Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.735738
Title: Biomarker discovery in coronary heart disease with ultra-Widefield retinal imaging : presence and risk
Author: Robertson, Gavin
Awarding Body: University of Edinburgh
Current Institution: University of Edinburgh
Date of Award: 2017
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Abstract:
Retinal imaging with a fundus camera or scanning laser ophthalmoscope (SLO) allows a fast, non-invasive view to the body’s microvasculature. Evidence suggests that features associated with retinal blood vessels (for example, narrowing of arteries and increased vascular tortuosity) measured near to the optic disc are early biomarkers of disease such as diabetes, hypertension (HT) and cardiovascular disease. Ultra-widefield (UWF) ophthalmic imaging allows unique views of peripheral locations as well as the posterior pole, potentially facilitating a more comprehensive study of the state or health of the microvasculature than is afforded by conventional retinal imaging. It is envisaged that this will reveal new candidate biomarkers derivable from the retina which could help identify the presence of disease or improve risk stratification for serious illness. In this thesis, 532 individuals were recruited from a trial evaluating the added benefit of using computed tomography (CT) imaging in the diagnosis of coronary heart disease (CHD) to measure atherosclerotic plaque in the arteries of the heart muscle tissue. The trial participants were deeply phenotyped which allowed access to additional information including: presence and severity of CHD, hypertensive status, presence of diabetes, age, gender, and smoking status (all risk factors commonly associated with CHD). After CT imaging patients were invited for undilated UWF ophthalmic imaging using an Optos P200C SLO. To accurately measure features of blood vessels indicative of microvascular health or disease in these images required the development of a novel semi-automatic computerised technique to segment and analyse the retinal vasculature. This involved implementation of a supervised vessel segmentation algorithm utilising multi-scale matched filters, a neural network classifier and hysteresis thresholding. A true positive rate (TPR) of 0.702 (and standard deviation of 0.059), false positive rate (FPR) of 0.011 (0.006) and accuracy (Acc) of 0.965 (0.006) was achieved by the algorithm. This compared to TPR of 0.674 (0.062), FPR of 0.017 (0.004), and Acc of 0.957 (0.006) for state-of-the-art fundus camera vessel segmentation applied to UWF SLO. After segmentation and prior to the measurements of retinal vessel parameters, the distortions introduced by the instrument mapping the 3D retinal surface onto a 2D image plane were also accounted for utilising an established technique. This is especially important for measuring in the periphery of UWF images and has not previously been reported for biomarker discovery. Measurements from UWF SLO were compared between those participants with CHD (where a reduction in arterial width was hypothesised based on existing research with fundus cameras into cardiovascular disease), and those without to investigate whether a difference between the two groups existed. After appropriate statistical correction for confounding variables (i.e. age, gender, and hypertensive status) the results did not show a statistically significant difference for presence of CHD or for risk stratification. However, the analysis techniques that were developed in this thesis do allow a rapid investigation of retinal vascular parameters in UWF SLO. This has application to a number of other diseases, such as HT, where a more pronounced change to the appearance of vessels is anticipated, and to different areas of the peripheral retina not previously measurable with standard imaging techniques and existing algorithms.
Supervisor: MacGillivray, Thomas ; van Beek, Edwin ; Gray, Calum Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.735738  DOI: Not available
Keywords: retina ; segmentation ; cardiovascular disease
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