Multi-centre Raman spectral mapping of oesophageal cancer tissues: a study to assess system transferability.

The potential for Raman spectroscopy to provide early and improved diagnosis on a wide range of tissue and biopsy samples in situ is well documented. The standard histopathology diagnostic methods of reviewing H&E and/or immunohistochemical (IHC) stained tissue sections provides valuable clinical information, but requires both logistics (review, analysis and interpretation by an expert) and costly processing and reagents. Vibrational spectroscopy offers a complimentary diagnostic tool providing specific and multiplexed information relating to molecular structure and composition, but is not yet used to a significant extent in a clinical setting. One of the challenges for clinical implementation is that each Raman spectrometer system will have different characteristics and therefore spectra are not readily compatible between systems. This is essential for clinical implementation where classification models are used to compare measured biochemical or tissue spectra against a library training dataset. In this study, we demonstrate the development and validation of a classification model to discriminate between adenocarcinoma (AC) and non-cancerous intraepithelial metaplasia (IM) oesophageal tissue samples, measured on three different Raman instruments across three different locations. Spectra were corrected using system transfer spectral correction algorithms including wavenumber shift (offset) correction, instrument response correction and baseline removal. The results from this study indicate that the combined correction methods do minimize the instrument and sample quality variations within and between the instrument sites. However, more tissue samples of varying pathology states and greater tissue area coverage (per sample) are needed to properly assess the ability of Raman spectroscopy and system transferability algorithms over multiple instrument sites.

Imaging live cells grown on a three dimensional collagen matrix using Raman microspectroscopy.

Three dimensional collagen gels have been used as matrices for the imaging of live cells by Raman spectroscopy. The study is conducted on a human lung adenocarcinoma (A549) and a spontaneously immortalized human epithelial keratinocyte (HaCaT) cell line. The lateral resolution of the system has been estimated to be <1.5 µm making it possible to access the subcellular organization. Using K-means clustering analysis, it is shown that the different subcellular compartments of individual cells can be identified and differentiated. The biochemical specificity of the information contained in the Raman spectra allows the visualization of differences in the molecular signature of the different sub-cellular structures. Furthermore, to enhance the chemical information obtained from the spectra, principal component analysis has been employed, allowing the identification of spectral windows with a high variability. The comparison between the loadings calculated and spectra from pure biochemical compounds enables the correlation of the variations observed with the molecular content of the different cellular compartments.