Real-time Raman system for in vivo disease diagnosis

Optics miniaturization strategy for demanding Raman spectroscopy applications

Raman spectroscopy provides non-destructive, label-free quantitative studies of chemical compositions at the microscale as used on NASA's Perseverance rover on Mars. Such capabilities come at the cost of high requirements for instrumentation. Here we present a centimeter-scale miniaturization of a Raman spectrometer using cheap non-stabilized laser diodes, densely packed optics, and non-cooled small sensors. The performance is comparable with expensive bulky research-grade Raman systems. It has excellent sensitivity, low power consumption, perfect wavenumber, intensity calibration, and 7 cm-1 resolution within the 400-4000 cm-1 range using a built-in reference. High performance and versatility are demonstrated in use cases including quantification of methanol in beverages, in-vivo Raman measurements of human skin, fermentation monitoring, chemical Raman mapping at sub-micrometer resolution, quantitative SERS mapping of the anti-cancer drug methotrexate and in-vitro bacteria identification. We foresee that the miniaturization will allow realization of super-compact Raman spectrometers for integration in smartphones and medical devices, democratizing Raman technology.

Spectral effects and enhancement quantification in healthy human saliva with surface-enhanced Raman spectroscopy using silver nanopillar substrates

OBJECTIVES

Raman spectroscopy as a diagnostic tool for biofluid applications is limited by low inelastic scattering contributions compared to the fluorescence background from biomolecules. Surface-enhanced Raman spectroscopy (SERS) can increase Raman scattering signals, thereby offering the potential to reduce imaging times. We aimed to evaluate the enhancement related to the plasmonic effect and quantify the improvements in terms of spectral quality associated with SERS measurements in human saliva.

METHODS

Dried human saliva was characterized using spontaneous Raman spectroscopy and SERS. A fabrication protocol was implemented leading to the production of silver (Ag) nanopillar substrates by glancing angle deposition. Two different imaging systems were used to interrogate saliva from 161 healthy donors: a custom single-point macroscopic system and a Raman micro-spectroscopy instrument. Quantitative metrics were established to compare spontaneous RS and SERS measurements: the Raman spectroscopy quality factor (QF), the photonic count rate (PR), the signal-to-background ratio (SBR).

RESULTS

SERS measurements acquired with an excitation energy four times smaller than with spontaneous RS resulted in improved QF, PR values an order of magnitude larger and a SBR twice as large. The SERS enhancement reached 100×, depending on which Raman bands were considered.

CONCLUSIONS

Single-point measurement of dried saliva with silver nanopillars substrates led to reproducible SERS measurements, paving the way to real-time tools of diagnosis in human biofluids.

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.

Simultaneous Dual-Wavelength Source Raman Spectroscopy with a Handheld Confocal Probe for Analysis of the Chemical Composition of In Vivo Human Skin

Confocal Raman spectroscopy (CRS) is a powerful tool that has been widely used for biological tissue analysis because of its noninvasive nature, high specificity, and rich biochemical information. However, current commercial CRS systems suffer from limited detection regions (450-1750 cm-1), bulky sizes, nonflexibilities, slow acquisitions by consecutive excitations, and high costs if using a Fourier transform (FT) Raman spectroscopy with an InGaAs detector, which impede their adoption in clinics. In this study, we developed a portable CRS system with a simultaneous dual-wavelength source and a miniaturized handheld probe (120 mm × 60 mm × 50 mm) that can acquire spectra in both fingerprint (FP, 450-1750 cm-1) and high wavenumber (HW, 2800-3800 cm-1) regions simultaneously. An innovative design combining 671 and 785 nm lasers for simultaneous excitation through a compact and high-efficiency (>90%) wavelength combiner was implemented. Moreover, to decouple the fused FP and HW spectra, a first-of-its-kind precise Raman spectra separation algorithm (PRSSA) was developed based on the maximum a posteriori probability (MAP) estimate. The accuracy of spectra separation was greater than 99%, demonstrated in both phantom experiments and in vivo human skin measurements. The total data acquisition time was reduced by greater than 50% compared to other CRS systems. The results proved our proposed CRS system and PRSSA's superior capability in fast and ultrawideband spectra acquisition will significantly improve the integration of CRS in the clinical workflow.

Rapid diagnosis of membranous nephropathy based on serum and urine Raman spectroscopy combined with deep learning methods

Membranous nephropathy is the main cause of nephrotic syndrome, which has an insidious onset and may progress to end-stage renal disease with a high mortality rate, such as renal failure and uremia. At present, the diagnosis of membranous nephropathy mainly relies on the clinical manifestations of patients and pathological examination of kidney biopsy, which are expensive, time-consuming, and have certain chance and other disadvantages. Therefore, there is an urgent need to find a rapid, accurate and non-invasive diagnostic technique for the diagnosis of membranous nephropathy. In this study, Raman spectra of serum and urine were combined with deep learning methods to diagnose membranous nephropathy. After baseline correction and smoothing of the data, Gaussian white noise of different decibels was added to the training set for data amplification, and the amplified data were imported into ResNet, AlexNet and GoogleNet models to obtain the evaluation results of the models for membranous nephropathy. The experimental results showed that the three deep learning models achieved an accuracy of 1 for the classification of serum data of patients with membranous nephropathy and control group, and the discrimination of urine data was above 0.85, among which AlexNet was the best classification model for both samples. The above experimental results illustrate the great potential of serum- and urine-based Raman spectroscopy combined with deep learning methods for rapid and accurate identification of patients with membranous nephropathy.

Raman Spectroscopy: A Personalized Decision-Making Tool on Clinicians' Hands for In Situ Cancer Diagnosis and Surgery Guidance

Simple Summary

Cancer still constitutes one of the main global health challenges. Novel approaches towards understanding the molecular composition of the disease can be employed as adjuvant tools to current oncological applications. Raman spectroscopy has been contemplated and pursued to serve as a noninvasive, real time, in vivo tool which may uncover the molecular basis of cancer and simultaneously offer high specificity, sensitivity, and multiplexing capacity, as well as high spatial and temporal resolution. In this review, the potential impact of Spontaneous Raman spectroscopy in clinical applications related to cancer diagnosis and surgical removal is analyzed. Moreover, the coupling of Raman systems with modern instrumentation and machine learning methods has been explored as a prominent enhancement factor towards a personalized approach promoting objectivity and accuracy in surgical oncology.

Abstract

Accurate in situ diagnosis and optimal surgical removal of a malignancy constitute key elements in reducing cancer-related morbidity and mortality. In surgical oncology, the accurate discrimination between healthy and cancerous tissues is critical for the postoperative care of the patient. Conventional imaging techniques have attempted to serve as adjuvant tools for in situ biopsy and surgery guidance. However, no single imaging modality has been proven sufficient in terms of specificity, sensitivity, multiplexing capacity, spatial and temporal resolution. Moreover, most techniques are unable to provide information regarding the molecular tissue composition. In this review, we highlight the potential of Raman spectroscopy as a spectroscopic technique with high detection sensitivity and spatial resolution for distinguishing healthy from malignant margins in microscopic scale and in real time. A Raman spectrum constitutes an intrinsic “molecular finger-print” of the tissue and any biochemical alteration related to inflammatory or cancerous tissue state is reflected on its Raman spectral fingerprint. Nowadays, advanced Raman systems coupled with modern instrumentation devices and machine learning methods are entering the clinical arena as adjunct tools towards personalized and optimized efficacy in surgical oncology.

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.

Spatially-Resolved Multiply-Excited Autofluorescence and Diffuse Reflectance Spectroscopy: SpectroLive Medical Device for Skin In Vivo Optical Biopsy

This contribution presents the development of an optical spectroscopy device, called SpectroLive, that allows spatially-resolved multiply-excited autofluorescence and diffuse reflectance measurements. Besides describing the device, this study aims at presenting the metrological and safety regulation validations performed towards its aimed application to skin carcinoma in vivo diagnosis. This device is made of six light sources and four spectrometers for detection of the back-scattered intensity spectra collected through an optical probe (made of several optical fibers) featuring four source-to-detector separations (from 400 to 1000 µm). In order to be allowed by the French authorities to be evaluated in clinics, the SpectroLive device was successfully checked for electromagnetic compatibility and electrical and photobiological safety. In order to process spectra, spectral correction and metrological calibration were implemented in the post-processing software. Finally, we characterized the device’s sensitivity to autofluorescence detection: excitation light irradiance at the optical probe tip in contact with skin surface ranges from 2 to 11 W/m², depending on the light source. Such irradiances combined to sensitive detectors allow the device to acquire a full spectroscopic sequence within 6 s which is a short enough duration to be compatible with optical-guided surgery. All these results about sensitivity and safety make the SpectroLive device mature enough to be evaluated through a clinical trial that aims at evaluating its diagnostic accuracy for skin carcinoma diagnosis.

Diverse spectral band-based deep residual network for tongue squamous cell carcinoma classification using fiber optic Raman spectroscopy

The research is to propose a new classification framework, called diverse spectral band-based deep residual network (DSB-ResNet), which can distinguish tongue squamous cell carcinoma (TSCC) from non-cancerous tissue. A fiber optic Raman spectroscopy system is used to collect Raman spectral data of TSCC and normal tissues. DSB-ResNet takes advantage of diverse spectral band-based spectra without processing to derive spectral representations from different spectral bands of Raman spectra, which improves the ability to identify TSCC. To show the superiority of the proposed method, the existing methods are used as the competitive methods to compare with the DSB-RestNet, the results demonstrate our method has the highest performance with 97.38 %, 98.75 %, and 98.25 % for sensitivity, specificity, and accuracy, respectively. The experimental results show that the DSB-ResNet is able to distinguish TSCC from non-cancerous tissue successfully. The proposed method is expected to provide a theoretical and methodological base for accurate detection of TSCC.

Molecular imaging of inflammation - Current and emerging technologies for diagnosis and treatment

Inflammation is a key factor in multiple diseases including primary immune-mediated inflammatory diseases e.g. rheumatoid arthritis but also, less obviously, in many other common conditions, e.g. cardiovascular disease and diabetes. Together, chronic inflammatory diseases contribute to the majority of global morbidity and mortality. However, our understanding of the underlying processes by which the immune response is activated and sustained is limited by a lack of cellular and molecular information obtained in situ. Molecular imaging is the visualization, detection and quantification of molecules in the body. The ability to reveal information on inflammatory biomarkers, pathways and cells can improve disease diagnosis, guide and monitor therapeutic intervention and identify new targets for research. The optimum molecular imaging modality will possess high sensitivity and high resolution and be capable of non-invasive quantitative imaging of multiple disease biomarkers while maintaining an acceptable safety profile. The mainstays of current clinical imaging are computed tomography (CT), magnetic resonance imaging (MRI), ultrasound (US) and nuclear imaging such as positron emission tomography (PET). However, none of these have yet progressed to routine clinical use in the molecular imaging of inflammation, therefore new approaches are required to meet this goal. This review sets out the respective merits and limitations of both established and emerging imaging modalities as clinically useful molecular imaging tools in addition to potential theranostic applications.

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.

In-vivo Raman spectroscopy: from basics to applications

For more than two decades, Raman spectroscopy has found widespread use in biological and medical applications. The instrumentation and the statistical evaluation procedures have matured, enabling the lengthy transition from ex-vivo demonstration to in-vivo examinations. This transition goes hand-in-hand with many technological developments and tightly bound requirements for a successful implementation in a clinical environment, which are often difficult to assess for novice scientists in the field. This review outlines the required instrumentation and instrumentation parameters, designs, and developments of fiber optic probes for the in-vivo applications in a clinical setting. It aims at providing an overview of contemporary technology and clinical trials and attempts to identify future developments necessary to bring the emerging technology to the clinical end users. A comprehensive overview of in-vivo applications of fiber optic Raman probes to characterize different tissue and disease types is also given.

New insights of Raman spectroscopy for oral clinical applications

Oral injuries are currently diagnosed by histopathological analysis of biopsy, which is an invasive procedure and does not give immediate results.

Evaluation of Shifted Excitation Raman Difference Spectroscopy and Comparison to Computational Background Correction Methods Applied to Biochemical Raman Spectra

Raman spectroscopy provides label-free biochemical information from tissue samples without complicated sample preparation. The clinical capability of Raman spectroscopy has been demonstrated in a wide range of in vitro and in vivo applications. However, a challenge for in vivo applications is the simultaneous excitation of auto-fluorescence in the majority of tissues of interest, such as liver, bladder, brain, and others. Raman bands are then superimposed on a fluorescence background, which can be several orders of magnitude larger than the Raman signal. To eliminate the disturbing fluorescence background, several approaches are available. Among instrumentational methods shifted excitation Raman difference spectroscopy (SERDS) has been widely applied and studied. Similarly, computational techniques, for instance extended multiplicative scatter correction (EMSC), have also been employed to remove undesired background contributions. Here, we present a theoretical and experimental evaluation and comparison of fluorescence background removal approaches for Raman spectra based on SERDS and EMSC.

Endoscopic sensing of alveolar pH

Previously unobtainable measurements of alveolar pH were obtained using an endoscope-deployable optrode. The pH sensing was achieved using functionalized gold nanoshell sensors and surface enhanced Raman spectroscopy (SERS). The optrode consisted of an asymmetric dual-core optical fiber designed for spatially separating the optical pump delivery and signal collection, in order to circumvent the unwanted Raman signal generated within the fiber. Using this approach, we demonstrate a ~100-fold increase in SERS signal-to-fiber background ratio, and demonstrate multiple site pH sensing with a measurement accuracy of ± 0.07 pH units in the respiratory acini of an ex vivo ovine lung model. We also demonstrate that alveolar pH changes in response to ventilation.

Label-Free Raman Imaging to Monitor Breast Tumor Signatures

Although not yet ready for clinical application, methods based on Raman spectroscopy have shown significant potential in identifying, characterizing, and discriminating between noncancerous and cancerous specimens. Real-time and accurate medical diagnosis achievable through this vibrational optical method largely benefits from improvements in current technological and software capabilities. Not only is the acquisition of spectral information now possible in milliseconds and analysis of hundreds of thousands of data points achieved in minutes, but Raman spectroscopy also allows simultaneous detection and monitoring of several biological components. Besides demonstrating a significant Raman signature distinction between nontumorigenic (MCF-10A) and tumorigenic (MCF-7) breast epithelial cells, our study demonstrates that Raman can be used as a label-free method to evaluate epidermal growth factor activity in tumor cells. Comparative Raman profiles and images of specimens in the presence or absence of epidermal growth factor show important differences in regions attributed to lipid, protein, and nucleic acid vibrations. The occurrence, which is dependent on the presence of epidermal growth factor, of new Raman features associated with the appearance of phosphothreonine and phosphoserine residues reflects a signal transduction from the membrane to the nucleus, with concomitant modification of DNA/RNA structural characteristics. Parallel Western blotting analysis reveals an epidermal growth factor induction of phosphorylated Akt protein, corroborating the Raman results. The analysis presented in this work is an important step toward Raman-based evaluation of biological activity of epidermal growth factor receptors on the surfaces of breast cancer cells. With the ultimate future goal of clinically implementing Raman-guided techniques for the diagnosis of breast tumors (e.g., with regard to specific receptor activity), the current results just lay the foundation for further label-free optical tools to diagnose the disease.

Clinical instrumentation and applications of Raman spectroscopy

Clinical diagnostic devices provide new sources of information that give insight about the state of health which can then be used to manage patient care. These tools can be as simple as an otoscope to better visualize the ear canal or as complex as a wireless capsule endoscope to monitor the gastrointestinal tract. It is with tools such as these that medical practitioners can determine when a patient is healthy and to make an appropriate diagnosis when he/she is not. The goal of diagnostic medicine then is to efficiently determine the presence and cause of disease in order to provide the most appropriate intervention. The earliest form of medical diagnostics relied on the eye - direct visual observation of the interaction of light with the sample. This technique was espoused by Hippocrates in his 5th century BCE work Epidemics, in which the pallor of a patient's skin and the coloring of the bodily fluids could be indicative of health. In the last hundred years, medical diagnosis has moved from relying on visual inspection to relying on numerous technological tools that are based on various types of interaction of the sample with different types of energy - light, ultrasound, radio waves, X-rays etc. Modern advances in science and technology have depended on enhancing technologies for the detection of these interactions for improved visualization of human health. Optical methods have been focused on providing this information in the micron to millimeter scale while ultrasound, X-ray, and radio waves have been key in aiding in the millimeter to centimeter scale. While a few optical technologies have achieved the status of medical instruments, many remain in the research and development phase despite persistent efforts by many researchers in the translation of these methods for clinical care. Of these, Raman spectroscopy has been described as a sensitive method that can provide biochemical information about tissue state while maintaining the capability of delivering this information in real-time, non-invasively, and in an automated manner. This review presents the various instrumentation considerations relevant to the clinical implementation of Raman spectroscopy and reviews a subset of interesting applications that have successfully demonstrated the efficacy of this technique for clinical diagnostics and monitoring in large (n ≥ 50) in vivo human studies.

Developing fibre optic Raman probes for applications in clinical spectroscopy

Raman spectroscopy has been shown by various groups over the last two decades to have significant capability in discriminating disease states in bodily fluids, cells and tissues. Recent development in instrumentation, optics and manufacturing approaches has facilitated the design and demonstration of various novel in vivo probes, which have applicability for myriad of applications. This review focusses on key considerations and recommendations for application specific clinical Raman probe design and construction. Raman probes can be utilised as clinical tools able to provide rapid, non-invasive, real-time molecular analysis of disease specific changes in tissues. Clearly the target tissue location, the significance of spectral changes with disease and the possible access routes to the region of interest will vary for each clinical application considered. This review provides insight into design and construction considerations, including suitable probe designs and manufacturing materials compatible with Raman spectroscopy.

Noninvasive Detection of Inflammatory Changes in White Adipose Tissue by Label-Free Raman Spectroscopy

White adipose tissue inflammation (WATi) has been linked to the pathogenesis of obesity-related diseases, including type 2 diabetes, cardiovascular disease, and cancer. In addition to the obese, a substantial number of normal and overweight individuals harbor WATi, putting them at increased risk for disease. We report the first technique that has the potential to detect WATi noninvasively. Here, we used Raman spectroscopy to detect WATi with excellent accuracy in both murine and human tissues. This is a potentially significant advance over current histopathological techniques for the detection of WATi, which rely on tissue excision and, therefore, are not practical for assessing disease risk in the absence of other identifying factors. Importantly, we show that noninvasive Raman spectroscopy can diagnose WATi in mice. Taken together, these results demonstrate the potential of Raman spectroscopy to provide objective risk assessment for future cardiometabolic complications in both normal weight and overweight/obese individuals.

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.

Advances in the in Vivo Raman Spectroscopy of Malignant Skin Tumors Using Portable Instrumentation

Raman spectroscopy has emerged as a promising tool for real-time clinical diagnosis of malignant skin tumors offering a number of potential advantages: it is non-intrusive, it requires no sample preparation, and it features high chemical specificity with minimal water interference. However, in vivo tissue evaluation and accurate histopathological classification remain a challenging task for the successful transition from laboratory prototypes to clinical devices. In the literature, there are numerous reports on the applications of Raman spectroscopy to biomedical research and cancer diagnostics. Nevertheless, cases where real-time, portable instrumentations have been employed for the in vivo evaluation of skin lesions are scarce, despite their advantages in use as medical devices in the clinical setting. This paper reviews the advances in real-time Raman spectroscopy for the in vivo characterization of common skin lesions. The translational momentum of Raman spectroscopy towards the clinical practice is revealed by (i) assembling the technical specifications of portable systems and (ii) analyzing the spectral characteristics of in vivo measurements.

Computational chemical imaging for cardiovascular pathology: chemical microscopic imaging accurately determines cardiac transplant rejection

Rejection is a common problem after cardiac transplants leading to significant number of adverse events and deaths, particularly in the first year of transplantation. The gold standard to identify rejection is endomyocardial biopsy. This technique is complex, cumbersome and requires a lot of expertise in the correct interpretation of stained biopsy sections. Traditional histopathology cannot be used actively or quickly during cardiac interventions or surgery. Our objective was to develop a stain-less approach using an emerging technology, Fourier transform infrared (FT-IR) spectroscopic imaging to identify different components of cardiac tissue by their chemical and molecular basis aided by computer recognition, rather than by visual examination using optical microscopy. We studied this technique in assessment of cardiac transplant rejection to evaluate efficacy in an example of complex cardiovascular pathology. We recorded data from human cardiac transplant patients’ biopsies, used a Bayesian classification protocol and developed a visualization scheme to observe chemical differences without the need of stains or human supervision. Using receiver operating characteristic curves, we observed probabilities of detection greater than 95% for four out of five histological classes at 10% probability of false alarm at the cellular level while correctly identifying samples with the hallmarks of the immune response in all cases. The efficacy of manual examination can be significantly increased by observing the inherent biochemical changes in tissues, which enables us to achieve greater diagnostic confidence in an automated, label-free manner. We developed a computational pathology system that gives high contrast images and seems superior to traditional staining procedures. This study is a prelude to the development of real time in situ imaging systems, which can assist interventionists and surgeons actively during procedures.

Emerging technology: applications of Raman spectroscopy for prostate cancer

There is a need in prostate cancer diagnostics and research for a label-free imaging methodology that is nondestructive, rapid, objective, and uninfluenced by water. Raman spectroscopy provides a molecular signature, which can be scaled from micron-level regions of interest in cells to macroscopic areas of tissue. It can be used for applications ranging from in vivo or in vitro diagnostics to basic science laboratory testing. This work describes the fundamentals of Raman spectroscopy and complementary techniques including surface enhanced Raman scattering, resonance Raman spectroscopy, coherent anti-Stokes Raman spectroscopy, confocal Raman spectroscopy, stimulated Raman scattering, and spatially offset Raman spectroscopy. Clinical applications of Raman spectroscopy to prostate cancer will be discussed, including screening, biopsy, margin assessment, and monitoring of treatment efficacy. Laboratory applications including cell identification, culture monitoring, therapeutics development, and live imaging of cellular processes are discussed. Potential future avenues of research are described, with emphasis on multiplexing Raman spectroscopy with other modalities.

Raman spectroscopy for the discrimination of cancerous and normal skin

Various studies have shown promising results in using Raman spectroscopy (RS) for the detection of skin cancers.

In vivo Raman spectroscopy for detection of oral neoplasia: a pilot clinical study

We report a pilot study carried out to evaluate the applicability of in vivo Raman spectroscopy for differential diagnosis of malignant and potentially malignant lesions of human oral cavity in a clinical setting. The study involved 28 healthy volunteers and 171 patients having various lesions of oral cavity. The Raman spectra, measured from multiple sites of normal oral mucosa and of lesions belonging to three histopathological categories, viz. oral squamous cell carcinoma (OSCC), oral submucous fibrosis (OSMF) and leukoplakia (OLK), were subjected to a probability based multivariate statistical algorithm capable of direct multi-class classification. With respect to histology as the gold standard, the diagnostic algorithm was found to provide an accuracy of 85%, 89%, 85% and 82% in classifying the oral tissue spectra into the four tissue categories based on leave-one-subject-out cross validation. When employed for binary classification, the algorithm resulted in a sensitivity and specificity of 94% in discriminating normal from the rest of the abnormal spectra of OSCC, OSMF and OLK tissue sites pooled together.

Identification of spermatogenesis in a rat sertoli-cell only model using Raman spectroscopy: a feasibility study

PURPOSE

We determined whether Raman spectroscopy could identify spermatogenesis in a Sertoli-cell only rat model.

MATERIALS AND METHODS

A partial Sertoli-cell only model was created using a testicular hypothermia-ischemia technique. Bilateral testis biopsy was performed in 4 rats. Raman spectra were acquired with a probe in 1 mm3 samples of testicular tissue. India ink was used to mark the site of spectral acquisition. Comparative histopathology was applied to verify whether Raman spectra were obtained from Sertoli-cell only tubules or seminiferous tubules with spermatogenesis. Principal component analysis and logistic regression were used to develop a mathematical model to evaluate the predictive accuracy of identifying tubules with spermatogenesis vs Sertoli-cell only tubules.

RESULTS

Raman peak intensity changes were noted at 1,000 and 1,690 cm(-1) for tubules with spermatogenesis and Sertoli-cell only tubules, respectively. When principal components were used to predict whether seminferous tubules were Sertoli-cell only tubules or showed spermatogenesis, sensitivity and specificity were 96% and 100%, respectively. The ROC AUC to predict tubules with spermatogenesis with Raman spectroscopy was 0.98.

CONCLUSIONS

Raman spectroscopy is capable of identifying seminiferous tubules with spermatogenesis in a Sertoli-cell only ex vivo rat model. Future ex vivo studies of human testicular tissue are necessary to confirm whether these findings can be translated to the clinical setting.

Clinical Raman measurements under special ambient lighting illumination

One challenge in facing the application of biomedical Raman spectroscopy is that the Raman signal is acquired in a dark operation room. It is inconvenient for both the operator and the patient because it is difficult for the operator to accurately and precisely locate the target in the dark environment, and the patient feels uncomfortable in such a setting. In this note, we propose a method to implement biomedical Raman measurement with an illumination source, by multiple filtering of the illumination and the collection optics. Experimental results are demonstrated on skin Raman measurement under 785-nm excitation.

Clinical study of noninvasive in vivo melanoma and nonmelanoma skin cancers using multimodal spectral diagnosis

The goal of this study was to determine the diagnostic capability of a multimodal spectral diagnosis (SD) for in vivo noninvasive disease diagnosis of melanoma and nonmelanoma skin cancers. We acquired reflectance, fluorescence, and Raman spectra from 137 lesions in 76 patients using custom-built optical fiber-based clinical systems. Biopsies of lesions were classified using standard histopathology as malignant melanoma (MM), nonmelanoma pigmented lesion (PL), basal cell carcinoma (BCC), actinic keratosis (AK), and squamous cell carcinoma (SCC). Spectral data were analyzed using principal component analysis. Using multiple diagnostically relevant principal components, we built leave-one-out logistic regression classifiers. Classification results were compared with histopathology of the lesion. Sensitivity/specificity for classifying MM versus PL (12 versus 17 lesions) was 100%/100%, for SCC and BCC versus AK (57 versus 14 lesions) was 95%/71%, and for AK and SCC and BCC versus normal skin (71 versus 71 lesions) was 90%/85%. The best classification for nonmelanoma skin cancers required multiple modalities; however, the best melanoma classification occurred with Raman spectroscopy alone. The high diagnostic accuracy for classifying both melanoma and nonmelanoma skin cancer lesions demonstrates the potential for SD as a clinical diagnostic device.

Assessing variability of in vivo tissue Raman spectra

Raman spectroscopy (RS) has received increasing attention as a potential tool for clinical diagnostics. However, the unknown comparability of multiple tissue RS systems remains a major issue for technique standardization and future multisystem trials. In this study, we evaluated potential factors affecting data collection and interpretation, utilizing the skin as an example tissue. The effects of contact pressure and probe angle were characterized as potential user-induced variability sources. Similarly, instrumentation-induced variability sources of system stability and system-dependent response were also analyzed on skin and a nonvolatile biological tissue analog. Physiologically induced variations were studied on multiple tissue locations and patients. The effect of variability sources on spectral line shape and dispersion was analyzed with analysis-of-variance methods, and a new metric for comparing spectral dispersion was defined. In this study, in vivo measurements were made on multiple sites of skin from five healthy volunteers, with four stand-alone fiber optic probe-based tissue RS systems. System stability and controlled user-induced variables had no effects on obtained spectra. By contrast, instrumentation and anatomical location of measurement were significant sources of variability. These findings establish the comparability of tissue Raman spectra obtained by unique systems. Furthermore, we suggest steps for further procedural and instrumentation standardization prior to broad clinical applications of the technique.

Advances in the clinical application of Raman spectroscopy for cancer diagnostics

Light interacts with tissue in a number of ways including, elastic and inelastic scattering, reflection and absorption, leading to fluorescence and phosphorescence. These interactions can be used to measure abnormal changes in tissue. Initial optical biopsy systems have potential to be used as an adjunct to current investigative techniques to improve the targeting of blind biopsy. Future prospects with molecular-specific techniques may enable objective optical detection providing a real-time, highly sensitive and specific measurement of the histological state of the tissue. Raman spectroscopy has the potential to identify markers associated with malignant change and could be used as diagnostic tool for the early detection of precancerous and cancerous lesions in vivo. The clinical requirements for an objective, non-invasive, real-time probe for the accurate and repeatable measurement of pathological state of the tissue are overwhelming. This paper discusses some of the recent advances in the field.

Illuminating disease and enlightening biomedicine: Raman spectroscopy as a diagnostic tool

The discovery of the Raman effect in 1928 not only aided fundamental understanding about the quantum nature of light and matter but also opened up a completely novel area of optics and spectroscopic research that is accelerating at a greater rate during the last decade than at any time since its inception. This introductory overview focuses on some of the most recent developments within this exciting field and how this has enabled and enhanced disease diagnosis and biomedical applications. We highlight a small number of stimulating high-impact studies in imaging, endoscopy, stem cell research, and other recent developments such as spatially offset Raman scattering amongst others. We hope this stimulates further interest in this already exciting field, by 'illuminating' some of the current research being undertaken by the latest in a very long line of dedicated experimentalists interested in the properties and potential beneficial applications of light.

Raman imaging at biological interfaces: applications in breast cancer diagnosis

BACKGROUND

One of the most important areas of Raman medical diagnostics is identification and characterization of cancerous and noncancerous tissues. The methods based on Raman scattering has shown significant potential for probing human breast tissue to provide valuable information for early diagnosis of breast cancer. A vibrational fingerprint from the biological tissue provides information which can be used to identify, characterize and discriminate structures in breast tissue, both in the normal and cancerous environment.

RESULTS

The paper reviews recent progress in understanding structure and interactions at biological interfaces of the human tissue by using confocal Raman imaging and IR spectroscopy. The important differences between the noncancerous and cancerous human breast tissues were found in regions characteristic for vibrations of carotenoids, fatty acids, proteins, and interfacial water. Particular attention was paid to the role played by unsaturated fatty acids and their derivatives as well as carotenoids and interfacial water.

CONCLUSIONS

We demonstrate that Raman imaging has reached a clinically relevant level in regard to breast cancer diagnosis applications. The results presented in the paper may have serious implications on understanding mechanisms of interactions in living cells under realistically crowded conditions of biological tissue.

Diagnostic segregation of human brain tumours using Fourier-transform infrared and/or Raman spectroscopy coupled with discriminant analysis

The most common initial treatment received by patients with a brain tumour is surgical removal of the growth. Precise histopathological diagnosis of brain tumours is to some extent subjective. Furthermore, currently available diagnostic imaging techniques to delineate the excision border during cytoreductive surgery lack the required spatial precision to aid surgeons. We set out to determine whether infrared (IR) and/or Raman spectroscopy combined with multivariate analysis could be applied to discriminate between normal brain tissue and different tumour types (meningioma, glioma and brain metastasis) based on the unique spectral "fingerprints" of their biochemical composition. Formalin-fixed paraffin-embedded tissue blocks of normal brain and different brain tumours were de-waxed, mounted on low-E slides and desiccated before being analyzed using attenuated total reflection Fourier-transform IR (ATR-FTIR) and Raman spectroscopy. ATR-FTIR spectroscopy showed a clear segregation between normal and different tumour subtypes. Discrimination of tumour classes was also apparent with Raman spectroscopy. Further analysis of spectral data revealed changes in brain biochemical structure associated with different tumours. Decreased tentatively-assigned lipid-to-protein ratio was associated with increased tumour progression. Alteration in cholesterol esters-to-phenylalanine ratio was evident in grade IV glioma and metastatic tumours. The current study indicates that IR and/or Raman spectroscopy have the potential to provide a novel diagnostic approach in the accurate diagnosis of brain tumours and have potential for application in intra-operative diagnosis.

Real-time Raman spectroscopy for in vivo, online gastric cancer diagnosis during clinical endoscopic examination

Optical spectroscopic techniques including reflectance, fluorescence and Raman spectroscopy have shown promising potential for in vivo precancer and cancer diagnostics in a variety of organs. However, data-analysis has mostly been limited to post-processing and off-line algorithm development. In this work, we develop a fully automated on-line Raman spectral diagnostics framework integrated with a multimodal image-guided Raman technique for real-time in vivo cancer detection at endoscopy. A total of 2748 in vivo gastric tissue spectra (2465 normal and 283 cancer) were acquired from 305 patients recruited to construct a spectral database for diagnostic algorithms development. The novel diagnostic scheme developed implements on-line preprocessing, outlier detection based on principal component analysis statistics (i.e., Hotelling's T2 and Q-residuals) for tissue Raman spectra verification as well as for organ specific probabilistic diagnostics using different diagnostic algorithms. Free-running optical diagnosis and processing time of < 0.5 s can be achieved, which is critical to realizing real-time in vivo tissue diagnostics during clinical endoscopic examination. The optimized partial least squares-discriminant analysis (PLS-DA) models based on the randomly resampled training database (80% for learning and 20% for testing) provide the diagnostic accuracy of 85.6% [95% confidence interval (CI): 82.9% to 88.2%] [sensitivity of 80.5% (95% CI: 71.4% to 89.6%) and specificity of 86.2% (95% CI: 83.6% to 88.7%)] for the detection of gastric cancer. The PLS-DA algorithms are further applied prospectively on 10 gastric patients at gastroscopy, achieving the predictive accuracy of 80.0% (60/75) [sensitivity of 90.0% (27/30) and specificity of 73.3% (33/45)] for in vivo diagnosis of gastric cancer. The receiver operating characteristics curves further confirmed the efficacy of Raman endoscopy together with PLS-DA algorithms for in vivo prospective diagnosis of gastric cancer. This work successfully moves biomedical Raman spectroscopic technique into real-time, on-line clinical cancer diagnosis, especially in routine endoscopic diagnostic applications.

Precision of Raman spectroscopy measurements in detection of microcalcifications in breast needle biopsies

Microcalcifications are an early mammographic sign of breast cancer and a target for stereotactic breast needle biopsy. We developed Raman spectroscopy decision algorithms to detect breast microcalcifications, based on fit coefficients (FC) derived by modeling tissue Raman spectra as a linear combination of the Raman spectra of 9 chemical and morphologic components of breast tissue. However, little or no information is available on the precision of such measurements and its effect on the ability of Raman spectroscopy to make predictions for breast microcalcification detection. Here we report the precision, that is, the closeness of agreement between replicate Raman spectral measurements--and the model FC derived from them--obtained ex vivo from fresh breast biopsies from patients undergoing stereotactic breast needle biopsy, using a compact clinical Raman system. The coefficients of variation of the model FC averaged 0.03 for normal breast tissue sites, 0.12 for breast lesions without, and 0.22 for breast lesions with microcalcifications. Imprecision in the FC resulted in diagnostic discordance among replicates only for line-sitters, that is, tissue sites with FC values near the decision line or plane. The source of this imprecision and their implications for the use of Raman spectroscopy for guidance of stereotactic breast biopsies for microcalcifications are also discussed. In summary, we conclude that the precision of Raman spectroscopy measurements in breast tissue obtained using our compact clinical system is more than adequate to make accurate and repeatable predictions of microcalcifications in breast tissue using decision algorithms based on model FC. This provides strong evidence of the potential of Raman spectroscopy guidance of stereotactic breast needle biopsies for microcalcifications.

Fluorescence suppression using wavelength modulated Raman spectroscopy in fiber-probe-based tissue analysis

In the field of biomedical optics, Raman spectroscopy is a powerful tool for probing the chemical composition of biological samples. In particular, fiber Raman probes play a crucial role for in vivo and ex vivo tissue analysis. However, the high-fluorescence background typically contributed by the auto fluorescence from both a tissue sample and the fiber-probe interferes strongly with the relatively weak Raman signal. Here we demonstrate the implementation of wavelength-modulated Raman spectroscopy (WMRS) to suppress the fluorescence background while analyzing tissues using fiber Raman probes. We have observed a significant signal-to-noise ratio enhancement in the Raman bands of bone tissue, which have a relatively high fluorescence background. Implementation of WMRS in fiber-probe-based bone tissue study yielded usable Raman spectra in a relatively short acquisition time (∼30  s), notably without any special sample preparation stage. Finally, we have validated its capability to suppress fluorescence on other tissue samples such as adipose tissue derived from four different species.

Noise and artifact characterization of in vivo Raman spectroscopy skin measurements

In this work principal component analysis (PCA), a multivariate pattern recognition technique, is used to characterize the noise contribution of the experimental apparatus and two commonly used methods for fluorescence removal used in biomedical Raman spectroscopy measurements. These two methods are a fifth degree polynomial fitting and an iterative variation of it commonly known as the Vancouver method. The results show that the noise in Raman spectroscopy measurements is related to the spectral resolution of the measurement equipment, the intrinsic variability of the biological measurements, and the fluorescence removal algorithm used.

Raman 'optical biopsy' of human breast cancer

Raman imaging (RI) is a novel method of medical diagnostics of human breast cancer and has a potential to become a routine optical biopsy. Up to date the present study is the most statistically reliable Raman analysis based on data of normal, benign, and cancerous breast tissues for 146 patients. This paper present the first Raman 'optical biopsy' images of the normal and cancerous breast tissue of the same patient. The results presented here demonstrate the ability of Raman spectroscopy to accurately characterize cancer tissue and distinguish between normal (noncancerous), and cancerous types. The results provide evidence that carotenoids and lipids composition of cancerous breast tissues differs significantly from that of the surrounding noncancerous breast tissue and may be a key factor responsible for mechanisms of carcinogenesis. We have found that fatty acid composition of the cancerous breast tissue is markedly different from that of the surrounding noncancerous breast tissue. The cancerous breast tissue seems to be dominated by the metabolism products of the arachidonic acid - derived cyclic eicosanoids catalyzed by cyclooxygenase, while the noncancerous breast tissue is dominated by monounsaturated oleic acid and its derivatives.

Preclinical evaluation of Raman nanoparticle biodistribution for their potential use in clinical endoscopy imaging

Raman imaging offers unsurpassed sensitivity and multiplexing capabilities. However, its limited depth of light penetration makes direct clinical translation challenging. Therefore, a more suitable way to harness its attributes in a clinical setting would be to couple Raman spectroscopy with endoscopy. The use of an accessory Raman endoscope in conjunction with topically administered tumor-targeting Raman nanoparticles during a routine colonoscopy could offer a new way to sensitively detect dysplastic lesions while circumventing Raman's limited depth of penetration and avoiding systemic toxicity. In this study, the natural biodistribution of gold surface-enhanced Raman scattering (SERS) nanoparticles is evaluated by radiolabeling them with (64) Cu and imaging their localization over time using micropositron emission tomography (PET). Mice are injected either intravenously (IV) or intrarectally (IR) with approximately 100 microcuries (μCi) (3.7 megabecquerel (MBq)) of (64) Cu-SERS nanoparticles and imaged with microPET at various time points post injection. Quantitative biodistribution data are obtained as % injected dose per gram (%ID g(-1)) from each organ, and the results correlate well with the corresponding microPET images, revealing that IV-injected mice have significantly higher uptake (p < 0.05) in the liver (5 h = 8.96% ID g(-1); 24 h = 8.27% ID g(-1)) than IR-injected mice (5 h = 0.09% ID g(-1); 24 h = 0.08% ID g(-1)). IR-injected mice show localized uptake in the large intestine (5 h = 10.37% ID g(-1); 24 h = 0.42% ID g(-1)) with minimal uptake in other organs. Raman imaging of excised tissues correlate well with biodistribution data. These results suggest that the topical application of SERS nanoparticles in the mouse colon appears to minimize their systemic distribution, thus avoiding potential toxicity and supporting the clinical translation of Raman spectroscopy as an endoscopic imaging tool.

Raman spectroscopy and its urological applications

Purpose:

The Raman spectroscopic technology can be utilized for the detection of changes occurring at the molecular level during the pathological transformation of the tissue. The potential of its use in urology is still in its infancy and increasing utility of this technology will transform noninvasive tissue diagnosis. The Nobel laureate, Sir C.V. Raman is credited for the discovery of the principles of Raman spectroscopy.

Materials and Methods:

Applications of Raman spectroscopy in the bladder, renal, prostate, and other urological disorders were gathered from Medline and abstracts from recent international urological meetings. Current status and future directions of Raman spectroscopy in urology were also reviewed.

Results:

Raman spectroscopic technology is used to interrogate biological tissues. The potential use of this technology in urology has shown encouraging results in the in vitro diagnosis and grading of cancers of the bladder and the prostate. Raman microprobes have been used for the characterization and identification of renal lithiasis. Technology may be available for the urologists to determine the margin status intraoperatively during partial nephrectomy and radical prostatectomy. The future would see the development of optical fiber probes to incorporate them into catheters, endoscopes, and laparoscopes that will enable the urologist to obtain information during the operation.

Conclusion:

Raman spectroscopy is an exciting tool for real-time diagnosis and in vivo evaluation of living tissue. The potential applications of Raman spectroscopy may herald a new future in the management of various malignant, premalignant, and other benign conditions in urology.