Investigation of associations between retinal microvascular parameters and albuminuria in UK Biobank: a cross-sectional case-control study.

BACKGROUND: Associations between microvascular variation and chronic kidney disease (CKD) have been reported previously. Non-invasive retinal fundus imaging enables evaluation of the microvascular network and may offer insight to systemic risk associated with CKD. METHODS: Retinal microvascular parameters (fractal dimension [FD] - a measure of the complexity of the vascular network, tortuosity, and retinal arteriolar and venular calibre) were quantified from macula-centred fundus images using the Vessel Assessment and Measurement Platform for Images of the REtina (VAMPIRE) version 3.1 (VAMPIRE group, Universities of Dundee and Edinburgh, Scotland) and assessed for associations with renal damage in a case-control study nested within the multi-centre UK Biobank cohort study. Participants were designated cases or controls based on urinary albumin to creatinine ratio (ACR) thresholds. Participants with ACR ≥ 3 mg/mmol (ACR stages A2-A3) were characterised as cases, and those with an ACR < 3 mg/mmol (ACR stage A1) were categorised as controls. Participants were matched on age, sex and ethnic background. RESULTS: Lower FD (less extensive microvascular branching) was associated with a small increase in odds of albuminuria independent of blood pressure, diabetes and other potential confounding variables (odds ratio [OR] 1.18, 95% confidence interval [CI] 1.03-1.34 for arterioles and OR 1.24, CI 1.05-1.47 for venules). Measures of tortuosity or retinal arteriolar and venular calibre were not significantly associated with ACR. CONCLUSIONS: This study supports previously reported associations between retinal microvascular FD and other metabolic disturbances affecting the systemic vasculature. The association between retinal microvascular FD and albuminuria, independent of diabetes and blood pressure, may represent a useful indicator of systemic vascular damage associated with albuminuria

Automated quantification of retinal vessel morphometry in the UK Biobank Cohort

The following topics are dealt with: feature extraction; learning (artificial intelligence); image classification; image segmentation; computer vision; object detection; feedforward neural nets; image colour analysis; image representation; medical image processing

Suitability of UK biobank retinal images for automatic analysis of morphometric properties of the vasculature

To assess the suitability of retinal images held in the UK Biobank--the largest retinal data repository in a prospective population-based cohort--for computer assisted vascular morphometry, generating measures that are commonly investigated as candidate biomarkers of systemic disease.Non-mydriatic fundus images from both eyes of 2,690 participants--people with a self-reported history of myocardial infarction (n=1,345) and a matched control group (n=1,345)--were analysed using VAMPIRE software. These images were drawn from those of 68,554 UK Biobank participants who underwent retinal imaging at recruitment. Four operators were trained in the use of the software to measure retinal vascular tortuosity and bifurcation geometry.Total operator time was approximately 360 hours (4 minutes per image). 2,252 (84%) of participants had at least one image of sufficient quality for the software to process, i.e. there was sufficient detection of retinal vessels in the image by the software to attempt the measurement of the target parameters. 1,604 (60%) of participants had an image of at least one eye that was adequately analysed by the software, i.e. the measurement protocol was successfully completed. Increasing age was associated with a reduced proportion of images that could be processed (p=0.0004) and analysed (p<0.0001). Cases exhibited more acute arteriolar branching angles (p=0.02) as well as lower arteriolar and venular tortuosity (p<0.0001).A proportion of the retinal images in UK Biobank are of insufficient quality for automated analysis. However, the large size of the UK Biobank means that tens of thousands of images are available and suitable for computational analysis. Parametric information measured from the retinas of participants with suspected cardiovascular disease was significantly different to that measured from a matched control group