Characterizing variability in in vivo Raman spectroscopic properties of different anatomical sites of normal tissue in the oral cavity

Raman spectroscopy is an inelastic light scattering technique that is capable of probing biochemical and biomolecular structures and conformations of tissue. This study aims to characterize the in vivo Raman spectroscopic properties of different normal oral tissues in the fingerprint region (800–1800 cm⁻¹) and to assess distinctive biochemical variations of different anatomical regions in the oral cavity. A specially designed fiber‐optic Raman probe with a ball lens was utilized for real‐time, in vivo Raman measurements of various oral tissue sites (i.e. inner lip, attached gingiva, floor, dorsal tongue, ventral tongue, hard palate, soft palate, and buccal). The semiquantitative non‐negativity‐constrained least squares minimization fitting of reference biochemicals representing oral tissue constituents (i.e. hydroxyapatite, keratin, collagen, DNA, and oleic acid) and partial least squares‐discriminant analysis (PLS‐DA) were employed to assess the significance of inter‐anatomical variability. A total of 402 high‐quality in vivo oral Raman spectra were acquired from 20 subjects. The histological characteristics of different oral tissues were found to have influence on the in vivo Raman spectra and could be grossly divided into three major clusterings: (1) buccal, inner lip, and soft palate; (2) dorsal, ventral tongue, and floor; (3) gingiva and hard palate. The PLS‐DA multiclass algorithms were able to identify different tissue sites with varying accuracies (inner lip 83.1%, attached gingiva 91.3%, floor 86.1%, dorsal tongue 88.8%, ventral tongue 83.1%, hard palate 87.6%, soft palate 83.3%, and buccal mucosa 85.3%), bringing out the similarities among different oral tissues at the biomolecular level. This study discloses that inter‐anatomical variability is significant and should be considered as an important parameter in the interpretation and rendering of Raman diagnostic algorithms for oral tissue diagnosis and characterization. Copyright © 2011 John Wiley & Sons, Ltd.     

Comparison of molecular images as defined by Raman spectra between normal mucosa and squamous cell carcinoma in the oral cavity

Raman spectroscopy has been effectively applied to clinically differentiate normal and cancerous mucosal tissues. Micro‐Raman spectroscopy provides a tool to better understand the molecular basis for the Raman clinical signal. The objective of the current study was to utilize micro‐Raman spectroscopy to define the molecular/spectral differences between normal and abnormal squamous cell carcinoma (SCC) in oral mucosa (in vitro). Understanding this may help in identifying unique spectra or may be useful for in vivo application of this technology. Micro‐Raman (confocal) spectroscopy was used to obtain molecular images of normal and SCC cells of human oral mucosa. Four fresh flashed‐frozen tumor and four matched normal tongue specimens were studied. The spectra covered a wavenumber range from 300 to 4000 cm⁻¹ with a spectral resolution of 8 cm⁻¹ and a spatial resolution of 1.0 µm. The cells were located within thin sections of tongue mucosa biopsies. The excitation wavelength of 515 nm was used. We were able to obtain Raman images with rich information about the spectroscopic and structural features within the cytoplasm, cell membrane, and cell nuclei. Significant spectral differences were observed between the Raman images of normal and malignant squamous cells. The heterogeneity of tumor cells within the abnormal tissue was also demonstrated. Spectral differences demonstrated between both tissue types have provided important information regarding the origins of specific signals within the cells of each tissue type. In our search for specific spectral biomarkers, we believe that a cell surface protein, greatly upregulated in SCC cells, was discovered at 1583 cm⁻¹. Copyright © 2010 John Wiley & Sons, Ltd.     

Raman spectroscopic analysis of breast cancer tissues: identifying differences between normal,invasive ductal carcinoma and ductal carcinoma in situ of the breast tissue

A relatively non‐destructive method employing Raman spectroscopy for the analysis of histopathological specimens is described. Raman spectroscopy has allowed qualitative analysis of the same specimen used for histopathological evaluation. Breast cancer tissues have been analysed to demonstrate the feasibility of the chemical changes taking place in the biological tissue, which can be identified precisely, and the results are reproducible. Raman analysis of tissue sections provides distinct spectra that can be used to distinguish between the nuclear grades of ductal carcinoma in situ (DCIS) and invasive ductal carcinoma (IDC) of the breast. Sixty cases of breast carcinoma including DCIS and IDC and seven cases of normal breast tissues were studied employing the Raman spectroscopic technique. This study reports for the first time spectral differences between DCIS grades. It is concluded that Raman spectroscopy can objectively distinguish between DCIS and IDC grades and is non‐destructive and reproducible. It should become possible in future to use Raman spectroscopy as an informative and quantitative method suitable for classification of grades and diagnosis of breast carcinoma. Copyright © 2007 John Wiley & Sons, Ltd.     

Robust analysis of multiplexed SERS microscopy of Ag nanocubes using an alternating minimization algorithm

To drive the application of surface‐enhanced Raman spectroscopy (SERS) mapping in ex vivo diagnostic imaging and non‐biological material characterization, we have designed a robust and accurate multiplex spectral fitting method using an alternating minimization algorithm to extract individual constituent Raman spectra with very small overall fitting error (as low as 2%). For each mixed Raman signal, constituent spectra and mixture coefficients were estimated jointly based on reference spectra that were measured in the lab. Our method is based on a Poisson model to reflect the photon counting nature of Raman signals and includes the nonlinear noise in the measured data, making our method robust against data containing relatively large random noise. In our method, we minimized a cost function consisting of two terms: (1) the overall fitting error between the measured and modeled spectra and (2) the sum of the individual error between each reference spectrum and its corresponding constituent. This method inherently guarantees that the estimates will approach the global minimum with monotonic convergence. The accuracy of our method was validated by applying it to a SERS spectral fitting problem and comparing our results to those from existing methods. Copyright © 2013 John Wiley & Sons, Ltd.     

A robust method for automated background subtraction of tissue fluorescence

This paper introduces a new robust method for the removal of background tissue fluorescence from Raman spectra. Raman spectra consist of noise, fluorescence and Raman scattering. In order to extract the Raman scattering, both noise and background fluorescence must be removed, ideally without human intervention and preserving the original data. We describe the rationale behind our robust background subtraction method, determine the parameters of the method and validate it using a Raman phantom against other methods currently used. We also statistically compare the methods using the residual mean square (RMS) with a fluorescence‐to‐signal (F/S) ratio ranging from 0.1 to 1000. The method, ‘adaptive minmax’, chooses the subtraction method based on the F/S ratio. It uses multiple fits of different orders to maximize each polynomial fit. The results show that the adaptive minmax method was significantly better than any single polynomial fit across all F/S ratios. This method can be implemented as part of a modular automated real‐time diagnostic in vivo Raman system. Copyright © 2007 John Wiley & Sons, Ltd.     

Study of both fingerprint and high wavenumber Raman spectroscopy of pathological nasopharyngeal tissues

High wavenumber (HW) Raman spectroscopy has weaker fluorescence background compared with fingerprint (FP) region. This study aims to evaluate the discrimination feasibility of nasopharyngeal non‐cancerous and nasopharyngeal cancer (NPC) tissue with both FP and HW Raman spectroscopy. HW Raman spectra of nasopharyngeal tissue were obtained for the first time. Raman spectra were collected to differentiate nasopharyngeal non‐cancerous (n = 37) from NPC (n = 41) tissues in FP (800–1800cm⁻¹), HW (2700–3100cm⁻¹), and integrated FP/HW region. First, to assess the utility of this method, the averaged Raman spectral intensities and intensity ratios of corresponding Raman bands were analyzed in HW and FP regions, respectively. The results show that intensities as well as the ratios of specific Raman peaks might be helpful in distinguishing nasopharyngeal non‐cancerous from NPC tissue with the HW Raman spectroscopy, as with FP Raman reported before. The multivariate statistical method based on the combination of principal component analysis–liner discriminant analysis (PCA‐LDA), together with leave‐one‐patient‐out, cross‐validation diagnostic algorithm, was used for discriminating nasopharyngeal non‐cancerous from NPC tissue, generating sensitivities of 87.8%, 85.4%, and 95.1% and specificities of 86.5%, 91.9%, and 89.2%, respectively, with Raman spectroscopy in the FP, HW, and integrated FP/HW regions. The posterior probability of classification results and receiver operating characteristic curves were utilized to evaluate the discrimination of PCA‐LDA algorithm, verifying that HW Raman spectroscopy has a positive effect on the differentiation for the diagnosis of NPC tissue by integrated FP/HW Raman spectroscopy. What's more, the potential of Raman spectroscopy used for differentiating different pathology NPC tissues was also discussed. The results demonstrate that both FP and HW Raman spectroscopy have the potential for diagnosis and detection in early nasopharyngeal carcinoma, and HW Raman spectroscopy may improve the discrimination of NPC tissue compared with FP region alone, providing a promising diagnostic tool for the diagnosis of NPC tissue. Copyright © 2015 John Wiley & Sons, Ltd.     

拉曼光谱技术在病理诊断中的研究进展

拉曼光谱技术能够提供与物质特定分子结构相关的光谱信息,可用于识别生物组织微小的生化变异,具有快速、实时、无损、无需样本预处理等优点,在临床病理诊断领域极具应用前景。与常规组织病理学分析相比,拉曼光谱技术能够直接检测活体组织,简化了分析程序,缩短了诊断时间。人体病变组织的细胞分子组成和结构可能发生变化,这为拉曼光谱技术在组织病理诊断中的应用提供了检测依据。基于组织分子组成与结构的差异,结合机器学习和化学计量学方法,拉曼光谱技术可以提供客观的诊断信息,实现快速、低侵入的病理诊断。回顾了近十年来拉曼光谱技术在组织病理诊断中的研究进展,对取得的关键成果进行了总结,阐述了当前离体和活体应用拉曼光谱技术的一些关键问题。针对离体拉曼光谱检测,重点评估福尔马林固定石蜡包埋样本、冷冻样本和新鲜组织样本等离体样本的适用情况;阐述拉曼光谱数据收集的关键技术,包括适用光源、光谱范围,以及病理样本光谱采集的方式等。对于活体拉曼光谱检测,重点介绍了活体检测研究中拉曼光谱技术应用的两种形式：结合医用内窥镜进行体内检测,以及开放手术中的直接检测;综述了临床适用的拉曼系统,重点介绍了当前活体拉曼研究中应用的光纤探头。同时,文章也讨论了拉曼光谱数据的处理与分析方法,通过光谱预处理,特征提取与分类识别,构建拉曼光谱病理诊断模型,在小样本范围能够获得较好的诊断结果。考虑临床实际应用,仍需要不断优化分析方法,实现拉曼光谱与生化信息的关联,将样本个体差异的影响纳入分类模型中,以提升模型性能。文章对拉曼光谱应用于病理诊断中的关键问题进行了讨论,为进一步开展研究提供参考。未来需要更深入和广泛地开展离体和活体研究,以促进拉曼光谱技术在临床中的应用。     

Assessment of ex vivo perfused liver health by Raman spectroscopy

Raman spectroscopy was applied in this research to monitor the overall health and degradation of porcine livers perfused ex vivo using the VasoWaveW® perfusion system. A novel Raman‐based diagnostic analysis was developed that enables near real‐time and label‐free monitoring of organ health during ex vivo perfusion designed to extend the useful life of the organ for transplantation. Multivariate statistical analysis of Raman spectra of organ perfusate fluid, using a combination of principal component analysis and linear discriminant analysis, proved to be an effective technique to assess the degradation properties of the livers. Three livers (with replicates) were perfused ex vivo under different pressures and temperatures and were compared with a 24‐h time‐course. Results indicated that perfusion pressure was a more significant factor in organ degradation than was temperature. In addition, a non‐linear degradation profile was identified for all three perfused livers, and this profile was different for individual livers, demonstrating the time‐dependent transition from its initial ‘healthy’ state towards a more ‘unhealthy’ degenerative state at 24 h. The Raman spectroscopy‐based approach described here has potential applications in perfusion and diagnostic instrumentation that can be used in near real‐time during organ transit and in operating rooms to help identify appropriately healthy organs for transplantation. Copyright © 2015 John Wiley & Sons, Ltd.     

Possibilities for human skin characterization based on strongly reduced Raman spectroscopic information

Loss‐of‐function mutations in the gene coding for filaggrin are the single most important risk factor for development of atopic dermatitis and associated allergic rhinitis and asthma. Filaggrin is enzymatically degraded to natural moisturizing factor (NMF) in the stratum corneum (SC). In vivo Raman spectra of human skin can be used to quantify the NMF concentration in SC and thereby identify carriers of a loss‐of‐function mutation in the gene coding for filaggrin, which results in decreased NMF content. Here, we demonstrate that strongly reduced Raman spectral information is sufficient to make this differentiation. This is an important step towards development of a dedicated diagnostic device of reduced complexity, size and cost as compared to current state‐of‐the‐art Raman equipment. A genetic algorithm was used to select the spectral regions needed to classify skin based on normal or reduced NMF content in SC. Using the NMF content based on full spectral information as gold standard, only four Raman regions were required to create a linear discriminant analysis model that can differentiate between skin with low NMF and skin with normal NMF with a prediction accuracy of 93 %. Copyright © 2013 John Wiley & Sons, Ltd.     

Effects of laser excitation wavelength and optical mode on Raman spectra of human fresh colon,pancreas, and prostate tissues

Early cancer detection is the central and most important factor for allowing successful treatment and resultant positive long‐term patient outcomes. Recently, optical techniques have been applied to this purpose, although each has inherent limitations. In particular, Raman spectroscopy applied in the pathological diagnosis of cancerous tissues has received increasing attention, with the merit of being highly sensitive to the biochemical alterations in tissue compositions and applicable in vivo. Nevertheless, its application has been impeded by the high background intensity, which masks the Raman signal of biological molecules. In this work, the influence of laser excitation wavelength (785 vs. 830 nm) and optical mode (single mode vs. multimode) on the background intensity of fresh human tissues was studied. Based on the results, laser with 830 nm excitation demonstrated better background reduction than that with 785 nm excitation for the same optical mode, but the Raman signal intensity was conversely reduced, and the signal‐to‐noise ratio (SNR) not improved. In contrast, by comparing single‐mode and multimode 785 nm excitations, it was shown that the single‐mode laser with its smaller beam waist and beam propagation factor had better background reduction ability and an improvement of the SNRs. It is speculated that this decrease in background intensity comes from the effect of the optical mode on the Mie scattering from the biological tissue. High‐quality spectra based on a careful selection of both laser excitation wavelength and optical mode will benefit Raman measurements in further research focusing on spectral interpretation and histopathological correlation ultimately aimed toward intraoperative applications. Copyright © 2014 John Wiley & Sons, Ltd.     

Spectral unmixing combined with Raman imaging,a preferable analytic technique for molecule visualization

This article reviews spectral unmixing used as a new method for Raman imaging. Raman spectroscopy explores the vibrational information about specific chemical bonds in molecules, which can be used for label-free molecular visualization. However, chemical bonds are usually shared among different molecules, which results in closed or mixed Raman peaks of many molecules. Therefore, the acquired spectra cannot be directly used to reconstruct the Raman images, as pure component spectra are hidden under the acquired spectra. Spectral unmixing is an effective method to provide a meaningful spectrum of each component with no priori spectral information and to also reconstruct the compositional distribution images. This article summarizes some representative spectral unmixing approaches used for Raman imaging and many related researches. This review strives to introduce the combination of spectral unmixing and Raman imaging as an efficient analytic technique to characterize various constituents and make subtle understanding of those complex structures.     

Depth‐resolved in vivo micro‐Raman spectroscopy of a murine skin tumor model reveals cancer‐specific spectral biomarkers

We have developed a micro‐Raman spectrometer system for use to differentiate tumor lesions from normal skin using an in vivo animal model. A study of 494 Raman spectra from 24 mice revealed different spectral patterns at different depths and between normal and tumor‐bearing skin sites. A peak at 899 cm⁻¹ (possibly from proline or fatty acids) and one with higher intensity in the 1325–1330 cm⁻¹ range (assigned to nucleic acids) were correlated with the presence of tumors, which can potentially be used as biomarkers for skin cancer detection. Spectral diagnosis performed on the murine tumor model achieved a diagnostic sensitivity of 95.8% and specificity of 93.8%. These results encourage us to develop further the use of confocal Raman spectroscopy as a clinical tool for noninvasive human skin biochemical analysis, particularly in relation to skin cancer. Copyright © 2010 John Wiley & Sons, Ltd.     

A shifted‐excitation Raman difference spectroscopy (SERDS) evaluation strategy for the efficient isolation of Raman spectra from extreme fluorescence interference

A biochemical characterization of pathologies in biological tissue can be provided by Raman spectroscopy. Often, the raw spectrum is severely affected by fluorescence interference. We report and compare various spectra‐processing approaches required for the purification of Raman spectra from heavily fluorescence‐interfered raw spectra according to the shifted‐excitation Raman difference spectroscopy method. These approaches cover the entire spectra‐processing chain from the raw spectra to the purified Raman spectra. In detail, we compared (1) area normalization versus z‐score normalization, (2) direct reconstruction of the difference spectra versus reconstruction of zero‐centered difference spectra and (3) collective baseline correction of the reconstructed spectra versus piecewise baseline correction of the reconstructed spectra and, finally, (4) analyzed the influence of the shift of the excitation wavelength on the quality of the reconstructed spectra. Statistical analysis of the spectra showed that – in our experiments – the best results were obtained for the z‐score normalization before subtraction of the normalized spectra, followed by zero‐centering of the difference spectra before reconstruction and a piecewise baseline correction of the pure Raman spectra. With our equipment, a wavelength shift from 784 to 785 nm provided reconstructed spectra of best quality. The analyzed specimens were different tissue types of pigs, tissue from the oral cavity of humans and a model solution of dye dissolved in ethanol. © 2015 The Authors. Journal of Raman Spectroscopy published by John Wiley & Sons Ltd.     

Raman spectroscopy at different excitation wavelengths (1064, 785 and 532 nm) as a tool for diagnosis of colon cancer

Raman spectroscopy is structure sensitive non‐destructive method that allows observing the status of biological tissues with minimal impact. This method has a great potential in the diagnosis of various types of degenerative diseases including cancer damages. Near‐infrared Fourier transform (NIR‐FT)‐Raman (λ_ex ~1064 nm), NIR‐visible (Vis)‐Raman (λ_ex ~785 nm) and Vis‐Raman (λ_ex ~532 nm) spectra of normal and colorectal carcinoma colon tissue samples were recorded in macroscopic mode at 10–20 randomly chosen independent sites. In the cases of NIR‐Vis‐ and Vis‐Raman spectra, enhanced resonance effects were observed for tissue chromophores absorbing in the visible area. Evident spectral differences were noticed for Raman spectra of normal colon tissue samples in comparison with abnormal samples. The average Raman spectra of colon tissue samples were analysed by principal component analysis (PCA) to discriminate normal and abnormal tissues. PCA of combined dataset containing Raman intensities of chosen NIR‐FT, NIR‐Vis or Vis‐Raman bands led to discrimination of normal and abnormal colon tissue samples. Therefore, combination of these three Raman methods can be helpful for recognizing cancer lesions in colon for diagnostic purposes. Copyright © 2014 John Wiley & Sons, Ltd.     

Raman spectroscopy monitoring of the cellular activities of a tissue‐engineered ex vivo produced oral mucosal equivalent

To ensure quality control and assurance in tissue engineering, noninvasive, real‐time and aseptic evaluation of cell‐based devices is required before product release. In this study, Raman spectroscopy was applied to monitor the cellular activities of an oral mucosa equivalent (EVPOME) produced ex vivo from cultured autogenous oral keratinocytes and acellular dermis—AlloDerm. Raman spectra showed a positive correlation of the peak area ratio of amide I (1655 cm⁻¹)/phenylalanine (1004 cm⁻¹) with a negative linear regression (R² > 0.95) according to the number of cultured days, especially on the 14thand 21st day. This work demonstrates the successful application of Raman spectroscopy for quantitatively monitoring and evaluating the maturity of EVPOME. Copyright © 2010 John Wiley & Sons, Ltd.     

胃粘膜组织共焦显微拉曼光谱分类研究

采用基于小波变换的光谱去噪和背景扣除预处理技术,对32例(其中:13例正常,19例癌变)胃粘膜组织拉曼光谱进行分析,克服了手动背景扣除的一些缺点,并观察到一些新的光谱特征。基于此,给出能对所有正常组织和癌变组织进行有效分类的特征量和判据。通过研究这些特征量与胃粘膜组织癌变发展阶段之间的定量关系,可望实现胃癌的早期诊断。     

基于脉冲耦合神经网络的拉曼光谱定性分析

通过对脉冲耦合神经网络(pulse coupled neural network,PCNN)和拉曼光谱定性分析的研究,提出了基于PCNN的拉曼光谱定性分析方法.首先,利用PCNN神经元的疲劳与不应期特性将拉曼光谱数据进行编码;然后,基于改进的Horspool算法将检测样品对应编码与基码数据库中的所有基码逐一匹配,并得到各对应的匹配相似度,进而判定样品类别.相关实验和数据分析证明了该文方法的准确性和有效性.同时,该文方法避免了目前基于谱模版定性分析方法中待测样品拉曼光谱特征谱峰难以确定以及匹配分析冗余度高等不足,且对存储空间的要求仅为后者的5.8%.     

Raman spectroscopy measurement of levofloxacin lactate in blood using an optical fiber nano‐probe

Liquid chromatography and mass spectrometry were time‐consuming and expensive as the main methods for the drug analysis at present, and the samples must be pretreated. The Raman spectroscopy measurement methods were fast and simple, so the Raman spectroscopy methods for the drug analysis were explored in this paper. An optical fiber nano‐probe coated with gold nanoparticles was fabricated and used with surface‐enhanced Raman spectroscopy (SERS) to measure levofloxacin lactate. The resulting SERS spectra of levofloxacin lactate in mouse blood that was detected by the optical fiber nano‐probe clearly showed the characteristic wave numbers of levofloxacin lactate, indicating that optical fiber nano‐probes can be used with spectral techniques to analyze drugs in vitro or potentially even in vivo. Copyright © 2015 John Wiley & Sons, Ltd.     

Use of thermo‐Raman spectroscopy and chemometric analysis to identify dehydration steps of hydrated inorganic samples—application to copper sulfate pentahydrate

In situ thermo‐Raman spectroscopy (TRS) measurements were performed in order to investigate solid‐phase transformation of the copper sulfate pentahydrate from room temperature up to 300 °C. Band‐target entropy minimization (BTEM), a blind‐source separation algorithm, was employed in order to identify and reconstruct the pure component spectra of the species involved in the dehydration process. In spite of low signal‐to‐noise ratio and elevated baseline spectral data, BTEM was successfully utilized to identify and reconstruct four pure component spectra of copper sulfate pentahydrate, trihydrate, monohydrate, and anhydrate, which were formed during this thermally induced process. Subsequent mapping of these four pure component spectral estimates back onto the preprocessed spectra yielded the relative concentrations of each individual species. Finally, the transition temperatures of each dehydration step could be unambiguously deduced from the obtained concentration profile. The current study shows that combined thermo‐Raman spectroscopy and chemometric analysis provides an effective tool to determine the dehydration temperatures as well as to identify the structures of each individual species involved in a solid‐phase dehydration process. Copyright © 2009 John Wiley & Sons, Ltd.     

Origin of spectral interferences in femtosecond stimulated Raman microscopy

In femtosecond stimulated Raman microscopy (FSRM), a spectrally narrow (Raman pump) pulse and a broad (Raman probe) laser pulse are employed to generate the Raman spectra of microscopic objects. The resulting spectra exhibit, in addition to the Raman bands, spectral modulations of comparable amplitude. Here a model is devised that attributes these modulations to a four‐wave mixing (FWM) process. Two light fields of the probe pulse and one field of the pump pulse serve as input fields. The resulting FWM field experiences a heterodyne amplification by the probe field. Simulations based on this model reproduce the appearance of the spectral modulations. Furthermore, the amplitude of the modulations exhibits dependences on the energies of pump and probe pulses as well as on the nonlinear refractive index n₂, which are in line with the model. Copyright © 2011 John Wiley & Sons, Ltd.