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Title: Tissue characterisation by Raman spectroscopies
Author: Bourbousson, Manon Fanny
ISNI:       0000 0004 9355 0633
Awarding Body: University of Nottingham
Current Institution: University of Nottingham
Date of Award: 2020
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Cancer has a major impact on society in the United Kingdom and across the world. Lung cancer is the most common cancer worldwide. Advances in lung cancer diagnosis are essential to reduce the mortality burden. The current histopathology methods for the diagnosis of human lung tissues require highly specialised staff, are labour-intensive, and expensive. They could benefit from the development of new imaging techniques. In this work, we demonstrate the ability to use Raman spectroscopy as a non-destructive method for the analysis of the molecular composition of human lung tissues ex vivo. For different aspects of cancer research, non-destructive techniques are appreciated because they do not induce damage to the sample measured making them a possible additional technique in the cancer diagnosis routine. Raman spectroscopy is a chemical analysis method that detects molecular differences in biological tissue samples. It is a fast, accurate, and non-destructive approach well-suited for cancer detection. It has already been established that Raman spectroscopy may provide an improvement in diagnostic accuracy while at the same time reducing subjectivity in cancer studies compared to the standard techniques currently used in hospitals. The thesis starts by describing the experimental instrumentations developed to achieve Raman mapping measurements of biological tissues. The study began with the investigation of lung tissues by Raman spectroscopy mapping. The instrument we designed was assembled at Nottingham City Hospital. The system was aligned and calibrated with standard materials presenting established Raman shift frequencies. Then it was optimised minimizing the Raman shift error, and fully characterised in terms of spatial and depth resolution, and stability. The instrument allowed the collection of Raman spectral maps of fresh lung tissues, including cancerous samples, with high-quality spectra recorded in mapping mode with 20 μm step size and an acquisition time of 1 s per spectrum. A detailed spectral analysis was achieved showing the ability to extract molecular information from 18 freshly excised lung tissues including malignant and non-malignant tissues. We present the molecular markers detected in the Raman signal that differentiate tumour tissue from healthy tissue and from necrotic tissue. The precision of our instrument allowed us to detect bands never reported before in the literature. Then, our aim was to implement modifications to the experimental instrument design to limit the collection of tissue autofluorescence in the Raman spectra. Because the light backscattered from a sample is likely to exhibit directional dependency, we designed a new instrument allowing us to select the direction of collection of the signal, known as a polarised Raman micro-spectrometer. We performed the steps of alignment, calibration, and optimisation, by taking into account the polarisation dependence. The performance of this instrument was firstly tested by investigating tissue samples with a significantly lower fluorescence level than lung tissue. 15 skin samples from 7 patients were investigated. The calculation of the average depolarisation ratio coefficient revealed molecular vibrations specificities of connective tissue in different local environments. Additionally, principal component analysis (PCA) was performed emphasising the variation of biomolecules orientations in connective tissue for various samples. Finally, we present a new application of the use of polarised Raman spectroscopy based on varying the polarisation direction for the collection of a reduced fluorescent background in the case of lung tissues. The results from both spectroscopy techniques developed have validated the potential of Raman spectroscopy in tissue imaging for label-free monitoring of biomolecular variations in tissues and their future clinical translation in cancer research.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: QP1 Physiology (General) including influence of the environment ; RC 254 Neoplasms. Tumors. Oncology (including Cancer)