Abstract
Raman and infrared spectroscopy are optical spectroscopic techniques that use light scattering (Raman) and light absorption (infrared) to probe the vibrational energy levels of molecules in tissue samples. Using these techniques, one can gain an insight into the biochemical composition of cells and tissues by looking at the spectra produced and comparing them with spectra obtained from standards such as proteins, nucleic acids, lipids and carbohydrates. As a result of optical spectroscopy being able to measure these biochemical changes, diagnosis of cancer could take place faster than current diagnostic methods, assisting and offering pathologists and cytologists a novel technology in cancer screening and diagnosis.The purpose of this study is to use both spectroscopic techniques, in combination with multivariate statistical analysis tools, to analyze some of the major biochemical and morphological changes taking place during carcinogenesis and metastasis in lymph nodes and to develop a predictive model to correctly differentiate cancerous from benign lymph nodes taken from oesophageal cancer patients.The results of this study showed that Raman and infrared spectroscopy managed to correctly differentiate between cancerous and benign oesophageal lymph nodes with a training performance greater than 94% using principal component analysis (PCA)-fed linear discriminant analysis (LDA). Cancerous nodes had higher nucleic acid but lower lipid and carbohydrate content compared to benign nodes which is indicative of increased cell proliferation and loss of differentiation.With better understanding of the molecular mechanisms of carcinogenesis and metastasis together with use of multivariate statistical analysis tools, these spectroscopic studies will provide a platform for future development of real-time (in surgery) non-invasive diagnostic tools in medical research.