In vivo Raman spectroscopy of oral buccal mucosa: a study on malignancy associated changes (MAC)/cancer field effects (CFE)

The accuracy of Fiber-Optic Raman Spectroscopy in the detection and diagnosis of head and neck neoplasm in vivo: a systematic review and meta-analysis

Purpose

The aim of this article was to review and collectively assess the published studies of fiber-optic Raman spectroscopy (RS) of the in vivo detection and diagnosis of head and neck carcinomas, and to derive a consensus average of the accuracy, sensitivity and specificity.

Methods

The authors searched four databases, including Ovid-Medline, Ovid-Embase, Cochrane Library, and the China National Knowledge Infrastructure (CNKI), up to February 2023 for all published studies that assessed the diagnostic accuracy of fiber-optic RS in the in vivo detection of head and neck carcinomas. Nonqualifying studies were screened out in accordance with the specified exclusion criteria, and relevant information about the diagnostic performance of fiber-optic RS was excluded. Publication bias was estimated by Deeks' funnel plot asymmetry test. A random effects model was adopted to calculate the pooled sensitivity, specificity and diagnostic odds ratio (DOR). Additionally, the authors conducted a summary receiver operating characteristic (SROC) curve analysis and threshold analysis, reporting the area under the curve (AUC) to evaluate the overall performance of fiber-optic RS in vivo.

Results

Ten studies (including 16 groups of data) were included in this article, and a total of 5365 in vivo Raman spectra (cancer = 1,746; normal = 3,619) were acquired from 877 patients. The pooled sensitivity and specificity of fiber-optic RS of head and neck carcinomas were 0.88 and 0.94, respectively. SROC curves were generated to estimate the overall diagnostic accuracy, and the AUC was 0.96 (95% CI [0.94-0.97]). No significant publication bias was found in this meta-analysis by Deeks' funnel plot asymmetry test. The heterogeneity of these studies was significant; the Q test values of the sensitivity and specificity were 106.23 (P = 0.00) and 64.21 (P = 0.00), respectively, and the I2 index of the sensitivity and specificity were 85.88 (95% CI [79.99-91.77]) and 76.64 (95% CI [65.45-87.83]), respectively.

Conclusion

Fiber-optic RS was demonstrated to be a reliable technique for the in vivo detection of head and neck carcinoma with high accuracy. However, considering the high heterogeneity of these studies, more clinical studies are needed to reduce the heterogeneity, and further confirm the utility of fiber-optic Raman spectroscopy in vivo.

A New Detection Method of Oral and Oropharyngeal Squamous Cell Carcinoma Based on Multivariate Analysis of Surface Enhanced Raman Spectra of Salivary Exosomes

Raman spectroscopy recently proved a tremendous capacity to identify disease-specific markers in various (bio)samples being a non-invasive, rapid, and reliable method for cancer detection. In this study, we first aimed to record vibrational spectra of salivary exosomes isolated from oral and oropharyngeal squamous cell carcinoma patients and healthy controls using surface enhancement Raman spectroscopy (SERS). Then, we assessed this method's capacity to discriminate between malignant and non-malignant samples by means of principal component-linear discriminant analysis (PC-LDA) and we used area under the receiver operating characteristics with illustration as the area under the curve to measure the power of salivary exosomes SERS spectra analysis to identify cancer presence. The vibrational spectra were collected on a solid plasmonic substrate developed in our group, synthesized using tangential flow filtered and concentrated silver nanoparticles, capable of generating very reproducible spectra for a whole range of bioanalytes. SERS examination identified interesting variations in the vibrational bands assigned to thiocyanate, proteins, and nucleic acids between the saliva of cancer and control groups. Chemometric analysis indicated discrimination sensitivity between the two groups up to 79.3%. The sensitivity is influenced by the spectral interval used for the multivariate analysis, being lower (75.9%) when the full-range spectra were used.

Serum Raman spectroscopy: Prognostic applications in oral cancers

BACKGROUND

Loco-regional recurrences attributable to field cancerization and minimal residual cancer, remain prime causes of mortality in oral cancer (OC) subjects. The current study evaluates potential of serum Raman spectroscopy (SRS) to identify recurrence-prone OC subjects.

METHODS

Raman spectra of serum from eight healthy subjects (H) and 57 OC subjects (with-recurrence [R], without-recurrence [NR], and with suspicious-lesions [S]), before (BS) and after (AS) surgical excision of tumor were recorded. OC subjects were followed-up for 7-years.

RESULTS

DNA and protein alterations were observed in AS sera of all groups. 4-, 3-, and 2-model multivariate analyses were used to stratify BS and AS groups. H spectra were 100% distinguishable from all other groups. AS, R and NR were distinguished with high accuracy (84%) in all models. No stratification (~50%) was observed BS.

CONCLUSION

SRS shows potential to identify recurrence prone subjects, post-surgery, using serum collected as early as 1 week after surgery.

Classification of cytological samples from oral potentially malignant lesions through Raman spectroscopy: A pilot study

The potential of Raman microspectroscopy of exfoliated cells has been demonstrated for oral cancer diagnosis. In this study, brush biopsies were collected from the buccal mucosa/tongue of healthy donors (n = 31) and from oral mucosal dysplastic lesions (n = 31 patients). Raman spectra were acquired and subjected to partial least squares-discriminant analysis (PLS-DA). The patient samples could be differentiated from healthy donor samples with 96% sensitivity and 95% specificity. Furthermore, PLS-DA models were developed based on cytopathological and histopathological assessment. Low and high grade dysplasia could be discriminated with 64% sensitivity and 65% specificity based on cytopathological assessment, while 81% sensitivity and 86% specificity could be achieved when histopathological assessment was within six months of the brush biopsy sampling. Therefore, this explorative study has successfully demonstrated that Raman spectroscopy may have a role in monitoring patients with dysplasia and may reduce the need for multiple biopsies.

Raman micro-spectroscopic map estimating in vivo precision of tumor ablative effect achieved by photothermal therapy procedure

Photothermal-therapy (PTT) inculcates near-infrared laser guided local heating effect, where high degree of precision is expected, but not well proven to-date. An ex vivo tissue biochemical map with molecular/biochemical response showing the coverage area out of an optimized PTT procedure can reveal precision information. In this work, Raman-microscopic mapping and linear discriminant analysis of spectra of PTT treated and surrounding tissue areas ex vivo are done, revealing three distinct spectral clusters/zones, with minimal overlap between the core treated and adjacent untreated zone. The core treated zone showed intense nucleic-acid, cytochrome/mitochondria and protein damage, an adjacent zone showed lesser degree of damages and far zone showed minimal/no damage. Immunohistochemistry for γH2AX (DNA damage marker protein) in PTT exposed tissue also revealed similar results. Altogether, this study reveals the utility of Raman-microspectroscopy for fine-tuning safety parameters and precision that can be achieved from PTT mediated tumor ablation in preclinical/clinical application.

Biomedical applications of vibrational spectroscopy: Oral cancer diagnostics

Vibrational spectroscopy, based on either infrared absorption or Raman scattering, has attracted increasing attention for biomedical applications. Proof of concept explorations for diagnosis of oral potentially malignant disorders and cancer are reviewed, and recent advances critically appraised. Specific examples of applications of Raman microspectroscopy for analysis of histological, cytological and saliva samples are presented for illustrative purposes, and the future prospects, ultimately for routine, chairside in vivo screening are discussed.

Raman spectroscopy and artificial intelligence to predict the Bayesian probability of breast cancer

This study addresses the core issue facing a surgical team during breast cancer surgery: quantitative prediction of tumor likelihood including estimates of prediction error. We have previously reported that a molecular probe, Laser Raman spectroscopy (LRS), can distinguish healthy and tumor tissue. We now report that combining LRS with two machine learning algorithms, unsupervised k-means and stochastic nonlinear neural networks (NN), provides rapid, quantitative, probabilistic tumor assessment with real-time error analysis. NNs were first trained on Raman spectra using human expert histopathology diagnostics as gold standard (74 spectra, 5 patients). K-means predictions using spectral data when compared to histopathology produced clustering models with 93.2-94.6% accuracy, 89.8-91.8% sensitivity, and 100% specificity. NNs trained on k-means predictions generated probabilities of correctness for the autonomous classification. Finally, the autonomous system characterized an extended dataset (203 spectra, 8 patients). Our results show that an increase in DNA|RNA signal intensity in the fingerprint region (600-1800 cm-1) and global loss of high wavenumber signal (2800-3200 cm-1) are particularly sensitive LRS warning signs of tumor. The stochastic nature of NNs made it possible to rapidly generate multiple models of target tissue classification and calculate the inherent error in the probabilistic estimates for each target.

Risk prediction by Raman spectroscopy for disease-free survival in oral cancers

In the present study, the potential of Raman spectroscopy (RS) in predicting disease-free survival (DFS) in oral cancer patients has been explored. Raman spectra were obtained from the tumor and contralateral regions of 94 oral squamous cell carcinoma patients. These patients were managed surgically and recommended for adjuvant therapy. The Cox proportional survival analysis was carried out to identify the spectral regions that can be correlated to DFS. The survival analysis was performed with 95% confidence intervals, hazard ratio, and p-values in the 1200-1800 cm^-1 spectral region. Out of a total of 182 spectral points, 76 were found to be correlating with DFS, suggesting their utility to predict the patient outcome. The cut-off points of each correlating RS-point values were defined and tested towards predicting the DFS. The performance of predicting the power of spectral points was validated through Brier value, and it was found to be closer to the actual progression. The 76 spectral points identified from the tumors have the potential to accurately predict DFS in oral squamous cell carcinoma through a relatively simplistic prediction model in the absence of confounding factors.

Handheld macroscopic Raman spectroscopy imaging instrument for machine-learning-based molecular tissue margins characterization

SIGNIFICANCE

Raman spectroscopy has been developed for surgical guidance applications interrogating live tissue during tumor resection procedures to detect molecular contrast consistent with cancer pathophysiological changes. To date, the vibrational spectroscopy systems developed for medical applications include single-point measurement probes and intraoperative microscopes. There is a need to develop systems with larger fields of view (FOVs) for rapid intraoperative cancer margin detection during surgery.

AIM

We design a handheld macroscopic Raman imaging system for in vivo tissue margin characterization and test its performance in a model system.

APPROACH

The system is made of a sterilizable line scanner employing a coherent fiber bundle for relaying excitation light from a 785-nm laser to the tissue. A second coherent fiber bundle is used for hyperspectral detection of the fingerprint Raman signal over an area of 1  cm2. Machine learning classifiers were trained and validated on porcine adipose and muscle tissue.

RESULTS

Porcine adipose versus muscle margin detection was validated ex vivo with an accuracy of 99% over the FOV of 95  mm2 in ∼3  min using a support vector machine.

CONCLUSIONS

This system is the first large FOV Raman imaging system designed to be integrated in the workflow of surgical cancer resection. It will be further improved with the aim of discriminating brain cancer in a clinically acceptable timeframe during glioma surgery.

Vibrational Spectroscopy for Identification of Metabolites in Biologic Samples

Vibrational spectroscopy (mid-infrared (IR) and Raman) and its fingerprinting capabilities offer rapid, high-throughput, and non-destructive analysis of a wide range of sample types producing a characteristic chemical "fingerprint" with a unique signature profile. Nuclear magnetic resonance (NMR) spectroscopy and an array of mass spectrometry (MS) techniques provide selectivity and specificity for screening metabolites, but demand costly instrumentation, complex sample pretreatment, are labor-intensive, require well-trained technicians to operate the instrumentation, and are less amenable for implementation in clinics. The potential for vibration spectroscopy techniques to be brought to the bedside gives hope for huge cost savings and potential revolutionary advances in diagnostics in the clinic. We discuss the utilization of current vibrational spectroscopy methodologies on biologic samples as an avenue towards rapid cost saving diagnostics.

Raman microspectroscopic study for the detection of oral field cancerisation using brush biopsy samples

Field cancerisation (FC) is potentially an underlying cause of poor treatment outcomes of oral squamous cell carcinoma (OSCC). To explore the phenomenon using Raman microspectroscopy, brush biopsies from the buccal mucosa, tongue, gingiva and alveolus of healthy donors (n = 40) and from potentially malignant lesions (PML) of Dysplasia Clinic patients (n = 40) were examined. Contralateral normal samples (n = 38) were also collected from the patients. Raman spectra were acquired from the nucleus and cytoplasm of each cell, and subjected to partial least squares-discriminant analysis (PLS-DA). High discriminatory accuracy for donor and PML samples was achieved for both cytopalmic and nuclear data sets. Notably, contralateral normal (patient) samples were also accurately discriminated from donor samples and contralateral normal samples from patients with multiple lesions showed a similar spectral profile to PML samples, strongly indicating a FC effect. These findings support the potential of Raman microspectroscopy as a screening tool for PML using oral exfoliated cells.

Optical Biopsy of the Upper GI Tract Using Fluorescence Lifetime and Spectra

Screening and surveillance for gastrointestinal (GI) cancers by endoscope guided biopsy is invasive, time consuming, and has the potential for sampling error. Tissue endogenous fluorescence spectra contain biochemical and physiological information, which may enable real-time, objective diagnosis. We first briefly reviewed optical biopsy modalities for GI cancer diagnosis with a focus on fluorescence-based techniques. In an ex vivo pilot clinical study, we measured fluorescence spectra and lifetime on fresh biopsy specimens obtained during routine upper GI screening procedures. Our results demonstrated the feasibility of rapid acquisition of time-resolved fluorescence (TRF) spectra from fresh GI mucosal specimens. We also identified spectroscopic signatures that can differentiate between normal mucosal samples obtained from the esophagus, stomach, and duodenum.

Can ethanol affect the cell structure? A dynamic molecular and Raman spectroscopy study

The role that tobacco consumption plays in the etiology of oral cancer carcinogenesis, and of alcohol consumption acting as a co-factor, have been well established. However, in recent years, the contribution of alcohol consumption alone to oral cancer has been proposed. In fact, a high percentage of patients who develop oral cancer have both habits (tobacco and alcohol consumption), and other small patient groups only consume alcohol or do not have any other identifiable bad habits. In the present study we demonstrate, using a combination of dynamic molecular modelling and Raman spectroscopy, that ethanol has a significant effect on oral cells in vitro, mainly interacting with the lipids of the cell membrane, changing their conformation. Thus, it is possible to conclude that ethanol can affect the cell permeability, and by consequence serve as a possible trigger in oral carcinogenesis.

Raman exfoliative cytology for prognosis prediction in oral cancers: A proof of concept study

Oral cancer is associated with high rates of recurrence, attributable to field cancerization. Early detection of advanced field changes that can potentially progress to carcinoma can facilitate timely intervention and can lead to improved prognosis. Previous in vivo studies have successfully detected advanced field effects in oral cancers. Raman exfoliative cytology has previously shown to differentiate normal, oral pre-cancer and cancers. The present study explores Raman-exfoliative-cytology-based detection of field effects. Exfoliated cells were collected from tumor (n = 16) and contralateral-normal appearing mucosa (n = 16) of oral cancer patients, and healthy tobacco habitués (n = 20). After spectral acquisition, specimens were Pap-stained for cytological evaluation. Data analysis, by Principal Component Analysis and Principal Component-Linear Discriminant Analysis, indicate several spectral-misclassifications between contralateral normal and tumor, which were investigated and correlated with spectral, cytological and clinical outcomes. A qualitative analysis by grouping patients with number of misclassifications with tumor (Group 1: 0, Group 2: 1 and Group 3: >1) was explored. Group 3 with highest misclassifications showed spectral and cytological similarity to tumor group - one patient was a case of early inoperable residual disease, despite clear margins on histopathology. Thus, these misclassifications could be indicative of cancer field changes, and can prospectively help to identify patients susceptible to recurrences .

Chemometric analysis of integrated FTIR and Raman spectra obtained by non-invasive exfoliative cytology for the screening of oral cancer

FTIR spectroscopy and Raman spectroscopy of biological analytes are increasingly explored as screening tools for early detection of cancer.

Identification of Malignancy-Associated Changes in Histologically Normal Tumor-Adjacent Epithelium of Patients with HPV-Positive Oropharyngeal Cancer

The incidence of HPV-positive oropharyngeal cancer (HPV+ OPC) is increasing, thus presenting new challenges for disease detection and management. Noninvasive methods involving brush biopsies of diseased tissues were recently reported as insufficient for tumor detection in HPV+ OPC patients, likely due to differences between the site of tumor initiation at the base of involuted crypts and the site of brush biopsy at the crypt surface. We hypothesized that histologically normal surface epithelial cells in the oropharynx contain changes in nuclear morphology that arise due to tumor proximity. We analyzed the nuclear phenotype of matched tumor, tumor-adjacent normal, and contralateral normal tissues from biopsies of nine HPV+ OPC patients. Measurements of 89 nuclear features were used to train a random forest-based classifier to discriminate between normal and tumor nuclei. We then extracted voting scores from the trained classifier, which classify nuclei on a continuous scale from zero (“normal-like”) to one (“tumor-like”). In each case, the average score of the adjacent normal nuclei was intermediate between the tumor and contralateral normal nuclei. These results provide evidence for the existence of phenotypic changes in histologically normal, tumor-adjacent surface epithelial cells, which could be used as brush biopsy-based biomarkers for HPV+ OPC detection.

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.

Identification of morphological and biochemical changes in keratin-8/18 knock-down cells using Raman spectroscopy

Accurate understanding of cellular processes and responses to stimuli is of paramount importance in biomedical research and diagnosis. Raman spectroscopy (RS), a label-free and nondestructive spectroscopic method has the potential to serve as a novel 'theranostics' tool. Both fiber-optic and micro-Raman studies have demonstrated efficacy in diagnostics and therapeutic response monitoring. In the present study, we have evaluated the potential of micro-Raman spectroscopic maps in identifying changes induced by loss of K8/18 proteins in a tongue cancer cell line. Furthermore, we also evaluated the efficacy of less expensive and commercially available fiber probes to identify K8/18 wild and knock-down cell pellets, in view of the utility of cell pellet-based studies. The findings suggest that major differences in the cellular morphology and biochemical composition can be objectively identified and can be utilized for classification using both micro-Raman and fiber-probe-based RS. These findings highlight the potential of fiber-optic probe-based RS in noninvasive cellular phenotyping for diagnosis and therapeutic response monitoring, especially in low-resource settings.

Raman fiber-optical method for colon cancer detection: Cross-validation and outlier identification approach

Endoscopy plays a major role in early recognition of cancer which is not externally accessible and therewith in increasing the survival rate. Raman spectroscopic fiber-optical approaches can help to decrease the impact on the patient, increase objectivity in tissue characterization, reduce expenses and provide a significant time advantage in endoscopy. In gastroenterology an early recognition of malign and precursor lesions is relevant. Instantaneous and precise differentiation between adenomas as precursor lesions for cancer and hyperplastic polyps on the one hand and between high and low-risk alterations on the other hand is important. Raman fiber-optical measurements of colon biopsy samples taken during colonoscopy were carried out during a clinical study, and samples of adenocarcinoma (22), tubular adenomas (141), hyperplastic polyps (79) and normal tissue (101) from 151 patients were analyzed. This allows us to focus on the bioinformatic analysis and to set stage for Raman endoscopic measurements. Since spectral differences between normal and cancerous biopsy samples are small, special care has to be taken in data analysis. Using a leave-one-patient-out cross-validation scheme, three different outlier identification methods were investigated to decrease the influence of systematic errors, like a residual risk in misplacement of the sample and spectral dilution of marker bands (esp. cancerous tissue) and therewith optimize the experimental design. Furthermore other validations methods like leave-one-sample-out and leave-one-spectrum-out cross-validation schemes were compared with leave-one-patient-out cross-validation. High-risk lesions were differentiated from low-risk lesions with a sensitivity of 79%, specificity of 74% and an accuracy of 77%, cancer and normal tissue with a sensitivity of 79%, specificity of 83% and an accuracy of 81%. Additionally applied outlier identification enabled us to improve the recognition of neoplastic biopsy samples.

Raman technologies in cancer diagnostics

Despite significant effort, cancer still remains a leading cause of death worldwide. In order to reduce its burden, the development and improvement of noninvasive strategies for early detection and diagnosis of cancer are urgently needed. Raman spectroscopy, an optical technique that relies on inelastic light scattering arising from molecular vibrations, is one such strategy, as it can noninvasively probe cancerous markers using only endogenous contrast. In this review, spontaneous, coherent and surface enhanced Raman spectroscopies and imaging, as well as the fundamental principles governing the successful use of these techniques, are discussed. Methods for spectral data analysis are also highlighted. Utilization of the discussed Raman techniques for the detection and diagnosis of cancer in vitro, ex vivo and in vivo is described. The review concludes with a discussion of the future directions of Raman technologies, with particular emphasis on their clinical translation.

Monitoring the biochemical alterations in hypertension affected salivary gland tissues using Fourier transform infrared hyperspectral imaging

FTIR imaging shows biochemical differences between salivary glands from control and hypertensive rats.

Raman spectroscopy can discriminate between normal, dysplastic and cancerous oral mucosa: a tissue-engineering approach

Head and neck cancer (HNC) is the sixth most common malignancy worldwide. Squamous cell carcinoma, the primary cause of HNC, evolves from normal epithelium through dysplasia before invading the connective tissue to form a carcinoma. However, less than 18% of suspicious oral lesions progress to cancer, with diagnosis currently relying on histopathological evaluation, which is invasive and time consuming. A non-invasive, real-time, point-of-care method could overcome these problems and facilitate regular screening. Raman spectroscopy is a non-invasive optical technique with the ability to extract molecular level information to help determine the functional groups present in a tissue and the molecular conformations of tissue constituents. In the present study, Raman spectroscopy was assessed for its ability to discriminate between normal, dysplastic and HNC. Tissue engineered models of normal, dysplastic and HNC were constructed using normal oral keratinocytes, dysplastic and HNC cell lines, and their biochemical content predicted by interpretation of spectral characteristics. Spectral differences were evident in both the fingerprint (600/cm to 1800/cm) and high wave-number compartments (2800/cm to 3400/cm). Visible differences were seen in peaks relating to lipid content (2881/cm), protein structure (amide I, amide III), several amino acids and nucleic acids (600/cm to 1003/cm). Multivariate data analysis algorithms successfully identified subtypes of dysplasia and cancer, suggesting that Raman spectroscopy not only has the potential to differentiate between normal, pre-malignant and cancerous tissue models but could also be sensitive enough to detect subtypes of dysplasia or cancer on the basis of their subcellular differences. Copyright © 2016 John Wiley & Sons, Ltd.

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

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

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.

Automatic and objective oral cancer diagnosis by Raman spectroscopic detection of keratin with multivariate curve resolution analysis

We have developed an automatic and objective method for detecting human oral squamous cell carcinoma (OSCC) tissues with Raman microspectroscopy. We measure 196 independent Raman spectra from 196 different points of one oral tissue sample and globally analyze these spectra using a Multivariate Curve Resolution (MCR) analysis. Discrimination of OSCC tissues is automatically and objectively made by spectral matching comparison of the MCR decomposed Raman spectra and the standard Raman spectrum of keratin, a well-established molecular marker of OSCC. We use a total of 24 tissue samples, 10 OSCC and 10 normal tissues from the same 10 patients, 3 OSCC and 1 normal tissues from different patients. Following the newly developed protocol presented here, we have been able to detect OSCC tissues with 77 to 92% sensitivity (depending on how to define positivity) and 100% specificity. The present approach lends itself to a reliable clinical diagnosis of OSCC substantiated by the “molecular fingerprint” of keratin.

Recent advances in optical diagnosis of oral cancers: Review and future perspectives

Optical diagnosis techniques offer several advantages over traditional approaches, including objectivity, speed, and cost, and these label-free, noninvasive methods have the potential to change the future workflow of cancer management. The oral cavity is particularly accessible and, thus, such methods may serve as alternate/adjunct tools to traditional methods. Recently, in vivo human clinical studies have been initiated with a view to clinical translation of such technologies. A comprehensive review of optical methods in oral cancer diagnosis is presented. After an introduction to the epidemiology and etiological factors associated with oral cancers currently used, diagnostic methods and their limitations are presented. A thorough review of fluorescence, infrared absorption, and Raman spectroscopic methods in oral cancer diagnosis is presented. The applicability of minimally invasive methods based on serum/saliva is also discussed. The review concludes with a discussion on future demands and scope of developments from a clinical point of view. © 2015 Wiley Periodicals, Inc. Head Neck 38: E2403-E2411, 2016.

Recurrence prediction in oral cancers: a serum Raman spectroscopy study

High mortality rates associated with oral cancers can be primarily attributed to the failure of current histological procedures in predicting recurrence. Identifying recurrence related factors can lead to improved prognosis, optimized treatment and enhanced overall outcomes. Serum Raman spectroscopy has previously shown potential in the diagnosis of cancers, such as head and neck, cervix, breast, oral cancers, and also in predicting treatment response. In the present study, serum was collected from 22 oral cancer subjects [with recurrence (n = 10) and no-recurrence (n = 12)] before and after surgery and spectra were acquired using a Raman microprobe coupled with a 40× objective. Spectral acquisition parameters were as follows: λex = 785 nm, laser power = 30 mW, integration time: 12 s and averages: 3. Data was analyzed in a patient-wise approach using unsupervised PCA and supervised PC-LDA, followed by LOOCV. PCA and PC-LDA findings suggest that recurrent and non-recurrent cases cannot be classified in before surgery serum samples; an average classification efficiency of ∼78% was obtained in after-surgery samples. Mean and difference spectra and PCA loadings indicate that DNA and protein markers may be potential spectral markers for recurrence. RS of post surgery serum samples may have the potential to predict the probability of recurrence in clinics, after prospective large-scale validation.

Raman Spectroscopy of Experimental Oral Carcinogenesis: Study on Sequential Cancer Progression in Hamster Buccal Pouch Model

Oral cancers suffer from poor 5-year survival rates, owing to late detection of the disease. Current diagnostic/screening tools need to be upgraded in view of disadvantages like invasiveness, tedious sample preparation, long output times, and interobserver variances. Raman spectroscopy has been shown to identify many disease conditions, including oral cancers, from healthy conditions. Further studies in exploring sequential changes in oral carcinogenesis are warranted. In this Raman spectroscopy study, sequential progression in experimental oral carcinogenesis in Hamster buccal pouch model was investigated using 3 approaches-ex vivo, in vivo sequential, and in vivo follow-up. In all these studies, spectral changes show lipid dominance in early stages while later stages and tumors showed increased protein to lipid ratio and nucleic acids. On similar lines, early weeks of 7,12-dimethylbenz(a)anthracene-treated and control groups showed higher overlap and low classification. The classification efficiency increased progressively, reached a plateau phase and subsequently increased up to 100% by 14 weeks. The misclassifications between treated and control spectra suggested some changes in controls as well, which was confirmed by a careful reexamination of histopathological slides. These findings suggests Raman spectroscopy may be able to identify microheterogeneity, which may often go unnoticed in conventional biochemistry wherein tissue extracts are employed, as well as in histopathology. In vivo findings, quite comparable to gold-standard supported ex vivo findings, give further proof of Raman spectroscopy being a promising label-free, noninvasive diagnostic adjunct for future clinical applications.

Current concepts and future of noninvasive procedures for diagnosing oral squamous cell carcinoma--a systematic review

Background

Oral squamous cell carcinoma (OSCC) has a remarkably high incidence worldwide, and a fairly serious prognosis, encouraging further research into advanced technologies for noninvasive methods of making early diagnoses, ideally in primary care settings.

Objectives

Our purpose was to examine the validity of using advanced noninvasive technologies in diagnosis of OSCC by identifying and evaluating relevant published reports.

Data source

MEDLINE, EMBASE, and CINAHL were searched to identify clinical trials and other information published between 1990 and 10 June 2014; the searches of MEDLINE and EMBASE were updated to November 2014. Study selection: Studies of noninvasive methods of diagnosing OSCC, including oral brush biopsy, optical biopsy, saliva-based oral cancer diagnosis, and others were included.

Data extraction

Data were abstracted and evaluated in duplicate for possible relevance on two occasions at an interval of 2 months before being included or excluded.

Data synthesis

This study identified 163 studies of noninvasive methods for diagnosing OSCC that met the inclusion criteria. These included six studies of oral brush biopsy, 42 of saliva-based oral diagnosis, and 115 of optical biopsy. Sixty nine of these studies were assessed by the modified version of the QUADAS instrument. Saliva-based oral cancer diagnosis and optical biopsy were found to be promising noninvasive methods for diagnosing OSCC.

Limitation

The strength of evidence was rated low for accuracy outcomes because the studies did not report important details required to assess the risk for bias.

Conclusions

It is clear that screening for and early detection of cancer and pre-cancerous lesions have the potential to reduce the morbidity and mortality of this disease. Advances in technologies for saliva-based oral diagnosis and optical biopsy are promising pathways for the future development of more effective noninvasive methods for diagnosing OSCC that are easy to perform clinically in primary care settings.

Raman mapping of oral buccal mucosa: a spectral histopathology approach

Oral cancer is one of the most common cancers worldwide. One-fifth of the world's oral cancer subjects are from India and other South Asian countries. The present Raman mapping study was carried out to understand biochemical variations in normal and malignant oral buccal mucosa. Data were acquired using WITec alpha 300R instrument from 10 normal and 10 tumors unstained tissue sections. Raman maps of normal sections could resolve the layers of epithelium, i.e. basal, intermediate, and superficial. Inflammatory, tumor, and stromal regions are distinctly depicted on Raman maps of tumor sections. Mean and difference spectra of basal and inflammatory cells suggest abundance of DNA and carotenoids features. Strong cytochrome bands are observed in intermediate layers of normal and stromal regions of tumor. Epithelium and stromal regions of normal cells are classified by principal component analysis. Classification among cellular components of normal and tumor sections is also observed. Thus, the findings of the study further support the applicability of Raman mapping for providing molecular level insights in normal and malignant conditions.

Raman difference spectroscopy: a non-invasive method for identification of oral squamous cell carcinoma

The feasibility of shifted-excitation Raman difference spectroscopy (SERDS) as a label-free and non-invasive technique for an objective diagnosis of oral cancer (OSCC) was investigated by analyzing 12 ex vivo OSCC samples. 72 mean SERDS spectra from each three physiological tissue points and pathological lesions were correlated with the histo-pathological diagnosis. Principal component analysis (PCA) and linear discriminant analysis (LDA) showed excellent results with an area under the curve of 94.5% and a classification error of 9.7% (sensitivity: 86.1%; specificity: 94.4%). The SERDS Raman spectra of malignant and benignant tissues were discriminable with respect to the spectral features of proteins, lipids and nucleic acids. The presented method is capable of a highly accurate identification of OSCC. These findings suggest a high validity and reproducibility of SERDS combined with PCA and LDA analysis regarding oral cancer tissue.

Raman spectroscopic study of radioresistant oral cancer sublines established by fractionated ionizing radiation

Radiotherapy is an important treatment modality for oral cancer. However, development of radioresistance is a major hurdle in the efficacy of radiotherapy in oral cancer patients. Identifying predictors of radioresistance is a challenging task and has met with little success. The aim of the present study was to explore the differential spectral profiles of the established radioresistant sublines and parental oral cancer cell lines by Raman spectroscopy. We have established radioresistant sublines namely, 50Gy-UPCI:SCC029B and 70Gy-UPCI:SCC029B from its parental UPCI:SCC029B cell line, by using clinically admissible 2Gy fractionated ionizing radiation (FIR). The developed radioresistant character was validated by clonogenic cell survival assay and known radioresistance-related protein markers like Mcl-1, Bcl-2, Cox-2 and Survivin. Altered cellular morphology with significant increase (p<0.001) in the number of filopodia in radioresistant cells with respect to parental cells was observed. The Raman spectra of parental UPCI:SCC029B, 50Gy-UPCI:SCC029B and 70Gy-UPCI:SCC029B cells were acquired and spectral features indicate possible differences in biomolecules like proteins, lipids and nucleic acids. Principal component analysis (PCA) provided three clusters corresponding to radioresistant 50Gy, 70Gy-UPCI:SCC029B sublines and parental UPCI:SCC029B cell line with minor overlap, which suggest altered molecular profile acquired by the radioresistant cells due to multiple doses of irradiation. The findings of this study support the potential of Raman spectroscopy in prediction of radioresistance and possibly contribute to better prognosis of oral cancer.

Rapid detection of oral cancer using Ag–TiO2 nanostructured surface-enhanced Raman spectroscopic substrates

Developed Ag–TiO₂ based large area SERS substrate that enables spectroscopic detection and classification of oral squamous cell carcinoma with a specificity and sensitivity of 95.83% and 100%, respectively.