Novel Quantitative Analysis Using Optical Imaging (VELscope) and Spectroscopy (Raman) Techniques for Oral Cancer Detection (original) (raw)
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Raman Spectroscopy Analysis for Optical Diagnosis of Oral Cancer Detection
Journal of Clinical Medicine
Raman spectroscopy (RS) is widely used as a non-invasive technique in screening for the diagnosis of oral cancer. The potential of this optical technique for several biomedical applications has been proved. This work studies the efficacy of RS in detecting oral cancer using sub-site-wise differentiation. A total of 80 samples (44 tumor and 36 normal) were cryopreserved from three different sub-sites: The tongue, the buccal mucosa, and the gingiva of the oral mucosa during surgery. Linear discriminant analysis (LDA) and quadratic discriminant analysis (QDA) were used with principal component analysis (PCA) to classify the samples and the classifications were validated by leave-one-out-cross-validation (LOOCV) and k-fold cross-validation methods. The normal and tumor tissues were differentiated under the PCA-LDA model with an accuracy of 81.25% (sensitivity: 77.27%, specificity: 86.11%). The PCA-QDA classifier model differentiated these tissues with an accuracy of 87.5% (sensitivity: ...
Near-Infrared Raman Spectroscopy for Oral Carcinoma Diagnosis
Photomed Laser Surg, 2006
Raman spectroscopy has been applied as a diagnostic tool for the detection of cancers, due to its sensitivity to the changes in molecular composition and conformation that occurs in malignant tissues. The detection of weak Raman signals from biotissues becomes easier by FT-Raman due to fluorescence suppression. Methods: A carcinogen (7,12-dimethybenz[a]anthracene [DMBA]) was applied daily in the oral pouch of 21 hamster to induce oral carcinoma. After 14 weeks, the fragments of squamous cell carcinomas and oral normal tissue were collected and analyzed by FT-Raman spectroscopy, using a 1064-nm Nd:YAG laser line as an excitation source. A total of 123 spectra were obtained and divided in normal and malignant tissue groups, and analyzed statistically through principal components analysis (PCA) and classified using Mahalanobis distance. Results: Major differences between normal and malignant spectra seem to arise from the composition, conformational, and structural changes of proteins, and possible increase of its content in malignant epithelia. An algorithm based on PCA was able to separate the samples into two groups-normal and carcinoma. For the algorithm training group, 91% sensitivity and 69% specificity were observed, while the prospective group had 100% sensitivity and 55% specificity. Conclusion: The algorithm based on PCA has the potential for classifying Raman spectra and can be useful for detection of dysplastic and malign oral lesion. 348
Analytical Chemistry, 2015
Tumor-positive resection margins are a major problem in oral cancer surgery. High-wavenumber Raman spectroscopy is a reliable technique to determine the water content of tissues which may contribute to differentiate between tumor and healthy tissue. The aim of this study was to examine the use of Raman spectroscopy to differentiate tumor from surrounding healthy tissue in oral squamous cell carcinoma. From fourteen patients undergoing tongue resection for squamous cell carcinoma, the water content was determined at 170 locations on freshly excised tongue specimens using the Raman-bands of the OH-stretching vibrations (3350-3550cm-1) and of the CH-stretching vibrations (2910-2965cm-1). The results were correlated with histopathological assessment of hematoxylin and eosin stained thin tissue sections obtained from the Raman measurement locations. The water content values from squamous cell carcinoma measurements were significantly higher than from surrounding healthy tissue (p-value <0.0001). Tumor tissue could be detected with a sensitivity of 99% and a specificity of 92% using a cutoff water content value of 69%. Because the Raman measurements are fast and can be carried out on freshly excised tissue without any tissue preparation, this finding signifies an important step towards the development of an intra-operative tool for tumor resection guidance with the aim of enabling oncological radical surgery and improvement of patient outcome.
The Potential of Raman Spectroscopy in the Diagnosis of Dysplastic and Malignant Oral Lesions
Cancers
Early diagnosis, treatment and/or surveillance of oral premalignant lesions are important in preventing progression to oral squamous cell carcinoma (OSCC). The current gold standard is through histopathological diagnosis, which is limited by inter- and intra-observer errors and sampling errors. The objective of this work was to use Raman spectroscopy to discriminate between benign, mild, moderate and severe dysplasia and OSCC in formalin fixed paraffin preserved (FFPP) tissues. The study included 72 different pathologies from which 17 were benign lesions, 20 mildly dysplastic, 20 moderately dysplastic, 10 severely dysplastic and 5 invasive OSCC. The glass substrate and paraffin wax background were digitally removed and PLSDA with LOPO cross-validation was used to differentiate the pathologies. OSCC could be differentiated from the other pathologies with an accuracy of 70%, while the accuracy of the classifier for benign, moderate and severe dysplasia was ~60%. The accuracy of the cl...
Raman Micro-Spectroscopy for Rapid Screening of Oral Squamous Cell Carcinoma
Oral Surgery, Oral Medicine, Oral Pathology and Oral Radiology, 2015
Raman spectroscopy can provide a molecular-level fingerprint of the biochemical composition and structure of cells with excellent spatial resolution and could be useful to monitor changes in composition for dysplasia and early, non-invasive cancer diagnosis (carcinoma in situ), both ex-vivo and in vivo. In this study, we demonstrate this potential by collecting Raman spectra of nucleoli, nuclei and cytoplasm from oral epithelial cancer (SCC-4) and dysplastic (pre-cancerous, DOK) cell lines and from normal oral epithelial primary cell cultures, in vitro, which were then analysed by principal component analysis (PCA) as a multivariate statistical method to discriminate the spectra. Results show significant discrimination between cancer and normal cell lines. Furthermore, the dysplastic and cancer cell lines could be discriminated based on the spectral profiles of the cytoplasmic regions. The principal component loading plot, which elucidates the biochemical features responsible for the discrimination, showed significant contributions of nucleic acid and proteins for nucleolar and nuclear sites and variation in features of lipids for the cytoplasmic area. This technique may provide a rapid screening method and have potential use in the diagnosis of dysplasia and early, non-invasive oral cancer, the treatment of which involves much less extensive and complex surgery and a reduction in associated co-morbidity for the patient.
Investigation of the potential of Raman spectroscopy for oral cancer detection in surgical margins
Laboratory Investigation, 2015
The poor prognosis of oral cavity squamous cell carcinoma (OCSCC) patients is associated with residual tumor after surgery. Raman spectroscopy has the potential to provide an objective intra-operative evaluation of the surgical margins. Our aim was to understand the discriminatory basis of Raman spectroscopy at a histological level. In total, 127 pseudocolor Raman images were generated from unstained thin tissue sections of 25 samples (11 OCSCC and 14 healthy) of 10 patients. These images were clearly linked to the histopathological evaluation of the same sections after hematoxylin and eosin-staining. In this way, Raman spectra were annotated as OCSCC or as a surrounding healthy tissue structure (i.e., squamous epithelium, connective tissue (CT), adipose tissue, muscle, gland, or nerve). These annotated spectra were used as input for linear discriminant analysis (LDA) models to discriminate between OCSCC spectra and healthy tissue spectra. A database was acquired with 88 spectra of OCSCC and 632 spectra of healthy tissue. The LDA models could distinguish OCSCC spectra from the spectra of adipose tissue, nerve, muscle, gland, CT, and squamous epithelium in 100%, 100%, 97%, 94%, 93%, and 75% of the cases, respectively. More specifically, the structures that were most often confused with OCSCC were dysplastic epithelium, basal layers of epithelium, inflammation-and capillary-rich CT, and connective and glandular tissue close to OCSCC. Our study shows how well Raman spectroscopy enables discrimination between OCSCC and surrounding healthy tissue structures. This knowledge supports the development of robust and reliable classification algorithms for future implementation of Raman spectroscopy in clinical practice.
Journal of Biophotonics, 2020
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 potenti...
Scientific Reports, 2016
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. Molecular-level tissue characterization is highly potent for cancer diagnosis. As a tissue starts becoming cancerous, specific biomolecules are overexpressed or aberrantly expressed, which can be used as cancer molecular markers. If we can detect these molecular markers spectroscopically, it would lead to a new molecular-level cancer diagnosis with high objectivity. Keratin-family proteins (M.W. 40000 ~ 67000) are major components of fibrous structural proteins in epithelial cells. They play important roles in the formation of cytoskeleton network and help maintain the structural integrity of cellular morphology 1,2. Several studies have shown that keratin is aberrantly expressed in many different types of human epithelial cancers including skin cancer, lung cancer, breast cancer, cervix cancer, esophagus cancer, salivary gland cancer and oral cancer 3-6. In the present study, we focus on oral cancer. Oral squamous cell carcinoma (OSCC) is one of the most common cancers (95% in oral malignancy) in oral cavity. Keratin is a well-established molecular marker of OSCC; oral malignancy can be diagnosed by detecting the variations in keratin expression between OSCC and normal oral tissues 7,8. At present, keratin in oral tissues is detected and analyzed by means of immunohistochemistry (IHC). However, IHC is expensive, time-consuming and needs specialist attention. An economic and straightforward alternative for keratin detection in oral tissues is longed for. Spectroscopic methods for cancer diagnosis have made a rapid progress in recent years. In particular, Raman spectroscopy has been proven to be effective for discriminating cancerous against normal oral tissues 9-19. Spectroscopic discriminations of cancer tissues in these previous studies are mostly based on Principal
Diagnosis of head and neck squamous cell carcinoma using Raman spectroscopy: tongue tissues
Journal of Raman Spectroscopy, 2012
is a powerful optical technique capable of providing the structural information at the molecular level. Thus, the technique can be used to detect biochemical changes associated with carcinogenesis and identify the biomolecules involved in cancer. We studied the Raman spectral characteristics of normal, carcinoma in situ, and invasive squamous cell carcinoma (SCC) tissues of tongue, and identified the spectral features that can discriminate these three tissue types. We found that the intensities of Raman bands assignable to tryptophan increase while those attributable to protein keratin decrease when tissue changes from normal to invasive SCC. The variation observed in the intensity of many discriminating peaks including those of tryptophan and keratin as tissue changes from normal to carcinoma in situ and then to invasive SCC suggests that Raman spectroscopy can be used to monitor progression of the disease. We have also analyzed the data with multivariate statistical methods such as principal component analysis and discriminant function analysis. These chemometric methods clearly separate the whole data into three distinct groups consistent with results of pathology. We were able to detect with 91% success rate the normal and carcinoma in situ tissues and with 89% accuracy the invasive SCC tissues of the tongue.