Near-infrared Raman spectroscopy for optical diagnosis in the stomach: identification of Helicobacter-pylori infection and intestinal metaplasia

Diagnosis of ''Helicobacter pylori infection of the gastric biopsy'' by rapid urease test, histopathology and Raman spectroscopy

This study aim to investigate the diagnostic potential of Raman spectroscopy in comparison with rapid urease test and histopathology in diagnosis of H. pylori infection. A comparative study was conducted at Pathology Laboratory and a total of 94 samples were collected from patients based on Rome IV criteria. Sensitivity, specificity and accuracy of histopathology, rapid urease test and for Raman spectroscopy were investigated. Rapid urease test showed 23 false negative results of H. pylori as compared to Raman spectroscopy and histopathology. We concluded that Raman spectroscopy showed sensitivity (94.5%), accuracy (94.0%) and specificity of (87.5%) in the diagnosis of H. pylori infection. However rapid urease test showed specificity of 92.5% while low sensitivity 75%, and 78% accuracy as compared to Raman spectroscopy and histopathology . This study illustrates the applicability of Raman spectroscopy as a potent innovative detection tool for the molecular detection of H. pylori infection in gastritis.

Early Detection of Pre-Cancerous and Cancerous Cells Using Raman Spectroscopy-Based Machine Learning

Cancer is the most common and fatal disease around the globe, with an estimated 19 million newly diagnosed patients and approximately 10 million deaths annually. Patients with cancer struggle daily due to difficult treatments, pain, and financial and social difficulties. Detecting the disease in its early stages is critical in increasing the likelihood of recovery and reducing the financial burden on the patient and society. Currently used methods for the diagnosis of cancer are time-consuming, producing discomfort and anxiety for patients and significant medical waste. The main goal of this study is to evaluate the potential of Raman spectroscopy-based machine learning for the identification and characterization of precancerous and cancerous cells. As a representative model, normal mouse primary fibroblast cells (NFC) as healthy cells; a mouse fibroblast cell line (NIH/3T3), as precancerous cells; and fully malignant mouse fibroblasts (MBM-T) as cancerous cells were used. Raman spectra were measured from three different sites of each of the 457 investigated cells and analyzed by principal component analysis (PCA) and linear discriminant analysis (LDA). Our results showed that it was possible to distinguish between the normal and abnormal (precancerous and cancerous) cells with a success rate of 93.1%; this value was 93.7% when distinguishing between normal and precancerous cells and 80.2% between precancerous and cancerous cells. Moreover, there was no influence of the measurement site on the differentiation between the different examined biological systems.

Beyond images: Emerging role of Raman spectroscopy-based artificial intelligence in diagnosis of gastric neoplasia

White-light endoscopy with tissue biopsy is the gold standard interface for diagnosing gastric neoplastic lesions. However, misdiagnosis of lesions is a challenge because of operator variability and learning curve issues. These issues have not been resolved despite the introduction of advanced imaging technologies, including narrow band imaging, and confocal laser endomicroscopy. To ensure consistently high diagnostic accuracy among endoscopists, artificial intelligence (AI) has recently been introduced to assist endoscopists in the diagnosis of gastric neoplasia. Current endoscopic AI systems for endoscopic diagnosis are mostly based upon interpretation of endoscopic images. In real-life application, the image-based AI system remains reliant upon skilful operators who will need to capture sufficiently good quality images for the AI system to analyze. Such an ideal situation may not always be possible in routine practice. In contrast, non-image-based AI is less constraint by these requirements. Our group has recently developed an endoscopic Raman fibre-optic probe that can be delivered into the gastrointestinal tract via the working channel of any endoscopy for Raman measurements. We have also successfully incorporated the endoscopic Raman spectroscopic system with an AI system. Proof of effectiveness has been demonstrated in in vivo studies using the Raman endoscopic system in close to 1,000 patients. The system was able to classify normal gastric tissue, gastric intestinal metaplasia, gastric dysplasia and gastric cancer, with diagnostic accuracy of >85%. Because of the excellent correlation between Raman spectra and histopathology, the Raman-AI system can provide optical diagnosis, thus allowing the endoscopists to make clinical decisions on the spot. Furthermore, by allowing non-expert endoscopists to make real-time decisions as well as expert endoscopists, the system will enable consistency of care.

Raman Spectroscopy: A Novel Technology for Gastric Cancer Diagnosis

Gastric cancer is usually diagnosed at late stage and has a high mortality rate, whereas early detection of gastric cancer could bring a better prognosis. Conventional gastric cancer diagnostic methods suffer from long diagnostic times, severe trauma, and a high rate of misdiagnosis and rely heavily on doctors’ subjective experience. Raman spectroscopy is a label-free molecular vibrational spectroscopy technique that identifies the molecular fingerprint of various samples based on the inelastic scattering of monochromatic light. Because of its advantages of non-destructive, rapid, and accurate detection, Raman spectroscopy has been widely studied for benign and malignant tumor differentiation, tumor subtype classification, and section pathology diagnosis. This paper reviews the applications of Raman spectroscopy for the in vivo and in vitro diagnosis of gastric cancer, methodology related to the spectroscopy data analysis, and presents the limitations of the technique.

Development and characterization of a disposable submillimeter fiber optic Raman needle probe for enhancing real-time in vivo deep tissue and biofluids Raman measurements

We report on the development and characterization of disposable submillimeter fiber optic Raman needle probe for enhancing real-time in vivo tissue and biofluids Raman measurements. The submillimeter Raman probe is designed and fabricated using an aluminum-coated multimode fiber tapered with a semispherical lens, resulting in the coaxial laser excitation/Raman collection configuration for maximizing tissue and biofluid Raman measurements. We demonstrate that, with the use of the Raman needle probe associated with the structured background subtraction algorithms developed, high quality tissue Raman spectra covering both the fingerprint (FP) (800-1800cm^-1) and high-wavenumber (HW) (2800-3300cm^-1) regions can be acquired within subseconds from different tissue types (e.g., skin, muscle, fat, cartilage, liver, and brain) and biofluids (e.g., blood, urine). By advancing the Raman needle probe into the murine brain tissue model, high quality depth-resolved deep tissue Raman spectra can also be acquired rapidly. This work shows that the submillimeter fiberoptic Raman needle probe is capable of achieving real-time collection of deep tissue and biofluids FP/HW Raman spectra with high signal to noise ratios. This opens a new avenue with dual functioning of Raman optical biopsy and fine needle aspiration biopsy for enhancing in vivo deep tissue and biofluids diagnosis and characterization in different organs.

Optical Biopsy of the Upper GI Tract Using Fluorescence Lifetime and Spectra

Screening and surveillance for gastrointestinal (GI) cancers by endoscope guided biopsy is invasive, time consuming, and has the potential for sampling error. Tissue endogenous fluorescence spectra contain biochemical and physiological information, which may enable real-time, objective diagnosis. We first briefly reviewed optical biopsy modalities for GI cancer diagnosis with a focus on fluorescence-based techniques. In an ex vivo pilot clinical study, we measured fluorescence spectra and lifetime on fresh biopsy specimens obtained during routine upper GI screening procedures. Our results demonstrated the feasibility of rapid acquisition of time-resolved fluorescence (TRF) spectra from fresh GI mucosal specimens. We also identified spectroscopic signatures that can differentiate between normal mucosal samples obtained from the esophagus, stomach, and duodenum.

Advanced endoscopic methods in gastrointestinal diseases: a systematic review

Endoscopic imaging is the main method for detecting gastrointestinal diseases, which adversely affect human health. White light endoscopy (WLE) was the first method used for endoscopic examination and is still the preliminary step in the detection of gastrointestinal diseases during clinical examination. However, it cannot accurately diagnose gastrointestinal diseases owing to its poor correlation with histopathological diagnosis. In recent years, many advanced endoscopic methods have emerged to improve the detection accuracy by endoscopy. Chromoendoscopy (CE) enhances the contrast between normal and diseased tissues using biocompatible dye agents. Narrow band imaging (NBI) can improve the contrast between capillaries and submucosal vessels by changing the light source acting on the tissue using special filters to realize the visualization of the vascular structure. Flexible spectral imaging color enhancement (FICE) technique uses the reflectance spectrum estimation technique to obtain individual spectral images and reconstructs an enhanced image of the mucosal surface using three selected spectral images. The i-Scan technology takes advantage of the different reflective properties of normal and diseased tissues to obtain images, and enhances image contrast through post-processing algorithms. These abovementioned methods can be used to detect gastrointestinal diseases by observing the macroscopic structure of the digestive tract mucosa, but the ability of early cancer detection is limited with low resolution. However, based on the principle of confocal imaging, probe-based confocal laser endomicroscopy (pCLE) can enable cellular visualization with high-performance probes, which can present cellular morphology that is highly consistent with that shown by biopsy to provide the possibility of early detection of cancer. Other endoscopic imaging techniques including endoscopic optical coherence tomography (EOCT) and photoacoustic endoscopy (PAE), are also promising for diagnosing gastrointestinal diseases. This review focuses on these technologies and aims to provide an overview of different technologies and their clinical applicability.

Application of metasurface-enhanced infra-red spectroscopy to distinguish between normal and cancerous cell types

Fourier transform infrared (FTIR) spectra of biological cells can reveal clinically important information about cells' composition, including their normal or cancerous status. The recently emerged diagnostic technique of spectral cytopathology (SCP) combines FTIR with multivariate statistical analysis to detect cell abnormalities, differentiate between cell types, and monitor disease progression. We demonstrate a new variant of SCP, a metasurface-enhanced infrared reflection spectroscopic cytopathology (MEIRSC) that utilises judiciously designed plasmonic metasurfaces to localize and enhance the evanescent field near the cell's membrane, and to carry out spectroscopic interrogations of the cells attached to the metasurface using reflected infrared light. Our findings indicate that the MEIRSC approach enables us to differentiate between normal and cancerous human colon cells. The sensitivity of MEIRSC is such that a very small (about 50 nm deep) portion of the cell can yield valuable diagnostic information.

Label-free rapid identification of tumor cells and blood cells with silver film SERS substrate

The detection of circulating tumor cells (CTCs) from peripheral blood is considered as great significance for the diagnosis and prognosis of cancer patients. Raman spectroscopy is a highly sensitive optical detection technique that can provide fingerprint molecular identification information. In this paper, the silver film substrate surface-enhanced Raman scattering (SERS) was used to research several tumor cells, immortalized cells, clinical cancer cells isolated from cancer patient's tissue and blood cells. The results display that there is great difference for the nucleic acid characteristic peaks of those cells. The red blood cells have almost none nucleic acid characteristic peak and the SERS signals of white blood cells are only a slight increase. Except for immortalized cells and few tumor cells, the nucleic acid characteristic peaks of some tumor cells have huge enhancement. Nucleic acid characteristic peaks of clinical cancer cells also have greater enhancement. The discriminant model established by the intensity ratio of the nucleic acid characteristic peak 730 cm^-1 to the substrate background peak 900 cm^-1 shows that some tumor cells and clinical sample cells can be separated from white blood cells, but tumor cells with relatively low-DNA index cannot be differentiated from white blood cells. This study demonstrates that thin-film SERS technology can distinguish between blood cells and some types of tumor cells. This study opens up a new possible method for the detection of CTCs with label-free SERS spectra.

Combining high wavenumber and fingerprint Raman spectroscopy for the detection of prostate cancer during radical prostatectomy

For prostate cancer (PCa) patients, radical prostatectomy (complete removal of the prostate) is the only curative surgical option. To date, there is no clinical technique allowing for real-time assessment of surgical margins to minimize the extent of residual cancer. Here, we present a tissue interrogation technique using a dual excitation wavelength Raman spectroscopy system capable of sequentially acquiring fingerprint (FP) and high wavenumber (HWN) Raman spectra. Results demonstrate the ability of the system to detect PCa in post-prostatectomy specimens. In total, 477 Raman spectra were collected from 18 human prostate slices. Each area measured with Raman spectroscopy was characterized as either normal or cancer based on histopathological analyses, and each spectrum was classified based on supervised learning using support vector machines (SVMs). Based on receiver operating characteristic (ROC) analysis, FP (area under the curve [AUC] = 0.89) had slightly superior cancer detection capabilities compared with HWN (AUC = 0.86). Optimal performance resulted from combining the spectral information from FP and HWN (AUC = 0.91), suggesting that the use of these two spectral regions may provide complementary molecular information for PCa detection. The use of leave-one-(spectrum)-out (LOO) or leave-one-patient-out (LOPO) cross-validation produced similar classification results when combining FP with HWN. Our findings suggest that the application of machine learning using multiple data points from the same patient does not result in biases necessarily impacting the reliability of the classification models.

Using Raman Spectroscopy to Detect and Diagnose Skin Cancer In Vivo

Raman spectroscopy provides a noninvasive bedside tool that captures unique optical signals via molecular vibrations in tissue samples. Raman theory was discovered at the beginning of the twentieth century, but it was not until the past few decades that it has been used to differentiate skin neoplasms. We provide a brief description of Raman spectroscopy for in vivo skin cancer diagnosis, including the physical principles underlying Raman spectroscopy, its advantages, typical spectra of skin pathologies, and its clinical application for aiding skin cancer diagnosis.

Biomedical optical spectroscopy for the early diagnosis of gastrointestinal neoplasms

Gastrointestinal cancer is a leading contributor to cancer-related morbidity and mortality worldwide. Early diagnosis currently plays a key role in the prognosis of patients with gastrointestinal cancer. Despite the advances in endoscopy over the last decades, missing lesions, undersampling and incorrect sampling in biopsies, as well as invasion still result in a poor diagnostic rate of early gastrointestinal cancers. Accordingly, there is a pressing need to develop non-invasive methods for the early detection of gastrointestinal cancers. Biomedical optical spectroscopy, including infrared spectroscopy, Raman spectroscopy, diffuse scattering spectroscopy and autofluorescence, is capable of providing structural and chemical information about biological specimens with the advantages of non-destruction, non-invasion and reagent-free and waste-free analysis and has thus been widely investigated for the diagnosis of oesophageal, gastric and colorectal cancers. This review will introduce the advances of biomedical optical spectroscopy techniques, highlight their applications for the early detection of gastrointestinal cancers and discuss their limitations.

Advanced endoscopic imaging in gastric neoplasia and preneoplasia

Conventional white light endoscopy remains the current standard in routine clinical practice for early detection of gastric cancer. However, it may not accurately diagnose preneoplastic gastric lesions. The technological advancements in the field of endoscopic imaging for gastric lesions are fast growing. This article reviews currently available advanced endoscopic imaging modalities, in particular chromoendoscopy, narrow band imaging and confocal laser endomicroscopy, and their corresponding evidence shown to improve diagnosis of preneoplastic gastric lesions. Raman spectrometry and polarimetry are also introduced as promising emerging technologies.

Confocal Raman microscopy and multivariate statistical analysis for determination of different penetration abilities of caffeine and propylene glycol applied simultaneously in a mixture on porcine skin ex vivo

Propylene glycol is one of the known substances added in cosmetic formulations as a penetration enhancer. Recently, nanocrystals have been employed also to increase the skin penetration of active components. Caffeine is a component with many applications and its penetration into the epidermis is controversially discussed in the literature. In the present study, the penetration ability of two components - caffeine nanocrystals and propylene glycol, applied topically on porcine ear skin in the form of a gel, was investigated ex vivo using two confocal Raman microscopes operated at different excitation wavelengths (785nm and 633nm). Several depth profiles were acquired in the fingerprint region and different spectral ranges, i.e., 526-600cm(-1) and 810-880cm(-1) were chosen for independent analysis of caffeine and propylene glycol penetration into the skin, respectively. Multivariate statistical methods such as principal component analysis (PCA) and linear discriminant analysis (LDA) combined with Student's t-test were employed to calculate the maximum penetration depths of each substance (caffeine and propylene glycol). The results show that propylene glycol penetrates significantly deeper than caffeine (20.7-22.0μm versus 12.3-13.0μm) without any penetration enhancement effect on caffeine. The results confirm that different substances, even if applied onto the skin as a mixture, can penetrate differently. The penetration depths of caffeine and propylene glycol obtained using two different confocal Raman microscopes are comparable showing that both types of microscopes are well suited for such investigations and that multivariate statistical PCA-LDA methods combined with Student's t-test are very useful for analyzing the penetration of different substances into the skin.

Simultaneous fingerprint and high-wavenumber fiber-optic Raman spectroscopy enhances real-time in vivo diagnosis of adenomatous polyps during colonoscopy

Colorectal cancer can be prevented if detected early (e.g., precancerous polyps-adenoma). Endoscopic differential diagnosis of hyperplastic polyps (that have little or no risk of malignant transformation) and adenomas (that have prominent malignant latency) remains an unambiguous clinical challenge. Raman spectroscopy is an optical vibrational technique capable of probing biomolecular changes of tissue associated with neoplastic transformation. This work aims to apply a fiber-optic simultaneous fingerprint (FP) and high wavenumber (HW) Raman spectroscopy technique for real-time in vivo assessment of adenomatous polyps during clinical colonoscopy. We have developed a fiber-optic Raman endoscopic technique capable of simultaneously acquiring both the FP (i.e., 800-1800 cm(-1)) and HW (i.e., 2800-3600 cm(-1)) Raman spectra from colorectal tissue subsurface (<200 µm) for real-time assessment of colorectal carcinogenesis. In vivo FP/HW Raman spectra were acquired from 50 patients with 17 colorectal polyps during clinical colonoscopy. Prominent Raman spectral differences (p < 0.001) were found between hyperplastic (n = 118 spectra), adenoma (n = 184 spectra) that could be attributed to changes in inter- and intra-cellular proteins, lipids, DNA and water structures and conformations. Simultaneous FP/HW Raman endoscopy provides a diagnostic sensitivity of 90.9% and specificity of 83.3% for differentiating adenoma from hyperplastic polyps, which is superior to either the FP or HW Raman technique alone. This study shows that simultaneous FP/HW Raman spectroscopy technique has the potential to be a clinically powerful tool for improving early diagnosis of adenomatous polyps in vivo during colonoscopic examination.

Rapid Fiber-optic Raman Spectroscopy for Real-Time In Vivo Detection of Gastric Intestinal Metaplasia during Clinical Gastroscopy

We report a unique simultaneous fingerprint (FP) and high-wavenumber (HW) Raman spectroscopy technique coupled with a beveled fiber-optic Raman probe for improving in vivo detection of gastric intestinal metaplasia (IM)-precancerous lesions in real-time during clinical gastroscopy. A total of 4,520 high-quality in vivo FP/HW gastric Raman spectra (normal = 4,178; IM = 342) were acquired from 157 gastric patients undergoing endoscopic examination. Multivariate diagnostic algorithms based on principal components analysis and linear discriminant analysis together with the leave-one tissue site-out, cross-validation on in vivo tissue Raman spectra yield the diagnostic sensitivities of 89.3%, 89.3%, and 75.0%; specificities of 92.2%, 84.4%, and 82.0%; positive predictive values of 52.1%, 35.2%, and 28.4%; and negative predictive values of 98.9%, 98.8%, and 97.2%, respectively, by using the integrated FP/HW, FP, and HW Raman techniques for identifying IM from normal gastric tissue. Further, ROC curves generated show that the integrated FP/HW Raman technique gives the integration area under the ROC curve of 0.92 for IM classification, which is superior to either FP (0.89) or HW Raman (0.86) technique alone. This work demonstrates for the first time that the simultaneous FP/HW fiber-optic Raman spectroscopy has great potential to enhance early diagnosis of gastric precancer in vivo during routine endoscopic examination. Cancer Prev Res; 9(6); 476-83. ©2016 AACR.

Application of endoscopic molecular imaging in diagnosis of gastric intestinal metaplasia

Gastric intestinal metaplasia (GIM) is a precancerous lesion of intestinal type gastric carcinoma. Early diagnosis and follow-up can improve the detection rate of early gastric cancer. In recent years, with the integration of molecular imaging into endoscopy, auto fluorescence endoscopy, Raman spectroscopy, two-photon fluorescence endomicroscopy, and confocal laser endomicroscopy have emerged, which improves the detection rate of GIM. This paper reviews the progress of the application of endoscopic molecular imaging in the diagnosis of GIM.

Simultaneous fingerprint and high-wavenumber fiber-optic Raman spectroscopy improves in vivo diagnosis of esophageal squamous cell carcinoma at endoscopy

This work aims to evaluate clinical value of a fiber-optic Raman spectroscopy technique developed for in vivo diagnosis of esophageal squamous cell carcinoma (ESCC) during clinical endoscopy. We have developed a rapid fiber-optic Raman endoscopic system capable of simultaneously acquiring both fingerprint (FP)(800–1800 cm⁻¹) and high-wavenumber (HW)(2800–3600 cm⁻¹) Raman spectra from esophageal tissue in vivo. A total of 1172 in vivo FP/HW Raman spectra were acquired from 48 esophageal patients undergoing endoscopic examination. The total Raman dataset was split into two parts: 80% for training; while 20% for testing. Partial least squares-discriminant analysis (PLS-DA) and leave-one patient-out, cross validation (LOPCV) were implemented on training dataset to develop diagnostic algorithms for tissue classification. PLS-DA-LOPCV shows that simultaneous FP/HW Raman spectroscopy on training dataset provides a diagnostic sensitivity of 97.0% and specificity of 97.4% for ESCC classification. Further, the diagnostic algorithm applied to the independent testing dataset based on simultaneous FP/HW Raman technique gives a predictive diagnostic sensitivity of 92.7% and specificity of 93.6% for ESCC identification, which is superior to either FP or HW Raman technique alone. This work demonstrates that the simultaneous FP/HW fiber-optic Raman spectroscopy technique improves real-time in vivo diagnosis of esophageal neoplasia at endoscopy.

Endoscopic Raman Spectroscopy for Molecular Fingerprinting of Gastric Cancer: Principle to Implementation

Currently, positive endoscopic biopsy is the standard criterion for gastric cancer diagnosis but is invasive, often inconsistent, and delayed although early detection and early treatment is the most important policy. Raman spectroscopy is a spectroscopic technique based on inelastic scattering of monochromatic light. Raman spectrum represents molecular composition of the interrogated volume providing a direct molecular fingerprint. Several investigations revealed that Raman spectroscopy can differentiate normal, dysplastic, and adenocarcinoma gastric tissue with high sensitivity and specificity. Moreover, this technique can indentify malignant ulcer and showed the capability to analyze the carcinogenesis process. Automated on-line Raman spectral diagnostic system raised possibility to use Raman spectroscopy in clinical field. Raman spectroscopy can be applied in many fields such as guiding a target biopsy, optical biopsy in bleeding prone situation, and delineating the margin of the lesion. With wide field technology, Raman spectroscopy is expected to have specific role in our future clinical field.

Diagnosing Helicobacter pylori infection in vivo by novel endoscopic techniques

Infection with Helicobacter pylori (H. pylori) is a worldwide problem. Endoscopic observation of H. pylori infection in vivo would be helpful to obtain an immediate diagnosis. The aim of this review is to describe recent advances in endoscopic technology and to review the available literature pertaining to its clinical application in H. pylori infection. Endoscopic visualization of H. pylori infection is not always feasible using conventional endoscopy. Thus, advanced endoscopic techniques have been developed with the aim of providing a precise and ‘‘real-time’’ endoscopic diagnosis. Recently, new endoscopic techniques such as magnifying endoscopy, narrow band imaging, I-Scan, endocytoscopy and endomicroscopy help focus examination of the stomach to diagnose disease in a time-efficient manner, and the analysis of mucosal surface details is beginning to resemble histologic examination. The new detailed images have enabled endoscopists to observe microscopic structures, such as gastric pit patterns, microvessels and cell morphology. Accordingly, endoscopic prediction of H. pylori infection is possible by analysis of surface architecture of the mucosa, which influences the clinical management. These endoscopic techniques might lead us to easier diagnosis and treatment of H. pylori-related diseases.

Colonization resistance and microbial ecophysiology: using gnotobiotic mouse models and single-cell technology to explore the intestinal jungle

The highly diverse intestinal microbiota forms a structured community engaged in constant communication with itself and its host and is characterized by extensive ecological interactions. A key benefit that the microbiota affords its host is its ability to protect against infections in a process termed colonization resistance (CR), which remains insufficiently understood. In this review, we connect basic concepts of CR with new insights from recent years and highlight key technological advances in the field of microbial ecology. We present a selection of statistical and bioinformatics tools used to generate hypotheses about synergistic and antagonistic interactions in microbial ecosystems from metagenomic datasets. We emphasize the importance of experimentally testing these hypotheses and discuss the value of gnotobiotic mouse models for investigating specific aspects related to microbiota-host-pathogen interactions in a well-defined experimental system. We further introduce new developments in the area of single-cell analysis using fluorescence in situ hybridization in combination with metabolic stable isotope labeling technologies for studying the in vivo activities of complex community members. These approaches promise to yield novel insights into the mechanisms of CR and intestinal ecophysiology in general, and give researchers the means to experimentally test hypotheses in vivo at varying levels of biological and ecological complexity.

Simultaneous fingerprint and high-wavenumber confocal Raman spectroscopy enhances early detection of cervical precancer in vivo

Raman spectroscopy is a vibrational spectroscopic technique capable of nondestructively probing endogenous biomolecules and their changes associated with dysplastic transformation in the tissue. The main objectives of this study are (i) to develop a simultaneous fingerprint (FP) and high-wavenumber (HW) confocal Raman spectroscopy and (ii) to investigate its diagnostic utility for improving in vivo diagnosis of cervical precancer (dysplasia). We have successfully developed an integrated FP/HW confocal Raman diagnostic system with a ball-lens Raman probe for simultaneous acquistion of FP/HW Raman signals of the cervix in vivo within 1 s. A total of 476 in vivo FP/HW Raman spectra (356 normal and 120 precancer) are acquired from 44 patients at clinical colposcopy. The distinctive Raman spectral differences between normal and dysplastic cervical tissue are observed at ~854, 937, 1001, 1095, 1253, 1313, 1445, 1654, 2946, and 3400 cm(-1) mainly related to proteins, lipids, glycogen, nucleic acids and water content in tissue. Multivariate diagnostic algorithms developed based on partial least-squares-discriminant analysis (PLS-DA) together with the leave-one-patient-out, cross-validation yield the diagnostic sensitivities of 84.2%, 76.7%, and 85.0%, respectively; specificities of 78.9%, 73.3%, and 81.7%, respectively; and overall diagnostic accuracies of 80.3%, 74.2%, and 82.6%, respectively, using FP, HW, and integrated FP/HW Raman spectroscopic techniques for in vivo diagnosis of cervical precancer. Receiver operating characteristic (ROC) analysis further confirms the best performance of the integrated FP/HW confocal Raman technique, compared to FP or HW Raman spectroscopy alone. This work demonstrates, for the first time, that the simultaneous FP/HW confocal Raman spectroscopy has the potential to be a clinically powerful tool for improving early diagnosis and detection of cervical precancer in vivo during clinical colposcopic examination.

Raman spectroscopy: a potential tool for early objective diagnosis of neoplasia in the oesophagus

There is a profound clinical need for a diagnostic tool that will enable clinicians to identify early neoplastic change in the oesophagus. Raman Spectroscopy (RS) has demonstrated the potential to provide non-invasive, rapid, objective diagnosis of endoscopically invisible precancerous oesophageal dysplasia in vitro. RS analyses biological material to identify highly specific biochemical information that can be used to influence clinical care. Raman spectroscopic mapping could provide automated assessment of tissue biopsies to aid histopathological diagnosis in vitro. Furthermore, the recent development of fibre-optic Raman probes has enabled endoscopic assessment of oesophageal mucosa in vivo. Accurate identification of dysplasia will enable targeted endoscopic resection of early lesions preventing the development of oesophageal cancer. This review summarises the development of Raman systems for use as laboratory based analytical adjuncts and endoscopic diagnostic tools in the distal oesophagus.

In vivo diagnosis of cervical precancer using Raman spectroscopy and genetic algorithm techniques

This study aimed to evaluate the clinical utility of applying near-infrared (NIR) Raman spectroscopy and genetic algorithm-partial least squares-discriminant analysis (GA-PLS-DA) to identify biomolecular changes of cervical tissues associated with dysplastic transformation during colposcopic examination. A total of 105 in vivo Raman spectra were measured from 57 cervical sites (35 normal and 22 precancer sites) of 29 patients recruited, in which 65 spectra were from normal sites, while 40 spectra were from cervical precancerous lesions (i.e., 7 low-grade CIN and 33 high-grade CIN). The GA feature selection technique incorporated with PLS was utilized to study the significant biochemical Raman bands for differentiation between normal and precancer cervical tissues. The GA-PLS-DA algorithm with double cross-validation (dCV) identified seven diagnostically significant Raman bands in the ranges of 925-935, 979-999, 1080-1090, 1240-1260, 1320-1340, 1400-1420, and 1625-1645 cm(-1) related to proteins, nucleic acids and lipids in tissue, and yielded a diagnostic accuracy of 82.9% (sensitivity of 72.5% (29/40) and specificity of 89.2% (58/65)) for precancer detection. The results of this exploratory study suggest that Raman spectroscopy in conjunction with GA-PLS-DA and dCV methods has the potential to provide clinically significant discrimination between normal and precancer cervical tissues at the molecular level.

Combining near-infrared-excited autofluorescence and Raman spectroscopy improves in vivo diagnosis of gastric cancer

This study aims to evaluate the diagnostic utility of the combined near-infrared (NIR) autofluorescence (AF) and Raman spectroscopy for improving in vivo detection of gastric cancer at clinical gastroscopy. A rapid Raman endoscopic technique was employed for in vivo spectroscopic measurements of normal (n=1098) and cancer (n=140) gastric tissues from 81 gastric patients. The composite NIR AF and Raman spectra in the range of 800-1800 cm(-1) were analyzed using principal component analysis (PCA) and linear discriminant (LDA) to extract diagnostic information associated with distinctive spectroscopic processes of gastric malignancies. High quality in vivo composite NIR AF and Raman spectra can routinely be acquired from the gastric within 0.5s. The integrated intensity over the range of 800-1800 cm(-1) established the diagnostic implications (p=1.6E-14) of the change of NIR AF intensity associated with neoplastic transformation. PCA-LDA diagnostic modeling on the in vivo tissue NIR AF and Raman spectra acquired yielded a diagnostic accuracy of 92.2% (sensitivity of 97.9% and specificity of 91.5%) for identifying gastric cancer from normal tissue. The integration area under the receiver operating characteristic (ROC) curve using the combined NIR AF and Raman spectroscopy was 0.985, which is superior to either the Raman spectroscopy or NIR AF spectroscopy alone. This work demonstrates that the complementary Raman and NIR AF spectroscopy techniques can be integrated together for improving the in vivo diagnosis and detection of gastric cancer at endoscopy.

Characterizing variability in in vivo Raman spectra of different anatomical locations in the upper gastrointestinal tract toward cancer detection

Raman spectroscopy is an optical vibrational technology capable of probing biomolecular changes of tissue associated with cancer transformation. This study aimed to characterize in vivo Raman spectroscopic properties of tissues belonging to different anatomical regions in the upper gastrointestinal (GI) tract and explore the implications for early detection of neoplastic lesions during clinical gastroscopy. A novel fiber-optic Raman endoscopy technique was utilized for real-time in vivo tissue Raman measurements of normal esophageal (distal, middle, and proximal), gastric (antrum, body, and cardia) as well as cancerous esophagous and gastric tissues from 107 patients who underwent endoscopic examinations. The non-negativity-constrained least squares minimization coupled with a reference database of Raman active biochemicals (i.e., actin, histones, collagen, DNA, and triolein) was employed for semiquantitative biomolecular modeling of tissue constituents in the upper GI. A total of 1189 in vivo Raman spectra were acquired from different locations in the upper GI. The Raman spectra among the distal, middle, and proximal sites of the esophagus showed no significant interanatomical variability. The interanatomical variability of Raman spectra among normal gastric tissue (antrum, body, and cardia) was subtle compared to cancerous tissue transformation, whereas biomolecular modeling revealed significant differences between the two organs, particularly in the gastroesophageal junction associated with proteins, DNA, and lipids. Cancerous tissues can be identified across interanatomical regions with accuracies of 89.3% [sensitivity of 92.6% (162∕175); specificity of 88.6% (665∕751)], and of 94.7% [sensitivity of 90.9% (30∕33); specificity of 93.9% (216∕230)] in the gastric and esophagus, respectively, using partial least squares-discriminant analysis together with the leave-one tissue site-out, cross validation. This work demonstrates that Raman endoscopy technique has promising clinical potential for real-time, in vivo diagnosis and detection of malignancies in the upper GI at the molecular level.

Role of optical spectroscopy using endogenous contrasts in clinical cancer diagnosis

Optical spectroscopy has been intensively studied for cancer management in the past two decades. This review paper first introduces the background of optical spectroscopy for cancer management, which includes the advantages of optical techniques compared to other established techniques, the principle of optical spectroscopy and the typical setup of instrumentation. Then the recent progress in optical spectroscopy for cancer diagnosis in the following organs is reviewed: the brain, breast, cervix, lung, stomach, colon, prostate and the skin. Reviewed papers were selected from the PubMed database with keywords combining the terms of individual optical spectroscopy techniques and cancers. The primary focus is on the in vivo applications of optical spectroscopy in clinical studies. Ex vivo studies are also included for some organs to highlight special applications or when there are few in vivo results in the literature. Practical considerations of applying optical spectroscopy in clinical settings such as the speed, cost, complexity of operation, accuracy and clinical value are discussed. A few commercially available clinical instruments that are based on optical spectroscopy techniques are presented. Finally several technical challenges and standard issues are discussed and firm conclusions are made.

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

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

In vivo diagnosis of gastric cancer using Raman endoscopy and ant colony optimization techniques

This study aims to evaluate the clinical utility of image-guided Raman endoscopy for in vivo diagnosis of neoplastic lesions in the stomach at gastroscopy. A rapid-acquisition image-guided Raman endoscopy system with 785-nm excitation has been developed to acquire in vivo gastric tissue Raman spectra within 0.5 sec during clinical gastroscopic examinations. A total of 1,063 in vivo Raman spectra were acquired from 238 tissue sites of 67 gastric patients, in which 934 Raman spectra were from normal tissue whereas 129 Raman spectra were from neoplastic gastric tissue. The swarm intelligence-based algorithm (i.e., ant colony optimization (ACO) integrated with linear discriminant analysis (LDA)) was developed for spectral variables selection to identify the biochemical important Raman bands for differentiation between normal and neoplastic gastric tissue. The ACO-LDA algorithms together with the leave-one tissue site-out, cross validation method identified seven diagnostically important Raman bands in the regions of 850-875, 1,090-1,110, 1,120-1,130, 1,170-1,190, 1,320-1,340, 1,655-1,665 and 1,730-1,745 cm(-1) related to proteins, nucleic acids and lipids of tissue and provided a diagnostic sensitivity of 94.6% and specificity of 94.6% for distinction of gastric neoplasia. The predictive sensitivity of 89.3% and specificity of 97.8% were also achieved for an independent test validation dataset (20% of total dataset). This work demonstrates for the first time that the real-time image-guided Raman endoscopy associated with ACO-LDA diagnostic algorithms has potential for the noninvasive, in vivo diagnosis and detection of gastric neoplasia during clinical gastroscopy.

Diagnosis of Helicobacter pylori infection

If we had to give a general view of the articles published in the year 2010, we should conclude that the evidence in the year 2010 suggests that, also in Helicobacter pylori diagnosis, "the devil is in the details". In this sense, different studies suggested that skipping citric acid pretreatment or local validation or reducing the (13) C-urea dose markedly decreases the accuracy of the urea breath test. The studies also implied that, even between monoclonal stool tests, there are large differences between the marketed tests. Finally, even histology does not work adequately in patients with gastric cancer or extensive areas of intestinal metaplasia. In these cases, specific gastric sites should be biopsied to improve the reliability of histology.