8.1Introduction

Retinal image analyses aiming to examine early manifestation of ocular diseases in telemedicine (or ‘telescreening’) for diabetic retinopathy [1–4], glaucoma [5, 6] and retinopathy of prematurity [7–10] have been extensively investigated. Advancements in digital imaging (e.g. high-resolution images, image compression and image enhancement) and network technology (e.g. encrypted network and high-speed data connection) have allowed health screening facilities to link remote screening sites and ophthalmologists efficiently and securely. Whilst it is widely accepted that retinal imaging is useful for the detection of ‘eye diseases’, there is another emerging potential of retinal imaging as a novel test for the prediction of cardiovascular disease (CVD).

R. Kawasaki, M.D., MPH, Ph.D.

Retinal Vascular Imaging Centre, Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, University of Melbourne, 32 Gisborne Street, East Melbourne, 3002, VIC, Australia

Faculty of Medicine, Yamagata University,

Yamagata, Japan

Yong Loo Lin School of Medicine, Singapore Eye Research Institute, National University of Singapore, Singapore National Eye Centre, 11 Third Hospital Avenue, Singapore 168751, Singapore

e-mail: ophwty@nus.edu.sg

T.Y. Wong, M.D., MPH, Ph.D. ( )

Retinal Vascular Imaging Centre, Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, University of Melbourne, 32 Gisborne Street, East Melbourne, 3002, VIC, Australia

Recent epidemiologic studies have revealed that retinal vascular signs are associated with increased risk of CVD. And these observations offer a new concept that assessment for the presence or severity of retinal signs is potentially useful in identifying and screening persons with increased risk of subclinical and thus clinical CVD. In this chapter, we review this emerging evidence supporting the concept of utilizing retinal imaging in the prediction of CVD.

8.1.1Retinal Imaging

for Systemic Diseases

The retinal vasculature is unique in allowing direct and non-invasive observation of vascular health in vivo. Therefore, retinal vascular signs have been investigated for the possibility as a marker for systemic vascular disease. Early studies have been mainly focused on the association between hypertension and retinal vascular signs, and the concept of linking retinal vessel signs and CVD in this context is not new. In 1939, Keith, Wagner and Barker reported that persons with retinal vascular signs had a higher mortality from cardiovascular complications secondary to severe hypertension [11]. Since then, for nearly half a century, those retinal vessel signs have been thought to be only reflecting acute or chronic changes secondary to hypertension. In the last decade, however, longitudinal epidemiologic studies have re-evaluated novel aspect of retinal imaging, and some forms of retinal vessel changes

might be precedent of development of hypertension and diabetes and of pre-clinical and clinical CVD. This has been achieved by advances in computer-assisted digital retinal imaging techniques enabling us to capture and quantify subtle morphological changes in retinal vessels, which were not detectable in conventional grading by human graders. To date, there have been accumulated evidence supporting that retinal imaging can be applicable to risk prediction of various CVD including stroke, [12–16] coronary heart disease, myocardial infarction [12–14, 17–20], peripheral artery disease and CVD mortality [14, 17, 21–27].

8.1.2Homology Between Retinal and Systemic Microvasculature

Why do retinal changes provide information to identify CVD risks? There are common characteristics in the structure and function of the retinal microvasculature and microvasculature elsewhere in the body. For example, histopathological studies suggested that retinal vascular signs are closely related to pathological microvascular changes in other organs such as hypertensive retinal vascular changes in the brain [28] and myocardium [29]. Recent studies have also demonstrated that persons with lacunar stroke have functional alterations in the retinal haemodynamics [30], reduced retinal arteriolar-venule passage time [31]; acute patients with lacunar stroke were shown to be more likely to have retinal vascular abnormalities [32]. Pathologic changes in the retinal arteries parallel abnormal changes in the small cerebral arteries causing white matter lesions (WMLs) and lacunae [33– 36]. The close relationship between retinal and cerebral vascular changes is not surprising given the embryological, morphological and functional homologies due to their common origin from the internal carotid artery. Retinal vascular changes also parallel pathology in the coronary circulations, for example, retinal arteriolar narrowing strongly associated with the presence and severity of angiographic coronary artery occlusion [37, 38]. Further studies to determine the extent to which the retinal microvasculature is a

surrogate for microcirculation elsewhere in the body will strengthen the rationale for using retinal imaging to assess risk profile of CVD.

8.1.3Need for More Precise CVD Risk Prediction

What is the rationale using retinal imaging in CVD risk prediction? Why do we need to use retinal imaging in a risk prediction of CVD, whilst there are well-known risk factors for CVD such as hypertension, high cholesterol and smoking? Indeed, CVD is still the leading cause of death and a major public health problem not only in developed countries but also in emerging developing countries [39]. Identification of persons with high risk of CVD at asymptomatic pre-clinical stage holds the key to allow timely implementation of preventative interventions such as lifestyle modification (e.g. diet, physical exercise) and medications (e.g. cholesterol-lowering drugs) to effectively prevent CVD.

The current standard of risk prediction models such as the Framingham risk score [40] is provided as simple checklists and well adopted in various primary health-care guidelines. In the Framingham risk score, for example, 10-year risk of CVD in adults free of CVD is predicted by age, diabetes, smoking, blood pressure, cholesterol and body mass index [40]. And depending on their absolute risk, people with high risk of CVD may then be offered interventions such as blood pressure and cholesterol–lowering treatment, in addition to advice about relevant health behaviours (e.g. smoking cessation, physical activity). However, these current models and standards in CVD risk prediction are not precise enough to identify all the persons at risk of CVD. It is reported that up to 50% of CVD cases cannot be predicted by the Framingham risk score model alone, and it has a potential to either underestimate high-risk persons or overestimate low-risk persons [41]. Because current evidence shows that individuals’ susceptibility to CVD varies substantially, various new risk factors or markers are sought to improve risk prediction of CVD.

Retinal imaging has potential advantages as a test for CVD risk prediction. Firstly, it is based on direct examination of retinal vascular health which has a homology to microcirculation in the other parts of the body. Therefore, retinal imaging provides detailed information about the existence or absence of actual vascular damage. Secondly, it is accessible and repeatable as it only requires simple non-invasive procedure to collect sample (i.e. standard fundus photography). Thus, it will be well accepted in the general community screening. Thirdly, it has a capacity to be incorporated with telemedicine, allowing persons at remote areas to be screened with digital fundus camera without physical transport. Given emerging increase of CVD in developing countries, screening for CVD risk based on retinal imaging in the framework of telemedicine has a potential to become a fascinating alternative to conventional, laboratory-based test and risk assessment.

(ETDRS) scale [42]. The original protocol for the ETDRS scale was designed for a detailed assessment to determine the presence or severity of diabetic retinopathy, and it requires a strict procedure of fundus photography (i.e. seven fields, stereo fundus images recorded onto 35-mm colour reversal film, taken through pharmacologically dilated pupil) [42]. Although this scale is highly reliable to determine detailed severity of diabetic retinopathy in research settings, it is not suitable for a screening targeting general population. Therefore, modified or simplified retinal photography methods utilizing non-stereo images, less number of photographic fields or digital format have been explored as an alternative to the original ETDRS protocol. These modifications have been shown to be well tolerated in screening for general population [2, 4, 43–48]. For example, screening for retinopathy in general population is often done with a single macular disc–centred image. With this simplified screening, 7% with any retinopathy and 3% with sight-threatening retinopathy would

Signs Used for CVD Risk

Prediction (Fig. 8.1)

The retinal imaging linked to CVD can be broadly categorized into two domains: ‘retinal microvascular signs’ and ‘retinal vessel biometry’.

8.2.1Retinal Microvascular Signs

Retinopathy signs (Fig. 8.1a) consist of microaneurysms, retinal haemorrhages, hard exudates, soft exudates and more severe signs such as venous beading, intra-retinal microvascular abnormalities and retinal neovascularization. In persons with diabetes, these signs are commonly observed as ‘diabetic retinopathy’. However, the mild forms of these signs (e.g. microaneurysms and retinal haemorrhages) are also commonly observed in non-diabetic population with 5–10% prevalence rate. There have been numbers of different grading schemes for retinopathy, especially for diabetic retinopathy. The most

some patients have retinopathy lesions only in peripheral retina, whilst there are no retinopathies present in central field. However, in terms of overall sensitivity and specificity, there were no significant difference between using full-field images and single central-field image alone [48]. There are other focal retinal arteriolar signs, such as arterio-venous nicking (AVN) (Fig. 8.1b), focal arteriolar narrowing (FAN) (Fig. 8.1c) and enhanced arteriolar wall reflex.

8.2.2Retinal Vessel Biometry

Several semi-automated computer programs to measure retinal vascular calibre have been developed and applied to risk assessment for CVD. The most widely used program might be the one developed for the Atherosclerosis Risk in Communities (ARIC) study aiming to examine the retinal vascular signs of generalized arteriolar narrowing. This program measures individual arteriolar and venular calibres from digitized

Fig. 8.1 Retinopathy, retinal microvascular signs and retinal vessel calibre measurements. (a) Retinopathy (retinal haemorrhage arrow). (b) Arterio-venous nicking (arrow).

(c) Focal arteriolar narrowing (arrow). (d) Computerassisted measurement of retinal vessels. (e) Automated retinal vessel segmentation and measurement

retinal photographs centred on the optic disc. Photographs of sufficient quality for grading can be obtained using non-mydriatic digital fundus cameras. With the assistance of a trained grader identifying arterioles and venules, the program measures all retinal vessels passing through the region between 1/2 and 1 disc diameter from the optic disc margin (Fig. 8.1d). The cross-sectional diameter of retinal arterioles and venules is measured repeatedly (Fig. 8.1e) and summarized using formulae to obtain values representing the estimated calibre of central retinal artery (the central retinal artery equivalent [CRAE]) and central retinal vein (the central retinal vein equivalent [CRVE]) as well as their dimensionless quotient (arterio-venous ratio [AVR]) [49–51]. Reproducibility of this measurement has been shown to be high in both interand intra-grader agreement and utilized in several large-scale epidemiological studies [52, 53].

In the process of retinal vessel calibre measurements to be widely validated in epidemiologic

studies, the original formulae [49–51], developed for the ARIC study, utilized to combine individual retinal vascular diameters to estimate CRAE and CRVE have revised accordingly [54]. The original Parr-Hubbard formulae for CRAE and CRVE were derived from sample retinal images with branching points, calculating the relationship between individual trunk vessel and their respective branch vessels using a root mean square deviation model that best fits the observed data. Knudtson et al. further modified the ParrHubbard formulae [54] and demonstrated an efficient method using the biggest six vessels to represent CRAE and CRVE.

One limitation of retinal vessel calibre measurement is that currently available researches have largely focused on differences in mean retinal vessel calibre between groups of people. To allow the use of individual measurement of retinal vessel calibre as a potential risk marker for CVD, however, it should provide specific information that enables an assessment of absolute risk in individual