The ability to diagnose melanoma prior to metastasis could revolutionise the clinical environment. This would allow improved patient care via monitoring, rapid follow up of high-risk cases and improve patient mortality and morbidity. Biomedical spectroscopy can diagnose a wide range of pathologies however no study has made it from the laboratory into a clinical setting as a regulated spectroscopic test. To facilitate translation this thesis describes: • Development of the optimal methodology for the quantification of protein biomarkers. It was demonstrated that concentrations as low as 0.66 ± 0.05 mg mL-1, with a linearity of 0.992, can be achieved within patient samples. • Analysis of liquid serum samples led to discrimination of cancer vs. non-cancer with a sensitivity of 95.4 % and a specificity of 81.8 %, compared to the air-dried data set, which achieved 92.4 % and 84.4 %, respectively. Analysis of liquid samples removes the rate determining air drying step. Digitally drying the liquid spectrum was investigated to determine if an improvement could be achieved. The optimal result was achieved through the use of an extended multiplicative scatter correction algorithm, providing a sensitivity of 91.2 % and a specificity of 77.3 %. • Discussion and investigation of a longitudinal melanoma biobank containing 311 samples, from 110 patients. The use of recently developed, novel, clinical attenuated total reflectance-Fourier transform infrared (ATR-FTIR) technology was explored and achieved the ability to determine BRAF status in melanoma patients with a sensitivity and specificity of 77.7 % and 75.0 %, respectively.Finally, developments towards spectroscopic precision medicine and categorising of melanoma patients, based on analysis of their individual disease and treatment journeys, was completed. This thesis showcases the development of ATR-FTIR spectroscopy to allow for clinical translation and enable detection and monitoring of melanoma, for close monitoring of high-risk patients and the progression of therapeutic methods.
|Date of Award||8 Jan 2019|
- University Of Strathclyde
|Sponsors||University of Strathclyde|
|Supervisor||Matthew Baker (Supervisor) & Duncan Graham (Supervisor)|