Discrimination between Oral Cancer and Healthy Tissue Based on Water Content Determined by Raman Spectroscopy (original) (raw)
Related papers
Cancer research, 2016
Adequate resection of oral cavity squamous cell carcinoma (OCSCC) means complete tumor removal with a clear margin of more than 5 mm. For OCSCC 85% of the surgical resections appear inadequate. Raman spectroscopy is an objective and fast tool that can provide real-time information about the molecular composition of tissue and has the potential to provide an objective and fast intraoperative assessment of the entire resection surface. A previous study demonstrated that OCSCC can be discriminated from healthy surrounding tissue based on the higher water concentration in tumor. In this study we investigated how the water concentration changes across the tumor border towards the healthy surrounding tissue on freshly excised specimens from the oral cavity. Experiments were performed on tissue sections from 20 patients undergoing surgery for OCSCC. A transition from a high to a lower water concentration, from tumor (76% {plus minus} 8% of water) towards healthy surrounding tissue (54% {pl...
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.
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.
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: ...
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...
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
Raman spectroscopy of normal oral buccal mucosa tissues: study on intact and incised biopsies
Journal of Biomedical Optics, 2011
Oral squamous cell carcinoma is one of among the top 10 malignancies. Optical spectroscopy, including Raman, is being actively pursued as alternative/adjunct for cancer diagnosis. Earlier studies have demonstrated the feasibility of classifying normal, premalignant, and malignant oral ex vivo tissues. Spectral features showed predominance of lipids and proteins in normal and cancer conditions, respectively, which were attributed to membrane lipids and surface proteins. In view of recent developments in deep tissue Raman spectroscopy, we have recorded Raman spectra from superior and inferior surfaces of 10 normal oral tissues on intact, as well as incised, biopsies after separation of epithelium from connective tissue. Spectral variations and similarities among different groups were explored by unsupervised (principal component analysis) and supervised (linear discriminant analysis, factorial discriminant analysis) methodologies. Clusters of spectra from superior and inferior surfaces of intact tissues show a high overlap; whereas spectra from separated epithelium and connective tissue sections yielded clear clusters, though they also overlap on clusters of intact tissues. Spectra of all four groups of normal tissues gave exclusive clusters when tested against malignant spectra. Thus, this study demonstrates that spectra recorded from the superior surface of an intact tissue may have contributions from deeper layers but has no bearing from the classification of a malignant tissues point of view.
Ex vivo analysis of the oral epithelium by high-wavenumber Raman spectroscopy
International Journal of Biomedical Engineering and Technology, 2017
Raman spectroscopy at wavenumber region of 400-1800 cm-1 is an already proved promising technology for objective clinical evaluation of biological tissues to obtain their molecular fingerprint. The study of the highwavenumber region (2800-3100 cm-1) is also of interest to significantly shorten the diagnosis time due to the intense Raman signal in a narrower range. This work studies parameters dependence, Raman saturation in depth and repeatability of tissue measurements at this region and proposes three indices for quantitative diagnose in oral epithelium. Sixteen oral mucosa biopsies in different thicknesses were evaluated in varying laser powers. The nonsaturation of Raman signal up to 120 µm in depth was demonstrated. Three peaks (2874, 2926, 3056 cm-1) attributed to functional groups of interest in oral mucosa were identified from the Raman band deconvolution. The highwavenumber correspondence with the fingerprint region (400-1800 cm-1) was proven and three diagnose indices proposed to quantitatively evaluate oral epithelium tissue in routinely clinical practice.