Mudariki, Temba (2016) Diagnostic Neuropathology of Brain Tumours using Biophotonics and Spectrometry. Doctoral thesis, University of Central Lancashire.
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Abstract
Classification of tumours such as gliomas, which are on a continuous spectrum of histology and malignancy into distinct categories is still a challenge using histopathology. There has been significant advances in the techniques used to fight cancer in the past two decades. A number of studies have looked at different approaches to improve the accuracy in diagnosis using histopathology. This study evaluated a number of techniques to compliment histopathology. One study looked at vibrational spectroscopy, Raman and attenuated total reflection-fourier transform infrared (ATR-FTIR) looking at brain tumour cell lines. This study investigated the potential application of vibrational spectroscopy in the segregation of different types of brain tumours using two tumour cell lines, U87MG, 1321N1 and a control, SVGP12. Another study looked at two approaches, elemental profiling of both tissue and serum using inductively coupled plasma-mass spectrometry. Trace elements increase or deficiency has been linked to cancer development and progression. The final study looked at the diagnostic application of Raman spectroscopy to distinguish between gliomas, meningiomas, medulloblastoma and several other brain tumours from histological normal brain tissue from brain tumour patients used as controls. The three cell lines U87MG, SVGP12 and 1321N1 were cultured and grown on calcium fluoride slides in triplicates. Spectra from each cell line was taken using both Raman and ATR-FTIR. The spectra was then analysed using multivariate statistics. In the elemental profiling study serum and tissue samples from 55 patients with brain tumours were collected and analysed using ICP-MS. The elemental data was then evaluated using multivariate statistics to investigate significant differences. In the analysis of human brain tumours tissue blocks of both tumour and histological normal brain that were formalin fixed and paraffin embedded (FFPE) were processed and mounted on low-E slides, dewaxed using Xylene, washed with alcohol and water before storage at room temperature until analysis. Raman and ATR-FTIR were able to separate U87MG, SVGP12 and 1321N1 with very high classification accuracy. All the brain tumour groups investigated showed a deficiency of Mg, Fe, Cu, and Zn concentrations against reported levels from healthy individuals in the literature. Raman spectroscopy coupled with multivariate statistics was able to distinguish between normal brain tissue and normal brain tumour tissue used as controls. Classification of gliomas based on the degree of malignancy was also apparent with very high classification accuracy. Spectral panels were developed that can be used as biomarkers in the diagnosis of brain tumours. Raman and Infrared spectroscopy are types of vibrational spectroscopy which have the potential to be used as diagnostic tools in neuropathology. They provide an intrinsic molecular fingerprint of the sample based on the interaction of light. The panels can accurately identify and classify specific brain tumours alleviating the need to use complex statistical models. Raman and ATR-FTIR were able to elucidate chemical information from the samples which was used to differentiate the three cell lines with very high classification accuracy. Diagnosis of a brain tumour is not always a straight forward process and the current techniques used lack the desired level of precision in diagnosis and cytoreductive surgery.
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