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This study explores the utility of a novel image-guided Raman endoscopy technique for in vivo distinction of gastric cancer from normal tissue during clinical gastroscopy. The rapid-acquisition fiber-optic Raman endoscopy system developed was employed for in vivo gastric tissue Raman measurements at 785 nm laser excitation. A total of 1063 in vivo Raman spectra were acquired from 238 tissue sites of 67 gastric patients who underwent endoscopic ultrasound staging procedure, in which 934 Raman spectra were from 121 normal tissue sites whereas 129 Raman spectra were from 117 neoplastic gastric tissue sites. Gastric Raman spectra were fitted and reconstructed by using a linear combination of the eight basis reference spectra from the biochemicals (i.e., actin, albumin, collagen, DNA, histones, pepsinogen, phospholipids and triolein) in gastric tissue and also compared with the in vivo gastric Raman spectra measured. The resulting fit coefficients were further utilized through recursive partitioning techniques to develop diagnostic algorithms for gastric cancer diagnosis. High-quality in vivo Raman spectra in the range of 800-1800 cm(-1) can be acquired from gastric mucosa within 0.5s. The fit coefficients from albumin, nucleic acid, phospholipids and histones were found to be the most significant features for construction of the diagnostic model, giving rise to an overall accuracy of 93.7% (i.e., sensitivity of 94.0% (110/117) and specificity of 93.4% (113/121)) for in vivo discrimination of cancerous tissue from normal gastric tissue after the leave-one tissue site-out, cross-validation technique. This work demonstrates for the first time that image-guided Raman endoscopy technique has promising potential for the non-invasive, in vivo diagnosis and detection of gastric cancer at the molecular level.

Background The aim of this study was to evaluate the feasibility of using near-infrared (NIR) Raman spectroscopy for early diagnosis and typing of intestinal and diffuse adenocarcinoma of the stomach. Methods A dispersive-type NIR Raman system was used for tissue measurements. One hundred gastric tissue samples from 62 patients who underwent endoscopy or gastrectomy were used (70 normal tissue specimens and 30 adenocarcinomas). Principal components analysis (PCA) and multinomial logistic regression (MNLR) were used to develop diagnostic algorithms for tissue classification. Results High-quality Raman spectra ranging from 800 to 1800 cm−1 were acquired from gastric tissue within 5 s. There were significant differences in Raman spectra between normal stomach and the two gastric adenocarcinoma subtypes, particularly in the spectral ranges 850–1150, 1200–1500 and 1600–1750 cm−1, which contain signals related to proteins, nucleic acids and lipids. PCA–MNLR achieved predictive accuracies of 88, 92 and 94 per cent for normal stomach, and intestinal- and diffuse-type gastric adenocarcinomas respectively. Conclusion NIR Raman spectroscopy can detect gastric malignancy and identify the subtype of gastric adenocarcinoma.

Raman spectroscopy is a unique vibrational spectroscopic technique which can be used to probe biochemicals and biomolecular structures and conformations of tissues. The main objective of this study is to evaluate the feasibility of applying near-infrared (NIR) Raman spectroscopy for identification of nonneoplastic lesions (Helicobacter-pylori (Hp) infection, and intestinal metaplasia (IM)) highly associated with stomach cancer. A rapid-acquisition NIR Raman spectroscopic system was used for tissue Raman measurements at 785 nm excitation, and a total of 88 gastric tissue samples (57 normal; 11 Hp-infection; 20 IM) from 56 patients were measured. The principal components analysis (PCA) and linear discriminant analysis (LDA) techniques were implemented to develop effective diagnostic algorithms for classification of Raman spectra of different gastric tissue types. High-quality Raman spectra in the range of 800-1800 cm(-1) were acquired from gastric tissue within 5 seconds. Significant spectral differences in Raman spectra were observed among normal, Hp-infection and IM gastric tissue, particularly in the spectral ranges of 848-917, 960-1015, 1088-1133, 1206-1213, 1277-1313, 1395-1445, 1517-1549, 1607-1690, and 1714-1767 cm(-1) which contained signals related to proteins, lipids and porphyrin. PCA-LDA algorithms developed together with leave one patient out, cross validation technique yield diagnostic sensitivities of 91.7%, 80.0%, and 80.0%, and specificities of 80.0%, 100%, and 92.7%, respectively, for classification of normal, Hp-infection and IM gastric tissues. This work demonstrates the utility of NIR Raman spectroscopy for early diagnosis of Hp-infection and IM lesions in the gastric at the molecular level.

Raman spectroscopy is a molecular vibrational spectroscopic technique that is capable of optically probing the biomolecular changes associated with neoplastic transformation. The purpose of this study was to apply near-infrared (NIR) Raman spectroscopy for differentiating dysplasia from normal gastric mucosa tissue. A total of 65 gastric mucosa tissues (44 normal and 21 dysplasia) were obtained from 35 patients who underwent endoscopy investigation or gastrectomy operation for this study. A rapid NIR Raman system was utilized for tissue Raman spectroscopic measurements at 785-nm laser excitation. High-quality Raman spectra in the range of 800–1800 cm−1 can be acquired from gastric mucosa tissue within 5 s. Raman spectra showed significant differences between normal and dysplastic tissue, particularly in the spectral ranges of 850–1150, 1200–1500 and 1600–1750 cm−1, which contained signals related to proteins, nucleic acids and lipids. The diagnostic decision algorithm based on the combination of Raman peak intensity ratios of I875/I1450 and I1208/I1655 and the logistic regression analysis yielded a diagnostic sensitivity of 90.5% and specificity of 90.9% for identification of gastric dysplasia tissue. This work demonstrates that NIR Raman spectroscopy in conjunction with intensity ratio algorithms has the potential for the noninvasive diagnosis and detection of precancer in the stomach at the molecular level. Copyright © 2009 John Wiley & Sons, Ltd.

We demonstrate that two-photon excited endogenous fluorescence enables label-free morphological and functional imaging of various human blood cells. Specifically, we achieved distinctive morphological contrast to visualize morphology of important leukocytes, such as polymorphonuclear structure of granulocyte and mononuclear feature of agranulocyte, through the employment of the reduced nicotinamide adenine dinucleotide (NADH) fluorescence signals. In addition, NADH fluorescence images clearly reveal the morphological transformation process of neutrophils during disease-causing bacterial infection. Our findings also show that time-resolved NADH fluorescence can be potentially used for functional imaging of the phagocytosis of pathogens by leukocytes (neutrophils) in vivo. In particular, we found that free-to-bound NADH ratios measured in infected neutrophils increased significantly, which is consistent with a previous study that the energy consumed in the phagocytosis of neutrophils is mainly generated through the glycolysis pathway that leads to the accumulation of free NADH. Future work will focus on further developing and applying label-free imaging technology to investigate leukocyte-related diseases and disorders.

Real time and in vivo monitoring leukocyte behavior provides unique information to understand the physiological and pathological process of infection. In this study, we demonstrate that two-photon excited reduced nicotinamide adenine dinucleotide (NADH) fluorescence provides imaging contrast to distinguish granulocyte and agranulocyte. By using spectral and time-resolved NADH fluorescence, we study the immune response of human neutrophils against bacterial infection ( Escherichia coli ). The two-photon excited NADH fluorescence images clearly review the morphological changes from resting neutrophils (round shape) to activated neutrophils (ruffle shape) during phagocytosis. The free-tobound NADH ratio of neutrophils decreases after ingesting disease-causing pathogen: Escherichia coli . This finding may provide a new optical tool to investigate inflammatory processes by using NADH fluorescence in vivo .

We explore in vivo diagnostic utility of an in-house developed multimodal nonlinear optical microscopy for detection of squamous epithelia precancer. Our results reveal all epithelial sublayers and stroma provide significant diagnostic information.

We conducted a systematic study on two-photon excited fluorescence (TPEF) of hemoglobin using the near transform-limited and Gaussian-shaped femtosecond pulse sources. We found that the two-photon action cross section of hemoglobin drops over 2 orders of magnitude in the wavelength range from 550 to 800 nm, while the spectral and temporal characteristics of hemoglobin TPEF are insensitive to the change of excitation wavelength. In particular, our new findings showed that the hemoglobin fluorescence could be excited with sufficient efficiency using a conventional Ti:sapphire laser tuned at the wavelength close to 700 nm. With the employment of a time-resolved detection method, we demonstrated that the TPEF signals of hemoglobin excited by a Ti:sapphire laser could be clearly differentiated from other nonlinear signals presented within the living biological tissues, indicating that a standard TPEF microscope can become a routine tool for in vivo label-free microangiography imaging.

Raman spectroscopy is a unique vibrational spectroscopic technique which can be used to probe biochemicals and biomolecular structures and conformations of tissues. The main objective of this study is to evaluate the feasibility of applying near-infrared (NIR) Raman spectroscopy for identification of nonneoplastic lesions (Helicobacter-pylori (Hp) infection, and intestinal metaplasia (IM)) highly associated with stomach cancer. A rapid-acquisition NIR Raman spectroscopic system was used for tissue Raman measurements at 785 nm excitation, and a total of 88 gastric tissue samples (57 normal; 11 Hp-infection; 20 IM) from 56 patients were measured. The principal components analysis (PCA) and linear discriminant analysis (LDA) techniques were implemented to develop effective diagnostic algorithms for classification of Raman spectra of different gastric tissue types. High-quality Raman spectra in the range of 800-1800 cm(-1) were acquired from gastric tissue within 5 seconds. Significant spectral differences in Raman spectra were observed among normal, Hp-infection and IM gastric tissue, particularly in the spectral ranges of 848-917, 960-1015, 1088-1133, 1206-1213, 1277-1313, 1395-1445, 1517-1549, 1607-1690, and 1714-1767 cm(-1) which contained signals related to proteins, lipids and porphyrin. PCA-LDA algorithms developed together with leave one patient out, cross validation technique yield diagnostic sensitivities of 91.7%, 80.0%, and 80.0%, and specificities of 80.0%, 100%, and 92.7%, respectively, for classification of normal, Hp-infection and IM gastric tissues. This work demonstrates the utility of NIR Raman spectroscopy for early diagnosis of Hp-infection and IM lesions in the gastric at the molecular level.

In this work, we evaluated the diagnostic ability of near-infrared (NIR) Raman spectroscopy associated with the ensemble recursive partitioning algorithm based on random forests for identifying cancer from normal tissue in the larynx. A rapid-acquisition NIR Raman system was utilized for tissue Raman measurements at 785 nm excitation, and 50 human laryngeal tissue specimens (20 normal; 30 malignant tumors) were used for NIR Raman studies. The random forests method was introduced to develop effective diagnostic algorithms for classification of Raman spectra of different laryngeal tissues. High-quality Raman spectra in the range of 800-1800 cm(-1) can be acquired from laryngeal tissue within 5 seconds. Raman spectra differed significantly between normal and malignant laryngeal tissues. Classification results obtained from the random forests algorithm on tissue Raman spectra yielded a diagnostic sensitivity of 88.0% and specificity of 91.4% for laryngeal malignancy identification. The random forests technique also provided variables importance that facilitates correlation of significant Raman spectral features with cancer transformation. This study shows that NIR Raman spectroscopy in conjunction with random forests algorithm has a great potential for the rapid diagnosis and detection of malignant tumors in the larynx.

We report an integrated Raman spectroscopy and trimodal (white-light reflectance, autofluorescence, and narrow-band) imaging techniques for real-time in vivo tissue Raman measurements at endoscopy. A special 1.8 mm endoscopic Raman probe with filtering modules is developed, permitting effective elimination of interference of fluorescence background and silica Raman in fibers while maximizing tissue Raman collections. We demonstrate that high-quality in vivo Raman spectra of upper gastrointestinal tract can be acquired within 1 s or subseconds under the guidance of wide-field endoscopic imaging modalities, greatly facilitating the adoption of Raman spectroscopy into clinical research and practice during routine endoscopic inspections.

The purpose of this study is to apply near-infrared (NIR) Raman spectroscopy and classification and regression tree (CART) techniques for identifying molecular changes of tissue associated with cancer transformation. A rapid-acquisition NIR Raman system is utilized for tissue Raman spectroscopic measurements at 785-nm excitation. 73 gastric tissue samples (55 normal, 18 cancer) from 53 patients are measured. The CART technique is introduced to develop effective diagnostic algorithms for classification of Raman spectra of different gastric tissues. 80% of the Raman dataset are randomly selected for spectral learning, while 20% of the dataset are reserved for validation. High-quality Raman spectra in the range of 800 to 1800 cm(-1) are acquired from gastric tissue within 5 s. The diagnostic sensitivity and specificity of the learning dataset are 90.2 and 95.7%; and the predictive sensitivity and specificity of the independent validation dataset are 88.9 and 92.9%, respectively, for separating cancer from normal. The tissue Raman peaks at 875 and 1745 cm(-1) are found to be two of the most significant features to discriminate gastric cancer from normal tissue. NIR Raman spectroscopy in conjunction with the CART technique has the potential to provide an effective and accurate diagnostic means for cancer detection in the gastric system.

In this report, the diagnostic ability of near-infrared (NIR) Raman spectroscopy for identifying the malignant tumors from normal tissues in the larynx was studied. A rapid NIR Raman system was utilized. Multivariate statistical techniques were employed to develop effective diagnostic algorithms. Raman spectra in the range of 800-1,800 cm-1 differed significantly between normal and malignant tumor tissues. The diagnostic algorithms can yielded a diagnostic sensitivity of 92.9% and specificity 83.3% for separating malignant tumors from normal laryngeal tissues. NIR Raman spectroscopy with multivariate statistical techniques has a potential for the non-invasive detection of malignant tumors in the larynx.

Raman spectroscopy is a molecular vibrational spectroscopic technique that is capable of optically probing the biomolecular changes associated with diseased transformation. The purpose of this study was to explore near-infrared (NIR) Raman spectroscopy for identifying precancer (dysplasia) from normal gastric mucosa tissues. High-quality Raman spectra in the range of 800-1800 cm-1 can be acquired from gastric tissue within 5 seconds. Raman spectra showed significant differences between normal and dysplastic tissue, particularly in the spectral ranges of 850-900, 1,200-1,290 and 1,500-1,800 cm-1 which contained signals related to hydroxyproline, amide III and amide I of proteins, and C=C stretching of lipids, respectively. The ratio of Raman intensities at 875 to 1,450 cm-1 provided good differentiation between normal and dysplastic gastric tissue (unpaired Students' t -test, p

We explore diagnostic utility of a multicolor excitation multimodal nonlinear optical (NLO) microscopy for noninvasive detection of squamous epithelial precancer in vivo. The 7,12-dimenthylbenz(a)anthracene treated hamster cheek pouch was used as an animal model of carcinogenesis. The NLO microscope system employed was equipped with the ability to collect multiple tissue endogenous NLO signals such as two-photon excited fluores- cence of keratin, nicotinamide adenine dinucleotide, collagen, and tryptophan, and second harmonic generation of collagen in spectral and time domains simultaneously. A total of 34 (11 controlled and 23 treated) Golden Syrian hamsters with 62 in vivo spatially distinct measurement sites were assessed in this study. High-resolution label-free NLO images were acquired from stratum corneum, stratum granulosum-stratum basale, and stroma for all tissue measurement sites. A total of nine and eight features from 745 and 600 nm excitation wavelengths, respectively, involving tissue structural and intrinsic biochemical properties were found to contain significant diagnostic infor- mation for precancers detection (p < 0.05). Particularly, 600 nm excited tryptophan fluorescence signals emanating from stratum corneum was revealed to provide remarkable diagnostic utility. Multivariate statistical techniques confirmed the integration of diagnostically significant features from multicolor excitation wavelengths yielded improved diagnostic accuracy as compared to using the individual wavelength alone. © 2013 Society of Photo-Optical

Objective: Raman spectroscopy is a unique optical vibrational spectroscopic technique that is capable of noninvasively probing biomolecular changes associated with cancerous transformation. The aim of this study was to investigate the feasibility of a novel imaged-guided Raman endoscopy system developed for distinguishing cancer lesions from the non-cancerous tissues in the human stomach in vivo. Materials and Methods: A fiber-optic Raman endoscopy system was utilized for tissue Raman spectroscopic measurements at 785 nm laser excitation. A total of 20 in vivo gastric Raman measurement sites were used in this study, in which 15 sites were from 10 patients who underwent gastroscopic inspection, and 5 were from the suspicious lesion sites of 5 patients who underwent endoscopic ultrasound procedure. The histopathogical examinations on the biopsied tissues from the Raman measurement sites showed that 15 were non-cancerous and 5 were cancers. Multivariate statistical algorithms including principal component analysis (PCA) and linear discriminant analysis (LDA) were employed to determine the diagnostic sensitivity and specificity. Results: High-quality in vivo gastric Raman spectra in the range of 800-1800 cm−1 can be collected in less than 1 second, together with the simultaneous utilization of white-light reflectance imaging modality for guiding the Raman endoscopic probe to the suspicious tissue sites. Raman spectral shapes were significantly different between non-cancerous and cancers, particularly in the spectral ranges of 850-900 cm−1, 1000-1090 cm−1, 1200-1305 cm−1 and 1600-1800 cm−1 which contain signals related to hydroxyproline for collagen, phenylalanine, amide III, amide I and C=C stretching of lipids. The Raman technique together with PCA-LDA-based analytic algorithm yielded diagnostic sensitivity of 96.1% and specificity of 100% for detection of cancer from the non-cancerous gastric tissues in vivo. Conclusion: This study illustrates for the first time that the image-guided Raman endoscopy technique has promising clinical potential for rapid in vivo diagnosis of cancer tissues in the stomach. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 1165.