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

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

Raman spectroscopy of human skin for kidney failure detection

The object of this paper is in vivo study of skin spectral-characteristics in patients with kidney failure by conventional Raman spectroscopy in near infrared region. The experimental dataset was subjected to discriminant analysis with the projection on latent structures (PLS-DA). Application of Raman spectroscopy to investigate the forearm skin in 85 adult patients with kidney failure (90 spectra) and 40 healthy adult volunteers (80 spectra) has yielded the accuracy of 0.96, sensitivity of 0.94 and specificity of 0.99 in terms of identifying the target subjects with kidney failure. The autofluorescence analysis in the near infrared region identified the patients with kidney failure among healthy volunteers of the same age group with specificity, sensitivity, and accuracy of 0.91, 0.84, and 0.88, respectively. When classifying subjects by the presence of kidney failure using the PLS-DA method, the most informative Raman spectral bands are 1315 to 1330, 1450 to 1460, 1700 to 1800 cm⁻¹. In general, the performed study demonstrates that for in vivo skin analysis, the conventional Raman spectroscopy can provide the basis for cost-effective and accurate detection of kidney failure and associated metabolic changes in the skin.     

Determination of inclusion depth in ex vivo animal tissues using surface enhanced deep Raman spectroscopy

This work presents recent developments in spatially offset and transmission Raman spectroscopy for noninvasive detection and depth prediction of a single SERS inclusion located deep inside ex vivo biological tissues. The concept exploits the differential attenuation of Raman bands brought about by their different absorption due to tissue constituents enabling to predict the inclusion depth. Four different calibration models are tested and evaluated to predict the depth of surface enhanced Raman scattering labelled nanoparticles, within an up to 40 mm slab of porcine tissue. An external measurement carried out in transmission mode, with a noninvasively built model on the analysed sample, is shown to be insensitive to variations of the overall thickness of the tissue yielding an average root‐mean‐square error of prediction of 6.7%. The results pave the way for future noninvasive deep Raman spectroscopy in vivo enabling to localise cancer biomarkers for an early diagnosis of multiple diseases.      

Raman spectroscopy‐based detection of RNA viruses in saliva: A preliminary report

Several non‐invasive Raman spectroscopy‐based assays have been reported for rapid and sensitive detection of pathogens. We developed a novel statistical model for the detection of RNA viruses in saliva, based on an unbiased selection of a set of 65 Raman spectral features that mostly attribute to the RNA moieties, with a prediction accuracy of 91.6% (92.5% sensitivity and 88.8% specificity). Furthermore, to minimize variability and automate the downstream analysis of the Raman spectra, we developed a GUI‐based analytical tool “RNA Virus Detector (RVD).” This conceptual framework to detect RNA viruses in saliva could form the basis for field application of Raman Spectroscopy in managing viral outbreaks, such as the ongoing COVID‐19 pandemic. ( http://www.actrec.gov.in/pi-webpages/AmitDutt/RVD/RVD.html ).     

Imaging the invisible—Bioorthogonal Raman probes for imaging of cells and tissues

A revolutionary avenue for vibrational imaging with super‐multiplexing capability can be seen in the recent development of Raman‐active bioortogonal tags or labels. These tags and isotopic labels represent groups of chemically inert and small modifications, which can be introduced to any biomolecule of interest and then supplied to single cells or entire organisms. Recent developments in the field of spontaneous Raman spectroscopy and stimulated Raman spectroscopy in combination with targeted imaging of biomolecules within living systems are the main focus of this review. After having introduced common strategies for bioorthogonal labeling, we present applications thereof for profiling of resistance patterns in bacterial cells, investigations of pharmaceutical drug‐cell interactions in eukaryotic cells and cancer diagnosis in whole tissue samples. Ultimately, this approach proves to be a flexible and robust tool for in vivo imaging on several length scales and provides comparable information as fluorescence‐based imaging without the need of bulky fluorescent tags.     

Comparison of two methods for noninvasive determination of carotenoids in human and animal skin: Raman spectroscopy versus reflection spectroscopy

Based on compelling in vivo and in vitro studies on human skin, carotenoids are thought to be of great interest as powerful antioxidants acting to prevent free‐radical‐induced damages, including premature skin ageing and the development of skin diseases such as cancer. Among the available techniques that are suitable for noninvasive determination of carotenoids in human skin, are resonance Raman spectroscopy (RRS) and reflection spectroscopy (RS). For RS, a LED‐based miniaturized spectroscopic system (MSS) was developed for noninvasive measurement of carotenoids in human skin. The optimization and subsequent calibration of the MSS was performed with the use of RRS. A strong correlation between the carotenoid concentration determined by the RS and for the RRS system was achieved for human skin in vivo (R = 0.88) and for bovine udder skin in vitro (R = 0.81). (© 2012 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Blood plasma resonance Raman spectroscopy combined with multivariate analysis for esophageal cancer detection

We herein report a novel, reliable and inexpensive method for detecting esophageal cancer using blood plasma resonance Raman spectroscopy combined with multivariate analysis methods. The blood plasma samples were divided into late stage cancer group (n = 164), early stage cancer group (n = 35) and normal group (n = 135) based on clinical pathological diagnosis. Using a specially designed quartz capillary tube as sample holder, we obtained higher quality resonance Raman spectra of blood plasma than existing method. The study demonstrated that the carotenoids levels in blood plasma were reduced in esophageal cancer patients. The area under the receiver operating characteristic curve (and 95% confidence interval) calculated by wavenumber selection and principal component analysis combined with linear discriminant analysis (PC-LDA) algorithm were 0.894 (0.858-0.929), 0.901 (0.841-0.960) and 0.871 (0.799-0.942) for differentiating late cancer from normal, late cancer from early cancer, and early cancer from normal respectively. The contribution from the two carotenoids wavenumber regions of 1155 and 1515 cm⁻¹ were more than 84.2%. The results show that the plasma carotenoids could be a potential biomarker for screening esophageal cancer using resonance Raman spectroscopy combined with wavenumber selection and PC-LDA algorithms.      

Bladder tissue characterization using probe‐based Raman spectroscopy: Evaluation of tissue heterogeneity and influence on the model prediction

Existing approaches for early‐stage bladder tumor diagnosis largely depend on invasive and time‐consuming procedures, resulting in hospitalization, bleeding, bladder perforation, infection and other health risks for the patient. The reduction of current risk factors, while maintaining or even improving the diagnostic precision, is an underlying factor in clinical instrumentation research. For example, for clinic surveillance of patients with a history of noninvasive bladder tumors real‐time tumor diagnosis can enable immediate laser‐based removal of tumors using flexible cystoscopes in the outpatient clinic. Therefore, novel diagnostic modalities are required that can provide real‐time in vivo tumor diagnosis. Raman spectroscopy provides biochemical information of tissue samples ex vivo and in vivo and without the need for complicated sample preparation and staining procedures. For the past decade there has been a rise in applications to diagnose and characterize early cancer in different organs, such as in head and neck, colon and stomach, but also different pathologies, for example, inflammation and atherosclerotic plaques. Bladder pathology has also been studied but only with little attention to aspects that can influence the diagnosis, such as tissue heterogeneity, data preprocessing and model development. The present study presents a clinical investigative study on bladder biopsies to characterize the tumor grading ex vivo, using a compact fiber probe‐based imaging Raman system, as a crucial step towards in vivo Raman endoscopy. Furthermore, this study presents an evaluation of the tissue heterogeneity of highly fluorescent bladder tissues, and the multivariate statistical analysis for discrimination between nontumor tissue, and low‐ and high‐grade tumor.     

Real‐time in vivo cancer diagnosis using raman spectroscopy

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

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

Study on the interaction of β‐carotene and astaxanthin with trypsin and pepsin by spectroscopic techniques

β‐Carotene and astaxanthin are two carotenoids with powerful antioxidant properties, but the binding mechanisms of β‐carotene/astaxanthin to proteases remain unclear. In this study, the interaction of these two carotenoids with trypsin and pepsin was investigated using steady‐state and time‐resolved fluorescence measurements, synchronous fluorescence spectroscopy, UV–vis absorption spectroscopy and circular dichroism (CD) spectroscopy. The experimental results indicated that the quenching mechanisms of trypsin/pepsin by the two carotenoids are static processes. The binding constants of trypsin and pepsin with these two carotenoids are in the following order: astaxanthin–trypsin > astaxanthin–pepsin > β‐carotene–trypsin > β‐carotene–pepsin, respectively. Thermodynamic investigations revealed that the interaction between the two carotenoids and trypsin/pepsin is synergistically driven by enthalpy and entropy, and hydrophobic forces and electrostatic attraction have a significant role in the reactions. In addition, as shown by synchronous fluorescence spectroscopy, UV–vis absorption spectroscopy and CD, the two carotenoids may induce conformational and microenvironmental changes in trypsin/pepsin. The study provides an accurate and full basic data for clarifying the binding mechanisms of the two carotenoids with trypsin/pepsin and is helpful in understanding their effect on protein function and their biological activity in vivo. Copyright © 2015 John Wiley & Sons, Ltd.     

Comparative analysis of dermal collagen and lipids in cereblon ablated mice using a multimodal nonlinear optical system

By utilizing a multimodal nonlinear optical system that combines coherent anti-Stokes Raman scattering and second harmonic generation to investigate biological characteristics of dermal tissues ex vivo, we demonstrate the potential feasibility of using this optical approach as a powerful new investigative tool for future biomedical research. For this study, our optical system was utilized for the first time to analyze lipid and collagen profiles in cereblon knockout (KO) mouse skin, and we were able to discover significant alterations in the number of carbon–carbon double bonds (wild-type vs. cereblon KO; N_CC: 0.75 vs. 0.85) of skin fatty acids in triacylglycerides as well as changes in dermal collagen fibers (25% reduction in cereblon KO). By adopting our optical system to biological studies, we provide researchers with another diagnostic approach to validate their experimental results, which will significantly advance the state of biomedical research.     

Fast denoising and lossless spectrum extraction in stimulated Raman scattering microscopy

Stimulated Raman scattering (SRS) microscopy is a nonlinear optical imaging method for visualizing chemical content based on molecular vibrational bonds. However, the imaging speed and sensitivity are currently limited by the noise of the light beam probing the Raman process. In this paper, we present a fast non-average denoising and high-precision Raman shift extraction method, based on a self-reinforcing signal-to-noise ratio (SNR) enhancement algorithm, for SRS spectroscopy and microscopy. We compare the results of this method with the filtering methods and the reported experimental methods to demonstrate its high efficiency and high precision in spectral denoising, Raman peak extraction and image quality improvement. We demonstrate a maximum SNR enhancement of 10.3 dB in fixed tissue imaging and 11.9 dB in vivo imaging. This method reduces the cost and complexity of the SRS system and allows for high-quality SRS imaging without use of special laser, complicated system design and Raman tags.     

Back Cover: Autofluorescence and white light imaging‐guided endoscopic Raman and diffuse reflectance spectroscopy for in vivo nasopharyngeal cancer detection (J. Biophotonics 4/2018)

An integrated 4‐modality endoscopy system combining white light imaging, autofluorescence imaging, diffuse reflectance spectroscopy and Raman spectroscopy technologies was developed for in vivo endoscopic nasopharyngeal cancer detection. Both high diagnostic sensitivity (98.6%) and high specificity (95.1%) for differentiating cancer from normal tissue sites were achieved using this system combined with multivariate diagnostic algorithm, demonstrating great potential for improving real‐time, in vivo diagnosis of cancer at endoscopy. Further details can be found in the article by Duo Lin et al. ( e201700251 )

     

In vivo sensing of cutaneous edema: A comparative study of diffuse reflectance,Raman spectroscopy and multispectral imaging

Quantitative noninvasive assessment of water content in tissues is important for biomedicine. Optical spectroscopy is potentially capable of solving this problem; however, its applicability for clinical diagnostics remains questionable. The presented study compares diffuse reflectance spectroscopy, Raman spectroscopy and multispectral imaging in the characterization of cutaneous edema. The source-detector geometries for each method are selected based on Monte Carlo simulations results to detect the signal from the dermis. Then, the kinetics of the edema development is studied for two models. All methods demonstrate synchronous trends for histamine-induced edema: The water content reaches a maximum of 1 hour after histamine application and then gradually decreases. For the venous occlusion, a 51% increase in water content is observed with Raman spectroscopy. The differences in water content estimation by three methods are explained based on the light propagation model. The obtained results are essential for introducing quantitative optical water measurement technology to the clinics.     

Identification and characterization of bladder cancer by low‐resolution fiber‐optic Raman spectroscopy

Raman spectroscopy has been proved to be a promising diagnostic technique for various cancers detection. A major drawback for its clinical translation is the intrinsic weakness of Raman effects. Highly sensitive equipment and optimal measurement conditions are generally applied to overcome this drawback. However, these equipment are usually bulky, expensive and may also be easily influenced by surrounding environment. In this preliminary work, a low‐resolution fiber‐optic Raman sensing system is applied to evaluate the diagnostic potential of Raman spectroscopy to identify different bladder pathologies ex vivo. A total number of 262 spectra taken from 32 bladder specimens are included in this study. These spectra are categorized into 3 groups by histopathological analysis, namely normal bladder tissues, low‐grade bladder tumors and high‐grade bladder tumors. Principal component analysis fed artificial neural network are used to train a classification model for the spectral data with 10‐fold cross‐validation and an overall prediction accuracy of 93.1% is obtained. The sensitivities and specificities for normal bladder tissues, low‐grade bladder tumors and high‐grade bladder tumors are 88.5% and 95.1%, 90.3% and 98%, and 97.5% and 96.4%, respectively. These results demonstrate the potential of using a low‐resolution fiber‐optic Raman system for in vivo bladder cancer diagnosis.      

Superpixel Raman spectroscopy for rapid skin cancer margin assessment

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

Time-gated interferometric detection increases Raman scattering to fluorescence signal ratio in biological samples

Attainable levels of signal-to-background ratio (SBR) in Raman spectroscopy of biological samples is limited by the presence of endogenous fluorophores. It is customary to remove the ubiquitous fluorescence background using postacquisition data processing. However, new approaches are needed to reduce background contributions and maximize the fraction of the sensor dynamical range occupied by Raman photons. Time-resolved detection using pulsed lasers and time-gated measurements can be used to address the signal-to-background problem in biological samples by limiting light detection to nonresonant interaction phenomena with relaxation time scales occurring on sub-nanosecond time scales, thereby excluding contributions from resonant phenomena such as fluorescence. A time-gated Fourier-transform spectrometer was assembled using a commercially available interferometer, a single channel single-photon avalanche diode and time tagging electronics. A time gate of 300 ps increased the signal-to-background-ratio of the 1440 cm^?1 Raman band from 36% to 69% in an olive oil sample hereby demonstrating the potential of this approach for autofluorescence suppression.      

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

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

Classification of pathogenic bacteria by Raman spectroscopy combined with variational auto-encoder and deep learning

Rapid and early identification of pathogens is critical to guide antibiotic therapy. Raman spectroscopy as a noninvasive diagnostic technique provides rapid and accurate detection of pathogens. Raman spectrum of single cells serves as the “fingerprint” of the cell, revealing its metabolic characteristics. Rapid identification of pathogens can be achieved by combining Raman spectroscopy and deep learning. Traditional classification techniques frequently require lots of data for training, which is time costing to collect Raman spectra. For trace samples and strains that are difficult to culture, it is difficult to provide an accurate classification model. In order to reduce the number of samples collected and improve the accuracy of the classification model, a new pathogen detection method integrating Raman spectroscopy, variational auto-encoder (VAE), and long short-term memory network (LSTM) is proposed in this paper. We collect the Raman signals of pathogens and input them to VAE for training. VAE will generate a large number of Raman spectral data that cannot be distinguished from the real spectrum, and the signal-to-noise ratio is higher than that of the real spectrum. These spectra are input into the LSTM together with the real spectrum for training, and a good classification model is obtained. The results of the experiments reveal that this method not only improves the average accuracy of pathogen classification to 96.9% but also reduces the number of Raman spectra collected from 1000 to 200. With this technology, the number of Raman spectra collected can be greatly reduced, so that strains that are difficult to culture or trace can be rapidly identified.     

Effect of hemolysis on Fourier transform infrared and Raman spectra of blood plasma

Hemolysis is a very common phenomenon and is referred as the release of intracellular components from red blood cells to the extracellular fluid. Hemolyzed samples are often rejected in clinics due to the interference of hemoglobin and intracellular components in laboratory measurements. Plasma and serum based vibrational spectroscopy studies are extensively applied to generate spectral biomarkers for various diseases. However, no studies have reported the effect of hemolysis in blood based vibrational spectroscopy studies. This study was undertaken to evaluate the effect of hemolysis on infrared and Raman spectra of blood plasma. In this study, prostate cancer plasma samples (n = 30) were divided into three groups (nonhemolyzed, mildly hemolyzed, and moderately hemolyzed) based on the degree of hemolysis and FTIR and Raman spectra were recorded using high throughput (HT)‐FTIR and HT‐Raman spectroscopy. Discrimination was observed between the infrared and Raman spectra of nonhemolyzed and hemolyzed plasma samples using principal component analysis. A classical least square fitting analysis showed differences in the weighting of pure components in nonhemolyzed and hemolyzed plasma samples. Therefore, it is worth to consider the changes in spectral features due to hemolysis when comparing the results within and between experiments.