Lancaster, Gemma and Stefanovska, Aneta (2016) Oscillations in microvascular flow : their relationship to tissue oxygenation, cellular metabolic function and their diagnostic potential for detecting skin melanoma - clinical, experimental and theoretical investigations. PhD thesis, Lancaster University.
2016lancasterphd.pdf - Published Version
Available under License Creative Commons Attribution-NonCommercial-NoDerivs.
Download (37MB)
Abstract
Tumour vasculature is known to be inefficient and abnormal due to poorly regulated angiogenesis during tumour growth. This leads to irregular patterns of blood flow which are spatially and temporally heterogeneous. Many investigations into the characteristics of tumours are invasive and performed on animal models. However, continuous technological and theoretical advancement is leading to the use of non-invasive imaging techniques, providing in vivo information on humans. Here, data recorded using laser Doppler flowmetry (LDF) in malignant melanoma and control lesions are analysed using techniques designed for application to non-stationary, time-varying data. Many studies utilising LDF have previously revealed increased blood flow in malignant lesions, but very little attention has been paid to the dynamics of this blood flow, or how it changes over time. As it has been demonstrated previously that the oscillations observed within blood flow data are physiologically significant, failure to extract these characteristics loses information about the underlying dynamical system from which the blood flow data were recorded. Significant differences in blood flow dynamics are revealed and used in the development of a diagnostic test for melanoma. In addition to the characterization of the blood flow dynamics in melanoma, possible causes for the observed changes are investigated and related to two widely observed characteristics of cancer, intermittent hypoxia and altered cellular energy metabolism. The former is explored through the analysis of blood flow and oxygenation data recorded during dry static apnoea, whilst the latter is modelled using coupled phase oscillators.