Document Type

Theses, Ph.D

Rights

This item is available under a Creative Commons License for non-commercial use only

Disciplines

1.6 BIOLOGICAL SCIENCES, Biochemistry and molecular biology

Publication Details

Successfully submitted for theaward of PhD.

Abstract

Oral cancer is one of the most common malignancies worldwide, with over 350,000 to 400,000 new cases reported each year. Early detection, followed by appropriate treatment, can increase cure rates to 80 or 90%, and greatly improve the quality of life by minimising extensive, debilitating treatments. Usually, the clinical diagnosis of most head and neck neoplasms, including oral cancer, is performed through time-consuming and invasive biopsies followed by histological examination of the excised tissue and may present psychological trauma and risk of infection to patients. In addition, histological grading can be subjective, as it is based on subtle morphological changes. In this context, saliva is gaining interest as a diagnostic fluid, since it represents a non-invasive, safe, cheap source of complex biomolecular information that can easily be obtained from the oral cavity. In parallel, increased effort is being devoted to developing less invasive early diagnostic modalities for oral cancer, of which novel optical systems, such as Raman spectroscopy, hold great promise. The overall aim of this study is to develop methodologies for analysis of human saliva using Raman spectroscopy with a future applicability for oral cancer diagnosis. In order to optimise the measurement protocol, a number of different microscope configurations, source lasers, and substrates were trialled. Once the measurement protocol was optimised, it was validated using artificial saliva and real human saliva. The individual saliva constituent components as well as the artificial saliva itself were characterised and recorded. Following the standardisation protocol, real human whole saliva samples collected using two different collection methods were subjected to centrifugal filtration. The Raman signal from whole saliva was acquired and analysed through statistical tools, demonstrating the potential for diagnostic applications. Then, the Raman spectroscopic profiles of patients with saliva samples of different oral dysplastic pathologies, such as V epithelial oral dysplasia and oral cancer, were further analysed and spectroscopically assessed. To finalise, confounding factors, such as smoking habits and alcohol consumption, were also assessed in terms of their influence on the Raman classification of these pathologies. This research showed that, Raman spectroscopy was able to successfully discriminate stimulated saliva samples from healthy volunteers and patients with oral cancer or potentially malignant lesions, highlighting the weak influence of confounding factors, such as gender, age, smoking and alcohol consumption. However further studies are still required to improve classification among the different dysplasia grades.

DOI

https://doi.org/10.21427/6hty-gf29

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