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High contrast images of uterine tissue derived using Raman microspectroscopy with the empty modelling approach of multivariate curve resolution-alternating least squares

Research output: Contribution to journalJournal article

Published

Journal publication date2011
JournalAnalyst
Journal number23
Volume136
Number of pages10
Pages4950-4959
Original languageEnglish

Abstract

Approaches that allow one to rapidly understand tissue structure and functionality in situ remain to be developed. Such techniques are required in many instances, including where there is a need to remove with a high degree of confidence positive tumour margins during surgical excision. As biological tissue has little contrast, gold standard confirmation of surgical margins is conventionally undertaken by histopathological diagnosis of tissue architecture via optical microscopy. Vibrational spectroscopy techniques, when coupled to sophisticated computational analyses, are capable of constructing bio-molecular contrast images of unstained tissue. To assess the relative applicability of a range of candidate algorithms to distinguish the in situ bio-molecular structures of a complex tissue, the empty modelling approach of multivariate curve resolution-alternating least squares (MCR-ALS) was compared to hierarchical cluster analysis (HCA) or principal component analysis (PCA). Such chemometric analyses were applied to Raman images of benign (tumour-adjacent) endometrium, stage I and stage II endometrioid cancer. Re-constructed images from the in situ bio-molecular tissue architectures highlighted features associated with glandular epithelium, stroma, glandular lumen and myometrium. Of the tested chemometric analyses, MCR-ALS provided the best bio-molecular contrast images, superior to those derived following HCA or PCA, with clear and defined margins of histological features. Iteratively-resolved spectra identified wavenumbers responsible for the contrast image. Wavenumbers 1234 cm(-1) (Amide III), 1390 cm(-1) (CH(3) bend), 1675 cm(-1) (Amide I/lipid), 1275 cm(-1) (Amide III), 918 cm(-1) (proline) and 936 cm(-1) (proline, valine and proteins) were responsible for generating the majority of the contrast within MCR-ALS-generated images. Applications of sophisticated computational analyses coupled with vibrational spectroscopy techniques have the potential to lend novel functionality insights into bio-molecular structures in vivo.