Automated retinal microvascular quantification as a predictor of cardiovascular disease risk in later life

使用眼底照相机可以很容易地对眼睛后部的视网膜血管（动脉和静脉）进行成像。视网膜血管（特别是动脉）的形状和大小与晚年患心血管疾病的风险有关，并可能为高风险患者提供有价值的预测。最近的研究还表明，视网膜血管的大小和形状与早期的心血管危险因素（包括血压和血胆固醇）有关，这表明这些措施可能是血管健康的非侵入性标志物。成像和计算方法的进步为以越来越高的精度成像和分析视网膜血管提供了机会。然而，到目前为止，这些方法还不是完全自动化的（相对于相关数据集），并且严重依赖于操作员的参与，特别是区分动脉和静脉（其可能响应于疾病而在大小和形状上发生不同的变化）。这些问题限制了视网膜成像在心血管疾病和晚年其他关键慢性疾病，特别是眼部疾病（黄斑变性和青光眼）和2型糖尿病的大规模人群研究中的应用。该提案旨在在中年人的大型研究（包括UK Biobank - UKBB）中完全自动化视网膜图像中血管的识别和表征，包括动脉和静脉的识别。图像（来自超过70，000名参与者的近150，000张图像）将用于改进我们现有的视网膜血管尺寸和形状测量方法（包括血管宽度和迂曲度的测量，即，扭转/转动的测量），并检查它们与晚年心血管疾病风险的关系。中年人经常看家庭医生，并给予心血管疾病的风险评分（即，心脏病发作的风险），基于许多简单的测量（例如，年龄、性别、血压和血胆固醇）;这通常决定治疗（例如，BP药物，他汀类药物）处方。该项目汇集了一个成熟的多学科小组，其共同目标是开发可靠，自动化和高效的视网膜图像分析软件，该软件可免费获得，在大量视网膜图像中生成视网膜血管的丰富特征。将通过在小组内纳入适当的统计专门知识，确保创新性地使用从数千名参与者中产生的大规模数据。目前正在使用该小组内部开发的软件进行图像分析，本提案旨在将该软件开发成可供所有人使用的形式。该项目的潜在科学价值是可观的：（1）筛查：视网膜血管特征可以提供异常的测量，这些异常是晚年整体血管健康和严重血管疾病的预测因子。除了已建立的筛查工具，这可能会发现需要早期治疗的“高危人群”，从而减少与心血管事件相关的并发症。(2)新资源：所产生的经验证的视网膜测量结果将成为添加到这些队列中的数据，从而使更广泛的科学界能够进行进一步的研究。(3)协作：专家组的组合预计将在这些软件工具的性能方面产生阶跃变化。(4)通过使该小组开发的软件可供公众使用，确保了这项工作的长期科学价值。这确保了检查视网膜血管作为疾病风险和结果（循环系统和眼部疾病）预测因子的价值得到尽可能广泛的科学界的认可。

Retinal vessels (both arteries and veins) on the back of the eye are easily imaged using fundus cameras. The shape and size of retinal vessels (particularly arteries), have been related to risk of cardiovascular disease in later life and may provide valuable prediction of individuals at high risk of disease. Recent studies have also shown that retinal vessel size and shape are associated with cardiovascular risk factors (including blood pressure and blood cholesterol) from an early age, suggesting that these measures may be non-invasive markers of the health of blood vessels. Advances in imaging and computational methods are providing opportunities to image and analyse retinal vessels with increasing precision. However, to date these methods are not fully automated (with respect to the relevant datasets) and rely heavily on operator involvement, especially to distinguish arteries from veins (which may change in size and shape differently in response to disease). These problems limit the application of retinal imaging in large population studies of cardiovascular disease and other key chronic diseases in later life, particularly ocular disease (macular degeneration and glaucoma) and type 2 diabetes. This proposal aims to fully automate identification and characterisation of vessels in retinal images, including identification of arteries and veins, in large studies of middle aged adults (including UK Biobank - UKBB). Images (nearly 150,000 images from over 70,000 participants) will be used to refine our existing approaches to measurement of retinal vessel size and shape (which include both measures of vessel width and tortuosity, i.e., a measure of twisting / turning), and to examine their association with risk of cardiovascular disease in later life. Middle age adults are often seen by family doctors and given a risk score for cardiovascular disease (i.e., risk of heart attack), based on a number of simple measures (e.g., age, gender, blood pressure and blood cholesterol); this often determines whether treatments (e.g., BP medications, statins) are prescribed. The project brings together a well-established, multidisciplinary group with the shared aim of developing reliable, automated and efficient retinal image analysis software, which is freely available, generating a rich characterization of the retinal vessels in large numbers retinal images. Innovative use of the large-scale data generated from thousands of participants, will be ensured by the inclusion of appropriate statistical expertise within the group. Current image analysis is underway using software developed within the group, and this proposal seeks to develop the software into a usable form available to all. The potential scientific value of the project is appreciable: (1) Screening: retinal vessel characteristics may provide measures of abnormality that are predictors of overall vascular health and serious vascular disease in later life. In addition to established screening tools, this may identify "at-risk groups" in need of earlier treatment and therefore reduce the complications associated with cardiovascular events. (2) New resources: the validated retinal measurements generated will become themselves data to add to these cohorts, enabling further investigation by the wider scientific community. (3) Collaboration: Combination of specialist groups is expected to generate a step-change improvement in performance of these software tools. (4) Long-term scientific value of the work is assured by making the software developed by the group, available for public use. This ensures that the value of examining retinal vessels as a predictor of disease risk and outcome (both circulatory and ocular disease) is realised by the widest possible scientific community.