Retinal Oxygen Saturation, Blood Flow, Vascular Function and High Resolution Morphometric Imaging in the Living Human Eye

Overview

Canadians fear loss of vision more than any other disability. Vision loss has an enormous impact on quality-of-life and is extremely costly from a societal and economic perspective. In 2001, more than 600,000 Canadians were estimated to have severe vision loss, accounting for 17% of total disability in Canada. One in 9 individuals experience severe vision loss by 65 years of age; however, this increases to 1 in 4 individuals by 75 years. The financial cost of vision loss in Canada is $15.8 billion per year. There is a general perception that vision loss is "normal with aging" but 75% of vision loss is estimated to be preventable. The major causes of severe vision loss are age-related macular degeneration (ARMD), glaucoma, particularly primary open-angle glaucoma (POAG), and diabetic retinopathy (DR). Canada is headed for an epidemic of age-related eye disease and, unless something is done to prepare for this, severe vision loss will have significant consequences in terms of societal and economic costs. Through this proposed Research Program, and in conjunction with our international academic and private sector partners, we will build and develop unique quantitative imaging technologies to permit non-invasive assessment of visual changes, structural changes in the thickness of the retina at the back of the eye and also changes in the amount of blood flowing through the blood vessels that feed the retina with oxygen. This research will add to our basic knowledge in predicting the development of sight-threatening change in patients with the three diseases, and facilitate earlier detection of the problem to help us discover earlier treatments for people with these conditions. The reliability of each imaging technology will be assessed by determining its ability to differentiate between diseased and healthy eyes. Cross-sectional analyses at yearly intervals, as well as change over time analyses, will be undertaken.

There are a number of major steps that are required prior to the utilisation of these technologies in a clinical setting. This phase of the Proposal will aim to validate and calibrate the new technologies, explore the signal-to-noise ratio of RBF and oxygen saturation parameters, generate values to define the impact of absorption, morphological fundus variation and pre-retinal autofluorescence on oxygen saturation imaging and will establish a database of healthy control imaging values for both new technologies and the reproducibility of those measurements. Note: Sample size calculations have been conducted for all aspects of this phase of the protocol, based upon our extensive retinal vascular reactivity work. We will build and develop unique quantitative imaging technologies to that will permit us to explore the physiology of retinal and choroidal perfusion and vascular regulation, and retinal oxygenation. Having completed the Validation and Calibration phase, this research will ultimately add to our basic knowledge in predicting the development of sight-threatening change in patients with the ARMD, diabetic retinopathy and primary open glaucoma, and facilitate earlier detection of the problem to help us discover earlier treatments for people with these conditions. The reliability of each imaging technology will be assessed by determining its ability to differentiate between diseased and healthy eyes. Through this proposed Research Program, we will build and develop unique quantitative imaging technologies to: Comprehensively assess the blood supply to, and vascular regulation characteristics of the posterior segment of the eye, a diagnostic capability that is currently severely limited. Assess oxygen saturation disturbances in the retina and ON that occur prior to clinically detectable changes, diagnostic capability that currently does not exist. Using the retinal blood supply and oxygen saturation parameters, we will derive net oxygen delivery to the retina and optic nerve head (ONH), a diagnostic capability that does not exist