Investigation of the potential of Raman spectroscopy for oral cancer detection in surgical margins

Abstract

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.

In vivosubsite classification and diagnosis of oral cancers using Raman spectroscopy

“…Additionally, two recent studies have also investigated possibility of surgical demarcation using tumor and normal biopsies. 27,28 Development of diagnostic algorithms for oral cancer needs to take into consideration the anatomical di®erences between subsites. It is known that subsites in the oral cavity have distinct origins, and consequently distinct anatomical and molecular features.…”

How Close Are We to Real Time Optical Margin Control in Head and Neck Oncologic Surgery?

“…These analytic models could distinguish malignant spectra from the spectra of squamous epithelium in 75% of the cases. Structures that were most often confused with OCSCC were dysplastic epithelium, basal layers of epithelium, inflammation and capillary-rich connective tissue [76] . Certainly this study offered evidence that Raman spectroscopy can distinguish a variety of tissues, but the performance was insufficient to design an intraoperative margin protocol given the issues with spectra adjacent to the malignancy and the lack of specificity with other tissues in the region.…”

Development of a multimodal foveated endomicroscope for the detection of oral cancer

“…In an effort to overcome the limitations of COE and autofluorescence imaging, several modalities have been explored including nonlinear microscopy [16,17], Raman spectroscopy [18,19], fluorescence lifetime imaging (FLIM) [20,21], optical coherence tomography [22,23], spectroscopy with point spectrometers [24,25], multispectral imaging [26,27] and confocal microscopy [20,28]. While each of these methods delivers valuable information to aid in the diagnosis of oral cancer, studies have suggested that a combination of these techniques could improve performance [5,7,21,27].…”