Real-time Raman spectroscopy for in vivo skin cancer diagnosis

In vivo assessment of optical properties of melanocytic skin lesions and differentiation of melanoma from non-malignant lesions by high-definition optical coherence tomography

One of the most challenging problems in clinical dermatology is the early detection of melanoma. Reflectance confocal microscopy (RCM) is an added tool to dermoscopy improving considerably diagnostic accuracy. However, diagnosis strongly depends on the experience of physicians. High-definition optical coherence tomography (HD-OCT) appears to offer additional structural and cellular information on melanocytic lesions complementary to that of RCM. However, the diagnostic potential of HD-OCT seems to be not high enough for ruling out the diagnosis of melanoma if based on morphology analysis. The aim of this paper is first to quantify in vivo optical properties such as light attenuation in melanocytic lesions by HD-OCT. The second objective is to determine the best critical value of these optical properties for melanoma diagnosis. The technique of semi-log plot whereby an exponential function becomes a straight line has been implemented on HD-OCT signals coming from four successive skin layers (epidermis, upper papillary dermis, deeper papillary dermis and superficial reticular dermis). This permitted the HD-OCT in vivo measurement of skin entrance signal (SES), relative attenuation factor normalized for the skin entrance signal (µ_raf1) and half value layer (z_1/2). The diagnostic accuracy of HD-OCT for melanoma detection based on the optical properties, µ_raf1, SES and z_1/2 was high (95.6, 82.2 and 88.9 %, respectively). High negative predictive values could be found for these optical properties (96.7, 89.3 and 96.3 %, respectively) compared to morphologic assessment alone (89.9 %), reducing the risk of mistreating a malignant lesion to a more acceptable level (3.3 % instead of 11.1 %). HD-OCT seems to enable the combination of in vivo morphological analysis of cellular and 3-D micro-architectural structures with in vivo analysis of optical properties of tissue scatterers in melanocytic lesions. In vivo HD-OCT analysis of optical properties permits melanoma diagnosis with higher accuracy than in vivo HD-OCT analysis of morphology alone.

Raman spectroscopy for cancer diagnosis: how far have we come?

Raman spectroscopy is increasingly investigated for cancer diagnosis. As the potential of the technique is explored and realized, it is slowly making its way into clinics. There are more reports in recent years showing promise that it can help clinicians for cancer diagnosis. However, a number of challenges remain to be overcome, especially in vivo cancer diagnosis. In this article, the recent progress of the technique toward clinical cancer diagnosis is discussed from a critical perspective.

Label-free blood serum detection by using surface-enhanced Raman spectroscopy and support vector machine for the preoperative diagnosis of parotid gland tumors

BACKGROUND

It is difficult for the parotid gland neoplasms to make an accurate preoperative diagnosis due to the restriction of biopsy in the parotid gland neoplasms. The aim of this study is to apply the surface-enhanced Raman spectroscopy (SERS) method for the blood serum biochemical detection and use the support vector machine for the analysis in order to develop a simple but accurate blood serum detection for preoperative diagnosis of the parotid gland neoplasms.

METHODS

The blood serums were collected from four groups: the patients with pleomorphic adenoma, the patients with Warthin's tumor, the patients with mucoepidermoid carcinoma and the volunteers without parotid gland neoplasms. Au nanoparticles (Au NPs) were mixed with the blood serum as the SERS active nanosensor to enhance the Raman scattering signals produced by the various biochemical materials and high quality SERS spectrum were obtained by using the Raman microscope system. Then the support vector machine was utilized to analyze the differences of the SERS spectrum from the blood serum of different groups and established a diagnostic model to discriminate the different groups.

RESULTS

It was demonstrated that there were different intensities of SERS peaks assigned to various biochemical changes in the blood serum between the parotid gland tumor groups and normal control group. Compared with the SERS spectra of the normal serums, the intensities of peaks assigned to nucleic acids and proteins increased in the SERS spectra of the parotid gland tumor serums, which manifested the differences of the biochemical metabolites in the serum from the patients with parotid gland tumors. When the leave-one-sample-out method was used, support vector machine (SVM) played an outstanding performance in the classification of the SERS spectra with the high accuracy (84.1 % ~ 88.3 %), sensitivity (82.2 % ~ 97.4 %) and specificity (73.7 % ~ 86.7 %). Though the accuracy, sensitivity and specificity decreased in the leave-one-patient-out cross validation, the mucoepidermoid carcinoma was still easier to diagnose than other tumors.

DISCUSSION

The specific molecular differences of parotid gland tumors and normal serums were significantly demonstrated through the comparison between the various SERS spectra.But compared with the serum SERS spectra reported in the other studies, some differences exist between the spectra in this study and the ones reported in the lietratures. These differences may result from the various nano-particles, the different preparation of serum and equipment parameters, and we could need a further research to find an exact explanation.Based on the SERS spectra of the serum samples, SVM have shown a giant potential to diagnose the parotid gland tumors in our preliminary study. However, different cross validaiton methods could effect the accuracy and a further study involing a great number of samples should be needed.

CONCLUSIONS

This exploratory research demonstrated the great potential of SERS combined with SVM into a non-invasive clinical diagnostic method for preoperative diagnosis of parotid gland tumors. And the internal relation between the spectra and patients should be established in the further study.

Discrimination of liver malignancies with 1064 nm dispersive Raman spectroscopy

Raman spectroscopy has been widely demonstrated for tissue characterization and disease discrimination, however current implementations with either 785 or 830 nm near-infrared (NIR) excitation have been ineffectual in tissues with intense autofluorescence such as the liver. Here we report the use of a dispersive 1064 nm Raman system using a low-noise Indium-Gallium-Arsenide (InGaAs) array to discriminate highly autofluorescent bulk tissue ex vivo specimens from healthy liver, adenocarcinoma, and hepatocellular carcinoma (N = 5 per group). The resulting spectra have been combined with a multivariate discrimination algorithm, sparse multinomial logistic regression (SMLR), to predict class membership of healthy and diseased tissues, and spectral bands selected for robust classification have been extracted. A quantitative metric called feature importance is defined based on classification outputs and is used to guide the association of spectral features with biological indicators of healthy and diseased liver tissue. Spectral bands with high feature importance for healthy and liver tumor specimens include retinol, heme, biliverdin, or quinones (1595 cm(-1)); lactic acid (838 cm(-1)); collagen (873 cm(-1)); and nucleic acids (1485 cm(-1)). Classification performance in both binary (normal versus tumor, 100% sensitivity and 89% specificity) and three-group cases (classification accuracy: normal 89%, adenocarcinoma 74%, hepatocellular carcinoma 64%) indicates the potential for accurately separating healthy and cancerous tissues and suggests implications for utilizing Raman techniques during surgical guidance in liver resection.

On the horizon: Optical imaging for cutaneous squamous cell carcinoma

BACKGROUND

Surgical resection with negative margins remains the standard of care for high-risk cutaneous squamous cell carcinoma (SCC). However, surgical management is often limited by poor intraoperative tumor visualization and inability to detect occult nodal metastasis. The inability to intraoperatively detect microscopic disease can lead to additional surgery, tumor recurrence, and decreased survival.

METHODS

A comprehensive literature review was conducted to identify studies incorporating optical imaging technology in the management of cutaneous SCC (January 1, 2000-December 1, 2014).

RESULTS

Several innovative optical imaging techniques, Raman spectroscopy, confocal microscopy, and fluorescence imaging, have been developed for intraoperative surgical guidance. Fifty-seven studies review the ability of these techniques to improve cutaneous SCC localization at the gross and microscopic level.

CONCLUSION

Significant advances have been achieved with real-time optical imaging strategies for intraoperative cutaneous SCC margin assessment and tumor detection. Optical imaging holds promise in improving the percentage of negative surgical margins and in the early detection of micrometastatic disease. © 2015 Wiley Periodicals, Inc. Head Neck 38: E2204-E2213, 2016.

Raman spectroscopy for medical diagnostics--From in-vitro biofluid assays to in-vivo cancer detection

Raman spectroscopy is an optical technique based on inelastic scattering of light by vibrating molecules and can provide chemical fingerprints of cells, tissues or biofluids. The high chemical specificity, minimal or lack of sample preparation and the ability to use advanced optical technologies in the visible or near-infrared spectral range (lasers, microscopes, fibre-optics) have recently led to an increase in medical diagnostic applications of Raman spectroscopy. The key hypothesis underpinning this field is that molecular changes in cells, tissues or biofluids, that are either the cause or the effect of diseases, can be detected and quantified by Raman spectroscopy. Furthermore, multivariate calibration and classification models based on Raman spectra can be developed on large "training" datasets and used subsequently on samples from new patients to obtain quantitative and objective diagnosis. Historically, spontaneous Raman spectroscopy has been known as a low signal technique requiring relatively long acquisition times. Nevertheless, new strategies have been developed recently to overcome these issues: non-linear optical effects and metallic nanoparticles can be used to enhance the Raman signals, optimised fibre-optic Raman probes can be used for real-time in-vivo single-point measurements, while multimodal integration with other optical techniques can guide the Raman measurements to increase the acquisition speed and spatial accuracy of diagnosis. These recent efforts have advanced Raman spectroscopy to the point where the diagnostic accuracy and speed are compatible with clinical use. This paper reviews the main Raman spectroscopy techniques used in medical diagnostics and provides an overview of various applications.

Applications of Raman spectroscopy in skin research--From skin physiology and diagnosis up to risk assessment and dermal drug delivery

In the field of skin research, confocal Raman microscopy is an upcoming analytical technique. Substantial technical progress in design and performance of the individual setup components like detectors and lasers as well as the combination with confocal microscopy enables chemically selective and non-destructive sample analysis with high spatial resolution in three dimensions. Due to these advantages, the technique bears tremendous potential for diverse skin applications ranging from the analysis of physiological component distribution in skin tissue and the diagnosis of pathological states up to biopharmaceutical investigations such as drug penetration kinetics within the different tissue layers. This review provides a comprehensive introduction about the basic principles of Raman microscopy highlighting the advantages and considering the limitations of the technique for skin applications. Subsequently, an overview about skin research studies applying Raman spectroscopy is given comprising various in vitro as well as in vivo implementations. Furthermore, the future perspective and potential of Raman microscopy in the field of skin research are discussed.

In vivo study for the discrimination of cancerous and normal skin using fibre probe-based Raman spectroscopy

Raman spectroscopy has proved its capability as an objective, non-invasive tool for the detection of various melanoma and non-melanoma skin cancers (NMSC) in a number of studies. Most publications are based on a Raman microspectroscopic ex vivo approach. In this in vivo clinical evaluation, we apply Raman spectroscopy using a fibre-coupled probe that allows access to a multitude of affected body sites. The probe design is optimized for epithelial sensitivity, whereby a large part of the detected signal originates from within the epidermal layer's depth down to the basal membrane where early stages of skin cancer develop. Data analysis was performed on measurements of 104 subjects scheduled for excision of lesions suspected of being malignant melanoma (MM) (n = 36), basal cell carcinoma (BCC) (n = 39) and squamous cell carcinoma (SCC) (n = 29). NMSC were discriminated from normal skin with a balanced accuracy of 73% (BCC) and 85% (SCC) using partial least squares discriminant analysis (PLS-DA). Discriminating MM and pigmented nevi (PN) resulted in a balanced accuracy of 91%. These results lie within the range of comparable in vivo studies and the accuracies achieved by trained dermatologists using dermoscopy. Discrimination proved to be unsuccessful between cancerous lesions and suspicious lesions that had been histopathologically verified as benign by dermoscopy.

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.

Aptamer-conjugated theranostic hybrid graphene oxide with highly selective biosensing and combined therapy capability

Cancer is a life-threatening disease, which is rapidly becoming a global pandemic. Driven by this need, here we report for the first time an aptamer-conjugated theranostic magnetic hybrid graphene oxide-based assay for highly sensitive tumor cell detection from blood samples with combined therapy capability. AGE-aptamer-conjugated theranostic magnetic nanoparticle-attached hybrid graphene oxide was developed for highly selective detection of tumor cells from infected blood samples. Experimental data indicate that hybrid graphene can be used as a multicolor luminescence platform for selective imaging of G361 human malignant melanoma cancer cells. The reported results have also shown that indocyanine green (ICG)-bound AGE-aptamer-attached hybrid graphene oxide is capable of combined synergistic photothermal and photodynamic treatment of cancer. Targeted combined therapeutic treatment using 785 nm near-infrared (NIR) light indicates that the multimodal therapeutic treatment is highly effective for malignant melanoma cancer therapy. The reported data show that this aptamer-conjugated theranostic graphene oxide-based assay has exciting potential for improving cancer diagnosis and treatment.

Characterization and noninvasive diagnosis of bladder cancer with serum surface enhanced Raman spectroscopy and genetic algorithms

This study aims to characterize and classify serum surface-enhanced Raman spectroscopy (SERS) spectra between bladder cancer patients and normal volunteers by genetic algorithms (GAs) combined with linear discriminate analysis (LDA). Two group serum SERS spectra excited with nanoparticles are collected from healthy volunteers (n = 36) and bladder cancer patients (n = 55). Six diagnostic Raman bands in the regions of 481-486, 682-687, 1018-1034, 1313-1323, 1450-1459 and 1582-1587 cm(-1) related to proteins, nucleic acids and lipids are picked out with the GAs and LDA. By the diagnostic models built with the identified six Raman bands, the improved diagnostic sensitivity of 90.9% and specificity of 100% were acquired for classifying bladder cancer patients from normal serum SERS spectra. The results are superior to the sensitivity of 74.6% and specificity of 97.2% obtained with principal component analysis by the same serum SERS spectra dataset. Receiver operating characteristic (ROC) curves further confirmed the efficiency of diagnostic algorithm based on GA-LDA technique. This exploratory work demonstrates that the serum SERS associated with GA-LDA technique has enormous potential to characterize and non-invasively detect bladder cancer through peripheral blood.

Advantages and limitations of Raman spectroscopy for molecular diagnostics: an update

Over the last decade, Raman spectroscopy has gained more and more interest in research as well as in clinical laboratories. As a vibrational spectroscopy technique, it is complementary to the also well-established infrared spectroscopy. Through specific spectral patterns, substances can be identified and molecular changes can be observed with high specificity. Because of a high spatial resolution due to an excitation wavelength in the visible and near-infrared range, Raman spectroscopy combined with microscopy is very powerful for imaging biological samples. Individual cells can be imaged on the subcellular level. In vivo tissue examinations are becoming increasingly important for clinical applications. In this review, we present currently ongoing research in different fields of medical diagnostics involving linear Raman spectroscopy and imaging. We give a wide overview over applications for the detection of atherosclerosis, cancer, inflammatory diseases and pharmacology, with a focus on developments over the past 5 years. Conclusions drawn from Raman spectroscopy are often validated by standard methods, for example, histopathology or PCR. The future potential of Raman spectroscopy and its limitations are discussed in consideration of other non-linear Raman techniques.

Comparative analysis of combined spectral and optical tomography methods for detection of skin and lung cancers

Malignant skin tumors of different types were studied in vivo using optical coherence tomography (OCT), backscattering (BS), and Raman spectroscopy (RS). A multimodal method is proposed for early cancer detection based on complex analysis of OCT images by their relative alteration of scattered-radiation spectral intensities between malignant and healthy tissues. An increase in average accuracy of diagnosis was observed for a variety of cancer types (9% sensitivity, 8% specificity) by a multimodal RS-BS-OCT system in comparison with any of the three methods used separately. The proposed approach equalizes the processing rates for all methods and allows for simultaneous imaging and classification of tumors.

Characteristic wavenumbers of Raman spectra reveal the molecular mechanisms of oral leukoplakia and can help to improve the performance of diagnostic models

An effective method for diagnosing various grades of oral leukoplakia with dysplasia.

Perturbation factors in the clinical handling of a fiber-coupled Raman probe for cutaneous in vivo diagnostic Raman spectroscopy

The application of fiber-coupled Raman probes for the discrimination of cancerous and normal skin has the advantage of a non-invasive in vivo application, easy clinical handling, and access to the majority of body sites, which would otherwise be limited by stationary Raman microscopes. Nevertheless, including optical fibers and miniaturizing optical components, as well as measuring in vivo, involves the sensibility to external perturbation factors that could introduce artifacts to the acquired Raman spectra and thereby potentially reduce classification performance. In this study, typical perturbation factors of Raman measurements with a Raman fiber probe, optimized for clinical in vivo discrimination of skin cancer, were investigated experimentally. Measurements were performed under standardized conditions in clinical settings in vivo on human skin, as well as ex vivo on porcine ears. Raman spectra were analyzed in the fingerprint region between 1150 and 1730 cm(-1) using principal component analysis. The largest artifacts in the Raman spectra were found in measurements performed under the influence of strong ambient light conditions as well as after miscellaneous pre-treatments to the skin, such as use of a permanent marker or a sunscreen. Minor influences were also found in measurements using H2O immersion and when varying the probe contact force. The effect of reasonable variation of the fiber-bending radius was found to be of negligible impact. The influence of measurements on hairy or sun-exposed body sites, as well as inter-subject variation, was also investigated. The presented results may serve as a guide to avoid negative effects during the process of data acquisition and so avoid misclassification in tumor discrimination.

In vivo imaging of the tumor and its associated microenvironment using combined CARS / 2-photon microscopy

The use of confocal and multi-photon microscopy for intra-vital cancer imaging has impacted on our understanding of cancer cell behavior and interaction with the surrounding tumor microenvironment in vivo. However, many studies to-date rely on the use fluorescent dyes or genetically encoded probes that enable visualization of a structure or cell population of interest, but do not illuminate the complexity of the surrounding tumor microenvironment. Here, we show that multi-modal microscopy combining 2-photon fluorescence with CARS can begin to address this deficit, enabling detailed imaging of the tumor niche without the need for additional labeling. This can be performed on live tumor-bearing animals through optical observation windows, permitting real-time and longitudinal imaging of dynamic processes within the tumor niche.

Vision 20/20: the role of Raman spectroscopy in early stage cancer detection and feasibility for application in radiation therapy response assessment

Raman spectroscopy is an optical technique capable of identifying chemical constituents of a sample by their unique set of molecular vibrations. Research on the applicability of Raman spectroscopy in the differentiation of cancerous versus normal tissues has been ongoing for many years, and has yielded successful results in the context of prostate, breast, brain, skin, and head and neck cancers as well as pediatric tumors. Recently, much effort has been invested on developing noninvasive "Raman" probes to provide real-time diagnosis of potentially cancerous tumors. In this regard, it is feasible that the Raman technique might one day be used to provide rapid, minimally invasive real-time diagnosis of tumors in patients. Raman spectroscopy is relatively new to the field of radiation therapy. Recent work involving cell lines has shown that the Raman technique is able to identify proteins and other markers affected by radiation therapy. Although this work is preliminary, one could ask whether or not the Raman technique might be used to identify molecular markers that predict radiation response. This paper provides a brief review of Raman spectroscopic investigations in cancer detection, benefits and limitations of this method, advances in instrument development, and also preliminary studies related to the application of this technology in radiation therapy response assessment.

Rapid detection of nasopharyngeal cancer using Raman spectroscopy and multivariate statistical analysis

Optical spectroscopic techniques, including Raman spectroscopy, have shown promise for in vivo cancer diagnostics in a variety of organs. In this study, the potential use of a home-made Raman spectral system with a millimeter order excitation laser spot size combined with a multivariate statistical analysis for the rapid detection and discrimination of nasopharyngeal cancer from normal nasopharyngeal tissue was evaluated. Raman scattering signals were acquired from 16 normal and 32 nasopharyngeal carcinoma tissue samples. Linear discriminant analysis (LDA) based on principal component analysis (PCA) and partial least squares (PLS) were employed to generate diagnostic algorithms for the classification of different nasopharyngeal tissue types. Spectral differences in Raman spectra between the two types of tissues were revealed; the normalized intensities of Raman peaks at 1,001, 1,207 and 1,658 cm^-1 were more intense for nasopharyngeal carcinoma tissue compared to normal tissue, while Raman bands at 848, 936 and 1,446 cm^-1 were stronger in normal nasopharyngeal samples. The PCA-LDA algorithm together with leave-one-out cross validation yields a diagnostic sensitivity of 81% and a specificity of 87%, while the PLS method coupled with subwindow permutation analysis improves the diagnostic sensitivity and specificity to 85 and 88%, respectively. Therefore, Raman spectroscopy combined with PCA-LDA/PLS demonstrated good potential for improving the clinical diagnosis of nasopharyngeal cancers.

Spectroscopic approach for dynamic bioanalyte tracking with minimal concentration information

Vibrational spectroscopy has emerged as a promising tool for non-invasive, multiplexed measurement of blood constituents - an outstanding problem in biophotonics. Here, we propose a novel analytical framework that enables spectroscopy-based longitudinal tracking of chemical concentration without necessitating extensive a priori concentration information. The principal idea is to employ a concentration space transformation acquired from the spectral information, where these estimates are used together with the concentration profiles generated from the system kinetic model. Using blood glucose monitoring by Raman spectroscopy as an illustrative example, we demonstrate the efficacy of the proposed approach as compared to conventional calibration methods. Specifically, our approach exhibits a 35% reduction in error over partial least squares regression when applied to a dataset acquired from human subjects undergoing glucose tolerance tests. This method offers a new route at screening gestational diabetes and opens doors for continuous process monitoring without sample perturbation at intermediate time points.

Identification and characterization of colorectal cancer using Raman spectroscopy and feature selection techniques

This study aims to detect colorectal cancer with near-infrared Raman spectroscopy and feature selection techniques. A total of 306 Raman spectra of colorectal cancer tissues and normal tissues are acquired from 44 colorectal cancer patients. Five diagnostically important Raman bands in the regions of 815-830, 935-945, 1131-1141, 1447-1457 and 1665-1675 cm(-1) related to proteins, nucleic acids and lipids of tissues are identified with the ant colony optimization (ACO) and support vector machine (SVM). The diagnostic models built with the identified Raman bands provide a diagnostic accuracy of 93.2% for identifying colorectal cancer from normal Raman spectroscopy. The study demonstrates that the Raman spectroscopy associated with ACO-SVM diagnostic algorithms has great potential to characterize and diagnose colorectal cancer.

Clinical performance of the Nevisense system in cutaneous melanoma detection: an international, multicentre, prospective and blinded clinical trial on efficacy and safety

BACKGROUND

Even though progress has been made, the detection of melanoma still poses a challenge. In light of this situation, the Nevisense electrical impedance spectroscopy (EIS) system (SciBase AB, Stockholm, Sweden) was designed and shown to have the potential to be used as an adjunct diagnostic tool for melanoma detection.

OBJECTIVES

To assess the effectiveness and safety of the Nevisense system in the distinction of benign lesions of the skin from melanoma with electrical impedance spectroscopy.

METHODS

This multicentre, prospective, and blinded clinical study was conducted at five American and 17 European investigational sites. All eligible skin lesions in the study were examined with the EIS-based Nevisense system, photographed, removed by excisional biopsy and subjected to histopathological evaluation. A postprocedure clinical follow-up was conducted at 7 ± 3 days from the initial measurement. A total of 1951 patients with 2416 lesions were enrolled into the study; 1943 lesions were eligible and evaluable for the primary efficacy end point, including 265 melanomas - 112 in situ and 153 invasive melanomas with a median Breslow thickness of 0·57 mm [48 basal cell carcinomas (BCCs) and seven squamous cell carcinomas (SCCs)].

RESULTS

The observed sensitivity of Nevisense was 96·6% (256 of 265 melanomas) with an exact one-sided 95% lower confidence bound estimated at 94·2% and an observed specificity of 34·4%, and an exact two-sided 95% confidence bound estimated at 32·0-36·9%. The positive and negative predictive values of Nevisense were 21·1% and 98·2%, respectively. The observed sensitivity for nonmelanoma skin cancer was 100% (55 of 48 BCCs and seven SCCs) with an exact two-sided 95% confidence bound estimated at 93·5-100·0%.

CONCLUSIONS

Nevisense is an accurate and safe device to support clinicians in the detection of cutaneous melanoma.

Anatomy of noise in quantitative biological Raman spectroscopy

Raman spectroscopy is a fundamental form of molecular spectroscopy that is widely used to investigate structures and properties of molecules using their vibrational transitions. It relies on inelastic scattering of monochromatic laser light irradiating the specimen. After appropriate filtering the scattered light is dispersed onto a detector to determine the shift from the excitation wavelength, which appears in the form of characteristic spectral patterns. The technique can investigate biological samples and provide real-time diagnosis of diseases. However, despite its intrinsic advantages of specificity and minimal perturbation, the Raman scattered light is typically very weak and limits applications of Raman spectroscopy due to measurement (im)precision, driven by inherent noise in the acquired spectra. In this article, we review the principal noise sources that impact quantitative biological Raman spectroscopy. Further, we discuss how such noise effects can be reduced by innovative changes in the constructed Raman system and appropriate signal processing methods.

Monte Carlo simulation of in vivo Raman spectral measurements of human skin with a multi-layered tissue optical model

Raman photon generation inside human skin and escaping to skin surface were modeled in an eight-layered skin optical model. Intrinsic Raman spectra of different skin layers were determined by microscopy measurements of excised skin tissue sections. Monte Carlo simulation was used to study the excitation light distribution and intrinsic Raman signal distortion caused by tissue reabsorption and scattering during in vivo measurements. The simulation results demonstrated how different skin layers contributed to the observed in vivo Raman spectrum. Using the strongest Raman peak at 1445 cm(-1) as an example, the simulation suggested that the integrated contributions of the stratum corneum layer is 1.3%, the epidermis layer 28%, the dermis layer 70%, and the subcutaneous fat layer 1.1%. Reasonably good matching between the calculated spectrum and the measured in vivo Raman spectra was achieved, thus demonstrated great utility of our modeling method and approaches for help understanding the clinical measurements.

Use of a mechanical iris-based fiber optic probe for spatially offset Raman spectroscopy

We demonstrated a mechanical iris-based fiber optic probe with adjustable spatial offsets for spatially offset Raman spectroscopy (SORS). In the fiber probe, the excitation fiber was fixed at the center of the iris, and the collection fibers were movable with blades of the iris. Moreover, we studied the gap effect between the probe and the sample and demonstrated this fiber optic probe can be used as a platform for surface-enhanced SORS applications. This fiber probe design could potentially provide a design-efficient and cost-effective solution for various Raman applications.

Imaging of ex vivo nonmelanoma skin cancers in the optical and terahertz spectral regions optical and terahertz skin cancers imaging

We tested the hypothesis that polarization sensitive optical and terahertz imaging may be combined for accurate nonmelanoma skin cancer (NMSC) delineation. Nine NMSC specimens were imaged. 513 μm and 440 nm wavelengths were used for terahertz and optical imaging, respectively. Histopathology was processed for evaluation. Terahertz reflectance of NMSC was quantified. Our results demonstrate that cross-polarized terahertz images correctly identified location of the tumours, whereas cross-polarized and polarization difference optical images accurately presented morphological features. Cross-polarized terahertz images exhibited lower reflectivity values in cancer as compared to normal tissue. Combination of optical and terahertz imaging shows promise for intraoperative delineation of NMSC.

1064 nm dispersive Raman spectroscopy of tissues with strong near-infrared autofluorescence

Raman spectroscopy is an established technique for molecularly specific characterization of tissues. However, even with near-infrared (NIR) excitation, some tissues possess background autofluorescence, which can overwhelm Raman scattering. Here, we report collection of spectra from tissues with strong autofluorescence using a 1064 nm system with a high-throughput dispersive spectrometer and deep-cooled InGaAs array. Spectra collected at 1064 nm were compared with those collected at 785 nm in specimens from human breast, liver, and kidney. The results demonstrate superior performance at 1064 nm in the liver and kidney, where NIR autofluorescence is intense. The results indicate the feasibility of new biomedical applications for Raman spectroscopy at 1064 nm in tissues with strong autofluorescence.

Multifunctional hybrid graphene oxide for label-free detection of malignant melanoma from infected blood

The development of multifunctional graphene oxide for label-free detection of malignant melanoma from infected blood is reported.

Combined fluorescence-Raman spectroscopic setup for the diagnosis of melanocytic lesions

Two optical fibre-based probes for spectroscopic measurements on human tissues were designed and developed. The two probes combine fluorescence and Raman spectroscopy in a multimodal approach. The fluorescence excitation was provided by two laser diodes emitting in the UV (378 nm) and in the visible (445 nm) range, while a third source in the NIR (785 nm) was used for Raman. The device was tested on freshly excised human skin biopsies clinically diagnosed as malignant melanoma, melanocytic nevus, or healthy skin. Discrimination of lesions based on their fluorescence and Raman spectra showed good correlation with the subsequent histological examination.

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.

Raman and coherent anti-Stokes Raman scattering microscopy studies of changes in lipid content and composition in hormone-treated breast and prostate cancer cells

Increasing interest in the role of lipids in cancer cell proliferation and resistance to drug therapies has motivated the need to develop better tools for cellular lipid analysis. Quantification of lipids in cells is typically done by destructive chromatography protocols that do not provide spatial information on lipid distribution and prevent dynamic live cell studies. Methods that allow the analysis of lipid content in live cells are therefore of great importance. Using micro-Raman spectroscopy and coherent anti-Stokes Raman scattering (CARS) microscopy, we generated a lipid profile for breast (T47D, MDA-MB-231) and prostate (LNCaP, PC3) cancer cells upon exposure to medroxyprogesterone acetate (MPA) and synthetic androgen R1881. Combining Raman spectra with CARS imaging, we can study the process of hormone-mediated lipogenesis. Our results show that hormone-treated cancer cells T47D and LNCaP have an increased number and size of intracellular lipid droplets and higher degree of saturation than untreated cells. MDA-MB-231 and PC3 cancer cells showed no significant changes upon treatment. Principal component analysis with linear discriminant analysis of the Raman spectra was able to differentiate between cancer cells that were treated with MPA, R1881, and untreated.

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.

Antioxidant induces DNA damage, cell death and mutagenicity in human lung and skin normal cells

Clinical trials have shown that antioxidant supplementation increased the risk of lung and skin cancers, but the underlying molecular mechanism is unknown. Here, we show that epigallocatechin gallate (EGCG) as an exemplary antioxidant induced significant death and DNA damage in human lung and skin normal cells through a reductive mechanism. Our results show direct evidence of reductive DNA damage in the cells. We found that EGCG was much more toxic against normal cells than H₂O₂ and cisplatin as toxic and cancer-causing agents, while EGCG at low concentrations (≤100 μM) increased slightly the lung cancer cell viability. EGCG induced DNA double-strand breaks and apoptosis in normal cells and enhanced the mutation frequency. These results provide a compelling explanation for the clinical results and unravel a new reductive damaging mechanism in cellular processes. This study therefore provides a fresh understanding of aging and diseases, and may lead to effective prevention and therapies.

Deeper understanding of biological tissue: quantitative correlation of MALDI-TOF and Raman imaging

In order to achieve a comprehensive description of biological tissue, spectral information about proteins, lipids, nucleic acids, and other biochemical components need to be obtained concurrently. Different analytical techniques may be combined to record complementary information of the same sample. Established techniques, which can be utilized to elucidate the biochemistry of tissue samples are, for instance, MALDI-TOF-MS and Raman microscopic imaging. With this contribution, we combine these two techniques for the first time. The combination of both techniques allows the utilization and interpretation of complementary information (i.e., the information about the protein composition derived from the Raman spectra with data of the lipids analyzed by the MALDI-TOF measurements). Furthermore, we demonstrate how spectral information from MALDI-TOF experiments can be utilized to interpret Raman spectra.

Raman spectroscopy in nanomedicine: current status and future perspective

Raman spectroscopy is a branch of vibration spectroscopy that is capable of probing the chemical composition of materials. Recent advances in Raman microscopy have significantly added to the range of applications, which now extend from medical diagnostics to exploring the interfaces between biological organisms and nanomaterials. In this review, Raman is introduced in a general context, highlighting some of the areas in which the technique has been successful in the past, as well as some of the potential benefits it offers over other analytical modalities. The subset of Raman techniques that specifically probe the nanoscale, namely surface- and tip-enhanced Raman spectroscopy, will be described and specific applications relevant to nanomedical applications will be reviewed. Progress in the use of traditional label-free Raman for investigation of nanoscale interactions will be described, and recent developments in coherent anti-Stokes Raman scattering will be explored, particularly its applications to biomedical and nanomedical fields.

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.

Estimating soft tissue thickness from light-tissue interactions--a simulation study

Immobilization and marker-based motion tracking in radiation therapy often cause decreased patient comfort. However, the more comfortable alternative of optical surface tracking is highly inaccurate due to missing point-to-point correspondences between subsequent point clouds as well as elastic deformation of soft tissue. In this study, we present a proof of concept for measuring subcutaneous features with a laser scanner setup focusing on the skin thickness as additional input for high accuracy optical surface tracking. Using Monte-Carlo simulations for multi-layered tissue, we show that informative features can be extracted from the simulated tissue reflection by integrating intensities within concentric ROIs around the laser spot center. Training a regression model with a simulated data set identifies patterns that allow for predicting skin thickness with a root mean square error of down to 18 µm. Different approaches to compensate for varying observation angles were shown to yield errors still below 90 µm. Finally, this initial study provides a very promising proof of concept and encourages research towards a practical prototype.

Optical techniques for the noninvasive diagnosis of skin cancer

PURPOSE

The aim of this paper is to provide an overview of the most investigated optical diagnostic techniques: optical coherence tomography, fluorescence spectrometry, reflectance spectrometry, Raman spectroscopy, and confocal microscopy.

METHODS

A search of three databases was conducted using specific keywords and explicit inclusion and exclusion criteria for the analysis of the performances of these techniques in the pre- and postoperative diagnosis of skin cancers.

RESULTS

Optical coherence tomography has shown promising results in the assessment of deep margins of skin tumors and inflammatory skin diseases, but differentiating premalignant from malignant lesions proved to be less effective. Fluorescence spectroscopy proved to be effective in revealing the biochemical composition of tissue; early detection of malignant melanoma was reliable only with stepwise two-photon excitation of melanin, while tumoral margin assessment and differential diagnosis between malignant and non-malignant lesions showed some conflicting results. Characterization of the structural properties of tissue can be made using diffuse reflectance spectrometry, and the values of the specificity and sensitivity of this method are ranging between 72-92 % and 64-92 %, respectively. Raman spectroscopy proved to have better results both in carcinoma and melanoma diagnosis with sensitivities and specificities above 90 % and high above 50 %, respectively. Confocal microscopy is the closest technique to pathological examination and has gained the most clinical acceptance, despite the need for a standardization of the interpretation algorithm.

CONCLUSIONS

In conclusion, these optical techniques proved to be effective in the diagnosis of skin cancer, but further studies are needed in finding the appropriate method or combination of methods that can have wide clinical applications.