Discrimination of oesophageal transformation stages to adenocarcinoma in human tissue samples using Raman microspectroscopy

Abstract

The gold standard for diagnosis of oesophageal adenocarcinoma still requires histological examination of mucosal biopsies obtained at oesophagogastroduodenoscopy. Herein, Raman spectral analysis of ex vivo oesophageal tissue was performed, including all classifications to oesophageal adenocarcinoma. This study adds further validation to previous human oesophageal tissue studies identifying the potential for Raman spectroscopy in differentiating between all classes in oesophageal transformation to oesophageal adenocarcinoma [normal; inflammatory; Barrett’s oesophagus; low-grade dysplasia; high-grade dysplasia; and, oesophageal adenocarcinoma]. Tissue spectra were analysed using principal component analysis-quadratic discriminant analysis (PCA-QDA), successive projections algorithm-quadratic discriminant analysis or genetic algorithm-quadratic discriminant analysis. The variables selected were then used for discriminating the tissue classes based on the unique spectral "fingerprints" of their biochemical composition. Accuracy tests including sensitivity and specificity were determined. The best model using PCA-QDA successfully classified normal, inflammatory, Barrett’s oesophagus, low-grade dysplasia, high-grade dysplasia and oesophageal adenocarcinoma tissues with 91%–100% accuracy, 90%-100% sensitivity, and 71%–100% specificity. Amongst the main distinguishing features in the pre-processed Raman spectra, the wavenumbers at 1296 cm-1 (CH2 deformation), 1448 cm-1 (CH2/CH3 deformation) and 1668 cm−1 (Amide I) were found to increase in amplitude with increasing differentiation. Raman spectroscopy exhibits promise in distinguishing the stages leading to oesophageal adenocarcinoma and may play a role in surveillance programs in premalignant conditions such as Barrett’s oesophagus.