Intraoperative spectroscopic evaluation of sentinel lymph nodes in breast cancer surgery

BACKGROUND AND OBJECTIVES

Sentinel lymph node (SLN) biopsy is a standard procedure for patients with breast cancer and normal axilla on imaging. Positive SLNs on histological examination can lead to a subsequent surgery for axillary lymph node clearance (ALNC). Here we report a non-destructive technique based on autofluorescence (AF) imaging and Raman spectroscopy for intra-operative assessment of SLNs excised in breast cancer surgery.

METHODS

A microscope integrating AF imaging and Raman spectroscopy modules was built to allow scanning of lymph node biopsy samples. During AF-Raman measurements, AF imaging determined optimal sampling locations for Raman spectroscopy measurements. After optimisation of the AF image analysis and training of classification models based on data from 85 samples, the AF-Raman technique was tested on an independent set of 81 lymph nodes comprising 58 fixed and 23 fresh specimens. The sensitivity and specificity of AF-Raman were calculated using post-operative histology as a standard of reference.

RESULTS

The independent test set contained 66 negative lymph nodes and 15 positive lymph nodes according to the reference standard, collected from 78 patients. For this set of specimens, the area under the receiver operating characteristic (ROC) curve for the AF-Raman technique was 0.93 [0.83-0.98]. AF-Raman was then operated in a regime that maximised detection specificity, producing a 94% detection accuracy: 80% sensitivity and 97% specificity. The main confounders for SLN metastasis were areas rich in histiocytes clusters, for which only few Raman spectra had been included in the training dataset.

DISCUSSION

This preliminary study indicates that with further development and extension of the training dataset by inclusion of additional Raman spectra of histiocytes clusters and capsule, the AF-Raman may become a promising technique for intra-operative assessment of SLNs. Intra-operative detection of positive biopsies could avoid second surgery for axillary clearance.

Distinct spectral signatures unfold ECM stiffness-triggered biochemical changes in breast cancer cells

Cancer progression often accompanies the stiffening of extracellular matrix (ECM) in and around the tumor, owing to extra deposition and cross-linking of collagen. Stiff ECM has been linked with poor prognosis and is known to fuel invasion and metastasis, notably in breast cancer. However, the underlying biochemical or metabolic changes and the cognate molecular signatures remain elusive. Here, we explored Raman spectroscopy to unveil the spectral fingerprints of breast cancer cells in response to extracellular mechanical cues. Using stiffness-tuneable hydrogels, we showed that cells grown on stiff ECM displayed morphological changes with high proliferation. We further demonstrated that Raman Spectroscopy, a label-free and non-invasive technique, could provide comprehensive information about the biochemical environment of breast cancer cells in response to varying ECM stiffness. Raman spectroscopic analysis classified the cells into distinct clusters based on principal component-based linear discriminant analysis (PC-LDA). Multivariate curve resolution-alternating least squares (MCR-ALS) analysis indicated that cells cultured on stiff ECM exhibited elevated nucleic acid content and lesser lipids. Interestingly, increased intensity of Raman bands corresponding to cytochrome-c was also observed in stiff ECM conditions, suggesting mitochondrial modulation. The key findings harboured by spectral profiles were also corroborated by transmission electron microscopy, confirming altered metabolic status as reflected by increased mitochondria number and decreased lipid droplets in response to ECM stiffening. Collectively, these findings not only give the spectral signatures for mechanoresponse but also provide the landscape of biochemical changes in response to ECM stiffening.

Rapid multi-task diagnosis of oral cancer leveraging fiber-optic Raman spectroscopy and deep learning algorithms

Introduction

Oral cancer, a predominant malignancy in developing nations, represents a global health challenge with a five-year survival rate below 50%. Nonetheless, substantial reductions in both its incidence and mortality rates can be achieved through early detection and appropriate treatment. Crucial to these treatment plans and prognosis predictions is the identification of the pathological type of oral cancer.

Methods

Toward this end, fiber-optic Raman spectroscopy emerges as an effective tool. This study combines Raman spectroscopy technology with deep learning algorithms to develop a portable intelligent prototype for oral case analysis. We propose, for the first time, a multi-task network (MTN) Raman spectroscopy classification model that utilizes a shared backbone network to simultaneously achieve different clinical staging and histological grading diagnoses.

Results

The developed model demonstrated accuracy rates of 94.88%, 94.57%, and 94.34% for tumor staging, lymph node staging, and histological grading, respectively. Its sensitivity, specificity, and accuracy compare closely with the gold standard: routine histopathological examination.

Discussion

Thus, this prototype proposed in this study has great potential for rapid, non-invasive, and label-free pathological diagnosis of oral cancer.

High wavenumber Raman spectroscopy for intraoperative assessment of breast tumour margins

Optimal oncological results and patient outcomes are achieved in surgery for early breast cancer with breast conserving surgery (BCS) where this is appropriate. A limitation of BCS occurs when cancer is present at, or close, to the resection margin - termed a 'positive' margin - and re-excision is recommended to reduce recurrence rate. This is occurs in 17% of BCS in the UK and there is therefore a critical need for a way to assess margin status intraoperatively to ensure complete excision with adequate margins at the first operation. This study presents the potential of high wavenumber (HWN) Raman spectroscopy to address this. Freshly excised specimens from thirty patients undergoing surgery for breast cancer were measured using a surface Raman probe, and a multivariate classification model to predict normal versus tumour was developed from the data. This model achieved 77.1% sensitivity and 90.8% specificity following leave one patient out cross validation, with the defining features being differences in water content and lipid versus protein content. This demonstrates the feasibility of HWN Raman spectroscopy to facilitate future intraoperative margin assessment at specific locations. Clinical utility of the approach will require further research.

A deep learning model designed for Raman spectroscopy with a novel hyperparameter optimization method

Raman spectroscopy is a spectroscopic technique typically used to determine vibrational modes of molecules and is commonly used in chemistry to provide a structural fingerprint by which molecules can be identified. With the help of deep learning, Raman spectroscopy can be analyzed more efficiently and thus provide more accurate molecular information. However, no general neural network is designed for one-dimensional Raman spectral data so far. Furthermore, different combinations of hyperparameters of neural networks lead to results with significant differences, so the optimization of hyperparameters is a crucial issue in deep learning modeling. In this work, we propose a deep learning model designed for Raman spectral data and a hyperparameter optimization method to achieve its best performance, i.e., a method based on the simulated annealing algorithm to optimize the hyperparameters of the model. The proposed model and optimization method have been fully validated in a glioma Raman spectroscopy dataset. Compared with other published methods including linear regression, support vector regression, long short-term memory, VGG and ResNet, the mean squared error is reduced by 0.1557 while the coefficient determination is increased by 0.1195 on average.

Raman spectroscopy: current applications in breast cancer diagnosis, challenges and future prospects

Despite significant improvements in the way breast cancer is managed and treated, it continues to persist as a leading cause of death worldwide. If detected and diagnosed early, when tumours are small and localised, there is a considerably higher chance of survival. However, current methods for detection and diagnosis lack the required sensitivity and specificity for identifying breast cancer at the asymptomatic or very early stages. Thus, there is a need to develop more rapid and reliable methods, capable of detecting disease earlier, for improved disease management and patient outcome. Raman spectroscopy is a non-destructive analytical technique that can rapidly provide highly specific information on the biochemical composition and molecular structure of samples. In cancer, it has the capacity to probe very early biochemical changes that accompany malignant transformation, even prior to the onset of morphological changes, to produce a fingerprint of disease. This review explores the application of Raman spectroscopy in breast cancer, including discussion on its capabilities in analysing both ex-vivo tissue and liquid biopsy samples, and its potential in vivo applications. The review also addresses current challenges and potential future uses of this technology in cancer research and translational clinical application.

How molecular imaging will enable robotic precision surgery : The role of artificial intelligence, augmented reality, and navigation

Molecular imaging is one of the pillars of precision surgery. Its applications range from early diagnostics to therapy planning, execution, and the accurate assessment of outcomes. In particular, molecular imaging solutions are in high demand in minimally invasive surgical strategies, such as the substantially increasing field of robotic surgery. This review aims at connecting the molecular imaging and nuclear medicine community to the rapidly expanding armory of surgical medical devices. Such devices entail technologies ranging from artificial intelligence and computer-aided visualization technologies (software) to innovative molecular imaging modalities and surgical navigation (hardware). We discuss technologies based on their role at different steps of the surgical workflow, i.e., from surgical decision and planning, over to target localization and excision guidance, all the way to (back table) surgical verification. This provides a glimpse of how innovations from the technology fields can realize an exciting future for the molecular imaging and surgery communities.

Intra-operative assessment of sentinel lymph nodes for breast cancer surgery: An update

Lymph node (LN) involvement is the strongest prognostic factor in operable breast cancer (BC). Therefore, accurate assessment of LN status is essential for management of BC patients. The introduction of sentinel LN approach reduced the need for extensive axillary surgery to achieve accurate staging. However, positive sentinel LN as determined on postoperative histological examination often leads to a second axillary operation to ensure an accurate staging and that positive non-sentinel LNs are removed. Although preoperative assessment of LN has improved significantly, its accuracy remains insufficient to avoid further axillary surgery and is not sufficient to predict the status of the LN. Therefore, intraoperative evaluation of the sentinel LN to determine the need for completing lymph node dissection in case of metastasis can provide an important approach to guide BC management decision making. This article reviews the techniques available and under development for intraoperative detection of sentinel LN metastasis in BC surgery. The key features of each technique are described in detail, emphasising the benefits offered by label-free optical techniques: minimal sample preparation, high spatial resolution, and immediate on-site implementation. Optical techniques have the potential to provide a cost-effective and accurate intraoperative platform for the assessment of SLN within the operating theatre.

Using the Method of "Optical Biopsy" of Prostatic Tissue to Diagnose Prostate Cancer

Simple Summary

Analytical discrimination models of Raman spectra of prostate cancer tissue were constructed by using the projections onto latent structures data analysis (PLS-DA) method for different wavelengths of exciting radiation—532 and 785 nm. These models allowed us to divide the Raman spectra of prostate cancer and the spectra of hyperplasia sites for validation datasets with the accuracy of 70–80%, depending on the specificity value. Meanwhile, for the calibration datasets, the accuracy values reached 100% for the excitation of a laser with a wavelength of 785 nm. Due to the registration of Raman “fingerprints”, the main features of cellular metabolism occurring in the tissue of a malignant prostate tumor were confirmed, namely the absence of aerobic glycolysis, over-expression of markers, and a strong increase in the concentration of cholesterol and its esters, as well as fatty acids and glutamic acid.

Abstract

The possibilities of using optical spectroscopy methods in the differential diagnosis of prostate cancer were investigated. Analytical discrimination models of Raman spectra of prostate tissue were constructed by using the projections onto latent structures data analysis(PLS-DA) method for different wavelengths of exciting radiation—532 and 785 nm. These models allowed us to divide the Raman spectra of prostate cancer and the spectra of hyperplasia sites for validation datasets with the accuracy of 70–80%, depending on the specificity value. Meanwhile, for the calibration datasets, the accuracy values reached 100% for the excitation of a laser with a wavelength of 785 nm. Due to the registration of Raman “fingerprints”, the main features of cellular metabolism occurring in the tissue of a malignant prostate tumor were confirmed, namely the absence of aerobic glycolysis, over-expression of markers (FASN, SREBP1, stearoyl-CoA desaturase, etc.), and a strong increase in the concentration of cholesterol and its esters, as well as fatty acids and glutamic acid. The presence of an ensemble of Raman peaks with increased intensity, inherent in fatty acid, beta-glucose, glutamic acid, and cholesterol, is a fundamental factor for the identification of prostate cancer.

Diagnostic prospects and preclinical development of optical technologies using gold nanostructure contrast agents to boost endogenous tissue contrast

Numerous developments in optical biomedical imaging research utilizing gold nanostructures as contrast agents have advanced beyond basic research towards demonstrating potential as diagnostic tools; some of which are translating into clinical applications. Recent advances in optics, lasers and detection instrumentation along with the extensive, yet developing, knowledge-base in tailoring the optical properties of gold nanostructures has significantly improved the prospect of near-infrared (NIR) optical detection technologies. Of particular interest are optical coherence tomography (OCT), photoacoustic imaging (PAI), multispectral optoacoustic tomography (MSOT), Raman spectroscopy (RS) and surface enhanced spatially offset Raman spectroscopy (SESORS), due to their respective advancements. Here we discuss recent technological developments, as well as provide a prediction of their potential to impact on clinical diagnostics. A brief summary of each techniques' capability to distinguish abnormal (disease sites) from normal tissues, using endogenous signals alone is presented. We then elaborate on the use of exogenous gold nanostructures as contrast agents providing enhanced performance in the above-mentioned techniques. Finally, we consider the potential of these approaches to further catalyse advances in pre-clinical and clinical optical diagnostic technologies.

Optical biomedical imaging research utilising gold nanostructures as contrast agents has advanced beyond basic science, demonstrating potential in various optical diagnostic tools; some of which are currently translating into clinical applications.

Raman spectroscopy for rapid intra-operative margin analysis of surgically excised tumour specimens

Raman spectroscopy, a form of vibrational spectroscopy, has the ability to provide sensitive and specific biochemical analysis of tissue. This review article provides an in-depth analysis of the suitability of different Raman spectroscopy techniques in providing intra-operative margin analysis in a range of solid tumour pathologies. Surgical excision remains the primary treatment of a number of solid organ cancers. Incomplete excision of a tumour and positive margins on histopathological analysis is associated with a worse prognosis, the need for adjuvant therapies with significant side effects and a resulting financial burden. The provision of intra-operative margin analysis of surgically excised tumour specimens would be beneficial for a number of pathologies, as there are no widely adopted and accurate methods of margin analysis, beyond histopathology. The limitations of Raman spectroscopic studies to date are discussed and future work necessary to enable translation to clinical use is identified. We conclude that, although there remain a number of challenges in translating current techniques into a clinically effective tool, studies so far demonstrate that Raman Spectroscopy has the attributes to successfully perform highly accurate intra-operative margin analysis in a clinically relevant environment.

Raman Spectroscopy for Rapid Evaluation of Surgical Margins during Breast Cancer Lumpectomy

Failure to precisely distinguish malignant from healthy tissue has severe implications for breast cancer surgical outcomes. Clinical prognoses depend on precisely distinguishing healthy from malignant tissue during surgery. Laser Raman spectroscopy (LRS) has been previously shown to differentiate benign from malignant tissue in real time. However, the cost, assembly effort, and technical expertise needed for construction and implementation of the technique have prohibited widespread adoption. Recently, Raman spectrometers have been developed for non-medical uses and have become commercially available and affordable. Here we demonstrate that this current generation of Raman spectrometers can readily identify cancer in breast surgical specimens. We evaluated two commercially available, portable, near-infrared Raman systems operating at excitation wavelengths of either 785 nm or 1064 nm, collecting a total of 164 Raman spectra from cancerous, benign, and transitional regions of resected breast tissue from six patients undergoing mastectomy. The spectra were classified using standard multivariate statistical techniques. We identified a minimal set of spectral bands sufficient to reliably distinguish between healthy and malignant tissue using either the 1064 nm or 785 nm system. Our results indicate that current generation Raman spectrometers can be used as a rapid diagnostic technique distinguishing benign from malignant tissue during surgery.

Ex Vivo Raman Spectrochemical Analysis Using a Handheld Probe Demonstrates High Predictive Capability of Brain Tumour Status

With brain tumour incidence increasing, there is an urgent need for better diagnostic tools. Intraoperatively, brain tumours are diagnosed using a smear preparation reported by a neuropathologist. These have many limitations, including the time taken for the specimen to reach the pathology department and for results to be communicated to the surgeon. There is also a need to assist with resection rates and identifying infiltrative tumour edges intraoperatively to improve clearance. We present a novel study using a handheld Raman probe in conjunction with gold nanoparticles, to detect primary and metastatic brain tumours from fresh brain tissue sent for intraoperative smear diagnosis. Fresh brain tissue samples sent for intraoperative smear diagnosis were tested using the handheld Raman probe after application of gold nanoparticles. Derived Raman spectra were inputted into forward feature extraction algorithms to build a predictive model for sensitivity and specificity of outcome. These results demonstrate an ability to detect primary from metastatic tumours (especially for normal and low grade lesions), in which accuracy, sensitivity and specificity were respectively equal to 98.6%, 94.4% and 99.5% for normal brain tissue; 96.1%, 92.2% and 97.0% for low grade glial tumours; 90.3%, 89.7% and 90.6% for high grade glial tumours; 94.8%, 63.9% and 97.1% for meningiomas; 95.4%, 79.2% and 98.8% for metastases; and 99.6%, 88.9% and 100% for lymphoma, based on smear samples (κ = 0.87). Similar results were observed when compared to the final formalin-fixed paraffin embedded tissue diagnosis (κ = 0.85). Overall, our results have demonstrated the ability of Raman spectroscopy to match results provided by intraoperative smear diagnosis and raise the possibility of use intraoperatively to aid surgeons by providing faster diagnosis. Moving this technology into theatre will allow it to develop further and thus reach its potential in the clinical arena.

Clinical applications of infrared and Raman spectroscopy: state of play and future challenges

This review examines the state-of-the-art of clinical applications of infrared absorption and Raman spectroscopy, outstanding challenges, and progress towards translation.

Detection of Lymph Node Metastases with SERRS Nanoparticles

PURPOSE

The accurate detection of lymph node metastases in prostate cancer patients is important to direct treatment decisions. Our goal was to develop an intraoperative imaging approach to distinguish normal from metastasized lymph nodes. We aimed at developing and testing gold-silica surface-enhanced resonance Raman spectroscopy (SERRS) nanoparticles that demonstrate high uptake within normal lymphatic tissue and negligible uptake in areas of metastatic replacement.

PROCEDURES

We evaluated the ability of SERRS nanoparticles to delineate lymph node metastases in an orthotopic prostate cancer mouse model using PC-3 cells transduced with mCherry fluorescent protein. Tumor-bearing mice (n = 6) and non-tumor-bearing control animals (n = 4) were injected intravenously with 30 fmol/g SERRS nanoparticles. After 16-18 h, the retroperitoneal lymph nodes were scanned in situ and ex vivo with a Raman imaging system and a handheld Raman scanner and data corroborated with fluorescence imaging for mCherry protein expression and histology.

RESULTS

The SERRS nanoparticles demonstrated avid homing to normal lymph nodes, but not to metastasized lymph nodes. In cases where lymph nodes were partially infiltrated by tumor cells, the SERRS signal correctly identified, with sub-millimeter precision, healthy from metastasized components.

CONCLUSIONS

This study serves as a first proof-of-principle that SERRS nanoparticles enable high precision and rapid intraoperative discrimination between normal and metastasized lymph nodes.

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.

Characterisation of a fibre optic Raman probe within a hypodermic needle

We demonstrate the first use of a multifibre Raman probe that fits inside the bore of a hypodermic needle. A Raman probe containing multiple collection fibres provides improved signal collection efficiency in biological samples compared with a previous two-fibre design. Furthermore, probe performance (signal-to-noise ratios) compared favourably with the performance achieved in previous Raman microscope experiments able to distinguish between benign lymph nodes, primary malignancies in lymph nodes and secondary malignancies in lymph nodes. The experimental measurements presented here give an indication of the sampling volume of the Raman needle probe in lymphoid tissues. Liquid tissue phantoms were used that contained scattering medium encompassing a range of scattering properties similar to those of a variety of tissue types, including lymph node tissues. To validate the appropriateness of the phantoms, the sampling depth of the probe was also measured in excised lymph node tissue. More than 50 % of Raman photons collected were found to originate from between the tip of the needle and a depth of 500 μm into the tissue. The needle probe presented here achieves spectral quality comparable to that in numerous studies previously demonstrating Raman disease discrimination. It is expected that this approach could achieve targeted subcutaneous tissue measurements and be viable for use for the in vivo Raman diagnostics of solid organs located within a few centimetres below the skin's surface. Graphical Abstract Schematic of multi-fibre Raman needle probe with disposible tips and proximal optical filtration.

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.

Spectropathology for the next generation: Quo vadis?

Vibrational spectroscopy for biomedical applications has shown great promise although its translation into clinical practice has, as yet, been relatively slow. This Editorial assesses the challenges facing the field and the potential way forward.

Discrimination of lymph node metastases using desorption electrospray ionisation-mass spectrometry imaging

Desorption electrospray ionisation mass spectrometry imaging (DESI-MSI) has been used for the identification of cancer within lymph nodes with accurate spatial distribution in comparison to gold standard matched immuno-histopathological images. The metabolic profile of the cancerous lymph nodes was similar to that of the primary tumour site.

Guiding brain tumor resection using surface-enhanced Raman scattering nanoparticles and a hand-held Raman scanner

The current difficulty in visualizing the true extent of malignant brain tumors during surgical resection represents one of the major reasons for the poor prognosis of brain tumor patients. Here, we evaluated the ability of a hand-held Raman scanner, guided by surface-enhanced Raman scattering (SERS) nanoparticles, to identify the microscopic tumor extent in a genetically engineered RCAS/tv-a glioblastoma mouse model. In a simulated intraoperative scenario, we tested both a static Raman imaging device and a mobile, hand-held Raman scanner. We show that SERS image-guided resection is more accurate than resection using white light visualization alone. Both methods complemented each other, and correlation with histology showed that SERS nanoparticles accurately outlined the extent of the tumors. Importantly, the hand-held Raman probe not only allowed near real-time scanning, but also detected additional microscopic foci of cancer in the resection bed that were not seen on static SERS images and would otherwise have been missed. This technology has a strong potential for clinical translation because it uses inert gold-silica SERS nanoparticles and a hand-held Raman scanner that can guide brain tumor resection in the operating room.

A "schizophotonic" all-in-one nanoparticle coating for multiplexed SE(R)RS biomedical imaging

SERS nanoprobes for in vivo biomedical applications require high quantum yield, long circulation times, and maximum colloidal stability. Traditional synthetic routes require high metal-dye affinities and are challenged by unfavorable electrostatic interactions and limited scalability. We report the synthesis of a new near-IR active poly(N-(2-hydroxypropyl) methacrylamide) (pHPMA). The integration of various SERS reporters into a biocompatible polymeric surface coating allows for controlled dye incorporation, high colloidal stability, and optimized in vivo circulation times. This technique allows the synthesis of very small (<20 nm) SERS probes, which is crucial for the design of excretable and thus highly translatable imaging agents. Depending on their size, the "schizophotonic" nanoparticles can emit both SERS and fluorescence. We demonstrate the capability of this all-in-one gold surface coating and SERS reporter for multiplexed lymph-node imaging.

Biochemical characterization of human gingival crevicular fluid during orthodontic tooth movement using Raman spectroscopy

This study used Raman spectroscopy to report the first human gingival crevicular fluid (GCF) biochemical characterization during the early phase of orthodontic tooth movement. This technique allows for label-free and noninvasive biochemical change monitoring in GCF during orthodontic tooth movement. Ten orthodontic patients (20.8 ± 2.5 years) participated in the study. GCF samples were obtained before (baseline, 0 days) and during orthodontic treatment at 1, 7 and 28 days. For Raman spectroscopic measurement, GCF samples (5 µl) were deposited onto a gold-coated substrate, then dried at room temperature. Raman spectra GCF analysis during orthodontic treatment indicated that the hydroxyapatite to primarily collagen-dominated matrix band (phosphate 984 cm(-1)/amide I 1667 cm(-1)) intensity ratio decreased at day 7 (P < 0.05). The carbonate apatite to hydroxyapatite ratio (carbonate 1088 cm(-1)/phosphate 984 cm(-1)) was significantly higher on day 7 compared to day 0 (P < 0.05). These results indicate that demineralization occurs during the alveolar bone remodeling process. We also found notable peak shifts in the amide I range during orthodontic tooth movement. The 1658 cm(-1) in baseline red shifted to 1667 cm(-1) at orthodontic treatment day 7. Curve fitting in the amide I (1615-1725 cm(-1)) range demonstrated that increased random coil conformation was accompanied by a decrease in β-sheet structure during orthodontic tooth movement. Thus, we suggest Raman spectroscopy could be used for label-free, non-invasive GCF quality assessment during orthodontic tooth movement. Furthermore, this method may prove to be a powerful diagnostic and prognostic tool for monitoring orthodontic tooth movement in a clinical setting.

Novel biospectroscopy sensor technologies towards environmental health monitoring in urban environments

Biospectroscopy is an emerging inter-disciplinary field that exploits the application of sensor technologies [e.g., Fourier-transform infrared spectroscopy, Raman spectroscopy] to lend novel insights into biological questions. Methods involved are relatively non-destructive so samples can subsequently be analysed by more conventional approaches, facilitating deeper mechanistic insights. Fingerprint spectra are derived and these consist of wavenumber-absorbance intensities; within a typical biological experiment, a complex dataset is quickly generated. Biological samples range from biofluids to cytology to tissues derived from human or sentinel sources, and analyses can be carried out ex vivo or in situ in living tissue. A reference range of a designated normal state can be derived; anything outside this is potentially atypical and discriminating chemical entities identified. Computational approaches allow one to minimize within-category confounding factors. Because of ease of sample preparation, low-cost and high-throughput capability, biospectroscopy approaches herald a new greener means of environmental health monitoring in urban environments.

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.

Infrared spectral histopathology (SHP): a novel diagnostic tool for the accurate classification of lung cancer

We report results of a study utilizing a recently developed tissue diagnostic method, based on label-free spectral techniques, for the classification of lung cancer histopathological samples from a tissue microarray. The spectral diagnostic method allows reproducible and objective diagnosis of unstained tissue sections. This is accomplished by acquiring infrared hyperspectral data sets containing thousands of spectra, each collected from tissue pixels about 6 μm on edge; these pixel spectra contain an encoded snapshot of the entire biochemical composition of the pixel area. The hyperspectral data sets are subsequently decoded by methods of multivariate analysis, which reveal changes in the biochemical composition between tissue types, and between various stages and states of disease. In this study, a detailed comparison between classical and spectral histopathology (SHP) is presented, which suggests SHP can achieve levels of diagnostic accuracy that is comparable to that of multi-panel immunohistochemistry.

Applications of Infrared and Raman Microspectroscopy of Cells and Tissue in Medical Diagnostics: Present Status and Future Promises

This paper summarizes the progress achieved over the past fifteen years in applying vibrational (Raman and IR) spectroscopy to problems of medical diagnostics and cellular biology. During this time, a number of research groups have verified the enormous information content of vibrational spectra; in fact, genomic, proteomic, and metabolomic information can be deduced by decoding the observed vibrational spectra. This decoding process is aided enormously by the availability of high-power computer workstations and advanced algorithms for data analysis. Furthermore, commercial instrumentation for the fast collection of both Raman and infrared microspectral data has rendered practical the collection of images based solely on spectral data. The progress in the field has been manifested by a steady increase in the number and quality of publications submitted by established and new research groups in vibrational biological and biomedical arenas.

Raman Spectroscopy for Clinical Oncology

Cancer is one of the leading causes of death throughout the world. Advancements in early and improved diagnosis could help prevent a significant number of these deaths. Raman spectroscopy is a vibrational spectroscopic technique which has received considerable attention recently with regards to applications in clinical oncology. Raman spectroscopy has the potential not only to improve diagnosis of cancer but also to advance the treatment of cancer. A number of studies have investigated Raman spectroscopy for its potential to improve diagnosis and treatment of a wide variety of cancers. In this paper the most recent advances in dispersive Raman spectroscopy, which have demonstrated promising leads to real world application for clinical oncology are reviewed. The application of Raman spectroscopy to breast, brain, skin, cervical, gastrointestinal, oral, and lung cancers is reviewed as well as a special focus on the data analysis techniques, which have been employed in the studies.

Raman spectroscopy: a potential tool for early objective diagnosis of neoplasia in the oesophagus

There is a profound clinical need for a diagnostic tool that will enable clinicians to identify early neoplastic change in the oesophagus. Raman Spectroscopy (RS) has demonstrated the potential to provide non-invasive, rapid, objective diagnosis of endoscopically invisible precancerous oesophageal dysplasia in vitro. RS analyses biological material to identify highly specific biochemical information that can be used to influence clinical care. Raman spectroscopic mapping could provide automated assessment of tissue biopsies to aid histopathological diagnosis in vitro. Furthermore, the recent development of fibre-optic Raman probes has enabled endoscopic assessment of oesophageal mucosa in vivo. Accurate identification of dysplasia will enable targeted endoscopic resection of early lesions preventing the development of oesophageal cancer. This review summarises the development of Raman systems for use as laboratory based analytical adjuncts and endoscopic diagnostic tools in the distal oesophagus.