Retinal Vasculometry Associations with Cardiometabolic Risk Factors in the European Prospective Investigation of Cancer-Norfolk Study

Longitudinal associations of retinal vessel morphology with intraocular pressure and blood pressure at follow-up visit-Findings from a Danish eye and vision cohort, Project FOREVER

PURPOSE

To characterise the retinal vasculometry of a Danish eye and vision cohort and examine associations with systolic blood pressure (BP), diastolic BP, mean arterial BP, and intraocular pressure (IOP).

DESIGN

Longitudinal study.

METHODS

The retinal vasculature of fundus images from the FOREVER (Finding Ophthalmic Risks and Evaluating the Value of Eye exams and their predictive Reliability) cohort was analysed using a fully automated image analysis program. Longitudinal associations of retinal vessel morphology at follow-up visit with IOP (baseline and follow-up) and BP (follow-up) were examined using multilevel linear regression models adjusting for age, sex and retinal vasculometry at baseline as fixed effects and person as random effect. Width measurements were additionally adjusted for the spherical equivalent.

RESULTS

A total of 2089 subjects (62% female) with a mean age of 61 (standard deviation 8) years and a mean follow-up period of 4.1 years (SD 0.6 years) were included. The mean arteriolar diameter was approximately 20% thinner than the mean venular diameter, and venules were about 21%-23% less tortuous than arterioles. BP at follow-up was associated with decreased arteriolar diameter from baseline to follow-up. After adjusting for baseline IOP, IOP at follow-up was associated with increased arteriolar tortuosity above baseline (0.59%, 95% CI 0.08-1.10, p-value 0.024).

CONCLUSION

In a Danish eye and vision cohort, variations in BP and alterations in IOP over time were associated with changes in the width and tortuosity of retinal vessels. Our findings contribute novel insights into retinal vascular alterations over time.

Associations between unilateral amblyopia in childhood and cardiometabolic disorders in adult life: a cross-sectional and longitudinal analysis of the UK Biobank

Background

Amblyopia is a common neurodevelopmental condition and leading cause of childhood visual impairment. Given the known association between neurodevelopmental impairment and cardiometabolic dysfunction in later life, we investigated whether children with amblyopia have increased risk of cardiometabolic disorders in adult life.

Methods

This was a cross-sectional and longitudinal analysis of 126,399 United Kingdom Biobank cohort participants who underwent ocular examination. A subset of 67,321 of these received retinal imaging. Data analysis was conducted between November 1st 2021 and October 15th 2022. Our primary objective was to investigate the association between amblyopia and a number of components of metabolic syndrome and individual cardiometabolic diseases. Childhood amblyopia, dichotomised as resolved or persisting by adulthood, cardiometabolic disease and mortality were defined using ophthalmic assessment, self-reported, hospital admissions and death records. Morphological features of the optic nerve and retinal vasculature and sublayers were extracted from retinal photography and optical coherence tomography. Associations between amblyopia and cardiometabolic disorders as well as retinal markers were investigated in multivariable-adjusted regression models.

Findings

Individuals with persisting amblyopia (n = 2647) were more likely to be obese (adjusted odds ratio (95% confidence interval): 1.16 (1.05; 1.28)), hypertensive (1.25 (1.13; 1.38)) and diabetic (1.29 (1.04; 1.59)) than individuals without amblyopia (controls, (n = 18,481)). Amblyopia was also associated with an increased risk of myocardial infarction (adjusted hazard ratio: 1.38 (1.11; 1.72)) and death (1.36 (1.15; 1.60)). On retinal imaging, amblyopic eyes had significantly increased venular caliber (0.29 units (0.21; 0.36)), increased tortuosity (0.11 units (0.03; 0.19)), but lower fractal dimension (-0.23 units (-0.30; -0.16)) and thinner ganglion cell-inner plexiform layer (mGC-IPL, -2.85 microns (-3.47; -2.22)). Unaffected fellow eyes of individuals with amblyopia also had significantly lower retinal fractal dimension (-0.08 units (-0.15; -0.01)) and thinner mGC-IPL (-1.14 microns (-1.74; -0.54)). Amblyopic eyes with a persisting visual deficit had smaller optic nerve disc height (-0.17 units (-0.25; -0.08)) and width (-0.13 units (-0.21; -0.04)) compared to control eyes.

Interpretation

Although further research is needed to understand the basis of the observed associations, healthcare professionals should be cognisant of greater cardiometabolic dysfunction in adults who had childhood amblyopia. Differences in retinal features in both the amblyopic eye and the unaffected non-amblyopic suggest generalised versus local processes.

Funding

Medical Research Council (MR/T000953/1) and the National Institute for Health and Care Research.

CF-Loss: Clinically-relevant feature optimised loss function for retinal multi-class vessel segmentation and vascular feature measurement

Characterising clinically-relevant vascular features, such as vessel density and fractal dimension, can benefit biomarker discovery and disease diagnosis for both ophthalmic and systemic diseases. In this work, we explicitly encode vascular features into an end-to-end loss function for multi-class vessel segmentation, categorising pixels into artery, vein, uncertain pixels, and background. This clinically-relevant feature optimised loss function (CF-Loss) regulates networks to segment accurate multi-class vessel maps that produce precise vascular features. Our experiments first verify that CF-Loss significantly improves both multi-class vessel segmentation and vascular feature estimation, with two standard segmentation networks, on three publicly available datasets. We reveal that pixel-based segmentation performance is not always positively correlated with accuracy of vascular features, thus highlighting the importance of optimising vascular features directly via CF-Loss. Finally, we show that improved vascular features from CF-Loss, as biomarkers, can yield quantitative improvements in the prediction of ischaemic stroke, a real-world clinical downstream task. The code is available at https://github.com/rmaphoh/feature-loss.

Finding Ophthalmic Risk and Evaluating the Value of Eye exams and their predictive Reliability (FOREVER)-A cohort study in a Danish high street optician setting: Design and methodology

PURPOSE

The purpose of the study was to describe the rationale and design of Project FOREVER (Finding Ophthalmic Risk and Evaluating the Value of Eye exams and their predictive Reliability).

DESIGN

Project FOREVER will build a comprehensive database of clinical eye and vision data collected from ~280 000 adults at 100 optician stores across Denmark. The FOREVER database (FOREVERdb) includes detailed data from refraction, visual acuity, intraocular pressure, corneal thickness, visual field assessments and retinal fundus images. Linkage to the comprehensive Danish national registries with, that is diagnostic and prescribing data permits investigation of rare associations and risk factors. 30 000 individuals over 50 also provide a saliva sample for later genetic studies and blood pressure measurements. Of these 30 000, 10 000 will also get optical coherence tomography (OCT) nerve and retinal scans. This subpopulation data is reviewed by ophthalmologists for disease detection. All participants will be asked to complete a questionnaire assessing lifestyle, self-perceived eye health and general health. Enrolment of participants began in April 2022.

PERSPECTIVE

The FOREVERdb is a powerful tool to answer a wide range of research questions that can pave the way for better eye health. This database will provide valuable insights for future studies investigating the correlations between eye and general health in a Danish population cohort, enabling research to identify potential risk factors for a range of diseases.

Automated Retinal Vessel Analysis Based on Fundus Photographs as a Predictor for Non-Ophthalmic Diseases-Evolution and Perspectives

The study of retinal vessels in relation to cardiovascular risk has a long history. The advent of a dedicated tool based on digital imaging, i.e., the retinal vessel analyzer, and also other software such as Integrative Vessel Analysis (IVAN), Singapore I Vessel Assessment (SIVA), and Vascular Assessment and Measurement Platform for Images of the Retina (VAMPIRE), has led to the accumulation of a formidable body of evidence regarding the prognostic value of retinal vessel analysis (RVA) for cardiovascular and cerebrovascular disease (including arterial hypertension in children). There is also the potential to monitor the response of retinal vessels to therapies such as physical activity or bariatric surgery. The dynamic vessel analyzer (DVA) remains a unique way of studying neurovascular coupling, helping to understand the pathogenesis of cerebrovascular and neurodegenerative conditions and also being complementary to techniques that measure macrovascular dysfunction. Beyond cardiovascular disease, retinal vessel analysis has shown associations with and prognostic value for neurological conditions, inflammation, kidney function, and respiratory disease. Artificial intelligence (AI) (represented by algorithms such as QUantitative Analysis of Retinal vessel Topology and siZe (QUARTZ), SIVA-DLS (SIVA-deep learning system), and many others) seems efficient in extracting information from fundus photographs, providing prognoses of various general conditions with unprecedented predictive value. The future challenges will be integrating RVA and other qualitative and quantitative risk factors in a unique, comprehensive prediction tool, certainly powered by AI, while building the much-needed acceptance for such an approach inside the medical community and reducing the "black box" effect, possibly by means of saliency maps.

Influence of secondhand smoke exposure on the retinal vasculature of children in Hong Kong

BACKGROUND

A recent prospective demonstrated that cardiovascular risk factors in early childhood were associated with later cardiovascular events. However, the impact of secondhand smoke (SHS) on children is unclear. The aims of this study is to determine the effects of SHS exposure on the retinal vasculature of children.

METHODS

This is a population-based cross-sectional study of children aged 6 to 8 years. All participants received comprehensive ophthalmic examinations and retinal photography. Data on SHS exposure was derived from a validated questionnaire. A validated deep-learning system was used to automatically estimate retinal arteriolar and venular calibers from retinal photographs. Associations of quantitative retinal vessel caliber values with SHS exposure, number of smokers in the household, and total number of cigarettes smoked were determined by analyses of covariance (ANCOVA) after adjusting for potential confounders. Test of trend was determined by treating categorical risk factors as continuous ordinal variables.

RESULTS

Here we show children exposed to SHS have wider retinal arteriolar (CRAE 152.1 µm vs. 151.3 µm, p < 0.001) and venular (CRVE 216.7 µm vs. 215.5 µm, p < 0.001) calibers compared to those in smoke-free homes, after adjustment for different factors. Wider arteriolar and venular calibers are also associated with increasing number of smokers in the family (p trend < 0.001) and more cigarettes smoked among family smokers (p trend<0.001).

CONCLUSIONS

Exposure to SHS at home is associated with changes in retinal vasculature among children. This reinforces the adverse effect of secondhand smoking around children though further research incorporating comprehensive assessment of potential confounders is necessary.

Retinal microvasculature and incident dementia over 10 years: The Three-City-Alienor cohort

Introduction

We explored the longitudinal relationship between retinal vascular features and dementia incidence over 10 years.

Methods

Among 584 participants from the Three-City-Alienor (3C-Alienor) population-based cohort, quantitative retinal vascular features (caliber, tortuosity, fractal dimension) were measured using semi-automated software. Dementia was actively diagnosed over the follow-up period.

Results

One hundred twenty-eight participants (21.9%) developed dementia over a median of 7.1 years. In Cox proportional hazards models adjusted for sociodemographic characteristics, apolipoprotein E (APOE) ε4, and vascular factors, increased retinal arteriolar tortuosity was associated with all-cause dementia (hazard ratio per standard deviation increase, 1.21; 95% confidence interval: 1.02-1.44). Wider retinal calibers and a higher venular tortuosity were associated with mixed/vascular dementia, but not Alzheimer's disease. Fractal dimensions were not associated with dementia.

Discussion

Changes in the retinal microvasculature were associated with dementia risk. More studies are needed to replicate these findings and determine which features might help identify persons at risk at an early stage.

HIGHLIGHTS

The retinal microvasculature might reflect the brain microvasculatureWe explored the association between retinal vascular features and incident dementia584 participants from the Three-City-Alienor cohort were followed-up over 10 yearsIncreased arteriolar tortuosity and venular calibers were associated with dementia riskRetinal imaging might help identify persons at risk of future dementia.

Comprehensive retinal vascular measurements: time in range is associated with peripheral retinal venular calibers in type 2 diabetes in China

AIM

Retinal vascular parameters are biomarkers of diabetic microangiopathy. We aimed to investigate the relationship between time in range (TIR) assessed by continuous glucose monitoring (CGM) and retinal vascular parameters in patients with type 2 diabetes in China.

METHODS

The TIR assessed by CGM and retinal photographs were obtained at the same time from adults with type 2 diabetes who were recruited. Retinal vascular parameters were extracted from retinal photographs by a validated fully automated computer program, and TIR was defined as between 3.9-7.8 mmol/L over a 24-h period. The association between TIR and caliber of retinal vessels distributed in different zones were analyzed using multivariable linear regression analyses.

RESULTS

For retinal vascular parameters measurements, the peripheral arteriovenous and middle venular calibers widen with decreasing TIR quartiles (P < 0.05). Lower TIR was associated with wider peripheral venule after adjusting for potential confounders. Even after further correction for GV, there was still a significant correlation between TIR and peripheral vascular calibers (CV: β = - 0.015 [- 0.027, - 0.003], P = 0.013; MAGE: β = - 0.013 [- 0.025, - 0.001], P = 0.038) and SD: β = - 0.013 [- 0.026, - 0.001], P = 0.004). Similar findings were not found for the middle and central venular calibers or arterial calibers located in different zones.

CONCLUSIONS

The TIR was associated with adverse changes to peripheral retinal venules but not central and middle vessels in patients with type 2 diabetes, suggesting that peripheral retinal vascular calibers may be affected by glycemic fluctuations earlier.

Automated analysis of vessel morphometry in retinal images from a Danish high street optician setting

PURPOSE

To evaluate the test performance of the QUARTZ (QUantitative Analysis of Retinal vessel Topology and siZe) software in detecting retinal features from retinal images captured by health care professionals in a Danish high street optician chain, compared with test performance from other large population studies (i.e., UK Biobank) where retinal images were captured by non-experts.

METHOD

The dataset FOREVERP (Finding Ophthalmic Risk and Evaluating the Value of Eye exams and their predictive Reliability, Pilot) contains retinal images obtained from a Danish high street optician chain. The QUARTZ algorithm utilizes both image processing and machine learning methods to determine retinal image quality, vessel segmentation, vessel width, vessel classification (arterioles or venules), and optic disc localization. Outcomes were evaluated by metrics including sensitivity, specificity, and accuracy and compared to human expert ground truths.

RESULTS

QUARTZ's performance was evaluated on a subset of 3,682 images from the FOREVERP database. 80.55% of the FOREVERP images were labelled as being of adequate quality compared to 71.53% of UK Biobank images, with a vessel segmentation sensitivity of 74.64% and specificity of 98.41% (FOREVERP) compared with a sensitivity of 69.12% and specificity of 98.88% (UK Biobank). The mean (± standard deviation) vessel width of the ground truth was 16.21 (4.73) pixels compared to that predicted by QUARTZ of 17.01 (4.49) pixels, resulting in a difference of -0.8 (1.96) pixels. The differences were stable across a range of vessels. The detection rate for optic disc localisation was similar for the two datasets.

CONCLUSION

QUARTZ showed high performance when evaluated on the FOREVERP dataset, and demonstrated robustness across datasets, providing validity to direct comparisons and pooling of retinal feature measures across data sources.

Exposure to endocrine disrupters and cardiometabolic health effects in preschool children: Urinary parabens are associated with wider retinal venular vessels

BACKGROUND AND AIM

Parabens are widely used as antimicrobial preservatives in personal care products. Studies investigating obesogenic or cardiovascular effects of parabens show discordant results, while data on preschool children are lacking. Paraben exposure during early childhood could have profound cardiometabolic effects later in life.

METHODS

In this cross-sectional study paraben concentrations [methyl (MeP), ethyl (EtP), propyl (PrP), butyl (BuP)] were measured by ultra-performance liquid chromatography/tandem mass spectrometry in 300 urinary samples of 4-6-year-old children of the ENVIRONAGE birth cohort. Paraben values below the limit of quantitation (LOQ) were imputed by censored likelihood multiple imputation. The associations between log-transformed paraben values and cardiometabolic measurements (BMI z-scores, waist circumference, blood pressure and retinal microvasculature) were analyzed in multiple linear regression models with a priori selected covariates. Effect modification by sex was investigated by including interaction terms.

RESULTS

Geometric means (geometric SD) of urinary MeP, EtP, and PrP levels above the LOQ were 32.60 (6.64), 1.26 (3.45), and 4.82 (4.11) μg/L, respectively. For BuP more than 96% of all measurements were below the LOQ. Regarding the microvasculature, we found direct associations between MeP and central retinal venular equivalent (β = 1.23, p = 0.039) and PrP with the retinal tortuosity index (x103)(β = 1.75, p = 0.0044). Furthermore, we identified inverse associations between MeP and ∑parabens with BMI z-scores (β = -0.067, p = 0.015 and β = -0.070, p = 0.014 respectively), and EtP with mean arterial pressure (β = -0.69, p = 0.048). The direction of association between EtP and BMI z-scores showed evidence for sex-specific differences with a direct trend in boys (β = 0.10, p = 0.060).

CONCLUSIONS

Already at young age paraben exposure is associated with potentially adverse changes in the retinal microvasculature.

Ocular images-based artificial intelligence on systemic diseases

PURPOSE

To provide a summary of the research advances on ocular images-based artificial intelligence on systemic diseases.

METHODS

Narrative literature review.

RESULTS

Ocular images-based artificial intelligence has been used in a variety of systemic diseases, including endocrine, cardiovascular, neurological, renal, autoimmune, and hematological diseases, and many others. However, the studies are still at an early stage. The majority of studies have used AI only for diseases diagnosis, and the specific mechanisms linking systemic diseases to ocular images are still unclear. In addition, there are many limitations to the research, such as the number of images, the interpretability of artificial intelligence, rare diseases, and ethical and legal issues.

CONCLUSION

While ocular images-based artificial intelligence is widely used, the relationship between the eye and the whole body should be more clearly elucidated.

Retinal vessel caliber and tortuosity and prediction of 5-year incidence of hypertension

PURPOSE

With arterial hypertension as a global risk factor for cerebrovascular and cardiovascular diseases, we examined whether retinal blood vessel caliber and tortuosity assessed by a vessel-constraint network model can predict the incidence of hypertension.

METHODS

The community-based prospective study included 9230 individuals who were followed for 5 years. Ocular fundus photographs taken at baseline were analyzed by a vessel-constraint network model.

RESULTS

Within the 5-year follow-up, 1279 (18.8%) and 474 (7.0%) participants out of 6813 individuals free of hypertension at baseline developed hypertension and severe hypertension, respectively. In multivariable analysis, a higher incidence of hypertension was related to a narrower retinal arteriolar diameter ( P  < 0.001), wider venular diameter ( P  = 0.005), and a smaller arteriole-to-venule diameter ratio ( P  < 0.001) at baseline. Individuals with the 5% narrowest arteriole or the 5% widest venule diameter had a 17.1-fold [95% confidence interval (CI):7.9, 37.2] or 2.3-fold (95% CI: 1.4, 3.7) increased risk for developing hypertension, as compared with those with the 5% widest arteriole or the 5% narrowest venule. The area under the receiver operator characteristic curve for predicting the 5-year incidence of hypertension and severe hypertension was 0.791 (95% CI: 0.778, 0.804) and 0.839 (95% CI: 0.821, 0.856), respectively. Although the venular tortuosity was positively associated with the presence of hypertension at baseline ( P  = 0.01), neither arteriolar tortuosity nor venular tortuosity was associated with incident hypertension (both P  ≥ 0.10).

CONCLUSION AND RELEVANCE

Narrower retinal arterioles and wider venules indicate an increased risk for incident hypertension within 5 years, while tortuous retinal venules are associated with the presence rather than the incidence of hypertension. The automatic assessment of retinal vessel features performed well in identifying individuals at risk of developing hypertension.

Sleeve gastrectomy improved microvascular phenotypes from obesity cohort, detected with optical coherence tomography angiography

AIMS

To examine how metabolic status is associated with microvascular phenotype and to identify variables associated with vascular remodeling after bariatric surgery, using noninvasive optical coherence tomography angiography (OCTA).

METHODS

The study included 136 obese subjects scheduled for bariatric surgery and 52 normal-weight controls. Patients with obesity were divided into metabolically healthy obesity (MHO) and metabolic syndrome (MetS) groups according to the diagnosis criteria of the Chinese Diabetes Society. Retinal microvascular parameters were measured by OCTA, including superficial capillary plexus (SCP) and deep capillary plexus (DCP) vessel densities. Follow-ups were performed at the baseline and 6 months after bariatric surgery.

RESULTS

Fovea SCP, average DCP, fovea DCP, parafovea DCP, and perifovea DCP vessel densities were significantly lower in the MetS group, compared to controls (19.91% vs. 22.49%, 51.60% vs. 54.20%, 36.64% vs. 39.14%, 56.24% vs. 57.65% and 52.59% vs. 55.58%, respectively, all p < .05). Parafovea SCP, average DCP, parafovea DCP, and perifovea DCP vessel densities significantly improved in patients with obesity 6 months after surgery, compared to baseline (54.21% vs. 52.97%, 54.43% vs. 50.95%, 58.29% vs. 55.54% and 55.76% vs. 51.82%, respectively, all p < .05). Multivariable analyses showed that baseline blood pressure and insulin were independent predictors of vessel density changes 6 months after surgery.

CONCLUSIONS

Retinal microvascular impairment occurred mainly in MetS rather than MHO patients. Retinal microvascular phenotype improved 6 months after bariatric surgery and baseline blood pressure and insulin status may be key determinants. OCTA may be a reliable method to evaluate the microvascular complications associated with obesity.

An efficient approach to estimate the risk of coronary artery disease for people living with HIV using machine-learning-based retinal image analysis

BACKGROUND

People living with HIV (PLWH) have increased risks of non-communicable diseases, especially cardiovascular diseases. Current HIV clinical management guidelines recommend regular cardiovascular risk screening, but the risk equation models are not specific for PLWH. Better tools are needed to assess cardiovascular risk among PLWH accurately.

METHODS

We performed a prospective study to determine the performance of automatic retinal image analysis in assessing coronary artery disease (CAD) in PLWH. We enrolled PLWH with ≥1 cardiovascular risk factor. All participants had computerized tomography (CT) coronary angiogram and digital fundus photographs. The primary outcome was coronary atherosclerosis; secondary outcomes included obstructive CAD. In addition, we compared the performances of three models (traditional cardiovascular risk factors alone; retinal characteristics alone; and both traditional and retinal characteristics) by comparing the area under the curve (AUC) of receiver operating characteristic curves.

RESULTS

Among the 115 participants included in the analyses, with a mean age of 54 years, 89% were male, 95% had undetectable HIV RNA, 45% had hypertension, 40% had diabetes, 45% had dyslipidemia, and 55% had obesity, 71 (61.7%) had coronary atherosclerosis, and 23 (20.0%) had obstructive CAD. The machine-learning models, including retinal characteristics with and without traditional cardiovascular risk factors, had AUC of 0.987 and 0.979, respectively and had significantly better performance than the model including traditional cardiovascular risk factors alone (AUC 0.746) in assessing coronary artery disease atherosclerosis. The sensitivity and specificity for risk of coronary atherosclerosis in the combined model were 93.0% and 93.2%, respectively. For the assessment of obstructive CAD, models using retinal characteristics alone (AUC 0.986) or in combination with traditional risk factors (AUC 0.991) performed significantly better than traditional risk factors alone (AUC 0.777). The sensitivity and specificity for risk of obstructive CAD in the combined model were 95.7% and 97.8%, respectively.

CONCLUSION

In this cohort of Asian PLWH at risk of cardiovascular diseases, retinal characteristics, either alone or combined with traditional risk factors, had superior performance in assessing coronary atherosclerosis and obstructive CAD.

SUMMARY

People living with HIV in an Asian cohort with risk factors for cardiovascular disease had a high prevalence of coronary artery disease (CAD). A machine-learning-based retinal image analysis could increase the accuracy in assessing the risk of coronary atherosclerosis and obstructive CAD.

GWAS on retinal vasculometry phenotypes

The eye is the window through which light is transmitted and visual sensory signalling originates. It is also a window through which elements of the cardiovascular and nervous systems can be directly inspected, using ophthalmoscopy or retinal imaging. Measurements of ocular parameters may therefore offer important information on the physiology and homeostasis of these two important systems. Here we report the results of a genetic characterisation of retinal vasculature. Four genome-wide association studies performed on different aspects of retinal vasculometry phenotypes, such as arteriolar and venular tortuosity and width, found significant similarities between retinal vascular characteristics and cardiometabolic health. Our analyses identified 119 different regions of association with traits of retinal vasculature, including 89 loci associated arteriolar tortuosity, the strongest of which was rs35131825 (p = 2.00×10-108), 2 loci with arteriolar width (rs12969347, p = 3.30×10-09 and rs5442, p = 1.9E-15), 17 other loci associated with venular tortuosity and 11 novel associations with venular width. Our causal inference analyses also found that factors linked to arteriolar tortuosity cause elevated diastolic blood pressure and not vice versa.

Multimodal deep learning of fundus abnormalities and traditional risk factors for cardiovascular risk prediction

Cardiovascular disease (CVD), the leading cause of death globally, is associated with complicated underlying risk factors. We develop an artificial intelligence model to identify CVD using multimodal data, including clinical risk factors and fundus photographs from the Samsung Medical Center (SMC) for development and internal validation and from the UK Biobank for external validation. The multimodal model achieves an area under the receiver operating characteristic curve (AUROC) of 0.781 (95% confidence interval [CI] 0.766-0.798) in the SMC and 0.872 (95% CI 0.857-0.886) in the UK Biobank. We further observe a significant association between the incidence of CVD and the predicted risk from at-risk patients in the UK Biobank (hazard ratio [HR] 6.28, 95% CI 4.72-8.34). We visualize the importance of individual features in photography and traditional risk factors. The results highlight that non-invasive fundus photography can be a possible predictive marker for CVD.

Association of Body Mass Index and Waist-to-Hip Ratio With Retinal Microvasculature in Healthy Chinese Adults: An Optical Coherence Tomography Angiography Study

PURPOSE

To investigate the association of body mass index (BMI) and waist-to-hip ratio (WHR) with macular vessel density (VD) and foveal avascular zone (FAZ), using optical coherence tomography angiography (OCTA), in healthy Chinese adults.

DESIGN

Cross-sectional study.

METHODS

A total of 1555 Chinese adults aged ≥ 50 years with no history of ocular disease were recruited from communities in Guangzhou, China. The OCTA was performed with a 6 × 6 mm macular angiography model. The FAZ of the superficial capillary plexus (SCP), and VD of SCP and deep capillary plexus (DCP) were calculated. Univariable and multivariable linear regression analyses were used to evaluate the effect of BMI and WHR on VD and FAZ.

RESULTS

The VD of the SCP increased as BMI increased, with average measurements of 39.30 ± 2.14 for normal, 39.52 ± 2.07 for overweight, and 39.76 ± 2.03 for obesity (P = .001). The VD of the DCP also increased with increasing BMI (P = .009). Multiple regression models confirmed a positive association between generalized obesity and superficial VD in the whole image (β = 0.350, P = .008), inner circle (β = 0.431, P = .032), and outer circle (β = 0.368, P = .005). After adjusting for confounders, tertile 3 of the WHR level was positively associated with superficial VD (β = 0.472, P = .033) and deep VD (β = 0.422, P = .034) only in the inner circle.

CONCLUSIONS

Generalized obesity was associated with increased superficial VD, while abdominal obesity was associated with increased superficial and deep VD only in the inner circle. Different manifestations of the retinal microvasculature may reflect distinct roles of body composition on macular vessel alterations and disease occurrence.

Application of Deep Learning to Retinal-Image-Based Oculomics for Evaluation of Systemic Health: A Review

The retina is a window to the human body. Oculomics is the study of the correlations between ophthalmic biomarkers and systemic health or disease states. Deep learning (DL) is currently the cutting-edge machine learning technique for medical image analysis, and in recent years, DL techniques have been applied to analyze retinal images in oculomics studies. In this review, we summarized oculomics studies that used DL models to analyze retinal images-most of the published studies to date involved color fundus photographs, while others focused on optical coherence tomography images. These studies showed that some systemic variables, such as age, sex and cardiovascular disease events, could be consistently robustly predicted, while other variables, such as thyroid function and blood cell count, could not be. DL-based oculomics has demonstrated fascinating, "super-human" predictive capabilities in certain contexts, but it remains to be seen how these models will be incorporated into clinical care and whether management decisions influenced by these models will lead to improved clinical outcomes.

Artificial intelligence-enabled retinal vasculometry for prediction of circulatory mortality, myocardial infarction and stroke

AIMS

We examine whether inclusion of artificial intelligence (AI)-enabled retinal vasculometry (RV) improves existing risk algorithms for incident stroke, myocardial infarction (MI) and circulatory mortality.

METHODS

AI-enabled retinal vessel image analysis processed images from 88 052 UK Biobank (UKB) participants (aged 40-69 years at image capture) and 7411 European Prospective Investigation into Cancer (EPIC)-Norfolk participants (aged 48-92). Retinal arteriolar and venular width, tortuosity and area were extracted. Prediction models were developed in UKB using multivariable Cox proportional hazards regression for circulatory mortality, incident stroke and MI, and externally validated in EPIC-Norfolk. Model performance was assessed using optimism adjusted calibration, C-statistics and R² statistics. Performance of Framingham risk scores (FRS) for incident stroke and incident MI, with addition of RV to FRS, were compared with a simpler model based on RV, age, smoking status and medical history (antihypertensive/cholesterol lowering medication, diabetes, prevalent stroke/MI).

RESULTS

UKB prognostic models were developed on 65 144 participants (mean age 56.8; median follow-up 7.7 years) and validated in 5862 EPIC-Norfolk participants (67.6, 9.1 years, respectively). Prediction models for circulatory mortality in men and women had optimism adjusted C-statistics and R² statistics between 0.75-0.77 and 0.33-0.44, respectively. For incident stroke and MI, addition of RV to FRS did not improve model performance in either cohort. However, the simpler RV model performed equally or better than FRS.

CONCLUSION

RV offers an alternative predictive biomarker to traditional risk-scores for vascular health, without the need for blood sampling or blood pressure measurement. Further work is needed to examine RV in population screening to triage individuals at high-risk.

Recent trends and advances in fundus image analysis: A review

Automated retinal image analysis holds prime significance in the accurate diagnosis of various critical eye diseases that include diabetic retinopathy (DR), age-related macular degeneration (AMD), atherosclerosis, and glaucoma. Manual diagnosis of retinal diseases by ophthalmologists takes time, effort, and financial resources, and is prone to error, in comparison to computer-aided diagnosis systems. In this context, robust classification and segmentation of retinal images are primary operations that aid clinicians in the early screening of patients to ensure the prevention and/or treatment of these diseases. This paper conducts an extensive review of the state-of-the-art methods for the detection and segmentation of retinal image features. Existing notable techniques for the detection of retinal features are categorized into essential groups and compared in depth. Additionally, a summary of quantifiable performance measures for various important stages of retinal image analysis, such as image acquisition and preprocessing, is provided. Finally, the widely used in the literature datasets for analyzing retinal images are described and their significance is emphasized.

Retinal microvascular associations with cardiometabolic risk factors differ by diabetes status: results from the UK Biobank

AIMS/HYPOTHESIS

The aim of the study was to examine the association of retinal vessel morphometry with BP, body composition and biochemistry, and to determine whether these associations differ by diabetes status.

METHODS

The UK Biobank ocular assessment included 68,550 participants aged 40-70 years who underwent non-mydriatic retinal photography, BP and body composition measurements, and haematological analysis. A fully automated image analysis program provided measurements of retinal vessel diameter and tortuosity. The associations between retinal vessel morphology and cardiometabolic risk factors by diabetes status were examined using multilevel linear regression, to provide absolute differences in vessel diameter and percentage differences in tortuosity (allowing for within-person clustering).

RESULTS

A total of 50,233 participants (a reduction from 68,550) were included in these analyses. Overall, those with diabetes had significantly more tortuous venules and wider arteriolar diameters compared with those without. Associations between venular tortuosity and cardiometabolic risk factors differed according to diabetes status (p interaction <0.01) for total fat mass index, HbA_1c, C-reactive protein, white cell count and granulocyte count. For example, a unit rise in white cell count was associated with a 0.18% increase (95% CI 0.05, 0.32%) in venular tortuosity for those without diabetes and a 1.48% increase (95% CI 0.90, 2.07%) among those with diabetes. For arteriolar diameter, significant interactions were evident for systolic BP, diastolic BP, mean arterial pressure (MAP) and LDL-cholesterol. For example, a 10 mmHg rise in systolic BP was associated with a -0.92 μm difference (95% CI -0.96 to -0.88 μm) in arteriolar diameter for those without diabetes, and a -0.58 μm difference (95% CI -0.76 to -0.41 μm) among those with diabetes. No interactions were observed for arteriolar tortuosity or venular diameters.

CONCLUSIONS/INTERPRETATION

We provide clear evidence of the modifying effect of diabetes on cardiometabolic risk factor associations with retinal microvascular architecture. These observations suggest the occurrence of preclinical disease processes, and may be a sign of impaired autoregulation due to hyperglycaemia, which has been suggested to play a pivotal role in the development of diabetes-related microvascular complications.

DATA AVAILABILITY

The data supporting the results reported here are available through the UK Biobank ( https://www.ukbiobank.ac.uk/enable-your-research/apply-for-access ).

FIVES: A Fundus Image Dataset for Artificial Intelligence based Vessel Segmentation

Retinal vasculature provides an opportunity for direct observation of vessel morphology, which is linked to multiple clinical conditions. However, objective and quantitative interpretation of the retinal vasculature relies on precise vessel segmentation, which is time consuming and labor intensive. Artificial intelligence (AI) has demonstrated great promise in retinal vessel segmentation. The development and evaluation of AI-based models require large numbers of annotated retinal images. However, the public datasets that are usable for this task are scarce. In this paper, we collected a color fundus image vessel segmentation (FIVES) dataset. The FIVES dataset consists of 800 high-resolution multi-disease color fundus photographs with pixelwise manual annotation. The annotation process was standardized through crowdsourcing among medical experts. The quality of each image was also evaluated. To the best of our knowledge, this is the largest retinal vessel segmentation dataset for which we believe this work will be beneficial to the further development of retinal vessel segmentation.

Retinal vessel diameters and function in cardiovascular risk and disease

In the last two decades evidence has gradually accumulated suggesting that the eye may be a unique window for cardiovascular risk stratification based on the assessment of subclinical damage of retinal microvascular structure and function. This can be facilitated by non-invasive analysis of static retinal vessel diameters and dynamic recording of flicker light-induced and endothelial function-related dilation of both retinal arterioles and venules. Recent new findings have made retinal microvascular biomarkers strong candidates for clinical implementation as reliable risk predictors. Beyond a review of the current evidence and state of research, the article aims to discuss the methodological benefits and pitfalls and to identify research gaps and future directions. Above all, the potential use for screening and treatment monitoring of cardiovascular disease risk are highlighted. The article provides fundamental comprehension of retinal vessel imaging by explaining anatomical and physiological essentials of the retinal microcirculation leading to a detailed description of the methodological approach. This allows for better understanding of the underlying retinal microvascular pathology associated with the prevalence and development of cardiovascular disease. A body of new evidence is presented on the clinical validity and predictive value of retinal vessel diameters and function for incidence cardiovascular disease and outcome. Findings in children indicate the potential for utility in childhood cardiovascular disease prevention, and the efficacy of exercise interventions highlight the treatment sensitivity of retinal microvascular biomarkers. Finally, coming from the availability of normative data, solutions for diagnostic challenges are discussed and conceptual steps towards clinical implementation are put into perspective.

Retinal blood vessel calibre and vascular ageing in a general Spanish population: A EVA study

INTRODUCTION

The aim of this work was to analyse the association of the retinal arteriolar calibre and the arteriole/venule index (AV index) with vascular ageing in a general population without previous cardiovascular disease.

MATERIALS AND METHODS

Descriptive cross-sectional study. A total of 482 individuals without cardiovascular disease (mean age: 55.6 ± 14.2 years) were selected by random sampling, stratified by age and sex. The retinal arteriolar calibre was measured using digital fundus images of the back of the eye captured with a validated, semiautomatized and computer-assisted software (Index calculator). Vascular ageing was defined using three criteria based on the values of: (1) Carotid-femoral Pulse Wave Velocity (cfPWV), (2) Brachial-ankle Pulse Wave Velocity (baPWV) and (3) Carotid Intima-Media Thickness.

RESULTS

The AV index and arteriolar calibre show a negative correlation with age, arterial pressure, cardiovascular risk and parameters of vascular structure and function (p < 0.001 in all cases). We found lower mean values of the AV index and arteriolar calibre in the individuals with early vascular ageing compared to those with healthy vascular ageing. AV index was negatively correlated with cfPWV ((β=-2.9; 95% CI (-4.7; -1.1)), baPWV ((β=-3.2; 95% CI (-5.4; -0.9)) and vascular ageing index ((β=-1.7; 95% CI (-2.7; -0.7)). Arteriolar calibre showed a negative correlation with baPWV (β=-0.1; 95% CI (-0.2; -0.1)). In the logistic regression analysis, lower values of AV index ((OR=0.01; 95% CI (0.01-0.10), OR=0.03; 95% CI (0.01-0.11) and OR=0.09; 95% CI (0.01-0.67)) were associated with EVA defined with cfPWV, baPWV and vascular ageing index respectively, and lower values of arteriolar calibre ((OR=0.71; 95% CI (0.55-0.91)) were associated with EVA defined with vascular ageing index.

CONCLUSIONS

Lower values of AV index and retinal arteriolar calibre were associated with vascular ageing in a general Spanish population without previous cardiovascular disease.

Retinal arteriolar tortuosity and fractal dimension are associated with long-term cardiovascular outcomes in people with type 2 diabetes

AIMS/HYPOTHESIS

Our aim was to determine whether quantitative retinal traits in people with type 2 diabetes are independently associated with incident major cardiovascular events including CHD and stroke.

METHODS

A total of 1066 men and women with type 2 diabetes, aged 65-74 years, were followed up over 8 years in the population-based Edinburgh Type 2 Diabetes Study. Using retinal photographs taken at baseline and specialist software, a number of quantitative retinal traits were measured, including arteriolar and venular widths and tortuosity as well as fractal dimension (a measure of the branching pattern complexity of the retinal vasculature network). Incident CHD events occurring during follow-up included fatal and non-fatal myocardial infarction, first episodes of angina and coronary interventions for CHD. Incident cerebrovascular events included fatal and non-fatal stroke or transient ischaemic attack. Cox proportional hazard regression analyses were performed to identify the association of the retinal traits with cardiovascular events in the population with retinal data available (n = 1028).

RESULTS

A total of 200 participants had an incident cardiovascular event (139 CHD and 61 cerebrovascular events). Following adjustment for age and sex, arteriolar tortuosity and fractal dimension were associated with cerebrovascular events (HR 1.27 [95% CI 1.02, 1.58] and HR 0.74 [95% CI 0.57, 0.95], respectively), including with stroke alone (HR 1.30 [95% CI 1.01, 1.66] and HR 0.73 [95% CI 0.56, 0.97], respectively). These associations persisted after further adjustment for established cardiovascular risk factors (HR 1.26 [95% CI 1.01, 1.58] and HR 0.73 [95% CI 0.56, 0.94], respectively). Associations generally reduced in strength after a final adjustment for the presence of diabetic retinopathy, but the association of fractal dimension with incident cerebrovascular events and stroke retained statistical significance (HR 0.73 [95% CI 0.57, 0.95] and HR 0.72 [95% CI 0.54, 0.97], respectively). Associations of retinal traits with CHD were generally weak and showed no evidence of statistical significance.

CONCLUSIONS/INTERPRETATION

Arteriolar tortuosity and fractal dimension were associated with incident cerebrovascular events, independent of a wide range of traditional cardiovascular risk factors including diabetic retinopathy. These findings suggest potential for measurements of early retinal vasculature change to aid in the identification of people with type 2 diabetes who are at increased risk from stroke.

Correlation between retinal vascular parameters and cystatin C in patients with type 2 diabetes

AIMS

To investigate the relationship between retinal vascular parameters and cystatin C in patients with type 2 diabetes in northwestern China.

METHODS

This was a cross-sectional study of 1689 patients with type 2 diabetes. A validated fully automated computer program was used to extract retinal vascular parameters from the entire vascular tree. Multiple logistic regression analyses were conducted to investigate the relationship between these vascular measurements and cystatin C.

RESULTS

For retinal vascular geometrical measurements, smaller arteriolar fractal dimension was related to high cystatin C after adjusting for multiple variables (odds ratio [OR] 0.149, 95% CI 0.042-0.532). For retinal vascular caliber measurements, narrower central and middle arteriolar calibers were related to high cystatin C after adjusting for multiple variables (central: OR 0.922, 95% CI 0.886-0.960; middle: OR 0.940, 95% CI 0.901-0.981). Wider central, middle and peripheral venular calibers were associated with high cystatin C after adjusting for multiple variables (central: OR 1.058, 95% CI 1.003-1.117; middle: OR 1.094, 95% CI 1.040-1.150; peripheral: OR 1.075, 95% CI 1.023-1.130).

CONCLUSIONS

Multiple retinal vascular geometrical and caliber measurements are associated with cystatin C in type 2 diabetic patients. Further studies are needed to explore whether these retinal vascular changes can predict the incidence and progress of diabetic nephropathy.

Systemic retinal biomarkers

PURPOSE OF REVIEW

Systemic retinal biomarkers are biomarkers identified in the retina and related to evaluation and management of systemic disease. This review summarizes the background, categories and key findings from this body of research as well as potential applications to clinical care.

RECENT FINDINGS

Potential systemic retinal biomarkers for cardiovascular disease, kidney disease and neurodegenerative disease were identified using regression analysis as well as more sophisticated image processing techniques. Deep learning techniques were used in a number of studies predicting diseases including anaemia and chronic kidney disease. A virtual coronary artery calcium score performed well against other competing traditional models of event prediction.

SUMMARY

Systemic retinal biomarker research has progressed rapidly using regression studies with clearly identified biomarkers such as retinal microvascular patterns, as well as using deep learning models. Future systemic retinal biomarker research may be able to boost performance using larger data sets, the addition of meta-data and higher resolution image inputs.

Retinal microvascular parameters are not associated with diabetes in the Northern Ireland Cohort for the Longitudinal Study of Ageing

BACKGROUND

The retinal microvasculature offers unique non-invasive evaluation of systemic microvascular abnormalities. Previous studies reported associations between retinal microvascular parameters (RMPs) and diabetes. The aim of this study was to assess associations between RMPs and diabetes in a cross-sectional analysis of older persons from the Northern Ireland Cohort for the Longitudinal Study of Ageing (NICOLA).

METHODS

RMPs (central retinal arteriolar/venular equivalents, arteriolar to venular ratio, fractal dimension, and tortuosity) were measured from optic disc-centred fundus images using semi-automated software. Associations were assessed between RMPs and diabetes status with adjustment for potential confounders.

RESULTS

Data were included for 1762 participants with 209 classified as having diabetes. Participants had a mean age of 62.1 ± 8.5 years, and 54% were female. As expected, participants with diabetes had significantly higher mean glycated haemoglobin A1c compared to participants without diabetes (57.4 ± 17.6 mmol/mol versus 37.0 ± 4.2 mmol/mol, respectively). In unadjusted and minimally adjusted regression, arteriolar to venular ratio, arteriolar tortuosity and venular tortuosity were significantly associated with diabetes (minimally adjusted odds ratio [OR] = 0.85; 95% confidence intervals [CIs] 0.73, 0.99; P = 0.04, OR = 1.18; 95% CI 1.02, 1.37; P = 0.03 and OR = 1.20; 95% CI 1.04, 1.38; P = 0.01, respectively), although all failed to remain significant following adjustment for potential confounders. No additional associations between other RMPs and diabetes were detected.

CONCLUSION

Despite previously reported associations between diabetes and RMPs, our study failed to corroborate these associations in an older community-based cohort.

Optic disc and peripapillary vessel density measured with optical coherence tomography angiography and its associations in Chinese adults: a large population-based study

PURPOSE

To investigate the optic disc and peripapillary vessel density, as well as its ocular and systemic associations, in healthy eyes among adult Chinese population.

METHODS

A population-based cross-sectional eye survey was conducted on Chinese adults residing in Hong Kong. 1891 eyes from 1891 participants who completed 4.5×4.5 mm optical coherence tomography angiography scans were recruited. Among the 1891 eyes, 404 were excluded due to low scan quality, optic disc or retinal disorders and non-Chinese ethnicity. The vessel densities (VDs) at nerve fibre layer plexus (NFLP) at both optic disc and peripapillary were collected for analysis. Multiple linear regression analysis was performed to determine the ocular and systemic associations of NFLP VD.

RESULTS

The study included 1487 participants (men: 41.2%) with a mean age of 48.8±15.4 years. The mean NFLP VD of the whole en face image, inside disc and peripapillary region was 53.8%, 42.7% and 60.3%, respectively. In the multivariable model, decreased NFLP VDs were significantly associated with older age, male gender, longer axial length (AL) and lower Signal Strength Index.

CONCLUSIONS

This large population-based cross-sectional study provided quantitative data of optic disc and peripapillary NFLP VD which may serve as a normative reference for clinical use. Apart from age, gender and AL, the scan signal strength also should be taken into consideration during the assessment of NFLP VD.

Predicting sex from retinal fundus photographs using automated deep learning

Deep learning may transform health care, but model development has largely been dependent on availability of advanced technical expertise. Herein we present the development of a deep learning model by clinicians without coding, which predicts reported sex from retinal fundus photographs. A model was trained on 84,743 retinal fundus photos from the UK Biobank dataset. External validation was performed on 252 fundus photos from a tertiary ophthalmic referral center. For internal validation, the area under the receiver operating characteristic curve (AUROC) of the code free deep learning (CFDL) model was 0.93. Sensitivity, specificity, positive predictive value (PPV) and accuracy (ACC) were 88.8%, 83.6%, 87.3% and 86.5%, and for external validation were 83.9%, 72.2%, 78.2% and 78.6% respectively. Clinicians are currently unaware of distinct retinal feature variations between males and females, highlighting the importance of model explainability for this task. The model performed significantly worse when foveal pathology was present in the external validation dataset, ACC: 69.4%, compared to 85.4% in healthy eyes, suggesting the fovea is a salient region for model performance OR (95% CI): 0.36 (0.19, 0.70) p = 0.0022. Automated machine learning (AutoML) may enable clinician-driven automated discovery of novel insights and disease biomarkers.

Vascular health assessment with flow-mediated dilatation and retinal image analysis: a pilot study in an adult population from Cape Town

AIM

Flow-mediated dilatation (FMD) and retinal vascular analysis (RVA) may assist in predicting cardiovascular disease (CVD) but are poorly characterised in South Africa. We recorded baseline FMD and retinal vascular widths in healthy participants, and investigated associations with cardiovascular risk factors.

METHODS

Endothelial function (measured with FMD), microvascular structure (evaluated via fundus image analysis) and major CVD risk factors were assessed in 66 participants from Cape Town.

RESULTS

Median FMD% was 9.6%, with higher values in females. Mean retinal arteriolar and venular widths were ˜156 and ˜250 µm, respectively. FMD was not associated with CVD risk factors. Hypertension was associated with narrower retinal arterioles and venules.

CONCLUSIONS

We report novel baseline FMD data in healthy South African adults from the Western Cape, and show that retinal microvascular calibres are associated with blood pressure. Our baseline FMD and RVA data could serve as a reference for future studies in South Africa.

Association of reduced retinal arteriolar tortuosity with depression in older participants from the Northern Ireland Cohort for the Longitudinal Study of Ageing

INTRODUCTION

The retina shares similar anatomical and physiological features with the brain and subtle variations in retinal microvascular parameters (RMPs) may reflect similar vascular variation in the brain. The aim of this study was to assess associations between RMPs and measures of depression in the Northern Ireland Cohort for the Longitudinal Study of Ageing.

METHODS

RMPs (arteriolar and venular caliber, fractal dimension and tortuosity) were measured from optic disc centred fundus images using semi-automated software. Depression was characterised by the Centre for Epidemiologic Studies Depression Scale (CES-D) in the absence of mild cognitive impairment or use of anti-depressive medications. Associations between depression and RMPs were assessed by regression analyses with adjustment for potential confounders.

RESULTS

Data were available for 1376 participants of which 113 (8.2%) and 1263 (91.8%) were classified with and without depression. Participants had a mean age of 62.0 ± 8.4 yrs., 52% were female, and 8% were smokers. Individuals with depression had a higher CES-D score than those without (22.0 ± 6.2 versus 4.4 ± 3.9). Lower values of arteriolar tortuosity were significantly associated with depression, before and after adjustment for potential confounders (odds ratio = 0.79; 95% confidence intervals: 0.65, 0.96; P = 0.02).

CONCLUSION

Decreased retinal arteriolar tortuosity, a measure of the complexity of the retinal microvasculature was associated with depression in older adults independent of potential confounding factors. Retinal measures may offer opportunistic assessment of microvascular health associated with outcomes of depression.

Retinal Vasculometry Associations With Glaucoma: Findings From the European Prospective Investigation of Cancer-Norfolk Eye Study

Purpose

To examine retinal vasculometry associations with different glaucomas in older British people.

Design

Cross-sectional study.

Methods

A total of 8,623 European Prospective Investigation into Cancer-Norfolk Eye study participants were examined, who underwent retinal imaging, ocular biometry assessment, and clinical ascertainment of ocular hypertensive or glaucoma status (including glaucoma suspect [GS], high-tension open-angle glaucoma [HTG], and normal-tension glaucoma [NTG]). Automated measures of arteriolar and venular tortuosity, area, and width from retinal images were obtained. MainOutcomeMeasures: Associations between glaucoma and retinal vasculometry outcomes were analyzed using multilevel linear regression, adjusted for age, sex, height, axial length, intraocular and systemic blood pressure, and within-person clustering, to provide absolute differences in width and area, and percentage differences in vessel tortuosity. Presence or absence of within-person-between-eye differences in retinal vasculometry by diagnoses were examined.

Results

A total of 565,593 vessel segments from 5,947 participants (mean age 67.6 years, SD 7.6 years, 57% women) were included; numbers with HTG, NTG, and GS in at least 1 eye were 87, 82, and 439, respectively. Thinner arterioles (−3.2 μm; 95% confidence interval [CI] −4.4 μm, −1.9 μm) and venules (−2.7 μm; 95% CI −4.9 μm, −0.5 μm) were associated with HTG. Reduced venular area was associated with HTG (−0.2 mm²; 95% CI −0.3 mm², −0.1 mm²) and NTG (−0.2 mm²; 95% CI −0.3 mm², −0.0 mm²). Less tortuous retinal arterioles and venules were associated with all glaucomas, but only significantly for GS (−3.9%; 95% CI −7.7%, −0.1% and −4.8%; 95% CI −7.4%, −2.1%, respectively). There was no evidence of within-person-between-eye differences in retinal vasculometry associations by diagnoses.

Conclusions

Retinal vessel width associations with glaucoma and novel associations with vessel area and tortuosity, together with no evidence of within-person-between-eye differences in retinal vasculometry, suggest a vascular cause of glaucoma.

•

Retinal vessel measurements, including (as a first report) vessel tortuosity and area, were associated with high-tension glaucoma and other glaucoma-related outcomes.

•

Novel analyses showing that within-person-between-eye glaucoma diagnoses, intraocular pressure, and retinal vasculometry were uncorrelated provides further evidence that systemic microvascular changes may cause glaucoma.

Retinal Vascular Tortuosity and Diameter Associations with Adiposity and Components of Body Composition

OBJECTIVE

The aim of this study was to assess whether adiposity or body composition relates to microvascular characteristics of the retina, indicative of cardiometabolic function.

METHODS

A fully automated QUARTZ software processed retinal images from 68,550 UK Biobank participants (aged 40-69 years). Differences in retinal vessel diameter and tortuosity with body composition measures from the Tanita analyzer were obtained by using multilevel regression analyses adjusted for age, sex, ethnicity, clinic, smoking, and Townsend deprivation index.

RESULTS

Venular tortuosity and diameter increased by approximately 2% (P < 10^-300 ) and 0.6 μm (P < 10^-6 ), respectively, per SD increase in BMI, waist circumference index, waist-hip ratio, total body fat mass index, and fat-free mass index (FFMI). Venular associations with adiposity persisted after adjustment for FFMI, whereas associations with FFMI were weakened by FMI adjustment. Arteriolar diameter (not tortuosity) narrowing with FFMI was independent of adiposity (-0.6 μm; -0.7 to -0.4 μm per SD increment of FFMI), while adiposity associations with arteriolar diameter were largely nonsignificant after adjustment for FFMI.

CONCLUSIONS

This demonstrates, on an unprecedented scale, that venular tortuosity and diameter are more strongly associated with adiposity, whereas arteriolar diameter relates more strongly to fat-free mass. Different attributes of the retinal microvasculature may reflect distinct roles of body composition and fatness on the cardiometabolic system.

Comprehensive retinal vascular measurements: a novel association with renal function in type 2 diabetic patients in China

To examine the association between various retinal vascular measurements and microalbuminuria in patients with type 2 diabetes in a northwestern China study. Data from 911 patients with type 2 diabetes were analyzed. Novel retinal vascular measurements from the whole vascular tree were extracted using a validated fully automatic computer program. Retinal vascular measurements were analyzed continuously and categorically for associations with microalbuminuria using multiple logistic regressions, adjusted for related variables. In logistic regression adjusting for multiple variables, microalbuminuria was associated with smaller peripheral arteriolar caliber, larger peripheral venular caliber, larger arteriolar tortuosity, and smaller arteriolar fractal dimension (p = 0.028, p < 0.001, p = 0.038, p = 0.035, respectively). In further categorical analyses, microalbuminuria was related to smaller peripheral arteriolar caliber [T1 vs. T3: odds ratio (OR) 2.029; 95% confidence interval (CI) 1.186–3.473], larger peripheral venular caliber (T1 vs. T3: OR 0.609; 95% CI 0.362–1.024), and smaller arteriolar fractal dimension (T1 vs. T3: OR 1.659; 95% CI 1.028–2.675). Microalbuminuria in type 2 diabetes is associated with both retinal vascular caliber and geometry. These noninvasive vascular measurements serve as potential preclinical markers to identify populations at high risk of early kidney disease in the course of diabetes.

The eye, the kidney, and cardiovascular disease: old concepts, better tools, and new horizons

Chronic kidney disease (CKD) is common, with hypertension and diabetes mellitus acting as major risk factors for its development. Cardiovascular disease is the leading cause of death worldwide and the most frequent end point of CKD. There is an urgent need for more precise methods to identify patients at risk of CKD and cardiovascular disease. Alterations in microvascular structure and function contribute to the development of hypertension, diabetes, CKD, and their associated cardiovascular disease. Homology between the eye and the kidney suggests that noninvasive imaging of the retinal vessels can detect these microvascular alterations to improve targeting of at-risk patients. Retinal vessel-derived metrics predict incident hypertension, diabetes, CKD, and cardiovascular disease and add to the current renal and cardiovascular risk stratification tools. The advent of optical coherence tomography (OCT) has transformed retinal imaging by capturing the chorioretinal microcirculation and its dependent tissue with near-histological resolution. In hypertension, diabetes, and CKD, OCT has revealed vessel remodeling and chorioretinal thinning. Clinical and preclinical OCT has linked retinal microvascular pathology to circulating and histological markers of injury in the kidney. The advent of OCT angiography allows contrast-free visualization of intraretinal capillary networks to potentially detect early incipient microvascular disease. Combining OCT's deep imaging with the analytical power of deep learning represents the next frontier in defining what the eye can reveal about the kidney and broader cardiovascular health.

Age and sex affect deep learning prediction of cardiometabolic risk factors from retinal images

Deep neural networks can extract clinical information, such as diabetic retinopathy status and individual characteristics (e.g. age and sex), from retinal images. Here, we report the first study to train deep learning models with retinal images from 3,000 Qatari citizens participating in the Qatar Biobank study. We investigated whether fundus images can predict cardiometabolic risk factors, such as age, sex, blood pressure, smoking status, glycaemic status, total lipid panel, sex steroid hormones and bioimpedance measurements. Additionally, the role of age and sex as mediating factors when predicting cardiometabolic risk factors from fundus images was studied. Predictions at person-level were made by combining information of an optic disc centred and a macula centred image of both eyes with deep learning models using the MobileNet-V2 architecture. An accurate prediction was obtained for age (mean absolute error (MAE): 2.78 years) and sex (area under the curve: 0.97), while an acceptable performance was achieved for systolic blood pressure (MAE: 8.96 mmHg), diastolic blood pressure (MAE: 6.84 mmHg), Haemoglobin A1c (MAE: 0.61%), relative fat mass (MAE: 5.68 units) and testosterone (MAE: 3.76 nmol/L). We discovered that age and sex were mediating factors when predicting cardiometabolic risk factors from fundus images. We have found that deep learning models indirectly predict sex when trained for testosterone. For blood pressure, Haemoglobin A1c and relative fat mass an influence of age and sex was observed. However, achieved performance cannot be fully explained by the influence of age and sex. In conclusion we confirm that age and sex can be predicted reliably from a fundus image and that unique information is stored in the retina that relates to blood pressure, Haemoglobin A1c and relative fat mass. Future research should focus on stratification when predicting person characteristics from a fundus image.

Association Between Maternal Prepregnancy Body Mass Index and Anthropometric Parameters, Blood Pressure, and Retinal Microvasculature in Children Age 4 to 6 Years

IMPORTANCE

Maternal prepregnancy body mass index (BMI; calculated as weight in kilograms divided by height in meters squared) has previously been associated with offspring cardiometabolic risk factors, such as fat mass, glucose and insulin levels, and blood pressure, but these associations appear to be largely mediated by offspring BMI. To our knowledge, no studies have assessed alterations in the retinal microvasculature in association with maternal prepregnancy BMI.

OBJECTIVE

To investigate the association between maternal prepregnancy BMI and anthropometric parameters, blood pressure, and retinal vessel parameters in children age 4 to 6 years.

DESIGN, SETTING, AND PARTICIPANTS

Participants included mother-child pairs of the population-based Environmental Influence on Early Aging (ENVIRONAGE) birth cohort study (Flanders, Belgium) who were recruited at birth from February 2010 to June 2014 and followed-up at age 4 to 6 years between October 2014 and July 2018. Data were analyzed from February 2019 to April 2019.

EXPOSURES

Maternal prepregnancy BMI based on height and weight measurements at the first antenatal visit (weeks 7-9 of gestation).

MAIN OUTCOMES AND MEASURES

Children's anthropometric, blood pressure, and retinal microcirculation measurements at age 4 to 6 years. Retinal vessel diameters and the tortuosity index, a measure for the curvature of the retinal vasculature, were obtained by fundus image analysis.

RESULTS

This study included 240 mothers and children with a mean (SD) age of 29. 9 (4.2) years and 54.8 (4.7) months, respectively. Of these, 114 children (47.5%) were boys. Maternal prepregnancy BMI was positively associated with the child's birth weight, BMI, waist circumference, blood pressure, and retinal vessel tortuosity. A 1-point increase in maternal prepregnancy BMI was associated with a 0.26-mm Hg (95% CI, 0.08-0.44) higher mean arterial pressure for their children, with similar estimates for systolic and diastolic blood pressure. Independent from the association with blood pressure, a 1-point increase in maternal prepregnancy BMI was associated with a 0.40 (95% CI, 0.01-0.80) higher retinal tortuosity index (× 103). The hypothesis that these associations reflect direct intrauterine mechanisms is supported by the following observations: associations were independent of the current child's BMI and the estimates for paternal BMI at the follow-up visit did not reach significance.

CONCLUSIONS AND RELEVANCE

Considering that blood pressure tracks from childhood into adulthood and microvascular changes may be early markers of cardiometabolic disease development, our results suggest that maternal prepregnancy BMI is an important modifiable risk factor for later-life cardiovascular health of the offspring.

Insights into Systemic Disease through Retinal Imaging-Based Oculomics

Among the most noteworthy developments in ophthalmology over the last decade has been the emergence of quantifiable high-resolution imaging modalities, which are typically non-invasive, rapid and widely available. Such imaging is of unquestionable utility in the assessment of ocular disease however evidence is also mounting for its role in identifying ocular biomarkers of systemic disease, which we term oculomics. In this review, we highlight our current understanding of how retinal morphology evolves in two leading causes of global morbidity and mortality, cardiovascular disease and dementia. Population-based analyses have demonstrated the predictive value of retinal microvascular indices, as measured through fundus photography, in screening for heart attack and stroke. Similarly, the association between the structure of the neurosensory retina and prevalent neurodegenerative disease, in particular Alzheimer's disease, is now well-established. Given the growing size and complexity of emerging multimodal datasets, modern artificial intelligence techniques, such as deep learning, may provide the optimal opportunity to further characterize these associations, enhance our understanding of eye-body relationships and secure novel scalable approaches to the risk stratification of chronic complex disorders of ageing.

Multiloss Function Based Deep Convolutional Neural Network for Segmentation of Retinal Vasculature into Arterioles and Venules

The arterioles and venules (AV) classification of retinal vasculature is considered as the first step in the development of an automated system for analysing the vasculature biomarker association with disease prognosis. Most of the existing AV classification methods depend on the accurate segmentation of retinal blood vessels. Moreover, the unavailability of large-scale annotated data is a major hindrance in the application of deep learning techniques for AV classification. This paper presents an encoder-decoder based fully convolutional neural network for classification of retinal vasculature into arterioles and venules, without requiring the preliminary step of vessel segmentation. An optimized multiloss function is used to learn the pixel-wise and segment-wise retinal vessel labels. The proposed method is trained and evaluated on DRIVE, AVRDB, and a newly created AV classification dataset; and it attains 96%, 98%, and 97% accuracy, respectively. The new AV classification dataset is comprised of 700 annotated retinal images, which will offer the researchers a benchmark to compare their AV classification results.

Associations of Retinal Microvascular Diameters and Tortuosity With Blood Pressure and Arterial Stiffness: United Kingdom Biobank

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To examine the baseline associations of retinal vessel morphometry with blood pressure (BP) and arterial stiffness in United Kingdom Biobank. The United Kingdom Biobank included 68 550 participants aged 40 to 69 years who underwent nonmydriatic retinal imaging, BP, and arterial stiffness index assessment. A fully automated image analysis program (QUARTZ [Quantitative Analysis of Retinal Vessel Topology and Size]) provided measures of retinal vessel diameter and tortuosity. The associations between retinal vessel morphology and cardiovascular disease risk factors/outcomes were examined using multilevel linear regression to provide absolute differences in vessel diameter and percentage differences in tortuosity (allowing within person clustering), adjusted for age, sex, ethnicity, clinic, body mass index, smoking, and deprivation index. Greater arteriolar tortuosity was associated with higher systolic BP (relative increase, 1.2%; 95% CI, 0.9; 1.4% per 10 mmHg), higher mean arterial pressure, 1.3%; 0.9, 1.7% per 10 mmHg, and higher pulse pressure (PP, 1.8%; 1.4; 2.2% per 10 mmHg). Narrower arterioles were associated with higher systolic BP (−0.9 µm; −0.94, −0.87 µm per 10 mmHg), mean arterial pressure (−1.5 µm; −1.5, −1.5 µm per 10 mmHg), PP (−0.7 µm; −0.8, −0.7 µm per 10 mmHg), and arterial stiffness index (−0.12 µm; −0.14, −0.09 µm per ms/m²). Associations were in the same direction but marginally weaker for venular tortuosity and diameter. This study assessing the retinal microvasculature at scale has shown clear associations between retinal vessel morphometry, BP, and arterial stiffness index. These observations further our understanding of the preclinical disease processes and interplay between microvascular and macrovascular disease.

Novel Genetic Locus Influencing Retinal Venular Tortuosity Is Also Associated With Risk of Coronary Artery Disease

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The retina may provide readily accessible imaging biomarkers of global cardiovascular health. Increasing evidence suggests variation in retinal vascular traits is highly heritable. This study aimed to identify the genetic determinants of retinal vascular traits.