Method development: Raman spectroscopy‐based histopathology of oral mucosa. (15th May 2013)

• Record Type: Journal Article
• Authors: Cals, Froukje L. J.; Bakker Schut, Tom C.; Koljenović, Senada; Puppels, Gerwin J.; de, Robert J. Baatenburg
• Is Part Of: Journal of Raman spectroscopy. Volume 44:Number 7(2013:Jul.)
• Page Start: 963
• Page End: 972
• Publication Date: 2013-05-15
• Subjects: Raman spectroscopy -- Periodicals; 535.846
• DOI: 10.1002/jrs.4318
• Languages: English
• ISSNs: 0377-0486

Abstract

<abstract abstract-type="main"> <title> <x xml:space="preserve">Abstract</x> </title> <p>An earlier and more accurate detection of (small) cancerous and precancerous lesions in the oral cavity is essential to improve the prognosis of oral squamous cell carcinomas. Raman spectroscopy is being pursued as a potential method to realize this improvement, since the technique provides objective information on a biochemical level and can be used for real‐time guidance of the diagnostic procedure.</p> <p>Since oral mucosal tissue is inhomogeneous and comprises different layers and histological structures, a good understanding of the signal contributions of the individual layers and structures is required for an accurate interpretation of <italic>in vivo</italic> tissue spectra measurement volumes. The aim of this study was to create a standardized method to collect and analyse the spectral contributions of individual histopathological structures in oral mucosa.</p> <p>The method is based on Raman microspectroscopic mapping of unstained frozen tissue sections and subsequent histopathological annotation of the features in the resulting Raman images. The obtained annotated reference spectra were used as input in an unsupervised hierarchical cluster analysis in order to determine the spectral characteristics and variance within one histo(patho)logical structure.</p> <p>The described method resulted in an annotated database of Raman spectral characteristics of individual histopathological structures encountered in oral tissue. This database can be used as input for the development of classification and quantification algorithms, in order to achieve a high specificity and sensitivity for clinical diagnostic instruments. Additionally, this database can be used to optimize the exact location and measurement volume of <italic>in vivo</italic> measurements. Copyright © 2013 John Wiley & Sons, Ltd.</p> </abstract>