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 detection of human cutaneous beta‐carotene using computational optical clearing

The content of dermal beta‐carotene can be a good indicator showing the body health. Because, it is involved in production of vitamin A maintaining healthy skin and mucous membranes. Also, it reduces the risk of cardiovascular diseases and its antioxidant capacity prevents the formation of cancerous cells. In this work, we use Raman spectroscopy and a low‐cost diffuse reflectance spectroscopy (DRS) to detect the dermal beta‐carotene spectra. We apply computational optical clearing (OC) method to in vivo evaluation the concentration of this chromophore. The results show that Raman spectroscopy is a good tool for in vitro detection of carotenoids but is not able to clearly discriminate the individual carotenoids in skin tissue in vivo. The results also show that using OC enhances the ability of low‐cost diffuse reflection spectroscopy for in vivo detection of dermal beta‐carotene in humans. This method can be used as a low‐cost and portable device to screening the concentration of chromophores such as melanin and carotenoid molecules for oncological studies.     

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.

     

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.      

Wide‐field color imaging of scatter‐based tissue contrast using both high spatial frequency illumination and cross‐polarization gating

This study characterizes the scatter‐specific tissue contrast that can be obtained by high spatial frequency (HSF) domain imaging and cross‐polarization (CP) imaging, using a standard color imaging system, and how combining them may be beneficial. Both HSF and CP approaches are known to modulate the sensitivity of epi‐illumination reflectance images between diffuse multiply scattered and superficially backscattered photons, providing enhanced contrast from microstructure and composition than what is achieved by standard wide‐field imaging. Measurements in tissue‐simulating optical phantoms show that CP imaging returns localized assessments of both scattering and absorption effects, while HSF has uniquely specific sensitivity to scatter‐only contrast, with a strong suppression of visible contrast from blood. The combination of CP and HSF imaging provided an expanded sensitivity to scatter compared with CP imaging, while rejecting specular reflections detected by HSF imaging. ex vivo imaging of an atlas of dissected rodent organs/tissues demonstrated the scatter‐based contrast achieved with HSF, CP and HSF‐CP imaging, with the white light spectral signal returned by each approach translated to a color image for intuitive encoding of scatter‐based contrast within images of tissue. The results suggest that visible CP‐HSF imaging could have the potential to aid diagnostic imaging of lesions in skin or mucosal tissues and organs, where just CP is currently the standard practice imaging modality.      

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

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

     

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.     

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.     

A comparative evaluation of diffuse reflectance and Raman spectroscopy in the detection of cervical cancer

Optical spectroscopic techniques show improved diagnostic accuracy for non‐invasive detection of cervical cancers. In this study, sensitivity and specificity of two in vivo modalities, i.e diffuse reflectance spectroscopy (DRS) and Raman spectroscopy (RS), were compared by utilizing spectra recorded from the same sites (67 tumor (T), 22 normal cervix (C), and 57 normal vagina (V)). Data was analysed using principal component – linear discriminant analysis (PC‐LDA), and validated using leave‐one‐out‐cross‐validation (LOOCV). Sensitivity, specificity, positive predictive value and negative predictive value for classification between normal (N) and tumor (T) sites were 91%, 96%, 95% and 93%, respectively for RS and 85%, 95%, 93% and 88%, respectively for DRS. Even though DRS revealed slightly lower diagnostic accuracies, owing to its lower cost and portability, it was found to be more suited for cervical cancer screening in low resource settings. On the other hand, RS based devices could be ideal for screening patients with centralised facilities in developing countries.

     

Characterizing biochemical and morphological variations of clinically relevant anatomical locations of oral tissue in vivo with hybrid Raman spectroscopy and optical coherence tomography technique

This study aims to characterize biochemical and morphological variations of the clinically relevant anatomical locations of in vivo oral tissue (ie, alveolar process, lateral tongue and floor of the mouth) by using hybrid Raman spectroscopy (RS) and optical coherence tomography (OCT) technique. A total of 1049 in vivo fingerprint (FP: 800‐1800 cm^?1) and high wavenumber (HW: 2800‐3600 cm^?1) Raman spectra were acquired from different oral tissue (alveolar process = 331, lateral tongue = 339 and floor of mouth = 379) of 26 normal subjects in the oral cavity under the OCT imaging guidance. The total Raman dataset were split into 2 parts: 80% for training and 20% for testing. Tissue optical attenuation coefficients of alveolar process, lateral tongue and the floor of the mouth were derived from OCT images, revealing the inter‐anatomical morphological differences; while RS uncovers subtle FP/HW Raman spectral differences among different oral tissues that can be attributed to the differences in inter‐ and intra‐cellular proteins, lipids, DNA and water structures and conformations, enlightening biochemical variability of different oral tissues at the molecular level. Partial least squares‐discriminant analysis implemented on the training dataset show that the integrated tissue optical attenuation coefficients and FP/HW Raman spectra provide diagnostic sensitivities of 99.6%, 82.3%, 50.2%, and specificities of 97.0%, 75.1%, 92.1%, respectively, which are superior to using either RS (sensitivities of 90.2%, 77.5%, 48.8%, and specificities of 95.8%, 72.1%, 88.8%) or optical attenuation coefficients derived from OCT (sensitivities of 75.0%, 78.2%, 47.2%, and specificities of 96.2%, 67.7%, 85.0%) for the differentiation among alveolar process, lateral tongue and the floor of the mouth. Furthermore, the diagnostic algorithms applied to the independent testing dataset based on hybrid RS‐OCT technique gives predictive diagnostic sensitivities of 100%, 76.5%, 51.3%, and specificities of 95.1%, 77.6%, 89.6%, respectively, for the classifications among alveolar process, lateral tongue and the floor of the mouth, which performs much better than either RS or optical attenuation coefficient derived from OCT imaging. This work suggests that inter‐anatomical morphological and biochemical variability are significant which should be considered as an important parameter in the interpretation and rendering of hybrid RS‐OCT technique for oral tissue diagnosis and characterization.      

Investigation of the source‐detector separation in near infrared spectroscopy for healthy and clinical applications

Understanding near infrared light propagation in tissue is vital for designing next generation optical brain imaging devices. Monte Carlo (MC) simulations provide a controlled mechanism to characterize and evaluate contributions of diverse near infrared spectroscopy (NIRS) sensor configurations and parameters. In this study, we developed a multilayer adult digital head model under both healthy and clinical settings and assessed light‐tissue interaction through MC simulations in terms of partial differential pathlength, mean total optical pathlength, diffuse reflectance, detector light intensity and spatial sensitivity profile of optical measurements. The model incorporated four layers: scalp, skull, cerebrospinal‐fluid and cerebral cortex with and without a customizable lesion for modeling hematoma of different sizes and depths. The effect of source‐detector separation (SDS) on optical measurements' sensitivity to brain tissue was investigated. Results from 1330 separate simulations [(4 lesion volumes × 4 lesion depths for clinical +3 healthy settings) × 7 SDS × 10 simulation = 1330)] each with 100 million photons indicated that selection of SDS is critical to acquire optimal measurements from the brain and recommended SDS to be 25 to 35 mm depending on the wavelengths to obtain optical monitoring of the adult brain function. The findings here can guide the design of future NIRS probes for functional neuroimaging and clinical diagnostic systems.      

Diffuse reflectance spectroscopy in Barrett’s Esophagus: developing a large field‐of‐view screening method discriminating dysplasia from metaplasia

We evaluated diffuse reflectance spectroscopy implemented as a small field‐of‐view technique for discrimination of dysplasia from metaplasia in Barrett’s esophagus as an adjuvant to autofluorescence endoscopy. Using linear discriminant analysis on 2579 spectra measured in 54 patients identified an optimum a 4‐wavelength classifier (at 485, 513, 598 and 629 nm). Sensitivity and specificity for a test data set were 0.67 and 0.85, respectively. Spectroscopic results show that this technique could be implemented in wide‐field imaging mode to improve the accuracy of existing endoscopy techniques for finding early pre‐malignant lesions in Barrett’s esophagus. Results show that the discrimination occurs likely due to redistribution of blood content in the tissue sensed by the optical probing with the wavelength‐dependent sampling depth. (© 2014 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Optical diagnosis of laryngeal cancer using high wavenumber Raman spectroscopy

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

Label‐free imaging and spectroscopy for early detection of cervical cancer

The label‐free imaging and spectroscopy method was studied on cervical unstained tissue sections obtained from 36 patients. The native fluorescence spectra of tissues are analyzed by the optical redox ratio (ORR), which is defined as fluorescence intensity ratio between NADH and FAD, and indicates the metabolism change with the cancer development. The ORRs of normal tissues are consistently higher than those of precancer or cancerous tissues. A criterion line of ORR at 5.0 can be used to discriminate cervical precancer/cancer from normal tissues. The sensitivity and specificity of the native fluorescence spectroscopy method for cervical cancer diagnosis are determined as 100% and 91%. Moreover, the native fluorescence spectroscopy study is much more sensitive on the healthy region of cervical precancer/cancer patients compared with the traditional clinical staining method. The results suggest label‐free imaging and spectroscopy is a fast, highly sensitive and specific method on the detection of cervical cancer.      

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.     

Cell classification with low‐resolution Raman spectroscopy (LRRS)

The identification of individual eukaryotic and prokaryotic cells is the backbone of clinical pathology and provides crucial information about the genesis and progression of a disease. While most commonly fluorescent‐label based methods are applied, label‐free methods, such as Raman spectroscopy, are elegant alternatives. A major disadvantage of Raman spectroscopy is the low signal yield resulting in long acquisition times, making it impractical for high‐throughput clinical analysis. As a rule, Raman‐based cell identification relies on high‐resolution Raman spectra. This comes at a cost of detected Raman photons. In this letter we show that while the proper biochemical characterization of cells requires high‐resolution Raman spectra, the proper classification of cells does not. By varying the slit‐width between 50 µm and 500 µm it is possible to show that detected Raman signal from eukaryotic cells increased up to seven‐fold. Raman‐based cell classification was performed on three cancer cell lines: Jurkat, MiaPaca2, and Capan1, at three different resolutions 8 cm^–1, 24 cm^–1, and 48 cm^–1. Moreover, we have simulated the resolution decrease due to low‐diffraction gratings by binning neighboring pixels together. In both cases the cells were well classifiable using support vectors machine (SVM).

For anyone working in the field of Raman spectroscopy this picture of Sir C.V. Raman is recognizable, even with reduced spatial resolution. Raman spectra of eukaryotic cells can also be recognized even with six fold reduced spectral resolution.     

SERS and integrative imaging upon internalization of quantum dots into human oral epithelial cells

CdTe quantum dots (QDs) are widely used in bio‐applications due to their size and highly efficient optical properties. However internalization mechanisms thereof for the variety of freshly extracted, not cultivated human cells and their specific molecular interactions remains an open topic for discussion. In this study, we assess the internalization mechanism of CdTe quantum dots (3.3 nm) capped with thioglycolic acid using non cultivated oral epithelial cells obtained from healthy donors. Naked gold nanoparticles (40 nm) were successfully used as nanosensors for surface‐enhanced Raman spectroscopy to efficiently identify characteristic Raman peaks, providing new evidence indicating that the first interactions of these QDs with epithelial cells occurred preferentially with aromatic rings and amine groups of amino acid residues and glycans from trans‐membrane proteins and cytoskeleton. Using an integrative combination of advanced imaging techniques, including ultra‐high resolution SEM, high resolution STEM coupled with EDX spectroscopy together with the results obtained by Raman spectroscopy, it was determined that thioglycolic acid capped CdTe QDs are efficiently internalized into freshly extracted oral epithelial cells only by facilitated diffusion, distributed into cytoplasm and even within the cell nucleus in three minutes.

     

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.     

Raman spectroscopy for accurately characterizing biomolecular changes in androgen‐independent prostate cancer cells

Metastatic prostate cancer resistant to hormonal manipulation is considered the advanced stage of the disease and leads to most cancer‐related mortality. With new research focusing on modulating cancer growth, it is essential to understand the biochemical changes in cells that can then be exploited for drug discovery and for improving responsiveness to treatment. Raman spectroscopy has a high chemical specificity and can be used to detect and quantify molecular changes at the cellular level. Collection of large data sets generated from biological samples can be employed to form discriminatory algorithms for detection of subtle and early changes in cancer cells. The present study describes Raman finger printing of normal and metastatic hormone‐resistant prostate cancer cells including analyses with principal component analysis and linear discrimination. Amino acid‐specific signals were identified, especially loss of arginine band. Androgen‐resistant prostate cancer cells presented a higher content of phenylalanine, tyrosine, DNA and Amide III in comparison to PNT2 cells, which possessed greater amounts of L‐arginine and had a B conformation of DNA. The analysis utilized in this study could reliably differentiate the 2 cell lines (sensitivity 95%; specificity 88%).