Diagnostic potential of near-infrared Raman spectroscopy in the colon: differentiating adenomatous from hyperplastic polyps

Preliminary study on the optical diagnosis of orbital rhabdomyosarcoma by Raman spectroscopy

To investigate the Raman spectral features of orbital rhabdomyosarcoma (ORMS) tissue and normal orbital tissue in vitro, and to explore the feasibility of Raman spectroscopy for the optical diagnosis of ORMS. 23 specimens of ORMS and 27 specimens of normal orbital tissue were obtained from resection surgery and measured in vitro using Raman spectroscopy coupled to a fiber optic probe. The important spectral differences between the tissue categories were exploited for tissue classification with the multivariate statistical techniques of principal component analysis (PCA) and linear discriminant analysis (LDA). Compared to normal tissue, the Raman peak intensities located at 1450 and 1655 cm-1 were significantly lower for ORMS (p < 0.05), while the peak intensities located at 721, 758, 1002, 1088, 1156, 1206, 1340, 1526 cm-1 were significantly higher (p < 0.05). Raman spectra differences between normal tissue and ORMS could be attributed to the changes in the relative amounts of biochemical components, such as nucleic acids, tryptophan, phenylalanine, carotenoid and lipids. The Raman spectroscopy technique together with PCA-LDA modeling provides a diagnostic accuracy of 90.0%, sensitivity of 91.3%, and specificity of 88.9% for ORMS identification. Significant differences in Raman peak intensities exist between normal orbital tissue and ORMS. This work demonstrated for the first time that the Raman spectroscopy associated with PCA-LDA diagnostic algorithms has promising potential for accurate, rapid and noninvasive optical diagnosis of ORMS at the molecular level.

Extended Analysis of Raman Spectra Using Artificial Intelligence Techniques for Colorectal Abnormality Classification

Raman spectroscopy (RS) techniques are attracting attention in the medical field as a promising tool for real-time biochemical analyses. The integration of artificial intelligence (AI) algorithms with RS has greatly enhanced its ability to accurately classify spectral data in vivo. This combination has opened up new possibilities for precise and efficient analysis in medical applications. In this study, healthy and cancerous specimens from 22 patients who underwent open colorectal surgery were collected. By using these spectral data, we investigate an optimal preprocessing pipeline for statistical analysis using AI techniques. This exploration entails proposing preprocessing methods and algorithms to enhance classification outcomes. The research encompasses a thorough ablation study comparing machine learning and deep learning algorithms toward the advancement of the clinical applicability of RS. The results indicate substantial accuracy improvements using techniques like baseline correction, L2 normalization, filtering, and PCA, yielding an overall accuracy enhancement of 15.8%. In comparing various algorithms, machine learning models, such as XGBoost and Random Forest, demonstrate effectiveness in classifying both normal and abnormal tissues. Similarly, deep learning models, such as 1D-Resnet and particularly the 1D-CNN model, exhibit superior performance in classifying abnormal cases. This research contributes valuable insights into the integration of AI in medical diagnostics and expands the potential of RS methods for achieving accurate malignancy classification.

Practices, Potential, and Perspectives for Detecting Predisease Using Raman Spectroscopy

Raman spectroscopy shows great potential for practical clinical applications. By analyzing the structure and composition of molecules through real-time, non-destructive measurements of the scattered light from living cells and tissues, it offers valuable insights. The Raman spectral data directly link to the molecular composition of the cells and tissues and provides a "molecular fingerprint" for various disease states. This review focuses on the practical and clinical applications of Raman spectroscopy, especially in the early detection of human diseases. Identifying predisease, which marks the transition from a healthy to a disease state, is crucial for effective interventions to prevent disease onset. Raman spectroscopy can reveal biological processes occurring during the transition states and may eventually detect the molecular dynamics in predisease conditions.

Determination of esophageal squamous cell carcinoma and gastric adenocarcinoma on raw tissue using Raman spectroscopy

BACKGROUND

Cancer detection is a global research focus, and novel, rapid, and label-free techniques are being developed for routine clinical practice. This has led to the development of new tools and techniques from the bench side to routine clinical practice. In this study, we present a method that uses Raman spectroscopy (RS) to detect cancer in unstained formalin-fixed, resected specimens of the esophagus and stomach. Our method can record a clear Raman-scattered light spectrum in these specimens, confirming that the Raman-scattered light spectrum changes because of the histological differences in the mucosal tissue.

AIM

To evaluate the use of Raman-scattered light spectrum for detecting endoscop-ically resected specimens of esophageal squamous cell carcinoma (SCC) and gastric adenocarcinoma (AC).

METHODS

We created a Raman device that is suitable for observing living tissues, and attempted to acquire Raman-scattered light spectra in endoscopically resected specimens of six esophageal tissues and 12 gastric tissues. We evaluated formalin-fixed tissues using this technique and captured shifts at multiple locations based on feasibility, ranging from six to 19 locations 200 microns apart in the vertical and horizontal directions. Furthermore, a correlation between the obtained Raman scattered light spectra and histopathological diagnosis was performed.

RESULTS

We successfully obtained Raman scattered light spectra from all six esophageal and 12 gastric specimens. After data capture, the tissue specimens were sent for histopathological analysis for further processing because RS is a label-free methodology that does not cause tissue destruction or alterations. Based on data analysis of molecular-level substrates, we established cut-off values for the diagnosis of esophageal SCC and gastric AC. By analyzing specific Raman shifts, we developed an algorithm to identify the range of esophageal SCC and gastric AC with an accuracy close to that of histopathological diagnoses.

CONCLUSION

Our technique provides qualitative information for real-time morphological diagnosis. However, further in vivo evaluations require an excitation light source with low human toxicity and large amounts of data for validation.

In vivo Raman spectroscopy in the diagnostics of colon cancer

Early detection and accurate diagnosis of colorectal carcinoma are crucial for successful treatment, yet current methods can be invasive and even inaccurate in some cases. In this work, we present a novel approach for in vivo tissue diagnostics of colorectal carcinoma using Raman spectroscopy. This almost non-invasive technique allows for fast and accurate detection of colorectal carcinoma and its precursors, adenomatous polyps, enabling timely intervention and improved patient outcomes. Using several methods of supervised machine learning, we were able to achieve over 91% accuracy in distinguishing colorectal lesions from healthy epithelial tissue and more than 90% classification accuracy for premalignant adenomatous polyps. Moreover, our models enabled the discrimination of cancerous and precancerous lesions with a mean accuracy of almost 92%. Such results demonstrate the potential of in vivo Raman spectroscopy to become a valuable tool in the fight against colon cancer.

Fluorescence-Based Microendoscopic Sensing System for Minimally Invasive In Vivo Bladder Cancer Diagnosis

Bladder cancer is commonly diagnosed by evaluating the tissue morphology through cystoscopy, and tumor resection is used as the primary treatment approach. However, these methods are limited by lesion site specificity and resection margin, and can thereby fail to detect cancer lesions at early stages. Nevertheless, rapid diagnosis without biopsy may be possible through fluorescence sensing. Herein, we describe a minimally invasive imaging system capable of sensing even small tumors through a 1.2 mm diameter flexible fiber bundle microprobe. We demonstrate that this new device can be used for the early diagnosis of bladder cancer in rats. Bladder cancer was induced in rats using the carcinogen N-butyl-N-(4-hydroxybutyl)nitrosamine (BBN), and a togglable filter capable of PpIX fluorescence sensing was installed in the microendoscopic system. Following 5-aminolevulinic acid administration, tissue in the early stages of bladder cancer was successfully identified with fluorescence detection and confirmed with hematoxylin/eosin and ferrochelatase staining. Although the time required for BBN to induce bladder cancer varied between 3 and 4 weeks among the rats, the microendoscopic system allowed the minimally invasive follow-up on cancer development.

Development of a SERS based cancer diagnosis approach employing cryosectioned thyroid tissue samples on PDMS

An efficient SERS based novel analytical approach named Cryosectioned-PDMS was developed systematically and evaluated applying on 64 thyroid biopsy samples. To utilize thyroid biopsy samples, a 20-μl volume of h-AgNPs suspension was dropped on a 5-μm thick cryosectioned biopsy specimen placed on the PDMS coated glass slide. The SERS spectra from a 10 × 10 points array acquired by mapping 22.5 μm × 22.5 μm sized area from suspended dried droplets placed on the tissue surface. The probability of correctly predicted performance for diagnosis of malignant, benign and healthy tissues was resulted in the accuracy of 100 % for the spectral bands at 667, 724, 920, 960, 1052, 1096, 1315 and 1457 cm^-1 using PCA-fed LDA machine learning. The Cryosectioned-PDMS biophotonic approach with PCA-LDA predictive model demonstrated that the vibrational signatures can accurately recognize the fingerprint of cancer pathology from a healthy one with a simple and fast sample preparation methodology.

In vivo Raman spectroscopy for bladder cancer detection using a superficial Raman probe compared to a nonsuperficial Raman probe

Raman spectroscopy is promising as a noninvasive tool for cancer diagnosis. A superficial Raman probe might improve the classification of bladder cancer, because information is gained solely from the diseased tissue and irrelevant information from deeper layers is omitted. We compared Raman measurements of a superficial to a nonsuperficial probe, in bladder cancer diagnosis. Two-hundred sixteen Raman measurements and biopsies were taken in vivo from at least one suspicious and one unsuspicious bladder location in 104 patients. A Raman classification model was constructed based on histopathology, using a principal-component fed linear-discriminant-analysis and leave-one-person-out cross-validation. The diagnostic ability measured in area under the receiver operating characteristics curve was 0.95 and 0.80, the sensitivity was 90% and 85% and the specificity was 87% and 88% for the superficial and the nonsuperficial probe, respectively. We found inflammation to be a confounder and additionally we found a gradual transition from benign to low-grade to high-grade urothelial carcinoma. Raman spectroscopy provides additional information to histopathology and the diagnostic value using a superficial probe.

High Spatial and Temporal Resolution NIR-IIb Gastrointestinal Imaging in Mice

Conventional biomedical imaging modalities, including endoscopy, X-rays, and magnetic resonance, are invasive and insufficient in spatial and temporal resolutions for gastrointestinal (GI) tract imaging to guide prognosis and therapy. Here we report a noninvasive method based on lanthanide-doped nanocrystals with ∼1530 nm fluorescence in the near-infrared-IIb window (NIR-IIb, 1500-1700 nm). The rational design of nanocrystals have led to an absolute quantum yield (QY) up to 48.6%. Further benefiting from the minimized scattering through the NIR-IIb window, we enhanced the spatial resolution to ∼1 mm in GI tract imaging, which is ∼3 times higher compared with the near-infrared-IIa (NIR-IIa, 1000-1500 nm) method. The approach also realized a high temporal resolution of 8 frames per second; thus the moment of mice intestinal peristalsis can be captured. Furthermore, with a light-sheet imaging system, we demonstrated a three-dimensional (3D) imaging on the GI tract. Moreover, we successfully translated these advances to diagnose inflammatory bowel disease.

From Raman to SESORRS: moving deeper into cancer detection and treatment monitoring

Raman spectroscopy is a non-invasive technique that allows specific chemical information to be obtained from various types of sample. The detailed molecular information that is present in Raman spectra permits monitoring of biochemical changes that occur in diseases, such as cancer, and can be used for the early detection and diagnosis of the disease, for monitoring treatment, and to distinguish between cancerous and non-cancerous biological samples. Several techniques have been developed to enhance the capabilities of Raman spectroscopy by improving detection sensitivity, reducing imaging times and increasing the potential applicability for in vivo analysis. The different Raman techniques each have their own advantages that can accommodate the alternative detection formats, allowing the techniques to be applied in several ways for the detection and diagnosis of cancer. This feature article discusses the various forms of Raman spectroscopy, how they have been applied for cancer detection, and the adaptation of the techniques towards their use for in vivo cancer detection and in clinical diagnostics. Despite the advances in Raman spectroscopy, the clinical application of the technique is still limited and certain challenges must be overcome to enable clinical translation. We provide an outlook on the future of the techniques in this area and what we believe is required to allow the potential of Raman spectroscopy to be achieved for clinical cancer diagnostics.

Raman Imaging and Fluorescence Lifetime Imaging Microscopy for Diagnosis of Cancer State and Metabolic Monitoring

Hurdles for effective tumor therapy are delayed detection and limited effectiveness of systemic drug therapies by patient-specific multidrug resistance. Non-invasive bioimaging tools such as fluorescence lifetime imaging microscopy (FLIM) and Raman-microspectroscopy have evolved over the last decade, providing the potential to be translated into clinics for early-stage disease detection, in vitro drug screening, and drug efficacy studies in personalized medicine. Accessing tissue- and cell-specific spectral signatures, Raman microspectroscopy has emerged as a diagnostic tool to identify precancerous lesions, cancer stages, or cell malignancy. In vivo Raman measurements have been enabled by recent technological advances in Raman endoscopy and signal-enhancing setups such as coherent anti-stokes Raman spectroscopy or surface-enhanced Raman spectroscopy. FLIM enables in situ investigations of metabolic processes such as glycolysis, oxidative stress, or mitochondrial activity by using the autofluorescence of co-enzymes NADH and FAD, which are associated with intrinsic proteins as a direct measure of tumor metabolism, cell death stages and drug efficacy. The combination of non-invasive and molecular-sensitive in situ techniques and advanced 3D tumor models such as patient-derived organoids or microtumors allows the recapitulation of tumor physiology and metabolism in vitro and facilitates the screening for patient-individualized drug treatment options.

Ex Vivo Vibration Spectroscopic Analysis of Colorectal Polyps for the Early Diagnosis of Colorectal Carcinoma

Colorectal cancer is one of the most common and often fatal cancers in humans, but it has the highest chance of a cure if detected at an early precancerous stage. Carcinogenesis in the colon begins as an uncontrolled growth forming polyps. Some of these polyps can finally be converted to colon cancer. Early diagnosis of adenomatous polyps is the main approach for screening and preventing colorectal cancer, and vibration spectroscopy can be used for this purpose. This work is focused on evaluating FTIR and Raman spectroscopy as a tool in the ex vivo analysis of colorectal polyps, which could be important for the early diagnosis of colorectal carcinoma. Multivariate analyses (PCA and LDA) were used to assist the spectroscopic discrimination of normal colon tissue, as well as benign and malignant colon polyps. The spectra demonstrated evident differences in the characteristic bands of the main tissue constituents, i.e., proteins, nucleic acids, lipids, polysaccharides, etc. Suitable models for discriminating the three mentioned diagnostic groups were proposed based on multivariate analyses of the spectroscopic data. LDA classification was especially successful in the case of a combined set of 55 variables from the FTIR, FT Raman and dispersion Raman spectra. This model can be proposed for ex vivo colorectal cancer diagnostics in combination with the colonoscopic extraction of colon polyps for further testing. This pilot study is a precursor for the further evaluation of the diagnostic potential for the simultaneous in vivo application of colonoscopic Raman probes.

Non-invasive diagnosis of colorectal cancer by Raman spectroscopy: Recent developments in liquid biopsy and endoscopy approaches

Colorectal cancer (CRC) is the third most common cancer diagnosed globally and is also one of the leading causes of cancer deaths in both men and women. The progression of CRC is slow and is often contained in colon but the risk increases with age. Based on the high certainty that the net benefit of screening in an age group is substantial, screening for CRC is recommended beginning at the age of 50. Currently, most of the incidence is concentrated in developed countries but the rate is increasing rapidly in developing geographies. Detecting CRC at an early stage is critical to reduce morbidity and mortality. Colonoscopy is the most preferred screening method but not very widely implemented due to practical considerations such as cost involved, lack of personnel and facility. To address these concerns, Raman spectroscopy (RS) has been suggested as a viable alternative due to its potential as a rapid non-invasive diagnostic tool. Recently, several studies have been reported but many variations of RS applications in CRC exists and are not well understood by non-specialists. This review focuses particularly on developments of Raman based liquid biopsy and endoscopic studies in order to throw light on each of their significance and limitations. Necessary developments in the future to translate RS into a clinical tool for screening and diagnosis of CRC are also briefly presented.

First experience in clinical application of hyperspectral endoscopy for evaluation of colonic polyps

Early detection and resection of adenomatous polyps prevents their progression to colorectal cancer (CRC), significantly improving patient outcomes. Polyps are typically identified and removed during white-light colonoscopy. Unfortunately, the rate of interval cancers that arise between CRC screening events remains high, linked to poor visualization of polyps during screening and incomplete polyp removal. Here, we sought to evaluate the potential of a hyperspectral endoscope (HySE) to enhance polyp discrimination for detection and resection. We designed, built and tested a new compact HySE in a proof-of-concept clinical study. We successfully collected spectra from three tissue types in seven patients undergoing routine colonoscopy screening. The acquired spectral data from normal tissue and polyps, both pre- and post- resection, were subjected to quantitative analysis using spectral angle mapping and machine learning, which discriminated the data by tissue type, meriting further investigation of HySE as a clinical tool.

A graphical user interface (NWUSA) for Raman spectral processing, analysis and feature recognition

It is a practical necessity for non-professional users to interpret biologically derived Raman spectral information for obtaining accurate and reliable analytical results. An integrated Raman spectral analysis software (NWUSA) was developed for spectral processing, analysis, and feature recognition. It provides a user-friendly graphical interface to perform the following preprocessing tasks: spectral range selection, cosmic ray removal, polynomial fitting based background subtraction, Savitzky-Golay smoothing, area-under-curve normalization, mean-centered procedure, as well as multivariate analysis algorithms including principal component analysis (PCA), linear discriminant analysis, partial least squares-discriminant analysis, support vector machine (SVM), and PCA-SVM. A spectral dataset obtained from two different samples was utilized to evaluate the performance of the developed software, which demonstrated that the analysis software can quickly and accurately achieve functional requirements in spectral data processing and feature recognition. Besides, the open-source software can not only be customized with more novel functional modules to suit the specific needs, but also benefit many Raman based investigations, especially for clinical usages.

Can Coupling Multiple Complementary Methods Improve the Spectroscopic Based Diagnosis of Gastrointestinal Illnesses? A Proof of Principle Ex Vivo Study Using Celiac Disease as the Model Illness

Spectroscopic methods are a promising approach for providing a point-of-care diagnostic method for gastrointestinal mucosa associated illnesses. Such a tool is desired to aid immediate decision making and to provide a faster pathway to appropriate treatment. In this pilot study, Raman, near-infrared, low frequency Raman, and autofluoresence spectroscopic methods were explored alone and in combination for the diagnosis of celiac disease. Duodenal biopsies (n = 72) from 24 participants were measured ex vivo using the full suite of studied spectroscopic methods. Exploratory principal component analysis (PCA) highlighted the origin of spectral differences between celiac and normal tissue with celiac biopsies tending to have higher protein relative to lipid signals and lower carotenoid spectral signals than the samples with normal histology. Classification of the samples based on the histology and overall diagnosis was carried out for all combinations of spectroscopic methods. Diagnosis based classification (majority rule of class per participant) yielded sensitivities of 0.31 to 0.77 for individual techniques, which was increased up to 0.85 when coupling multiple techniques together. Likewise, specificities of 0.50 to 0.67 were obtained for individual techniques, which was increased up to 0.78 when coupling multiple techniques together. It was noted that the use of antidepressants contributed to false positives, which is believed to be associated with increased serotonin levels observed in the gut mucosa in both celiac disease and the use of selective serotonin reuptake inhibitors (SSRIs); however, future work with greater numbers is required to confirm this observation. Inclusion of two additional spectroscopic methods could improve the accuracy of diagnosis (0.78) by 7% over Raman alone (0.73). This demonstrates the potential for further exploration and development of a multispectroscopic system for disease diagnosis.

Evaluation of wavelength ranges and tissue depth probed by diffuse reflectance spectroscopy for colorectal cancer detection

Colorectal cancer (CRC) is the third most common type of cancer worldwide and the second most deadly. Recent research efforts have focused on developing non-invasive techniques for CRC detection. In this study, we evaluated the diagnostic capabilities of diffuse reflectance spectroscopy (DRS) for CRC detection by building 6 classification models based on support vector machines (SVMs). Our dataset consists of 2889 diffuse reflectance spectra collected from freshly excised ex vivo tissues of 47 patients over wavelengths ranging from 350 and 1919 nm with source-detector distances of 630-µm and 2500-µm to probe different depths. Quadratic SVMs were used and performance was evaluated using twofold cross-validation on 10 iterations of randomized training and test sets. We achieved (93.5 ± 2.4)% sensitivity, (94.0 ± 1.7)% specificity AUC by probing the superficial colorectal tissue and (96.1 ± 1.8)% sensitivity, (95.7 ± 0.6)% specificity AUC by sampling deeper tissue layers. To the best of our knowledge, this is the first DRS study to investigate the potential of probing deeper tissue layers using larger SDD probes for CRC detection in the luminal wall. The data analysis showed that using a broader spectrum and longer near-infrared wavelengths can improve the diagnostic accuracy of CRC as well as probing deeper tissue layers.

Novel endoscopic optical diagnostic technologies in medical trial research: recent advancements and future prospects

Novel endoscopic biophotonic diagnostic technologies have the potential to non-invasively detect the interior of a hollow organ or cavity of the human body with subcellular resolution or to obtain biochemical information about tissue in real time. With the capability to visualize or analyze the diagnostic target in vivo, these techniques gradually developed as potential candidates to challenge histopathology which remains the gold standard for diagnosis. Consequently, many innovative endoscopic diagnostic techniques have succeeded in detection, characterization, and confirmation: the three critical steps for routine endoscopic diagnosis. In this review, we mainly summarize researches on emerging endoscopic optical diagnostic techniques, with emphasis on recent advances. We also introduce the fundamental principles and the development of those techniques and compare their characteristics. Especially, we shed light on the merit of novel endoscopic imaging technologies in medical research. For example, hyperspectral imaging and Raman spectroscopy provide direct molecular information, while optical coherence tomography and multi-photo endomicroscopy offer a more extensive detection range and excellent spatial-temporal resolution. Furthermore, we summarize the unexplored application fields of these endoscopic optical techniques in major hospital departments for biomedical researchers. Finally, we provide a brief overview of the future perspectives, as well as bottlenecks of those endoscopic optical diagnostic technologies. We believe all these efforts will enrich the diagnostic toolbox for endoscopists, enhance diagnostic efficiency, and reduce the rate of missed diagnosis and misdiagnosis.

Vibrational Spectroscopy for In Vitro Monitoring Stem Cell Differentiation

Stem cell technology has attracted considerable attention over recent decades due to its enormous potential in regenerative medicine and disease therapeutics. Studying the underlying mechanisms of stem cell differentiation and tissue generation is critical, and robust methodologies and different technologies are required. Towards establishing improved understanding and optimised triggering and control of differentiation processes, analytical techniques such as flow cytometry, immunohistochemistry, reverse transcription polymerase chain reaction, RNA in situ hybridisation analysis, and fluorescence-activated cell sorting have contributed much. However, progress in the field remains limited because such techniques provide only limited information, as they are only able to address specific, selected aspects of the process, and/or cannot visualise the process at the subcellular level. Additionally, many current analytical techniques involve the disruption of the investigation process (tissue sectioning, immunostaining) and cannot monitor the cellular differentiation process in situ, in real-time. Vibrational spectroscopy, as a label-free, non-invasive and non-destructive analytical technique, appears to be a promising candidate to potentially overcome many of these limitations as it can provide detailed biochemical fingerprint information for analysis of cells, tissues, and body fluids. The technique has been widely used in disease diagnosis and increasingly in stem cell technology. In this work, the efforts regarding the use of vibrational spectroscopy to identify mechanisms of stem cell differentiation at a single cell and tissue level are summarised. Both infrared absorption and Raman spectroscopic investigations are explored, and the relative merits, and future perspectives of the techniques are discussed.

In situ exploring Chidamide, a histone deacetylase inhibitor, induces molecular changes of leukemic T-lymphocyte apoptosis using Raman spectroscopy

Though it has been demonstrated that Chidamide (CS055/HBI-8000), a novel benzamide class of histone deacetylase (HDAC) subtype-selectively inhibitor, reveals better anticancer effect in acute leukemia, but it remains unknown about the precise mechanism of Chidamide-induced acute leukemia cell apoptosis due to the lack of in situ molecular changes information. Based on Raman spectral analysis, we find that the action of Chidamide on Jurkat cell will lead to an addition of an acetyl group to a specific lysine residue at the end of histone amino acid, and greatly enhance the acetylation of histones H1, H2A, H2B, H3, and H4, and then destroy the electrostatic force between the alkaline terminal of the positive charged arginine side chain and the negative charged DNA of phosphate group, finally cause the depolymerization of DNA and histone octamer in chromatin nucleosome depolymerization and the relaxation of chromatin. Accordingly, the accumulation of reactive oxygen species (ROS) and the decreasing of mitochondrial membrane potential (MMP) are observed. For comparison, we also present the corresponding results of suberoylanilide hydroxamic acid (SAHA) and MS-275 inhibitors. The achieved results show that proliferation of Chidamide-treated Jurkat cells is low relative to MS-275 or SAHA, and the action of Chidamide or MS-275 on Jurkat cells lead to obvious increasing in histones H1, H2A, H2B, H3, and H4, whereas the action effect of SAHA is mainly observed in histones H1, H2A, H2B, H3 but weak in histone H4. Moreover, it is found that Chidamide-induced histone H3 acetylation in Jurkat cells is stronger than MS-275 and SAHA. Collectively, by Raman spectral analysis, we achieve the dynamic behavior of biochemical components, molecular conformation and morphological changes of HDAC inhibitors-treated Jurkat cells. Importantly, our research is the first to demonstrate that the action site of HDAC inhibitors on Jurkat cell is located in the DNA minor groove. Most importantly, the application of Raman spectrum in exploring in-situ molecular changes information, histone acetylation modification in epigenetics, drug action sites and cell cycle affected by HDAC inhibitors will supply new idea and reference for the design and modification of HDAC inhibitors.

The Status of Advanced Imaging Techniques for Optical Biopsy of Colonic Polyps

The progressive miniaturization of photonic components presents the opportunity to obtain unprecedented microscopic images of colonic polyps in real time during endoscopy. This information has the potential to act as "optical biopsy" to aid clinical decision-making, including the possibility of adopting new paradigms such as a "resect and discard" approach for low-risk lesions. The technologies discussed in this review include confocal laser endomicroscopy, optical coherence tomography, multiphoton microscopy, Raman spectroscopy, and hyperspectral imaging. These are in different stages of development and clinical readiness, but all show the potential to produce reliable in vivo discrimination of different tissue types. A structured literature search of the imaging techniques for colorectal polyps has been conducted. The significant developments in endoscopic imaging were identified for each modality, and the status of current development was discussed. Of the advanced imaging techniques discussed, confocal laser endomicroscopy is in clinical use and, under optimal conditions with an experienced operator, can provide accurate histological assessment of tissue. The remaining techniques show potential for incorporation into endoscopic equipment and practice, although further component development is needed, followed by robust prospective validation of accuracy. Optical coherence tomography illustrates tissue "texture" well and gives good assessment of mucosal thickness and layers. Multiphoton microscopy produces high-resolution images at a subcellular resolution. Raman spectroscopy and hyperspectral imaging are less developed endoscopically but provide a tissue "fingerprint" which can distinguish between tissue types. Molecular imaging may become a powerful adjunct to other techniques, with its ability to precisely label specific molecules within tissue and thereby enhance imaging.

Raman spectroscopy combined with multivariate analysis to study the biochemical mechanism of lung cancer microwave ablation

Lung cancer is the leading cause of death in cancer patients, and microwave ablation (MWA) has been extensively used in clinical treatment. In this study, we characterized the spectra of MWA-treated and untreated lung squamous cell carcinoma (LSCC) tissues, as well as healthy lung tissue, and conducted a preliminary analysis of spectral variations associated with MWA treatment. The results of characteristic spectral analysis of different types of tissues indicated that MWA treatment induces an increase in the content of nucleic acids, proteins, and lipid components in lung cancer tissues. The discriminant model based on the principal component analysis - linear discriminant analysis (PCA-LDA) algorithm together with leave-one-out cross validation (LOOCV) method yield the sensitivities of 90%, 80%, and 96%, and specificities of 86.2%, 93.8%, and 100% among untreated and MWA-treated cancerous tissue, and healthy lung tissue, respectively. These results indicate that Raman spectroscopy combined with multivariate analysis techniques can be used to explore the biochemical response mechanism of cancerous tissue to MWA therapy.

Red blood cells under varying extracellular tonicity conditions: an optical tweezers combined with micro-Raman study

Extracellular tonicity has a significant influence on human red blood cell deformation capability. Advancements in the area of laser physics and optical trapping have opened up a plethora of applications for understanding cell structure and dynamics. Here, Raman Tweezers technique was employed to investigate the impact of extracellular tonicity by exposing human red blood cells to both hypertonic and hypotonic intravenous fluids. Heme aggregation was observed in hypertonic saline solution, accompanied with damage in membrane protein. Loss of intracellular hemoglobin in hypotonic solution was evident from the decrease in porphyrin breathing mode present at 752 cm^-1. Oxygen binding to the central iron in the red blood cell heme was also affected under both hyper/hypo tonicity conditions. Morphological deviation of discocytes to echinocytes/spherocytes were also evident from quantitative phase imaging. Principal component analysis have showed clear differentiation of samples in order to classify the control erythrocytes and the tonicity stressed erythrocytes. Present study has also demonstrated the application of Raman Tweezers spectroscopy as a potential tool for probing red blood cell under different stress conditions.

Quality assessment of cryopreserved biospecimens reveals presence of intact biomolecules

Recapitulation of tumor features in isolated biomolecules is preeminently dependent on obtaining reliable quality biospecimen. Moreover, quality assessment of biobanked specimens at regular intervals is an essential intervention for carrying out effective translational and clinical research. In the current study, genomic DNA was extracted from 140 fresh frozen tissues of oral, breast and colorectal specimens cryopreserved over a period of 3 to 8 months (short term) and 3 to 4 years (long term). Quantification of genomic DNA by absorption and fluorescence spectroscopy confirmed high concentration while qualitative analysis by gel electrophoresis showed intact bands for 94% and 87% of short- and long-term cohorts, respectively. PC-LDA based classification of Raman spectra showed overlapping groups of both cohorts suggesting the quality of DNA being preserved irrespective of storage period. To the best of our knowledge this is the first Indian biobank study reporting quality analysis of biospecimens cryopreserved at different time periods.

Diagnosis accuracy of Raman spectroscopy in colorectal cancer: A PRISMA-compliant systematic review and meta-analysis

BACKGROUND

The clinical significance of Raman spectroscopy (RS) in colorectal cancer (CRC) patients still remains underestimated. We performed this meta-analysis to elucidate the diagnostic value in CRC patients.

METHODS

We systematically searched electronic databases for published articles. Fixed effect model and random effect model were used to calculate the pooled sensitivity, specificity, diagnostic accuracy, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR) and positive posttest probability (PPP) of CRC. Meta-regression and subgroup analysis were conducted to assess potential source of heterogeneity. We also used Egger linear regression tests to assess risk of publication bias.

RESULTS

Thirteen studies had been included (679 patients: 186 with premalignant lesions and 493 with malignant lesions). The pooled sensitivity, specificity, diagnostic accuracy, PLR, NLR, DOR and PPP for CRC screening using RS were 0.94 (0.92-0.96), 0.94 (0.88-0.97), 0.96 (0.94-0.98), 16.44 (7.80-34.63), 0.062 (0.043-0.090), 263.65 (99.03-701.96) and 86%, respectively.

CONCLUSION

RS is a potentially useful tool for future CRC screening. It also offers potentially early detection for CRC patients.

A Review of New and Emerging Techniques For Optical Diagnosis of Colonic Polyps

BACKGROUND AND AIMS

Endoscopic imaging is a rapidly progressing field and benefits from miniaturization of advanced imaging technologies, which may allow accurate real-time characterization of lesions. The concept of the "optical biopsy" to predict polyp histology has gained prominence in recent years and may become clinically applicable with the advent of new imaging technology. This review aims to discuss current evidence and examine the emerging technologies as applied to the optical diagnosis of colorectal polyps.

METHODS

A structured literature search and review has been carried out of the evidence for diagnostic accuracy of image-enhanced endoscopy and emerging endoscopic imaging technologies. The image-enhanced endoscopy techniques are reviewed, including their basic scientific principles and current evidence for effectiveness. These include the established image-enhancement technologies such as narrow-band imaging, i-scan, and Fuji intelligent chromoendoscopy. More recent technologies including optical enhancement, blue laser imaging, and linked color imaging are discussed. Adjunctive imaging techniques in current clinical use are discussed, such as autofluorescence imaging and endocytoscopy. The emerging advanced imaging techniques are reviewed, including confocal laser endomicroscopy, optical coherence tomography, and Raman spectroscopy.

CONCLUSIONS

Large studies of the established image-enhancement techniques show some role for the optical diagnosis of polyp histology, although results have been mixed, and at present only the technique of narrow-band imaging is appropriate for the diagnosis of low-risk polyps when used by an expert operator. Other image-enhancement techniques will require further study to validate their accuracy but show potential to support the use of a "resect-and-discard" approach to low-risk polyps. New technologies show exciting potential for real-time diagnosis, but further clinical studies in humans have yet to be performed.

Synergy of Fluorescence and Near-Infrared Spectroscopy in Detection of Colorectal Cancer

BACKGROUND

Colorectal cancer is one of the most common malignancies worldwide. There is an urgent need for simple and fast methods to improve tumor detection in the diagnostic and intraoperative setting to avoid complications and provide objective information in distinguishing malignant and benign colorectal tissue. Optical spectroscopy methods have recently shown a great potential for this discrimination in different organs.

MATERIALS AND METHODS

In this pilot study, fluorescence emission spectra (excitation: 473 nm) and diffuse reflectance spectra (DRS) of normal and tumor tissues from resected colorectal cancer specimen were measured using fiber optical probes in an ex vivo setting, and the data were subjected to multivariate analysis.

RESULTS

Substantial spectral differences were found in the fluorescence and DRS spectra of colorectal cancer tissue in comparison to benign tissue. The diagnostic potential of a multimode optical system combining both spectroscopic methods was investigated by mathematical combination. Compared with the individual techniques, a higher sensitivity of the joint DRS-fluorescence optical system in the discrimination between malignant and benign colorectal tissue could be observed.

CONCLUSIONS

In the pilot study presented herein, a quick and reliable method to differentiate malignant and benign colorectal tissue ex vivo with different spectroscopic techniques using spectral fiber probes could be established. Joint fluorescence and near-infrared spectroscopy had a higher sensitivity in tissue discrimination and showed to be a promising combination of two spectroscopic methods. Further studies using the synergic effect of fluorescence and DRS spectroscopy are needed to transfer these findings into the in vivo situation.

All-in-one Raman spectroscopy approach to diagnosis of colorectal cancer: analysis of spectra in the fingerprint regions

Objectives: Raman spectroscopy yields precise information, not only regarding the secondary structure of proteins but also regarding the discrimination between normal and malignant tissues. There is, however, no standard measurement method. We evaluated the use of a miniaturized, handheld, all-in-one Raman spectrometer with a 1064-nm laser excitation source for the diagnosis of colorectal cancer. The ultimate goal is real-time, in vivo diagnosis. Methods: Tissue samples were obtained from 20 patients who underwent surgery for colorectal cancer. The samples were irradiated with the portable Progeny™ Raman spectrometer, with which the Raman spectra were also obtained. We searched for characteristic Raman shifts and examined whether these shifts could distinguish the cancer tissues. To improve accuracy, we divided the spectra into 100 cm⁻¹ bands and applied principal component analysis (PCA) to each range. We evaluated the contribution of each range for cancer discrimination. Results: Intensities at 1261 and 1427 cm⁻¹ differed significantly between the normal tissues and cancer tissues, but these did not efficiently discriminate the cancer tissues. However, we were able to identify the characteristic spectral range in fingerprint regions; accuracy was 85.1%. Conclusions: Use of the all-in-one type Raman spectrometer can efficiently discriminate colorectal cancer, not on the basis of the intensities at 1261 and 1427 cm⁻¹ but rather on the basis of PCA. Thus, Raman spectroscopy performed using a handheld device has potential to become a clinically powerful tool for producing high-quality data, obtaining highly reproducible measurements, and thus accurately diagnosing colorectal cancer.

Raman spectroscopy with a 1064-nm wavelength laser as a potential molecular tool for prostate cancer diagnosis: a pilot study

Raman spectroscopy is widely used to investigate the structure and property of the molecules from their vibrational transitions and may allow for the diagnosis of cancer in a fast, objective, and nondestructive manner. This experimental study aims to propose the use of the 1064-nm wavelength laser in a Raman spectroscopy and to evaluate its discrimination capability in prostate cancer diagnosis. Seventy-four spectra from patients who underwent radical prostatectomy were evaluated. The acquired signals were filtered, normalized, and corrected for possible oscillations in the laser intensity and fluorescence effects. Wilcoxon tests revealed significant differences between the benign and malign samples associated with the deformation vibration characteristic of nucleic acids, proteins, and lipids. A classifier based on support vector machines was able to predict the Gleason scores of the samples with 95% of accuracy, opening a perspective for the use of the 1064-nm excitatory wavelength in prostatic cancer diagnosis.

Advancing Raman microspectroscopy for cellular and subcellular analysis: towards in vitro high-content spectralomic analysis

In the confocal mode, Raman microspectroscopy can profile the biochemical content of biological cells at a subcellular level, and any changes to it by exogenous agents, such as therapeutic drugs or toxicants. As an exploration of the potential of the technique as a high-content, label-free analysis technique, this report reviews work to monitor the spectroscopic signatures associated with the uptake and response pathways of commercial chemotherapeutic agents and polymeric nanoparticles by human lung cells. It is demonstrated that the signatures are reproducible and characteristic of the cellular event, and can be used, for example, to identify the mode of action of the agent as well as the subsequent cell death pathway, and even mechanisms of cellular resistance. Data mining approaches are discussed and a spectralomics approach is proposed.

Accuracy of Raman spectroscopy in differentiating brain tumor from normal brain tissue

Raman spectroscopy could be applied to distinguish tumor from normal tissues. This meta-analysis was conducted to assess the accuracy of Raman spectroscopy in differentiating brain tumor from normal brain tissue. PubMed and Embase were searched to identify suitable studies prior to Jan 1st, 2016. We estimated the pooled sensitivity, specificity, positive and negative likelihood ratios (LR), diagnostic odds ratio (DOR), and constructed summary receiver operating characteristics (SROC) curves to identity the accuracy of Raman spectroscopy in differentiating brain tumor from normal brain tissue. A total of six studies with 1951 spectra were included. For glioma, the pooled sensitivity and specificity of Raman spectroscopy were 0.96 (95% CI 0.94-0.97) and 0.99 (95% CI 0.98-0.99), respectively. The area under the curve (AUC) was 0.9831. For meningioma, the pooled sensitivity and specificity were 0.98 (95% CI 0.94-1.00) and 1.00 (95% CI 0.98-1.00), respectively. The AUC was 0.9955. This meta-analysis suggested that Raman spectroscopy could be an effective and accurate tool for differentiating glioma and meningioma from normal brain tissue, which would help us both avoid removal of normal tissue and minimize the volume of residual tumor.

A CD44-specific peptide, RP-1, exhibits capacities of assisting diagnosis and predicting prognosis of gastric cancer

Early diagnosis and evaluation of prognosis are both crucial for preventing poor prognosis of patients with gastric cancer (GC), a leading cause of cancer-related deaths worldwide. Cluster of differentiation 44 (CD44), an indicator of cancer stem cells, can be specifically targeted by molecular probes and detected in tissues of GC in a large quantity. In current study we found that RP-1, a specific peptide binding to CD44 protein, exhibited the potentials of specific binding to CD44 high-expressing cancer cells both in vitro and in vivo, and the capacity of predicting prognosis of human GC in a microarray assay. Results showed that RP-1 was characterized by high affinity, sensitivity and specificity, and low toxicity, suggesting RP-1 could be an ideal bio-probe for accessory diagnosis of GC. Further immunohistochemical studies and statistical analysis of tissue microarray of human GC demonstrated similar sensitivity and specificity of RP-1 with the monoclonal anti-CD44 antibody in the diagnosis of GC, and even proved that positive RP-1 could be an independent risk factor. Therefore, this study suggests RP-1 has the potentials of binding to CD44 protein expressed on the membrane of GC cells, and demonstrates the feasibility and reliability of its further application in molecular diagnosis and prognostic prediction of GC.

Rapid diagnostics of liver steatosis by Raman spectroscopyviafiber optic probe: a pilot study

Raman spectroscopyviafiber optic probes enables assessment of the liver condition and rapid quantification of liver steatosis, thus, this technique has the potential as a diagnostic tool.

A machine learning framework to analyze hyperspectral stimulated Raman scattering microscopy images of expressed human meibum

We develop and discuss a methodology for batch-level analysis of hyperspectral stimulated Raman scattering (hsSRS) data sets of human meibum in the CH-stretching vibrational range. The analysis consists of two steps. The first step uses a training set (n=19) to determine chemically meaningful reference spectra that jointly constitute a basis set for the sample. This procedure makes use of batch-level vertex component analysis (VCA), followed by unsupervised k-means clustering to express the data set in terms of spectra that represent lipid and protein mixtures in changing proportions. The second step uses a random forest classifier to rapidly classify hsSRS stacks in terms of the pre-determined basis set. The overall procedure allows a rapid quantitative analysis of large hsSRS data sets, enabling a direct comparison among samples using a single set of reference spectra. We apply this procedure to assess 50 specimens of expressed human meibum, rich in both protein and lipid, and show that the batch-level analysis reveals marked variation among samples that potentially correlate with meibum health quality.

Raman technologies in cancer diagnostics

Despite significant effort, cancer still remains a leading cause of death worldwide. In order to reduce its burden, the development and improvement of noninvasive strategies for early detection and diagnosis of cancer are urgently needed. Raman spectroscopy, an optical technique that relies on inelastic light scattering arising from molecular vibrations, is one such strategy, as it can noninvasively probe cancerous markers using only endogenous contrast. In this review, spontaneous, coherent and surface enhanced Raman spectroscopies and imaging, as well as the fundamental principles governing the successful use of these techniques, are discussed. Methods for spectral data analysis are also highlighted. Utilization of the discussed Raman techniques for the detection and diagnosis of cancer in vitro, ex vivo and in vivo is described. The review concludes with a discussion of the future directions of Raman technologies, with particular emphasis on their clinical translation.

Raman spectroscopy and regenerative medicine: a review

The field of regenerative medicine spans a wide area of the biomedical landscape-from single cell culture in laboratories to human whole-organ transplantation. To ensure that research is transferrable from bench to bedside, it is critical that we are able to assess regenerative processes in cells, tissues, organs and patients at a biochemical level. Regeneration relies on a large number of biological factors, which can be perturbed using conventional bioanalytical techniques. A versatile, non-invasive, non-destructive technique for biochemical analysis would be invaluable for the study of regeneration; and Raman spectroscopy is a potential solution. Raman spectroscopy is an analytical method by which chemical data are obtained through the inelastic scattering of light. Since its discovery in the 1920s, physicists and chemists have used Raman scattering to investigate the chemical composition of a vast range of both liquid and solid materials. However, only in the last two decades has this form of spectroscopy been employed in biomedical research. Particularly relevant to regenerative medicine are recent studies illustrating its ability to characterise and discriminate between healthy and disease states in cells, tissue biopsies and in patients. This review will briefly outline the principles behind Raman spectroscopy and its variants, describe key examples of its applications to biomedicine, and consider areas of regenerative medicine that would benefit from this non-invasive bioanalytical tool.

Evaluation of the diagnostic potential of ex vivo Raman spectroscopy in gastric cancers: fingerprint versus high wavenumber

The aim of this study was to apply Raman spectroscopy in the high wavenumber (HW) region (2800 to 3000??cm?1) for ex vivo detection of gastric cancer and compare its diagnostic potential with that of the fingerprint (FP) region (800 to 1800??cm?1). Raman spectra were collected in the FP and HW regions to differentiate between normal mucosa (n=38) and gastric cancer (n=37). The distinctive Raman spectral differences between normal and cancer tissues are observed at 853, 879, 1157, 1319, 1338, 1448, and 2932??cm?1 and are primarily related to proteins, lipids, nucleic acids, collagen, and carotenoids in the tissue. In FP and HW Raman spectroscopy for diagnosis of gastric cancer, multivariate diagnostic algorithms based on partial-least-squares discriminant analysis, together with leave-one-sample-out cross validation, yielded diagnostic sensitivities of 94.59% and 81.08%, and specificities of 86.84% and 71.05%, respectively. Receiver operating characteristic analysis further confirmed that the FP region model performance is superior to that of the HW region model. Better differentiation between normal and gastric cancer tissues can be achieved using FP Raman spectroscopy and PLS-DA techniques, but the complementary natures of the FP and HW regions make both of them useful in diagnosis of gastric cancer.

Advances in endoscopic imaging in ulcerative colitis

Modern strategies for the treatment of ulcerative colitis require more accurate tools for gastrointestinal imaging to better assess mucosal disease activity and long-term prognostic clinical outcomes. Recent advances in gastrointestinal luminal endoscopy are radically changing the role of endoscopy in every-day clinical practice and research trials. Advanced endoscopic imaging techniques including high-definition endoscopes, optical magnification endoscopy, and various chromoendoscopy techniques have remarkably improved endoscopic assessment of ulcerative colitis. More recently, optical biopsy techniques with either endocytoscopy or confocal laser endomicroscopy have shown great potential in predicting several histological changes in real time during ongoing endoscopy. Here, we review current applications of advanced endoscopic imaging techniques in ulcerative colitis and present the most promising upcoming headways in this field.

Label-free Raman spectroscopic imaging to extract morphological and chemical information from a formalin-fixed, paraffin-embedded rat colon tissue section

Animal models and archived human biobank tissues are useful resources for research in disease development, diagnostics and therapeutics. For the preservation of microscopic anatomical features and to facilitate long-term storage, a majority of tissue samples are denatured by the chemical treatments required for fixation, paraffin embedding and subsequent deparaffinization. These aggressive chemical processes are thought to modify the biochemical composition of the sample and potentially compromise reliable spectroscopic examination useful for the diagnosis or biomarking. As a result, spectroscopy is often conducted on fresh/frozen samples. In this study, we provide an extensive characterization of the biochemical signals remaining in processed samples (formalin fixation and paraffin embedding, FFPE) and especially those originating from the anatomical layers of a healthy rat colon. The application of chemometric analytical methods (unsupervised and supervised) was shown to eliminate the need for tissue staining and easily revealed microscopic features consistent with goblet cells and the dense populations of cells within the mucosa, principally via strong nucleic acid signals. We were also able to identify the collagenous submucosa- and serosa- as well as the muscle-associated signals from the muscular regions and blood vessels. Applying linear regression analysis to the data, we were able to corroborate this initial assignment of cell and tissue types by confirming the biological origin of each layer by reference to a subset of authentic biomolecular standards. Our results demonstrate the potential of using label-free Raman microspectroscopy to obtain superior imaging contrast in FFPE sections when compared directly to conventional haematoxylin and eosin (H&E) staining.

Intraoperative Raman spectroscopy of soft tissue sarcomas

BACKGROUND AND OBJECTIVE

Soft tissue sarcomas (STS) are a rare and heterogeneous group of malignant tumors that are often treated through surgical resection. Current intraoperative margin assessment methods are limited and highlight the need for an improved approach with respect to time and specificity. Here we investigate the potential of near-infrared Raman spectroscopy for the intraoperative differentiation of STS from surrounding normal tissue.

MATERIALS AND METHODS

In vivo Raman measurements at 785 nm excitation were intraoperatively acquired from subjects undergoing STS resection using a probe based spectroscopy system. A multivariate classification algorithm was developed in order to automatically identify spectral features that can be used to differentiate STS from the surrounding normal muscle and fat. The classification algorithm was subsequently tested using leave-one-subject-out cross-validation.

RESULTS

With the exclusion of well-differentiated liposarcomas, the algorithm was able to classify STS from the surrounding normal muscle and fat with a sensitivity and specificity of 89.5% and 96.4%, respectively.

CONCLUSION

These results suggest that single point near-infrared Raman spectroscopy could be utilized as a rapid and non-destructive surgical guidance tool for identifying abnormal tissue margins in need of further excision. Lasers Surg. Med. 48:774-781, 2016. © 2016 Wiley Periodicals, Inc.

Statistical strategies to reveal potential vibrational markers for in vivo analysis by confocal Raman spectroscopy

The analysis of biological systems by spectroscopic techniques involves the evaluation of hundreds to thousands of variables. Hence, different statistical approaches are used to elucidate regions that discriminate classes of samples and to propose new vibrational markers for explaining various phenomena like disease monitoring, mechanisms of action of drugs, food, and so on. However, the technical statistics are not always widely discussed in applied sciences. In this context, this work presents a detailed discussion including the various steps necessary for proper statistical analysis. It includes univariate parametric and nonparametric tests, as well as multivariate unsupervised and supervised approaches. The main objective of this study is to promote proper understanding of the application of various statistical tools in these spectroscopic methods used for the analysis of biological samples. The discussion of these methods is performed on a set of in vivo confocal Raman spectra of human skin analysis that aims to identify skin aging markers. In the Appendix, a complete routine of data analysis is executed in a free software that can be used by the scientific community involved in these studies.

Role of Raman spectroscopy and surface enhanced Raman spectroscopy in colorectal cancer

Colorectal cancer (CRC) is the fourth most common cancer in the United Kingdom and is the second largest cause of cancer related death in the United Kingdom after lung cancer. Currently in the United Kingdom there is not a diagnostic test that has sufficient differentiation between patients with cancer and those without cancer so the current referral system relies on symptomatic presentation in a primary care setting. Raman spectroscopy and surface enhanced Raman spectroscopy (SERS) are forms of vibrational spectroscopy that offer a non-destructive method to gain molecular information about biological samples. The techniques offer a wide range of applications from in vivo or in vitro diagnostics using endoscopic probes, to the use of micro-spectrometers for analysis of biofluids. The techniques have the potential to detect molecular changes prior to any morphological changes occurring in the tissue and therefore could offer many possibilities to aid the detection of CRC. The purpose of this review is to look at the current state of diagnostic technology in the United Kingdom. The development of Raman spectroscopy and SERS in clinical applications relation for CRC will then be discussed. Finally, future areas of research of Raman/SERS as a clinical tool for the diagnosis of CRC are also discussed.

Raman spectroscopy of endoscopic colonic biopsies from patients with ulcerative colitis to identify mucosal inflammation and healing

Raman spectroscopy was used to differentiate between mucosally healed (or quiescent) and inflamed colon tissue, as assessed endoscopically, in patients with ulcerative colitis. From the analysis of the Raman spectra of 60 biopsy tissue samples, clear differences were identified between the spectra of the quiescent and inflamed tissue. Three carotenoid peaks were found to be approximately twice as intense in the inflamed tissue. Two phospholipid peaks were found to be significantly lower in the inflamed tissue. Using multivariate statistical analysis, we show that these five peaks can be used to discriminate between endoscopically quiescent and inflamed tissue. We also correlated the Raman data with a histological assessment of the tissue. Four of the five peaks were found to be significantly different between the spectra of histologically healed (or quiescent) and histologically inflamed tissue. These findings indicate the ability of Raman spectroscopy to accurately classify colon tissue as either quiescent or inflamed, irrespective of whether an endoscopic or histological grading scheme is followed. We thus demonstrate that Raman spectroscopy could potentially be used as an early diagnosis tool for assessing the presence of mucosal healing or inflammation in patients with ulcerative colitis.

Assessment of conjunctival microvilli abnormality by micro-Raman analysis - by G. Rusciano et al

Conjunctival microvilli are microscopic cellular membrane protrusions on apical epithelial cells, which increase the surface area available for tear adherence. Pathological alterations of microvilli structure affect the tear film stability and, conversely, dysfunctions of tear film composition can lead to a suffering epithelium (dry-eye syndrome). In this work we propose the use of micro-Raman analysis to reveal conjunctival microvilli abnormalities. Samples were obtained by impression cytology from patients by different stage of dry-eye syndrome. Our experimental outcomes demonstrate that Raman analysis, combined with the use of Principal Component Analysis, is able to detect different stages of microvilli reduction. Globally, these results hold promise for the use of Raman analysis for an objective, effective, non-invasive and potentially also in-vivo analysis of the conjunctiva in all the cases of microvilli-related ocular pathologies.