Optical diagnosis of laryngeal cancer using high wavenumber Raman spectroscopy

We report the implementation of the transnasal image-guided high wavenumber (HW) Raman spectroscopy to differentiate tumor from normal laryngeal tissue at endoscopy. A rapid-acquisition Raman spectroscopy system coupled with a miniaturized fiber-optic Raman probe was utilized to realize real-time HW Raman (2800-3020 cm(-1)) measurements in the larynx. A total of 94 HW Raman spectra (22 normal sites, 72 tumor sites) were acquired from 39 patients who underwent laryngoscopic screening. Significant differences in Raman intensities of prominent Raman bands at 2845, 2880 and 2920 cm(-1) (CH(2) stretching of lipids), and 2940 cm(-1) (CH(3) stretching of proteins) were observed between normal and cancer laryngeal tissue. The diagnostic algorithms based on principal components analysis (PCA) and linear discriminant analysis (LDA) together with the leave-one subject-out, cross-validation method on HW Raman spectra yielded a diagnostic sensitivity of 90.3% (65/72) and specificity of 90.9% (20/22) for laryngeal cancer identification. This study demonstrates that HW Raman spectroscopy has the potential for the noninvasive, real-time diagnosis and detection of laryngeal cancer at the molecular level.     

Portable spectroscopic system for in vivo skin neoplasms diagnostics by Raman and autofluorescence analysis

The present paper studies the applicability of a portable cost‐effective spectroscopic system for the optical screening of skin tumors. in vivo studies of Raman scattering and autofluorescence (AF) of skin tumors with the 785 nm excitation laser in the near‐infrared region included malignant melanoma, basal cell carcinoma and various types of benign neoplasms. The efficiency of the portable system was evaluated by comparison with a highly sensitive spectroscopic system and with the diagnosis accuracy of a human oncologist. Partial least square analysis of Raman and AF spectra was performed; specificity and sensitivity of various skin oncological pathologies detection varied from 78.9% to 100%. Hundred percent accuracy of benign and malignant skin tumors differentiation is possible only with a combined analysis of Raman and AF signals.      

Real‐time in vivo cancer diagnosis using raman spectroscopy

Raman spectroscopy has becoming a practical tool for rapid in vivo tissue diagnosis. This paper provides an overview on the latest development of real‐time in vivo Raman systems for cancer detection. Instrumentation, data handling, as well as oncology applications of Raman techniques were covered. Optic fiber probes designs for Raman spectroscopy were discussed. Spectral data pre‐processing, feature extraction, and classification between normal/benign and malignant tissues were surveyed. Applications of Raman techniques for clinical diagnosis for different types of cancers, including skin cancer, lung cancer, stomach cancer, oesophageal cancer, colorectal cancer, cervical cancer, and breast cancer, were summarized.

Schematic of a real‐time Raman spectrometer for skin cancer detection. Without correction, the image captured on CCD camera for a straight entrance slit has a curvature. By arranging the optic fiber array in reverse orientation, the curvature could be effectively corrected.     

Detection of ER stress in vivo by Raman spectroscopy

The endoplasmic reticulum (ER) is an organelle in which most membrane and secretory proteins are synthesized. If these proteins are not folded correctly, unfolded proteins accumulate in the ER lumen, causing a cellular situation known as ER stress. Recently, many studies on the relationship between ER stress and diseases have been reported. Thus, studies of ER stress in vivo should yield information that is useful in pathology. Model mice have been developed as a powerful tool to visualize ER stress in vivo, but this approach depends on transgenic technology. Here, we report on a method of detecting ER stress in vivo by Raman spectroscopy. Our experiments revealed that two specific Raman bands were reduced in both cultured cells and animal tissues in an ER stress dependent manner. This suggests that Raman spectroscopy could be a useful tool to detect ER stress in vivo without transgenic technology.     

Real‐time endoscopic Raman spectroscopy for in vivo early lung cancer detection

Currently the most sensitive method for localizing lung cancers in central airways is autofluorescence bronchoscopy (AFB) in combination with white light bronchoscopy (WLB). The diagnostic accuracy of WLB + AFB for high grade dysplasia (HGD) and carcinoma in situ is variable depending on physician's experience. When WLB + AFB are operated at high diagnostic sensitivity, the associated diagnostic specificity is low. Raman spectroscopy probes molecular vibrations and gives highly specific, fingerprint‐like spectral features and has high accuracy for tissue pathology classification. In this study we present the use of a real‐time endoscopy Raman spectroscopy system to improve the specificity. A spectrum is acquired within 1 second and clinical data are obtained from 280 tissue sites (72 HGDs/malignant lesions, 208 benign lesions/normal sites) in 80 patients. Using multivariate analyses and waveband selection methods on the Raman spectra, we have demonstrated that HGD and malignant lung lesions can be detected with high sensitivity (90%) and good specificity (65%).

     

Near-infrared autofluorescence spectroscopy for in vivo identification of hyperplastic and adenomatous polyps in the colon

This study reports the implementation of an endoscope-based near-infrared (NIR) autofluorescence (AF) spectroscopy technique for in vivo differentiation of normal, hyperplastic and adenomatous colonic polyps during clinical colonoscopic examination. A total of 198 in vivo NIR AF spectra in the range of 810–1050 nm were acquired from colonic tissues (normal (n = 116); hyperplastic (n = 48); and adenomatous polyps (n = 34)) of 96 patients undergoing colonoscopic screening. Significant differences (p < 0.001, one-way analysis of variance (ANOVA)) in in vivo NIR AF intensity among normal, hyperplastic, and adenomatous polyps are observed. Multivariate statistical techniques, including principal components analysis (PCA) and linear discriminate analysis (LDA) together with the leave-one tissue site-out, cross-validation, were used to develop diagnostic algorithms for distinguishing adenomatous polyps from normal and hyperplastic colonic polyps based on NIR AF spectral features. The PCA–LDA modeling on in vivo colonic NIR AF dataset yields diagnostic sensitivities of 83.6%, 77.1%, and 88.2%; and specificities of 96.3%, 88.0%, and 92.1%, respectively, for classification of normal, hyperplastic and adenomatous colonic polyps. This work suggests that NIR AF spectroscopy associated with PCA–LDA algorithms has potential for in vivo diagnosis and detection of colonic precancer at colonoscopy.     

Combined in vivo confocal Raman spectroscopy and confocal microscopy of human skin

In vivo confocal Raman spectroscopy is a noninvasive optical method to obtain detailed information about the molecular composition of the skin with high spatial resolution. In vivo confocal scanning laser microscopy is an imaging modality that provides optical sections of the skin without physically dissecting the tissue. A combination of both techniques in a single instrument is described. This combination allows the skin morphology to be visualized and (subsurface) structures in the skin to be targeted for Raman measurements. Novel results are presented that show detailed in vivo concentration profiles of water and of natural moisturizing factor for the stratum corneum that are directly related to the skin architecture by in vivo cross-sectional images of the skin. Targeting of skin structures is demonstrated by recording in vivo Raman spectra of sweat ducts and sebaceous glands in situ. In vivo measurements on dermal capillaries yielded high-quality Raman spectra of blood in a completely noninvasive manner. From the results of this exploratory study we conclude that the technique presented has great potential for fundamental skin research, pharmacology (percutaneous transport), clinical dermatology, and cosmetic research, as well as for noninvasive analysis of blood analytes, including glucose.     

Combining gene signatures improves prediction of breast cancer survival

Background

Several gene sets for prediction of breast cancer survival have been derived from whole-genome mRNA expression profiles. Here, we develop a statistical framework to explore whether combination of the information from such sets may improve prediction of recurrence and breast cancer specific death in early-stage breast cancers. Microarray data from two clinically similar cohorts of breast cancer patients are used as training (n = 123) and test set (n = 81), respectively. Gene sets from eleven previously published gene signatures are included in the study.

Principal Findings

To investigate the relationship between breast cancer survival and gene expression on a particular gene set, a Cox proportional hazards model is applied using partial likelihood regression with an L2 penalty to avoid overfitting and using cross-validation to determine the penalty weight. The fitted models are applied to an independent test set to obtain a predicted risk for each individual and each gene set. Hierarchical clustering of the test individuals on the basis of the vector of predicted risks results in two clusters with distinct clinical characteristics in terms of the distribution of molecular subtypes, ER, PR status, TP53 mutation status and histological grade category, and associated with significantly different survival probabilities (recurrence: p = 0.005; breast cancer death: p = 0.014). Finally, principal components analysis of the gene signatures is used to derive combined predictors used to fit a new Cox model. This model classifies test individuals into two risk groups with distinct survival characteristics (recurrence: p = 0.003; breast cancer death: p = 0.001). The latter classifier outperforms all the individual gene signatures, as well as Cox models based on traditional clinical parameters and the Adjuvant! Online for survival prediction.

Conclusion

Combining the predictive strength of multiple gene signatures improves prediction of breast cancer survival. The presented methodology is broadly applicable to breast cancer risk assessment using any new identified gene set.     

Study on gastric cancer blood plasma based on surface-enhanced Raman spectroscopy combined with multivariate analysis

A surface-enhanced Raman spectroscopy (SERS) method combined with multivariate analysis was developed for non-invasive gastric cancer detection. SERS measurements were performed on two groups of blood plasma samples: one group from 32 gastric patients and the other group from 33 healthy volunteers. Tentative assignments of the Raman bands in the measured SERS spectra suggest interesting cancer-specific biomolecular changes, including an increase in the relative amounts of nucleic acid, collagen, phospholipids and phenylalanine and a decrease in the percentage of amino acids and saccharide in the blood plasma of gastric cancer patients as compared with those of healthy subjects. Principal components analysis (PCA) and linear discriminant analysis (LDA) were employed to develop effective diagnostic algorithms for classification of SERS spectra between normal and cancer plasma with high sensitivity (79.5%) and specificity (91%). A receiver operating characteristic (ROC) curve was employed to assess the accuracy of diagnostic algorithms based on PCA-LDA. The results from this exploratory study demonstrate that SERS plasma analysis combined with PCA-LDA has tremendous potential for the non-invasive detection of gastric cancers.     

Raman spectroscopy of blood and urine liquid biopsies for ovarian cancer diagnosis: identification of chemotherapy effects

Blood plasma and serum Raman spectroscopy for ovarian cancer diagnosis has been applied in pilot studies, with promising results. Herein, a comparative analysis of these biofluids, with a novel assessment of urine, was conducted by Raman spectroscopy application in a large patient cohort. Spectra were obtained through samples measurements from 116 ovarian cancer patients and 307 controls. Principal component analysis identified significant spectral differences between cancers without previous treatment (n = 71) and following neo-adjuvant chemotherapy (NACT), (n = 45). Application of five classification algorithms achieved up to 73% sensitivity for plasma, high specificities and accuracies for both blood biofluids, and lower performance for urine. A drop in sensitivities for the NACT group in plasma and serum, with an opposite trend in urine, suggest that Raman spectroscopy could identify chemotherapy-related changes. This study confirms that biofluids' Raman spectroscopy can contribute in ovarian cancer's diagnostic work-up and demonstrates its potential in monitoring treatment response.     

拉曼光谱技术在病原菌感染诊断中的应用进展

快速准确诊断感染性疾病病原体是遏制超级细菌传播和抗生素滥用的重要防线。目前,临床病原菌感染诊断十分依赖于培养手段,导致检测周期长达数日,不但影响了患者的及时诊治,还间接导致抗生素的滥用。拉曼光谱技术是一种无损、高灵敏的分子指纹图谱检测技术,近年来在生物学领域得到广泛应用,其具有的免培养、快速、高特异性、低成本等优点为病原菌感染的诊断提供了新方案。本文阐述了拉曼光谱技术的原理和特点,综述了其在病原菌鉴定和抗菌药物敏感性试验方面的应用进展。     

Carotenoids contribution in rapid diagnosis of multiple sclerosis by Raman spectroscopy

Rapid and accurate diagnosis of any illness determines the success of treatment. The same applies to multiple sclerosis (MS), chronic, inflammatory, and neurodegenerative diseases (ND) of the central nervous system (CNS). Unfortunately, the definitive diagnosis of MS is prolonged and involves mainly clinical symptoms observation and magnetic resonance imaging (MRI) of the CNS. However, as we previously reported, Attenuated Total Reflectance Fourier Transform Infrared (ATR-FTIR) spectroscopy shed new light on the minimally invasive, label-free, and rapid diagnosis of this illness through blood fraction. Herein we introduce Raman spectroscopy coupled with chemometric analysis to provide more detailed information about the biochemical changes behind MS. This pilot study demonstrates that mentioned combination may provide a new diagnostic biomarker and bring closer to rapid MS diagnosis. It has been shown that Raman spectroscopy provides lipid and carotenoid molecules as useful biomarkers which may be applied for both diagnosis and treatment monitoring.     

Autofluorescence and white light imaging‐guided endoscopic Raman and diffuse reflectance spectroscopy for in vivo nasopharyngeal cancer detection

Nasopharyngeal cancer (NPC) is an endemic with high incidence in Southern China and Southeast Asia countries. Screening for NPC under conventional white light imaging (WLI) nasopharyngoscope examination remains a great clinical challenge due to its poor sensitivity. Here, we developed an integrated 4‐modality endoscopy system combining WLI, autofluorescence imaging (AFI), diffuse reflectance spectroscopy and Raman spectroscopy technologies for in vivo endoscopic cancer detection for the first time. A pilot clinical test of the system for NPC detection was conducted, in which 283 in vivo Raman and diffuse reflectance spectral data sets from 30 NPC patients and 30 healthy subjects were acquired under the guidance of AFI and WLI. Both high diagnostic sensitivity (98.6%) and high specificity (95.1%) for differentiating cancer from normal tissue sites were achieved using this system combined with principal component analysis‐linear discriminant analysis diagnostic algorithm, demonstrating great potential for improving real‐time, in vivo diagnosis of NPC at endoscopy.      

In vivo MR spectroscopy in diagnosis and research of neuropsychiatric disorders

Magnetic resonance spectroscopy is one of the most important tools for quantitative analysis of chemical composition and structure, and this non-invasive technique is now being applied in vivo to study biochemical processes in those neuropsychiatric disorders that are part of the phospholipid spectrum. Interpretation of a clinical magnetic resonance spectrum can provide information about membrane phospholipid turnover, cellular energetics, neuronal function, selected neurotransmitter activity and intracellular pH. Cerebral proton and phosphorus magnetic resonance spectroscopy findings are summarized in relation to schizophrenia, dyslexia and chronic fatigue syndrome.     

Superpixel Raman spectroscopy for rapid skin cancer margin assessment

Spontaneous Raman micro‐spectroscopy has been demonstrated great potential in delineating tumor margins; however, it is limited by slow acquisition speed. We describe a superpixel acquisition approach that can expedite acquisition between ~×100 and ×10 000, as compared to point‐by‐point scanning by trading off spatial resolution. We present the first demonstration of superpixel acquisition on rapid discrimination of basal cell carcinoma tumor from eight patients undergoing Mohs micrographic surgery. Results have been demonstrated high discriminant power for tumor vs normal skin based on the biochemical differences between nucleus, collagen, keratin and ceramide. We further perform raster‐scanned superpixel Raman imaging on positive and negative margin samples. Our results indicate superpixel acquisition can facilitate the use of Raman microspectroscopy as a rapid and specific tool for tumor margin assessment.     

Time-gated in vivo autofluorescence imaging of dental caries.

Laser-induced time-resolved autofluorescence from carious lesions of human teeth was studied by means of ultrashort pulsed laser systems, time-correlated single photon counting and time-gated imaging. Carious regions exhibited a slower fluorescence decay with a main 17 ns fluorescence lifetime than healthy hard dental tissue. The long-lived fluorophore present in carious lesions only emits in the red spectral region. Fluorescence decay time and spectral characteristics are typical of fluorescent metal-free porphyrin monomers. The spatial distribution of the long-lived endogenous porphyrin fluorophore within the tooth material was detected by time-gated nanosecond autofluorescence imaging. In particular, high contrast video images were obtained with an appropriate time delay of 15 ns to 25 ns between excitation and detection due to the suppression of short-lived autofluorescence of healthy tissue. First in vivo applications are reported indicating the potential of time-resolved fluorescence diagnostics for early caries- and dental plaque detection.     

Current problems in the diagnosis of gastric cancer

Based on their own long-term experience in diagnosing gastric cancer and by taking into account the fact that clinicians and diagnosticians analyze this problem insufficiently objectively, the authors of the paper try to convince the reader that it is necessary to revert to the problems of its diagnosis again. They proceed from recent new reports on gastric cancer pertaining to both its morphological forms and diagnostic capacities wherein current radiation diagnosis requires its active return to the problem of its detection. This standpoint of the authors is based on the date of over 6000 comprehensive studies of the stomach, of them 2800 cases have been diagnosed as having tumor lesions. In addition to the assessment of current radiation diagnosis of gastric cancer, which involves both routine X-ray study and ultrasonography, X-ray computed tomography, and magnetic resonance imaging of the stomach, the authors express their opinion on some organizational issues without which the diagnosis of this disease cannot be improved.