A Study of Hypertensive Retinopathy Changes for Stroke Prediction

Hypertensive retinopathy is an ailment that is highly connected to hypertension which help in stroke prediction. The presence of hypertensive retinopathy is diagnosed through image processing on the fundus image to identify the possible microvascular retinal abnormalities signs that lead to hypertension. Arterio-Venous Ratio (AVR) value is one of the main indicator of hypertensive retinopathy, useful for grading severity of hypertensive retinopathy and for prediction of risk of stroke. Image preprocessing were performed in this work to extract vessels in fundus image. In this thesis, fundus images were acquired from VICAVR and DRIVE databases

Do retinal microvascular abnormalities shed light on the pathophysiology of lacunar stroke?

Background. Lacunar strokes account for 25% of all ischaemic stroke but the exact nature of the causative cerebral small vessel abnormality remains unknown. Pathological studies are technically difficult and brain imaging cannot adequately characterise the cerebral small vessels. The retinal blood vessels are of similar size and physiology to the cerebral small vessels and may act as a surrogate marker for these cerebral small vessels. We therefore investigated retinal microvascular abnormalities in lacunar stroke. Methods. We performed a systematic review of retinal microvascular abnormalities in lacunar stroke to clarify associations and identify where further research was required. We then established a cohort of patients presenting with lacunar stroke with cortical stroke controls to investigate differences in retinal microvascular abnormalities between stroke subtypes. All patients had MRI brain at presentation and digital retinal photography of both eyes. We investigated the prevalence of retinopathy (hard and soft exudates or haemorrhages/microaneurysms), focal arteriolar narrowing and arteriovenous nicking . We developed, validated and used novel semi-automated techniques for measuring retinal arteriolar and venular widths, retinal arteriolar geometry (branching co-efficients (change in arteriolar cross sectional area across a bifurcation) and branching angles) and fractal dimensions (reflecting branching complexity) of the vasculature. We also assessed MRI parameters in lacunar stroke. We used multivariable analysis to correct for baseline imbalances in vascular risk factors. Results. From the systematic review we demonstrated that retinal microvascular abnormalities are associated with incident and prevalent stroke but that in general, strokes were inadequately characterised and there were no data regarding retinal microvascular abnormalities in ischaemic stroke subtypes. We recruited 253 patients, 129 lacunar strokes and 124 cortical strokes, mean age 68 years. We found no difference in the prevalence of retinopathy, arteriovenous nicking, focal arteriolar narrowing or arteriolar widths between lacunar and cortical stroke subtypes. We found that venules were wider in lacunar stroke. We found no differences in arteriolar branching co-efficients or arteriolar branching angles between lacunar and cortical strokes but found that deep white matter white matter hyperintensities on MRI were associated with increased branching co-efficients and periventricular white matter hyperintensities associated with decreased branching co-efficients. We found that the fractal dimension of the vascular tree was decreased in lacunar stroke. Furthermore we found that enlarged perivascular spaces on MRI are associated with lacunar stroke and white matter disease. Conclusions. We have clearly demonstrated that retinal microvascular abnormalities differ between lacunar and cortical stroke suggesting that a distinct small vessel vasculopathy may cause lacunar stroke. We have also identified MR markers of lacunar stroke. These results suggest that venular disease (a hitherto underresearched area) may play a role in the pathophysiology of lacunar stroke. Retinal microvascular abnormalities can act as markers for cerebral small vessel disease. We plan collaborative analyses with colleagues who have performed similar studies to further assess retinal abnormalities in lacunar stroke

The Genotype-Phenotype Correlation of the key features of Non-Proliferative Diabetic Retinopathy

Diabetic Retinopathy (DR) is a leading cause of visual impairment but its pathophysiology is not well understood. Moderate/severe non-proliferative DR (NPDR) is characterised by the presence of three features: deep haemorrhages (DH), venous beading (VB) and intraretinal microvascular abnormalities (IRMA). They are grouped together as risk factors for progression to sight threatening DR. It remains unclear whether these individual features have similar pathophysiologies, and whether they respond equally to anti-VEGF, a new therapy for NPDR. Optomap images of 504 NPDR eyes were examined to evaluate the distribution and prevalence of these three features. DNA samples from 199 patients with NPDR and 397 diabetic patients with no DR were collected. The genotype of specific candidate genes were evaluated in patients with DR, VB or IRMA vs no DR. Optical coherence tomography angiography (OCTA) images of 30 patients were examined for focal ischemia adjacent to VB and IRMA. The responses of these three features to anti-VEGF treatment were also re-examined in the images from the CLARITY trial. DH were present in most cases of NPDR. VB and IRMA did not always co-exist in the same eye and when they do, were often in different locations. VEGF, TGFb-1 and ARHGAP22 polymorphisms (ischaemia-related genes) were more common in patients with DR and IRMA, but not VB. Areas of focal ischaemia were more frequently adjacent to IRMA than to VB. DH and IRMA responded to anti-VEGF therapy but VB did not. These findings suggest that VB and IRMA do not share the same pathophysiology, and that IRMA are more likely to be ischaemic driven. Nonetheless, some IRMA may not be driven by ischaemia as they have no adjacent ischaemia on OCTA, do not carry the specific genotype, and do not respond to anti-VEGF. Furthermore, patients with VB may not benefit from anti-VEGF therapy

Assessment of retinal vascular geometry in normal and diabetic subjects

M.D.Diabetic retinopathy is the most common microvascular complication of diabetes mellitus and the leading cause of blindness in persons from age 20 to 74. The relative risk of blindness in persons with diabetes has been reported to be 5.2 times the risk of those without diabetes. The fundus abnormalities described in diabetic retinopathy result from structural damage to the microvasculature wall with subsequent leakage or as a result of retinal ischaemia with secondary overproduction of vascular growth factors. Several clinical and screening classifications schemes have been developed to categorize and quantify the severity of each of the retinopathic features based on the degree of retina involvement. The ultimate goals of these classification schemes have been to provide a system by which the natural history of the disease and the risk of progression of retinopathy and visual loss can be identified and the subsequent response to interventions can be evaluated to improve patient care. The present strategies for dealing with diabetic retinopathy address retinopathy that is already established. However, recent studies - supported by computer based imaging analysis – have focused on changes in retinal vascular caliber and demonstrated various associations with increased risk of diabetes and predicted the onset of microvascular retinal complications. This suggests that other structural and geometrical parameters might also be utilised, which can provide more information regarding the retinal vascular network. Few studies have reported different changes in retinal vascular geometry with age, systemic hypertension and peripheral vascular diseases. The objective of this thesis is to analyse the retinal vascular geometrical features in normal subjects and evaluate its role in diabetic subjects with different stages of diabetic retinopathy. For this purpose, a semi-manual vascular analysis technique is designed to measure and analyse the different retinal vascular geometrical parameters and ratios. The developed technique performance and precision is compared to other available manual and semi-manual vascular analysis techniques.The various sources of variability in retinal geometrical measurements are then evaluated, including observer’s measurement errors, variations in image capture, and potential short term changes in the subjects’ vascular geometrical features. The second step of this work is to perform a detailed analysis of the retinal vascular geometry in normal subjects, including the topographic distribution of different geometrical measurements across the fundus, the effect of different demographic and clinical factors, and the stability of measurements between both eyes. The next step evaluates the retinal vascular geometry in diabetic subjects with different grades of diabetic retinopathy to determine any changes of geometrical features with advancement of retinopathic stages. The results demonstrate significant associations of changes in vascular structural and geometrical features with increased stages of diabetic retinopathy. Finally, the predictive value of retinal vascular geometry analysis and its practical role on the individual level is analysed for a sample of subjects who progressed from no retinopathy to proliferative retinopathy as compared to a sample of subjects with no sign of progression. The preliminary results suggest that geometrical changes trend can be detected on the individual level with progression of diabetic retinopathy and those differences can be noted between progressors and non-progressors at baseline. In conclusion, this thesis describes novel retinal vascular geometrical markers indicative of establishment of advancing diabetic retinopathy, together with a potential predictive role in determining risk of future progression to proliferative retinopathy

Quantitative retinal traits and their association with cardiovascular disease and cardio-metabolic genetic variants in people with type 2 diabetes

Introduction: Type 2 diabetes (T2D) is one of the most prevalent noncommunicable diseases in the world and its cardiovascular complications present a huge socio-economic burden. In 2015, in the UK alone, 3.8 million people have been diagnosed with T2D and cardiovascular disease accounts for almost 1.7 million episodes throughout the country. Early diagnosis of cardiovascular disease in people with T2D thus becomes critical. The retina gives a unique opportunity to study the human microcirculation, which can then offer insights into the pathophysiology of cardiovascular disease. By using semi-automatic software, retinal images can provide quantitative traits derived from the microvasculature. Previous research has found that arteriolar and venular calibres are associated with cardiovascular outcomes such as hypertension and stroke. Moreover, retinal vascular tortuosity, a novel quantitative biomarker which measures the degree to which blood vessels visible in the retina twist and turn, has been associated with traditional cardiovascular risk factors in the general population. However, this area needs to be further explored, especially in the population with T2D and in prospective analyses. Aims: To determine whether quantitative retinal traits such as vessel widths, vessel tortuosity and multifractal dimensions are associated with the subsequent development of major cardiovascular events such as ischaemic heart disease and stroke in people with T2D. Also, to use a genome-wide association approach to investigate if these quantitative retinal traits are associated with cardio-metabolic genetic variants, which could help identify novel biomarkers of cardiovascular disease for future research. Methods: Analyses used the Edinburgh Type 2 Diabetes Study, a prospective cohort of 1066 men and women with T2D aged 60-75 years at baseline with eight years of follow-up for cardiovascular events. A total of 1028 retinal images from baseline were analysed using the semi-automatic retinal software VAMPIRE (Vascular Assessment and Measurement Platform for Images of the Retina). Cross-sectional analyses including ANOVA and Chi-square test were performed along with prospective analysis using Cox regression. Additionally, a genome-wide association study was performed to explore the association of 12 quantitative retinal traits with cardio-metabolic genetic variants. Imputation of variants included in the MetaboChip array was used. Results: In an unadjusted model, there was a significant association between arteriolar tortuosity and incident stroke (Hazard Ratio (HR) 1.26; 95% CI 1.02, 1.57; p=0.03). This association remained significant after full adjustment for age, sex, cardiovascular risk factors (body mass index, HbA1c, total cholesterol, duration of diabetes, renal dysfunction) and previous cardiovascular events (HR 1.26; 95% CI 1.01, 1.58; p=0.04). Multifractal dimensions, a novel retinal biomarker which provides an insight into vascular geometry, was inversely associated with incident stroke (unadjusted HR 0.73; 95% CI 0.57, 0.94; p=0.01). This association also remained significant after adjustment for age, sex, cardiovascular risk factors and previous cardiovascular event (HR 0.73; 95% CI 0.56, 0.94 p=0.02). Associations between other retinal traits and stroke, and between traits and ischaemic heart disease, tended not to be statistically significant, especially after multivariable adjustment. The genome-wide association analysis of arteriovenous ratio (ratio of arteriolar to venular vessel width) revealed a genome wide significant locus, rs73198094 (p = 5.27 x 10-8), an intergenic variant located between ASAH1 and LOC101929066 genes in chromosome 8. The ASAH1 gene has been associated with atrial fibrillation. Although no further single nucleotide polymorphisms reached genome-wide significance, some additional promising findings emerged. Analysis for retinal arteriolar width revealed a genome-wide suggestive intronic locus, rs4944903 (p= 8.5x10-7), of the gene POLD3 in chromosome 11. Identified loci for minimum arteriolar tortuosity, rs7991332 (p=1.54 x 10-6) and rs2172724 (p=2.46 x10-6), are located in the COL4A2 gene in chromosome 13 and another identified variant, rs7319323 (p=3.53 x 10-6), is located in an intron of the neighbouring COL4A1 gene. Previous studies showed the relevance of these genes including an association with stroke and intracerebral haemorrhage. These two genes encode collagen protein chains, which are major components of the vascular basement membrane. Another promising variant identified was the rs34013641 locus, associated with minimum venular tortuosity (p=2.81 x 10- 6), which is located in the MYH11 gene in chromosome 2. This gene encodes smooth muscle myosin heavy chain protein, which is highly expressed in human arteries. Finally, identified loci for the multifractal dimension D0, rs10963694 (p=8.53 x 10-7) and rs4977506 (p=4.95 x 10-6), located on the ADAMTSL-1 gene in chromosome 9, are also strong candidates in the pathophysiology of vascular disorders. Conclusions: In older people with T2D, arteriolar tortuosity and multifractal dimensions were significantly and independently associated with incident stroke. GWAS findings for these and other quantitative retinal traits offer insight into pathophysiological changes of the vasculature, which may result in cardiovascular disease. These findings, in the context of further research, could potentially be used to reveal biological mechanisms related to major cardiovascular complications of T2D and to guide efforts on prevention and early interventions

Automated retinal analysis

Diabetes is a chronic disease affecting over 2% of the population in the UK [1]. Long-term complications of diabetes can affect many different systems of the body including the retina of the eye. In the retina, diabetes can lead to a disease called diabetic retinopathy, one of the leading causes of blindness in the working population of industrialised countries. The risk of visual loss from diabetic retinopathy can be reduced if treatment is given at the onset of sight-threatening retinopathy. To detect early indicators of the disease, the UK National Screening Committee have recommended that diabetic patients should receive annual screening by digital colour fundal photography [2]. Manually grading retinal images is a subjective and costly process requiring highly skilled staff. This thesis describes an automated diagnostic system based oil image processing and neural network techniques, which analyses digital fundus images so that early signs of sight threatening retinopathy can be identified. Within retinal analysis this research has concentrated on the development of four algorithms: optic nerve head segmentation, lesion segmentation, image quality assessment and vessel width measurements. This research amalgamated these four algorithms with two existing techniques to form an integrated diagnostic system. The diagnostic system when used as a 'pre-filtering' tool successfully reduced the number of images requiring human grading by 74.3%: this was achieved by identifying and excluding images without sight threatening maculopathy from manual screening

Retinal vessel segmentation using textons

Segmenting vessels from retinal images, like segmentation in many other medical image domains, is a challenging task, as there is no unified way that can be adopted to extract the vessels accurately. However, it is the most critical stage in automatic assessment of various forms of diseases (e.g. Glaucoma, Age-related macular degeneration, diabetic retinopathy and cardiovascular diseases etc.). Our research aims to investigate retinal image segmentation approaches based on textons as they provide a compact description of texture that can be learnt from a training set. This thesis presents a brief review of those diseases and also includes their current situations, future trends and techniques used for their automatic diagnosis in routine clinical applications. The importance of retinal vessel segmentation is particularly emphasized in such applications. An extensive review of previous work on retinal vessel segmentation and salient texture analysis methods is presented. Five automatic retinal vessel segmentation methods are proposed in this thesis. The first method focuses on addressing the problem of removing pathological anomalies (Drusen, exudates) for retinal vessel segmentation, which have been identified by other researchers as a problem and a common source of error. The results show that the modified method shows some improvement compared to a previously published method. The second novel supervised segmentation method employs textons. We propose a new filter bank (MR11) that includes bar detectors for vascular feature extraction and other kernels to detect edges and photometric variations in the image. The k-means clustering algorithm is adopted for texton generation based on the vessel and non-vessel elements which are identified by ground truth. The third improved supervised method is developed based on the second one, in which textons are generated by k-means clustering and texton maps representing vessels are derived by back projecting pixel clusters onto hand labelled ground truth. A further step is implemented to ensure that the best combinations of textons are represented in the map and subsequently used to identify vessels in the test set. The experimental results on two benchmark datasets show that our proposed method performs well compared to other published work and the results of human experts. A further test of our system on an independent set of optical fundus images verified its consistent performance. The statistical analysis on experimental results also reveals that it is possible to train unified textons for retinal vessel segmentation. In the fourth method a novel scheme using Gabor filter bank for vessel feature extraction is proposed. The ii method is inspired by the human visual system. Machine learning is used to optimize the Gabor filter parameters. The experimental results demonstrate that our method significantly enhances the true positive rate while maintaining a level of specificity that is comparable with other approaches. Finally, we proposed a new unsupervised texton based retinal vessel segmentation method using derivative of SIFT and multi-scale Gabor filers. The lack of sufficient quantities of hand labelled ground truth and the high level of variability in ground truth labels amongst experts provides the motivation for this approach. The evaluation results reveal that our unsupervised segmentation method is comparable with the best other supervised methods and other best state of the art methods

Novel methods in retinal vessel calibre feature extraction for systemic disease assessment

Retina and its vascular network have unique branching characteristics morphology of which will change as a result of some systemic diseases, including hypertension, stroke and diabetes. Therefore, retinal image has been used as non-invasive screening window for risk assessment and prediction of such disease condition especially at the baseline. The assessment is based on a number of features among which vessel diameter (both individual and summary) and fractal dimension (FD) are the ones mostly associated with risk of diabetes and stroke. The association is linked to the higher risk of diabetes and stroke in people with narrower retinal arteriole diameter or change in overall fractal dimension independent of any risk factor (i.e. blood pressure, cardiovascular risk factors). Diameter measurement requires vessel edges to be located and tracked however; accurate edge perception is subject to image contrast, shadows, lighting condition and even presence of retinopathy legions close to vessel boundaries. This will lead to imprecision and inconsistencies between different automatic measurement techniques and may affect the significance of its association with disease condition in risk-assessment studies. As accuracy and success of diameter measurement is subject to large variations due to image artifacts it may not be suitable for fully automatic applications. In order to compensate for such error, at first two novel automatic vessel diameter measurement techniques were proposed and validated which were more robust in the presence of such image artifacts compared to similar methods. However, sometimes the exact edge location and actual diameter value is not of interest. In most case-control studies, it is of importance to comparatively evaluate the variations in retinal vessel diameter as a sign of retinopathy such as arteriolar nicking as an example of hypertensive retinopathy. Vessel diameter is often required to be compared with a reference value in many analytical assessments for diagnostic purpose. This includes monitoring the diameter variations of a specific vessel segment within single subject overtime or across multiple subjects. This helps ophthalmologists to understand whether it has undergone any significant change and perhaps associate it with a disease abnormality. A technique that can effectively quantify that change without being impaired by image artifacts is of more importance and one of the rationales of this study. This research hypothesized an edge independent solution for quantifying diameter variations when the actual diameter value is not required and proposed a new feature based on fractal analysis of vessel cross-section profile as a time series signal. This feature provides a link between FD as a global measure of the complexity and diameter variation as local property of a specific vessel segment. The clinical application of this feature has been validated on two population studies which showed promising result for assessment of mild non-proliferative diabetic retinopathy and 10-year stroke. This research work has also investigated whether the FD of retinal microvasculature would be affected by cyclic pulsations of retinal vessels and whether ECG synchronization is required prior to taking fundus images to compensate for this potential source of variations

Automatic computation of the arteriovenous ratio and assessment of its effectiveness as a prognostic indicator in hypertension

[Resumen] La retina es la única parte del cuerpo humano en donde se pueden observar los vasos sanguíneos directamente de una forma no invasiva mediante un examen de fondo de ojo. De esta manera, la imagen de la retina mediante las técnicas de procesamiento de imágenes se convirtió en un campo de clave para el diagnóstico precoz de varias enfermedades sistémicas que provocan alteraciones visibles en dicha imagen. Así, alteraciones en el ancho de los vasos retinianos se asocian con patologías tales como diabetes o hipertensión. De hecho, el estrechamiento de las arterias constituye un indicio precoz de la hipertensión arterial sistémica, siendo una característica del grado I de la retinopatía hipertensiva de acuerdo con la clasificación de Keith-Wagener-Barker. En este sentido, se han realizado esfuerzos para desarrollar programas asistidos por ordenador para medir con precisión los cambios en el ancho de los vasos a través del índice arteriovenoso (IAV), es decir, la relación entre los calibres de las arterias y las venas. Sin embargo, aunque estos sistemas se han usado en muchos estudios con fines de investigación, su aplicabilidad en la práctica clínica diaria es todavía discutida. En este trabajo, se propone una nueva metodología para el cálculo del IAV con el fin de estratificar el riesgo cardiovascular de los hipertensos. Por un lado, se ha desarrollado un método completamente automático para estimar el IAV en una imagen de fondo de ojo de un paciente. Por otro lado, se propone un sistema para monitorizar el IAV del paciente a lo largo del tiempo. Para este fin, las mediciones del IAV en las diferentes imágenes adquiridas sobre el mismo ojo del paciente en diferentes fechas se estiman usando el mismo conjunto de vasos medidos en las mismas áreas. Por lo tanto, la mediciones obtenidos de esta manera son comparables y precisas, debido a que son independientes en el conjunto de vasos seleccionados para el cálculo. Las dos técnicas se han integrado en SIRIUS, un sistema web destinado a incluir diferentes servicios en el campo del análisis de la imagen retiniana. El sistema incluye también gestión de pacientes y revisiones, lo que facilita el análisis de las lesiones retinianas causadas por diferentes patologías y su evolución después de un determinado tratamiento. Además al ser una aplicación distribuída a través de la web, proporciona un entorno de colaboración entre diferentes médicos, investigadores y centros.[Resumo] A retina é a única parte do corpo humano onde se poden observar os vasos sanguíneos directamente dunha maneira non invasiva mediante un examen do fondo do ollo. Desta maneira, a imaxe da retina mediante as técnicas de procesamento de imáxenes converteuse nun campo chave para o diagnóstico precoz de varias enfermidades sistémicas que provocan alteracións visibles en dita imaxe. Así, cambios no ancho dos vasos retinianos asócianse con patoloxías tales como a diabetes ou a hipertensión. De feito, o estreitamento das arterias constitúe un indicio prematuro da hipertensión arterial sistémica, sendo unha característica do grado I da retinopatía hipertensiva dacordo coa clasificación de Keith- Wagener-Barker. Neste sentido, fixerónse moitos esforzos para desenvolver programas asistidos por ordenador para medir con precisión os cambios no ancho dos vasos a través do índice arteriovenoso (IAV), é dicir, a relación entre os calibres das arterias e das veas. Nembargantes, aínda que estes sistemas foron usados en moitos estudios con fins investigadores, a sua aplicabilidade na práctica clínica diaria aínda é discutida. Neste traballo, proponse unha nova metodoloxía para o cálculo do IAV co fin de estratificar o risco cardiovascular dos hipertensos. Por un lado, desenvolveuse un método completamente automático para estimar o IAV nunha imaxe de fondo de ollo dun doente. Por outra banda, proponse un sistema para monitorizar o IAV dun doente a lo longo do tempo. Para isto, as medicións do IAV nas diferentes imaxes adquiridas sobre o mesmo ollo do doente en diferentes datas fanse usando o mesmo conxunto de vasos medidos nas mesmas áreas. Polo tanto, as medicións obtidas desta maneira son comparables e precisas, debido a que son independentes do conxunto de vasos seleccionados para o cálculo. As dúas técnicas foron integradas no SIRIUS, un sistema web destinado a incluir diferentes servicios no campo da análise da imaxe retiniana. O sistema inclúe tamén xestión de doentes e revisións, facilitando a análise e estudo das lesións retinianas causadas por diferentes patoloxías e a súa evolución despois dun determinado tratamento. Ademais ao ser unha aplicación distribuída a través da web, proporciona un entorno de colaboración entre diferentes médicos, investigadores e centros.[Abstract] Retina is the only part in the human body where blood vessels can be directly observed in a non-invasive way through an eye fundus examination. In this manner, the retinal imaging assisted by image processing techniques became a key field for the early diagnosis of several systemic diseases which cause visible alterations in the fundus image. Thus, changes in the retinal vessel widths are associated with pathologies such as diabetes or hypertension. In fact, arteriolar narrowing constitutes an early sign of systemic hypertension, being a feature for the grade I of hypertension retinopathy according to Keith-Wagener-Barker classification. In this sense, some efforts have been made to develop computer-assisted programs to measure accurately abnormalities in the vessel widths through the arteriovenous ratio (AVR), that is, the relation between arteriolar and venular vessel widths. However, although these systems have been used in many studies for research purposes, their applicability to daily clinical practice is yet discussed. In this work, a new methodology for the AVR computation is proposed in order to stratify the cardiovascular risk of hypertension. On one hand, a fully automatic method to estimate the AVR in a sample patient's image is developed. On the other hand, an AVR monitoring system to compute the patient's AVR over time was implemented. To this end, the AVR measurements computed in the different patient's images acquired from the same eye at different dates, uses the same set of vessels measured at the same areas. Thus, the measurements achieved in this manner are comparable and precise due to they are independent on the set of vessels selected for the calculus. The two approaches have been integrated in SIRIUS, a web-based system aimed to include different services in the field of retinal image analysis. It includes patient and checkup management, making easier to analyze the retinal lesions caused by different pathologies and their evolution after a specific treatment. Moreover, being a application distributed via the web, it provides a collaborative environment among different physicians, researchers and medical centers

Retinal Imaging in Alzheimer’s Disease

Identifying biomarkers of Alzheimer's disease (AD) will accelerate the understanding of its pathophysiology, facilitate screening and risk stratification, and aid in developing new therapies. Developments in non-invasive retinal imaging technologies, including optical coherence tomography (OCT), OCT angiography and digital retinal photography, have provided a means to study neuronal and vascular structures in the retina in people with AD. Both qualitative and quantitative measurements from these retinal imaging technologies (eg, thinning of peripapillary retinal nerve fibre layer, inner retinal layer, and choroidal layer, reduced capillary density, abnormal vasodilatory response) have been shown to be associated with cognitive function impairment and risk of AD. The development of computer algorithms for respective retinal imaging methods has further enhanced the potential of retinal imaging as a viable tool for rapid, early detection and screening of AD. In this review, we present an update of current retinal imaging techniques and their potential applications in AD research. We also discuss the newer retinal imaging techniques and future directions in this expanding field