In vivo Raman spectroscopy for detection of oral neoplasia: A pilot clinical study

Abstract

We report a pilot study carried out to evaluate the applicability of in vivo Raman spectroscopy for differential diagnosis of malignant and potentially malignant lesions of human oral cavity in a clinical setting. The study involved 28 healthy volunteers and 171 patients having various lesions of oral cavity. The Raman spectra, measured from multiple sites of normal oral mucosa and of lesions belonging to three histopathological categories, viz. oral squamous cell carcinoma (OSCC), oral submucous fibrosis (OSMF) and leukoplakia (OLK), were subjected to a probability based multivariate statistical algorithm capable of direct multi-class classification. With respect to histology as the gold standard, the diagnostic algorithm was found to provide an accuracy of 85%, 89%, 85% and 82% in classifying the oral tissue spectra into the four tissue categories based on leave-one-subject-out cross validation. When employed for binary classification, the algorithm resulted in a sensitivity and specificity of 94% in discriminating normal from the rest of the abnormal spectra of OSCC, OSMF and OLK tissue sites pooled together.

In vivosubsite classification and diagnosis of oral cancers using Raman spectroscopy

“…Previous studies on¯nger-print and high wavenumber region have demonstrated that buccal and labial mucosa, keratinized or masticatory mucosa and specialized mucosa on the tongue can be classi¯ed as distinct clusters of subsites. [34][35][36] While some studies indicate that these subsite-anatomical di®erences confound the healthy and pathological discrimination, 37 other studies have stated that the inherent anatomical di®erences may not hinder healthy vs pathological classi¯cation. 47 In the present study, Raman spectroscopic di®erences between the three common subsites of oral cancer development in the Indian subcontinent-buccal mucosa, movable mucosa of the lip and tongue were evaluated.…”

“…Further, the authors also suggest the use of anatomy-matched algorithms to increase discrimination between healthy and abnormal conditions. 37 There exist ambiguities in the anatomical classi¯cation of the buccal mucosa, tongue and lip subsites. Thus, in the present study, spectral contrast between the anatomical sites buccal mucosa, lip and tongue were investigated¯rst in healthy as well di®erent pathological conditions.…”

Non-Invasive Techniques for Detection and Diagnosis of Oral Potentially Malignant Disorders

“…In vivo Raman spectroscopy has shown efficacy in the detection of normal tissue, PMDs, cancer, and even of early changes such as cancer fieldeffects or malignancy-associated changes in the oral cavity (Singh et al 2012;Krishna et al 2014). However, the clinical applications of Raman spectroscopy have been limited by both the difficulty of capturing inherently weak tissue Raman signals and the relatively slow speed of spectrum acquisitions (Guze et al 2009).…”

Detection of Suspicious Tissue Lesions

“…The essential prerequisites for RS are biochemical changes that happen during neoplastic transformations in tissues [2]. Consequently, pathologic Raman spectra can largely be separated based on protein, DNA, and lipid (phospholipids and fatty acids) related spectral features.…”