Retinal vascular geometry and 6 year incidence and progression of diabetic retinopathy

A Novel Method for the Measurement of Retinal Arteriolar Bifurcation

INTRODUCTION

The purpose of this research was to develop protocols for evaluating the bifurcation parameters of retinal arteriole and establish a reference range of normal values.

METHODS

In this retrospective study, we measured a total of 1314 retinal arteriolar bifurcations from 100 fundus photographs. We selected 200 from these bifurcations for testing inter-measurer and inter-method agreement. Additionally, we calculated the normal reference range for retinal arteriolar bifurcation parameters and analyzed the effects of gender, age, and anatomical features on retinal arteriolar bifurcation.

RESULTS

The measurement method proposed in this study has demonstrated nearly perfect consistency among different measurers, with interclass correlation coefficient (ICC) for all bifurcation parameters of retinal arteriole exceeding 0.95. Among healthy individuals, the retinal arteriolar caliber was narrowest in young adults and increased in children, teenagers, and the elderly; retinal arteriolar caliber was greater in females than in males; and the diameter of the inferior temporal branch exceeded that of the superior temporal branch. The angle between the two branches of retinal arteriolar bifurcation was also greater in females than in males. When using the center of the optic disc as a reference point, the angle between the two branches of the retinal arteriole at the proximal or distal ends increased. In contrast, the estimated optimum theoretical values of retinal arteriolar bifurcation were not affected by these factors.

CONCLUSIONS

The method for the measurement of retinal arteriolar bifurcation in this study was highly accurate and reproducible. The diameter and branching angle of the retinal arteriolar bifurcation were more susceptible to the influence of gender, age, and anatomical features. In comparison, the estimated optimum theoretical values of retinal arteriolar bifurcation were relatively stable. Video available for this article.

Remnant cholesterol is correlated with retinal vascular morphology and diabetic retinopathy in type 2 diabetes mellitus: a cross-sectional study

BACKGROUND

The association between remnant cholesterol (RC) and diabetic retinopathy (DR) in type 2 diabetes mellitus (T2DM) remains unclear. Morphological changes in retinal vessels have been reported to predict vascular complications of diabetes, including DR.

METHODS

This cross-sectional study included 6535 individuals with T2DM. The RC value was calculated using the recognized formula. The retinal vascular parameters were measured using fundus photography. The independent relationship between RC and DR was analyzed using binary logistic regression models. Multiple linear regression and subgroup analyses were employed to investigate the link between RC and vascular parameters, including the retinal arteriolar diameter (CRAE), venular diameter (CRVE), and fractal dimension (Df). Mediation analysis was performed to assess whether the vascular morphology could explain the association between RC and DR.

RESULTS

RC was independently associated with DR in patients with a longer duration of T2DM (> 7 years). Patients with the highest quartile RC levels had larger CRAE (5.559 [4.093, 7.025] μm), CRVE (7.620 [5.298, 9.941] μm) and Df (0.013 [0.009, 0.017]) compared with patients with the lowest quartile RC levels. Results were robust across different subgroups. The association between RC and DR was mediated by CRVE (0.020 ± 0.005; 95% confidence interval: 0.012-0.032).

CONCLUSIONS

RC may be a risk factor for DR among those who have had T2DM for a longer period of time. Higher RC levels were correlated with wider retinal arterioles and venules as well as higher Df, and it may contribute to DR through the dilation of retinal venules.

Associations between retinal microvascular flow, geometry, and progression of diabetic retinopathy in type 2 diabetes: a 2-year longitudinal study

PURPOSE

To determine the association between retinal blood vessel flow and geometric parameters and the risk of diabetic retinopathy (DR) progression through a 2-year prospective cohort study.

METHODS

Patients with type 2 diabetes mellitus (T2DM) were recruited from a diabetic registry between November 2017 and March 2019. All participants underwent standardized examinations at the baseline and 2-year follow-up visit, and the presence and severity of DR were assessed based on standard seven-field color fundus photographs. They also underwent swept-source optical coherence tomography angiography (OCTA) imaging to obtain measurements of foveal avascular zone area, blood vessel density (VD), fractal dimension (FD), blood vessel tortuosity (BVT) in the superficial capillary plexus (SCP) and deep capillary plexus (DCP).

RESULTS

A total of 233 eyes of 125 patients were included, and 40 eyes (17.17%) experienced DR progression within 2 years. DR progression was significantly associated with lower baseline VD (odds ratio [OR] 2.323 per SD decrease; 95% confidence interval [CI] 1.456-3.708; P < 0.001), lower FD (OR, 2.484 per SD decrease; 95% CI 1.268-4.867; P = 0.008), and higher BVT (OR, 2.076 per SD increase; 95% CI 1.382-3.121; P < 0.001) of the DCP after adjusting for confounding factors. The addition of OCTA metrics improved the predictive ability of the original model for DR progression (area under the curve [AUC] from 0.725 to 0.805; P = 0.022).

CONCLUSIONS

OCTA-derived VD, FD and BVT in the DCP were independent predictors of DR progression and showed additive value when added to established risk models predicting DR progression.

A deep learning system for predicting time to progression of diabetic retinopathy

Diabetic retinopathy (DR) is the leading cause of preventable blindness worldwide. The risk of DR progression is highly variable among different individuals, making it difficult to predict risk and personalize screening intervals. We developed and validated a deep learning system (DeepDR Plus) to predict time to DR progression within 5 years solely from fundus images. First, we used 717,308 fundus images from 179,327 participants with diabetes to pretrain the system. Subsequently, we trained and validated the system with a multiethnic dataset comprising 118,868 images from 29,868 participants with diabetes. For predicting time to DR progression, the system achieved concordance indexes of 0.754-0.846 and integrated Brier scores of 0.153-0.241 for all times up to 5 years. Furthermore, we validated the system in real-world cohorts of participants with diabetes. The integration with clinical workflow could potentially extend the mean screening interval from 12 months to 31.97 months, and the percentage of participants recommended to be screened at 1-5 years was 30.62%, 20.00%, 19.63%, 11.85% and 17.89%, respectively, while delayed detection of progression to vision-threatening DR was 0.18%. Altogether, the DeepDR Plus system could predict individualized risk and time to DR progression over 5 years, potentially allowing personalized screening intervals.

Review and comparison of retinal vessel calibre and geometry software and their application to diabetes, cardiovascular disease, and dementia

Developments in retinal imaging technologies have enabled the quantitative evaluation of the retinal vasculature. Changes in retinal calibre and/or geometry have been reported in systemic vascular diseases, including diabetes mellitus (DM), cardiovascular disease (CVD), and more recently in neurodegenerative diseases, such as dementia. Several retinal vessel analysis softwares exist, some being disease-specific, others for a broader context. In the research setting, retinal vasculature analysis using semi-automated software has identified associations between retinal vessel calibre and geometry and the presence of or risk of DM and its chronic complications, and of CVD and dementia, including in the general population. In this article, we review and compare the most widely used semi-automated retinal vessel analysis softwares and their associations with ocular imaging findings in common systemic diseases, including DM and its chronic complications, CVD, and dementia. We also provide original data comparing retinal calibre grading in people with Type 1 DM using two softwares, with good concordance.

Retinal Vascular Geometry in Hypertension: cSLO-Based Method

INTRODUCTION

We aim to introduce a method using confocal scanning laser ophthalmoscopy (cSLO) images for measuring retinal vascular geometry, including vessel branch angle (BA), vessel diameter, vessel tortuosity, and fractal dimension (D_f), and to elucidate the relationship between hypertension and these metrics.

METHODS

A total of 119 participants (119 eyes) were enrolled, among which 72 were normotensive and 47 were hypertensive. Infrared cSLO images were extracted from the circular scan around the optics disc using a commercial cSLO + optical coherence tomography instrument. Preprocessed cSLO images were further analyzed using the appropriate tool/macro/plugin of ImageJ.

RESULTS

Intraclass correlation coefficients of selected methods used for conducting the cSLO-based geometric analyses were all higher than 0.80. Arterial/arteriolar BA, arteriolar vessel diameter, and total D_f in normotensive subjects were 85.80 ± 7.79°, 116.80 ± 12.58 μm, and 1.430 ± 0.037, respectively, significantly higher than those of hypertensive subjects (82.13 ± 10.83°, 108.2 ± 11.12 μm, and 1.361 ± 0.044, all P < 0.05). The aforementioned metrics remained negatively correlated with hypertension even after adjusting for age alone or age and gender (P < 0.05). However, the difference between arteriolar tortuosity and all studied venous/venular geometric parameters in both subjects was insignificant (all P > 0.05).

CONCLUSION

Proposed cSLO-based methods for assessing various vascular geometric parameters were highly repeatable and reproducible. Arterial/arteriolar BA, arteriolar vessel diameter, and total D_f were retinal vascular parameters significantly correlated with hypertension in a negative manner.

The impact of the image conversion factor and image centration on retinal vessel geometric characteristics

Background

This study aims to use fundus image material from a long-term retinopathy follow-up study to identify problems created by changing imaging modalities or imaging settings (e.g., image centering, resolution, viewing angle, illumination wavelength). Investigating the relationship of image conversion factor and imaging centering on retinal vessel geometric characteristics (RVGC), offers solutions for longitudinal retinal vessel analysis for data obtained in clinical routine.

Methods

Retinal vessel geometric characteristics were analyzed in scanned fundus photographs with Singapore-I-Vessel-Assessment using a constant image conversion factor (ICF) and an individual ICF, applying them to macula centered (MC) and optic disk centered (ODC) images. The ICF is used to convert pixel measurements into μm for vessel diameter measurements and to establish the size of the measuring zone. Calculating a constant ICF, the width of all analyzed optic disks is included, and it is used for all images of a cohort. An individual ICF, in turn, uses the optic disk diameter of the eye analyzed. To investigate agreement, Bland-Altman mean difference was calculated between ODC images analyzed with individual and constant ICF and between MC and ODC images.

Results

With constant ICF (n = 104 eyes of 52 patients) the mean central retinal equivalent was 160.9 ± 17.08 μm for arteries (CRAE) and 208.7 ± 14.7.4 μm for veins (CRVE). The individual ICFs resulted in a mean CRAE of 163.3 ± 15.6 μm and a mean CRVE of 219.0 ± 22.3 μm. On Bland–Altman analysis, the individual ICF RVGC are more positive, resulting in a positive mean difference for most investigated parameters. Arteriovenous ratio (p = 0.86), simple tortuosity (p = 0.08), and fractal dimension (p = 0.80) agreed well between MC and ODC images, while the vessel diameters were significantly smaller in MC images (p &lt; 0.002).

Conclusion

Scanned images can be analyzed using vessel assessment software. Investigations of individual ICF versus constant ICF point out the asset of utilizing an individual ICF. Image settings (ODC vs. MC) were shown to have good agreement.

AV-casNet: Fully Automatic Arteriole-Venule Segmentation and Differentiation in OCT Angiography

Automatic segmentation and differentiation of retinal arteriole and venule (AV), defined as small blood vessels directly before and after the capillary plexus, are of great importance for the diagnosis of various eye diseases and systemic diseases, such as diabetic retinopathy, hypertension, and cardiovascular diseases. Optical coherence tomography angiography (OCTA) is a recent imaging modality that provides capillary-level blood flow information. However, OCTA does not have the colorimetric and geometric differences between AV as the fundus photography does. Various methods have been proposed to differentiate AV in OCTA, which typically needs the guidance of other imaging modalities. In this study, we propose a cascaded neural network to automatically segment and differentiate AV solely based on OCTA. A convolutional neural network (CNN) module is first applied to generate an initial segmentation, followed by a graph neural network (GNN) to improve the connectivity of the initial segmentation. Various CNN and GNN architectures are employed and compared. The proposed method is evaluated on multi-center clinical datasets, including 3 ×3 mm2 and 6 ×6 mm2 OCTA. The proposed method holds the potential to enrich OCTA image information for the diagnosis of various diseases.

Deep Learning in Optical Coherence Tomography Angiography: Current Progress, Challenges, and Future Directions

Optical coherence tomography angiography (OCT-A) provides depth-resolved visualization of the retinal microvasculature without intravenous dye injection. It facilitates investigations of various retinal vascular diseases and glaucoma by assessment of qualitative and quantitative microvascular changes in the different retinal layers and radial peripapillary layer non-invasively, individually, and efficiently. Deep learning (DL), a subset of artificial intelligence (AI) based on deep neural networks, has been applied in OCT-A image analysis in recent years and achieved good performance for different tasks, such as image quality control, segmentation, and classification. DL technologies have further facilitated the potential implementation of OCT-A in eye clinics in an automated and efficient manner and enhanced its clinical values for detecting and evaluating various vascular retinopathies. Nevertheless, the deployment of this combination in real-world clinics is still in the "proof-of-concept" stage due to several limitations, such as small training sample size, lack of standardized data preprocessing, insufficient testing in external datasets, and absence of standardized results interpretation. In this review, we introduce the existing applications of DL in OCT-A, summarize the potential challenges of the clinical deployment, and discuss future research directions.

RV-ESA: A novel computer-aided elastic shape analysis system for retinal vessels in diabetic retinopathy

Diabetic retinopathy (DR), one of the most common and serious complications of diabetes, has become one of the main blindness diseases. The retinal vasculature is the only part of the human circulatory system that allows direct noninvasive visualization of the body's microvasculature, which provides the opportunity to detect the structural and functional changes before DR becomes unable to intervene. For decades, as the fundamental step in computer-assisted analysis of retinopathy, retinal vascular extraction methods have been largely developed. However, further research focusing on retinal vascular analysis is still in its infancy. Meanwhile, due to the complexity of retinal vascular structure, the relationship between vascular geometry and DR has never been concluded. This paper aims to provide a novel computer-aided shape analysis system for retinal vessels. To perform retinal vascular shape analysis, a mathematical geometric representation is firstly generated by utilizing the proposed shape modeling method. Then, several useful statistical tools (e.g. Graph Mean, Graph PCA) are adopted to quantitatively analyze the vascular shape. Besides, in order to visualize the changes in vascular shape in the progression of DR, a geodesic tool is used to display the deformation process for ophthalmologists to observe. The efficacy of this analysis system is demonstrated in the EyePACS dataset and the subsequent visit records of 98 patients from the proprietary dataset. The experimental results show that there is a certain correlation between the variation of retinal vascular shape and DR progression, and the Graph PCA scores of retinal vessels are negatively correlated with DR grades. The code of our RV-ESA system can be publicly available at github.com/XiaolingLuo/RV-ESA.

Changes in retinal vascular bifurcation in eyes with myopia

Objective

To evaluate the effect of myopia on retinal vascular bifurcation.

Methods

A cross-sectional study that retrospectively analyzed the fundus photographs and clinical data of 493 people who participated in routine physical examinations in Huadong Sanatorium. One eye of each subject was included in the analysis. Retinal vascular bifurcation measurements were extracted by using a validated computer program. One-way ANOVA and analysis of covariance were performed to compare the measurements across high myopia, low to moderate myopia, and non-myopia groups.

Results

The mean age was 41.83 ± 10.43 years and 63.49% were women. The mean spherical equivalent refraction (SER) was − 4.59 ± 3.07 D. Ninety-nine (20.08%) eyes met the definition of high myopia (SER ≤ -6.0 D), along with 234 (47.46%) low to moderate myopia (-6.0 D < SER <-0.5 D), and 160 (32.45%) non-myopia (SER ≥ -0.5 D). The differences in the arteriolar branching angle, venular branching coefficient, venular asymmetry ratio, venular angular asymmetry, and venular junctional exponent among the three groups remained significant (p < 0.05) after multivariate adjustment. Pairwise comparisons showed arteriolar branching angle and venular angular asymmetry in high myopia were significantly lower than low to moderate myopia (p < 0.001, p = 0.014 respectively) and non-myopia (p = 0.007, p = 0.048 respectively). Venular asymmetry ratio and venular branching coefficient in high myopia were significantly higher than low to moderate myopia (p = 0.029, p = 0.001 respectively) and non-myopia (p = 0.041, p = 0.043 respectively). There was a significant difference in venular junctional exponent between high myopia and low to moderate myopia (p = 0.031).

Conclusion

The vascular bifurcation differs in dependence on the myopic refractive error and a significant increase in the difference can be observed in high myopic eyes.

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.

Peripapillary Microvasculature Predicts the Incidence and Development of Diabetic Retinopathy: An SS-OCTA Study

PURPOSE

To examine the associations of peripapillary microvascular metrics with diabetic retinopathy (DR) incidence and development using swept-source optical coherence tomography angiography (SS-OCTA).

DESIGN

Prospective cohort study.

METHODS

1033 eyes from 1033 type II diabetes mellitus (T2D) patients were included with 2-year follow-up. The peripapillary microvascular metrics at the superficial capillary plexus (SCP) were measured by SS-OCTA at the baseline, including peripapillary vascular density (pVD) and vascular length density (pVLD). The DR incidence and progression were evaluated with seven standard fields of stereoscopic color fundus photographs. The associations were tested with logistic regression models after adjusting established risk factors and confounding factors. The prediction value of OCTA metrics was examined with the elevation of area under receiver operating characteristic curve (AUROC).

RESULTS

The 2-year incidence of DR was 25.1% (n=222) in NDR eyes, 7.4% DR progression (n=11) in DR eyes, and 4.17% RDR eyes (n=43) in all eyes. After adjusting established factors, lower whole image pVD (wi-pVD) (RR, 0.81; 95%CI, 0.68-0.96; P=0.015), circular pVD (circ-pVD) (RR, 0.79; 95%CI, 0.66-0.95; P=0.013), whole image pVLD (wi-pVLD) (RR, 0.79; 95%CI, 0.67-0.94; P=0.008) and circular pVLD (circ-pVLD) (RR, 0.76; 95%CI, 0.63-0.91; P=0.003) were significantly associated with increased risk of DR incidence; wi-pVD (RR, 0.48; 95%CI, 0.35-0.67; P<0.001), circ-pVD (RR, 0.65; 95%CI, 0.45-0.94; P=0.023) and wi-pVLD (RR, 0.46; 95%CI, 0.33-0.66; P<0.001) were associated with incident risk of RDR. Both pVD and pVLD of SCP were not associated with DR progression significantly. AUROC for DR incidence risk prediction model increased from 0.631 to 0.658 (4.28%; P=0.041) by circ-pVLD; the AUC of RDR incidence risk prediction model elevated from 0.631 to 0.752 by wi-pVD (19.18%; P=0.009), to 0.752 by circ-pVD (19.18%; P=0.009), and to 0.752 by wi-pVLD (19.18%; P=0.009).

CONCLUSION

Lower pVD and pVLD of SCP are associated with 2-year incident DR and RDR among T2D population. The peripapillary metrics imaged by SS-OCTA can provide additional value to the prediction of DR incidence and development.

Differential Effect of Generalized and Abdominal Obesity on the Development and Progression of Diabetic Retinopathy in Chinese Adults With Type 2 Diabetes

Background

The relationship between obesity and diabetic retinopathy (DR) remains controversial. The aim of this study was to assess the association of generalized obesity [assessed by body mass index (BMI)] and abdominal obesity [assessed by waist to hip ratio (WHR)] with incident DR, and vision-threatening DR (VTDR), and DR progression among Chinese adults with type 2 diabetic mellitus (T2DM).

Method

This prospective cohort study was conducted at the Zhongshan Ophthalmic Center, from November 2017 to December 2020. DR was assessed based on the 7-filed fundus photographs using the modified Airlie House Classification. Multivariable logistic regression models were used to evaluate the associations of BMI and WHR with the development and progression of DR after adjusting for age, sex, traditional risk factors, and mutually for BMI and WHR.

Results

Among the 1,370 eligible participants, 1,195 (87.2%) had no sign of any DR and 175 (12.8%) had DR at baseline examination. During the 2 years follow-up visit, 342 (28.6%) participants had incident DR, 11 (0.8%) participants developed VTDR, 15 (8.6%) demonstrated DR progression. After adjusting for confounders, the BMI was negatively associated with incident DR [relative risk (RR) =0.31; 95% confidence interval (CI), 0.26-0.38; P < 0.001] and incident VTDR (RR = 0.22; 95%CI, 0.11-0.43; P < 0.001), while WHR was positively associated with incident DR (RR = 1.47; 95% CI, 1.27-1.71; P < 0.001). BMI and WHR level were not significantly associated with 2-year DR progression in multivariate models (all P > 0.05).

Conclusions

This study provides longitudinal evidence that generalized obesity confer a protective effect on DR, while abdominal obesity increased the risk of DR onset in Chinese patients, indicating that abdominal obesity is a more clinically relevant risk marker of DR than generalized obesity.

Retinal Vascular Profile in Predicting Incident Cardiometabolic Diseases among Individuals with Diabetes

OBJECTIVE

To determine the longitudinal associations between retinal vascular profile (RVP) and four major cardiometabolic diseases; and to quantify the predictive improvements when adding RVP beyond traditional risk factors in individuals with diabetes.

METHODS

Subjects were enrolled from the Singapore Epidemiology of Eye Disease (SEED) study, a multi-ethnic population-based cohort. Four incident cardiometabolic diseases, calculated over a ~6-year period, were considered: cardiovascular disease (CVD), hypertension (HTN), diabetic kidney disease (DKD) and hyperlipidaemia (HLD). The RVP - vessel tortuosity, branching angle, branching coefficient, fractal dimension, vessel calibre, and DR status - was characterized at baseline using a computer-assisted program. Traditional risk factors at baseline included age, gender, ethnicity, smoking, blood pressure (BP), HbA1c, estimated glomerular filtration rate (eGFR) or cholesterol. The improvements in predictive performance when adding RVP (compared to only traditional risk factors) was calculated using several metrics including area under the receiver operating characteristics curve (AUC) and Net Reclassification Improvement (NRI).

RESULTS

Among 1,770 individuals with diabetes, incidences were 6.3% (n=79/1259) for CVD, 48.7% (n=166/341) for HTN, 14.6% (n=175/1199) for DKD, and 59.4% (n=336/566) for HLD. DR preceded the onset of CVD (RR 1.85[1.14;3.00]) and DKD (1.44 [1.06;1.96]). Narrower arteriolar calibre preceding the onset of HTN (0.84 [0.72;0.99]), and changes in arteriolar branching angle preceded the onset of CVD (0.78 [0.62;0.98]) and HTN (1.15 [1.03;1.29]). The largest predictive improvement was found for HTN with AUC increment of 3.4% (p=0.027) and better reclassification of 11.4% of the cases and 4.6% of the controls (p=0.008).

CONCLUSION

We found that RVPs improved the prediction of HTN in individuals with diabetes, but add limited information for CVD, DKD and HLD predictions.

Flow and geometrical alterations in retinal microvasculature correlated with the occurrence of diabetic retinopathy: evidence from a longitudinal study

PURPOSE

To assess the relationship between flow and geometric parameters in optical coherence tomography angiography (OCTA) images and the risk of incident diabetic retinopathy (DR).

METHODS

This prospective, observational cohort study recruited patients with type 2 diabetes without DR in Guangzhou, China and followed up annually. A commercially available OCTA device (DRI-OCT Triton; Topcon Inc., Tokyo, Japan) was used to obtain a variety of flow (foveal avascular zone [FAZ] area, vessel density [VD], vessel length density [VLD]) and geometric (fractal dimension [FD] and blood vessel tortuosity [BVT]) parameters in superficial capillary plexus (SCP) and deep capillary plexus (DCP). The odds ratio [OR] and its 95% confidential interval [CI] were calculated per 1-SD increase in each OCTA parameter.

RESULTS

Over a follow-up of one year, 182 of 1,698 participants (10.7%) developed incident DR. After adjusting for conventional risk factors and image quality score, the higher risk of DR onset was significantly associated with the reduced parafoveal VD of SCP (OR=0.81; 95% CI: 0.69, 0.96; P = 0.016), reduced parafoveal VLD of SCP (OR=0.73; 95% CI: 0.59, 0.90; P = 0.003), reduced FD of SCP (OR=0.73; 95% CI: 0.61, 0.87; P < 0.001), increased BVT of SCP (OR=1.39; 95% CI: 1.18, 1.64; P < 0.001) and increased BVT of DCP (OR=1.19; 95% CI: 1.01, 1.40; P = 0.033) .

CONCLUSION

Reduced vessel density and impaired vessel geometry posed higher susceptibility for DR onset in patients with type 2 diabetes, supporting the adoption of OCTA parameters as early monitoring indicators of the newly incident DR.

Retinal photograph-based deep learning predicts biological age, and stratifies morbidity and mortality risk

BACKGROUND

ageing is an important risk factor for a variety of human pathologies. Biological age (BA) may better capture ageing-related physiological changes compared with chronological age (CA).

OBJECTIVE

we developed a deep learning (DL) algorithm to predict BA based on retinal photographs and evaluated the performance of our new ageing marker in the risk stratification of mortality and major morbidity in general populations.

METHODS

we first trained a DL algorithm using 129,236 retinal photographs from 40,480 participants in the Korean Health Screening study to predict the probability of age being ≥65 years ('RetiAGE') and then evaluated the ability of RetiAGE to stratify the risk of mortality and major morbidity among 56,301 participants in the UK Biobank. Cox proportional hazards model was used to estimate the hazard ratios (HRs).

RESULTS

in the UK Biobank, over a 10-year follow up, 2,236 (4.0%) died; of them, 636 (28.4%) were due to cardiovascular diseases (CVDs) and 1,276 (57.1%) due to cancers. Compared with the participants in the RetiAGE first quartile, those in the RetiAGE fourth quartile had a 67% higher risk of 10-year all-cause mortality (HR = 1.67 [1.42-1.95]), a 142% higher risk of CVD mortality (HR = 2.42 [1.69-3.48]) and a 60% higher risk of cancer mortality (HR = 1.60 [1.31-1.96]), independent of CA and established ageing phenotypic biomarkers. Likewise, compared with the first quartile group, the risk of CVD and cancer events in the fourth quartile group increased by 39% (HR = 1.39 [1.14-1.69]) and 18% (HR = 1.18 [1.10-1.26]), respectively. The best discrimination ability for RetiAGE alone was found for CVD mortality (c-index = 0.70, sensitivity = 0.76, specificity = 0.55). Furthermore, adding RetiAGE increased the discrimination ability of the model beyond CA and phenotypic biomarkers (increment in c-index between 1 and 2%).

CONCLUSIONS

the DL-derived RetiAGE provides a novel, alternative approach to measure ageing.

Systematic bibliometric and visualized analysis of research hotspots and trends on the application of artificial intelligence in diabetic retinopathy

BACKGROUND

Artificial intelligence (AI), which has been used to diagnose diabetic retinopathy (DR), may impact future medical and ophthalmic practices. Therefore, this study explored AI's general applications and research frontiers in the detection and gradation of DR.

METHODS

Citation data were obtained from the Web of Science Core Collection database (WoSCC) to assess the application of AI in diagnosing DR in the literature published from January 1, 2012, to June 30, 2022. These data were processed by CiteSpace 6.1.R3 software.

RESULTS

Overall, 858 publications from 77 countries and regions were examined, with the United States considered the leading country in this domain. The largest cluster labeled "automated detection" was employed in the generating stage from 2007 to 2014. The burst keywords from 2020 to 2022 were artificial intelligence and transfer learning.

CONCLUSION

Initial research focused on the study of intelligent algorithms used to localize or recognize lesions on fundus images to assist in diagnosing DR. Presently, the focus of research has changed from upgrading the accuracy and efficiency of DR lesion detection and classification to research on DR diagnostic systems. However, further studies on DR and computer engineering are required.

Clinical Manifestations of Supra-Large Range Nonperfusion Area in Diabetic Retinopathy

OBJECTIVE

We describe the clinical manifestations of supra-large range nonperfusion area (SLRNPA) in diabetic retinopathy (DR).

METHODS

This was a retrospective case-control study. A total of 260 eyes of 236 patients with DR who underwent pars plana vitrectomy in the Department of Ophthalmology of Qingdao Municipal Hospital from February 2016 to June 2019 were enrolled. Fundus fluorescein angiography was performed after surgery to determine whether SLRNPA or non-SLRNPA in DR was present. All demographic and clinical data were carefully collected.

RESULTS

Forty-one eyes of 22 patients were diagnosed with SLRNPA in DR (15.77% of all eyes). Compared to non-SLRNPA, SLRNPA patients were more likely to be male and younger with earlier DR onset, a smoking history, other comorbidities, and a higher HbA1c level. SLRNPA in DR eyes exhibited more neovascular glaucoma (NVG) and diabetic keratopathy (DK) than did other eyes. Such eyes were more likely to require anti-VEGF therapy before surgery or a silicone oil or a gas tamponade during surgery and to suffer from persistent corneal epithelial erosion and NVG recurrence after surgery.

CONCLUSIONS

SLRNPA in DR is a severe status of DR. Treatment for DR patients with SLRNPA is difficult, and the prognosis is poor, so clinicians must thus pay more attention to SLRNPA in DR.

Macular Vascular Geometry Changes With Sex and Age in Healthy Subjects: A Fundus Photography Study

Purpose: To characterize the sex- and age-related alterations of the macular vascular geometry in a population of healthy eyes using fundus photography.

Methods: A cross-sectional study was conducted with 610 eyes from 305 healthy subjects (136 men, 169 women) who underwent fundus photography examination and was divided into four age groups (G1 with age ≤ 25 years, G2 with age 26–35 years, G3 with age 36–45 years, and G4 with age ≥ 46 years). A self-developed automated retinal vasculature analysis system allowed segmentation and separate multiparametric quantification of the macular vascular network according to the Early Treatment Diabetic Retinopathy Study (ETDRS). Vessel fractal dimension (D_f), vessel area rate (VAR), average vessel diameter (D_m), and vessel tortuosity (τ_n) were acquired and compared between sex and age groups.

Results: There was no significant difference between the mean age of male and female subjects (32.706 ± 10.372 and 33.494 ± 10.620, respectively, p > 0.05) and the mean age of both sexes in each age group (p > 0.05). The D_f, VAR, and D_m of the inner ring, the D_f of the outer ring, and the D_f and VAR of the whole macula were significantly greater in men than women (p < 0.001, p < 0.001, p < 0.05, respectively). There was no significant change of τ_n between males and females (p > 0.05). The D_f, VAR, and D_m of the whole macula, the inner and outer rings associated negatively with age (p < 0.001), whereas the τ_n showed no significant association with age (p > 0.05). Comparison between age groups observed that D_f started to decrease from G2 compared with G1 in the inner ring (p < 0.05) and D_f, VAR, and D_m all decreased from G3 compared with the younger groups in the whole macula, inner and outer rings (p < 0.05).

Conclusion: In the healthy subjects, macular vascular geometric parameters obtained from fundus photography showed that D_f, VAR, and D_m are related to sex and age while τ_n is not. The baseline values of the macular vascular geometry were also acquired for both sexes and all age groups.

Usefulness of Machine Learning for Identification of Referable Diabetic Retinopathy in a Large-Scale Population-Based Study

Purpose: To development and validation of machine learning-based classifiers based on simple non-ocular metrics for detecting referable diabetic retinopathy (RDR) in a large-scale Chinese population–based survey.

Methods: The 1,418 patients with diabetes mellitus from 8,952 rural residents screened in the population-based Dongguan Eye Study were used for model development and validation. Eight algorithms [extreme gradient boosting (XGBoost), random forest, naïve Bayes, k-nearest neighbor (KNN), AdaBoost, Light GBM, artificial neural network (ANN), and logistic regression] were used for modeling to detect RDR in individuals with diabetes. The area under the receiver operating characteristic curve (AUC) and their 95% confidential interval (95% CI) were estimated using five-fold cross-validation as well as an 80:20 ratio of training and validation.

Results: The 10 most important features in machine learning models were duration of diabetes, HbA1c, systolic blood pressure, triglyceride, body mass index, serum creatine, age, educational level, duration of hypertension, and income level. Based on these top 10 variables, the XGBoost model achieved the best discriminative performance, with an AUC of 0.816 (95%CI: 0.812, 0.820). The AUCs for logistic regression, AdaBoost, naïve Bayes, and Random forest were 0.766 (95%CI: 0.756, 0.776), 0.754 (95%CI: 0.744, 0.764), 0.753 (95%CI: 0.743, 0.763), and 0.705 (95%CI: 0.697, 0.713), respectively.

Conclusions: A machine learning–based classifier that used 10 easily obtained non-ocular variables was able to effectively detect RDR patients. The importance scores of the variables provide insight to prevent the occurrence of RDR. Screening RDR with machine learning provides a useful complementary tool for clinical practice in resource-poor areas with limited ophthalmic infrastructure.

Retinal microvasculature and time to pregnancy in a multi-ethnic pre-conception cohort in Singapore

STUDY QUESTION

Can abnormalities in retinal microvasculature representing adverse microcirculatory perfusion and inflammation shed light on the pathophysiology of female fecundability?

SUMMARY ANSWER

In our prospective study, abnormalities in retinal vascular geometric morphology (i.e. sparser arteriolar fractal and larger venular bifurcation) during pre-conception phase are temporarily associated with a prolonged time-to-pregnancy (TTP).

WHAT IS KNOWN ALREADY

Suboptimal retinal microcirculatory morphology has been associated with obesity, psychological stress and hypertension, all of which are known risk factors for reduced female fecundability.

STUDY DESIGN, SIZE, DURATION

A total of 652 women of Chinese, Malay or Indian ethnicity 18-45 years of age and planning to conceive spontaneously within the next 12 months were recruited during the pre-conception period into the Singapore PREconception Study of long-Term maternal and child Outcomes (S-PRESTO), from February 2015 to October 2017.

PARTICIPANTS/MATERIALS, SETTING, METHODS

During recruitment, we collected information on socio-demographic factors, menstrual characteristics and lifestyle behaviors and made anthropometric measurements. We assessed the following retinal microvascular features: caliber, branching angle and fractal dimension. We conducted follow-up telephone surveys to track each participant's pregnancy status at 6, 9 and 12 months after enrolment. We ascertained clinical pregnancies via ultrasonography, with TTP measured by the number of menstrual cycles required to achieve a clinical pregnancy over a 1-year follow-up. Then, we performed discrete-time proportional hazards models to estimate the fecundability odds ratio (FOR) and 95% CI for each retinal microvascular feature in association with TTP, after adjusting for major confounders, including body mass index and fasting glycemic level at study entry.

MAIN RESULTS AND THE ROLE OF THE CHANCE

Among 652 recruited women, 276 (42.3%) successfully conceived within 1 year of follow-up. The mean (and SD) was 1.24 (0.05) Df for retinal arteriolar dimension fraction and 78.45 (9.79) degrees for retinal venular branching angle, respectively. Non-linear relationship testing was performed before multiple adjustment in all associations and a non-monotonic association was detected between retinal venular branching angle and TTP. Compared with women in the highest tertile of retinal arteriolar fractal dimension, women in the second tertile had a prolonged TTP (FOR: 0.68; 95% CI: 0.51-0.92), as did women in the lowest tertile (FOR: 0.73; 95% CI: 0.55-0.98). Compared with women in the middle tertile of retinal venular branching angle, women in the highest tertile had a borderline prolonged TTP (FOR: 0.75; 95% CI: 0.56-1.02). No other retinal vascular features were significantly associated with TTP.

LIMITATIONS, REASONS FOR CAUTION

We were unable to adjust for other potential confounding factors such as female sexual function (e.g. frequency of sexual intercourse), which might introduce a residual bias. Moreover, even though this is a prospective cohort design, our findings can identify the temporal relationship but not necessarily infer a causal relationship between maternal microvasculature and TTP. Lastly, our study involving mainly Chinese, Malay and Indian ethnicities might not be generalizable to other races or ethnicities.

WIDER IMPLICATIONS OF THE FINDINGS

Suboptimal microcirculation may lead to reduced female fecundability. In the future, in addition to conventional ultrasonographic evaluation of ovarian and uterine physiological function, assessing the retinal microvasculature might be useful for assessment of ovarian age, fertility prediction and endometrial evaluation before assisted reproductive techniques for fertility treatments.

STUDY FUNDING/COMPETING INTEREST(S)

This research is supported by the Singapore National Research Foundation (NRF) under its Translational and Clinical Research (TCR) Flagship Programme and administered by the Singapore Ministry of Health's National Medical Research Council (NMRC) (Singapore-NMRC/TCR/004-NUS/2008; NMRC/TCR/012-NUHS/2014) and Singapore National Medical Research Council Transition Award (NMRC TA/0027/2014). The authors have no competing interests to declare.

TRIAL REGISTRATION NUMBER

ClinicalTrials.gov, NCT03531658.

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.

A novel multiple subdivision-based algorithm for quantitative assessment of retinal vascular tortuosity

Vascular tortuosity as an indicator of retinal vascular morphological changes can be quantitatively analyzed and used as a biomarker for the early diagnosis of relevant disease such as diabetes. While various methods have been proposed to evaluate retinal vascular tortuosity, the main obstacle limiting their clinical application is the poor consistency compared with the experts' evaluation. In this research, we proposed to apply a multiple subdivision-based algorithm for the vessel segment vascular tortuosity analysis combining with a learning curve function of vessel curvature inflection point number, emphasizing the human assessment nature focusing not only global but also on local vascular features. Our algorithm achieved high correlation coefficients of 0.931 for arteries and 0.925 for veins compared with clinical grading of extracted retinal vessels. For the prognostic performance against experts' prediction in retinal fundus images from diabetic patients, the area under the receiver operating characteristic curve reached 0.968, indicating a good consistency with experts' predication in full retinal vascular network evaluation.

Relationships Between Retinal Vascular Characteristics and Renal Function in Patients With Type 2 Diabetes Mellitus

Purpose

To develop a deep learning-based method to achieve vessel segmentation and measurement on fundus images, and explore the quantitative relationships between retinal vascular characteristics and the clinical indicators of renal function.

Methods

We recruited patients with type 2 diabetes mellitus with different stages of diabetic retinopathy (DR), collecting their fundus photographs and results of renal function tests. A deep learning framework for retinal vessel segmentation and measurement was developed. The correlation between the renal function indicators and the severity of DR were explored, then the correlation coefficients between indicators of renal function and retinal vascular characteristics were analyzed.

Results

We included 418 patients (eyes) with type 2 diabetes mellitus. The albumin to creatinine ratio, blood uric acid, blood creatinine, blood albumin, and estimated glomerular filtration rate were significantly correlated with the progression of DR (P < 0.05); no correlation existed in other metrics (P > 0.05). The fractal dimension was found to significantly correlate with most of the clinical parameters of renal function (P < 0.05).

Conclusions

The albumin to creatinine ratio, blood uric acid, blood creatinine, blood albumin, and estimated glomerular filtration rate have significant correlation with the progression of moderate to proliferative DR. Through deep learning-based vessel segmentation and measurement, the fractal dimension was found to significantly correlate with most clinical parameters of renal function.

Translational Relevance

Deep learning-based vessel segmentation and measurement on color fundus photographs could explore the relationships between retinal characteristics and renal function, facilitating earlier detection and intervention of type 2 diabetes mellitus complications.

Imaging the eye and its relevance to diabetes care

Diabetes is a major cause of vision loss globally, yet this devastating complication is largely preventable. Early detection and treatment of diabetic retinopathy necessitates screening. Ocular imaging is widely used clinically, both for the screening and management of diabetic retinopathy. Common eye conditions, such as glaucoma, cataracts and retinal vessel thrombosis, and signs of systemic conditions, such as hypertension, are frequently revealed. As well as imaging by a skilled clinician during an eye examination, non-ophthalmic clinicians, such as general practitioners, endocrinologists, nurses and trained health workers, can also can carry out diabetic eye screening. This process usually comprises local imaging with remote grading, mostly human grading. However, grading incorporating artificial intelligence is emerging. In a clinical research context, retinal vasculature analyses using semi-automated software in many populations have identified associations between retinal vessel geometry, such as vessel caliber, and the risk of diabetic retinopathy and other chronic complications of type 1 and type 2 diabetes. Similarly, evaluation of corneal nerves by corneal confocal microscopy is revealing diabetes-related abnormalities, and associations with and predictive power for other chronic diabetes complications. As yet, the value of retinal vessel geometry and corneal confocal microscopy measures at an individual level is uncertain. In this article, targeting non-ocular clinicians and researchers, we review existent and emerging ocular imaging and grading tools, including artificial intelligence, and their associations between ocular imaging findings and diabetes and its chronic complications.

Retinal venular tortuosity and fractal dimension predict incident retinopathy in adults with type 2 diabetes: the Edinburgh Type 2 Diabetes Study

AIMS/HYPOTHESIS

Our aim was to determine whether a range of prespecified retinal vessel traits were associated with incident diabetic retinopathy in adults with type 2 diabetes.

METHODS

In the prospective observational cohort Edinburgh Type 2 Diabetes Study of 1066 adults with type 2 diabetes, aged 60-75 years at recruitment, 718 were free from diabetic retinopathy at baseline. Baseline retinal traits including vessel widths, tortuosity (curvature) and fractal dimensions (network complexity), were quantified using fundus camera images and semiautomated software, and analysed using logistic regression for their association with incident diabetic retinopathy over 10 years.

RESULTS

The incidence of diabetic retinopathy was 11.4% (n = 82) over 10 years. After adjustment for a range of vascular and diabetes-related risk factors, both increased venular tortuosity (OR 1.51; 95% CI 1.15, 1.98; p = 0.003) and decreased fractal dimension (OR 0.75; 95% CI 0.58, 0.96; p = 0.025) were associated with incident retinopathy. There was no evidence of an association with arterial tortuosity, and associations between measurements of vessel widths and retinopathy lost statistical significance after adjustment for diabetes-related factors and vascular disease. Adding venular tortuosity to a model including established risk factors for diabetic retinopathy (HbA_1c, BP and kidney function) improved the discriminative ability (C statistic increased from 0.624 to 0.640, p = 0.013), but no such benefit was found with fractal dimension.

CONCLUSIONS/INTERPRETATION

Increased retinal venular tortuosity and decreased fractal dimension are associated with incident diabetic retinopathy, independent of classical risk factors. There is some evidence that venular tortuosity may be a useful biomarker to improve the predictive ability of models based on established retinopathy risk factors, and its inclusion in further risk prediction modelling is warranted.

Retinal microvascular signs and risk of diabetic kidney disease in asian and white populations

The objective was to examine prospectively the association between retinal microvascular signs and development of diabetic kidney disease (DKD) in Asian and White populations. We analysed two population-based cohorts, composing of 1,221 Asians (SEED) and 703 White (WESDR) adults with diabetes. Retinal microvascular signs at baseline included vascular caliber (arteriolar—CRAE, and venular—CRVE) and diabetic retinopathy (DR). Incident cases of DKD were identified after ~ 6-year. Incident cases were defined based on eGFR in SEED and proteinuria or history of renal dialysis in WESDR. The incidence of DKD were 11.8% in SEED and 14.0% in WESDR. Wider CRAE in SEED (OR = 1.58 [1.02, 2.45]) and wider CRVE (OR = 1.69 [1.02, 2.80)) in WESDR were associated with increased risk of DKD. Presence of DR was associated with an increased risk of DKD in both cohorts (SEED: OR = 1.91 [1.21, 3.01] in SEED, WESDR: OR = 1.99 [1.18, 3.35]). Adding DR and retinal vascular calibers in the model beyond traditional risk factors led to an improvement of predictive performance of DKD risk between 1.1 and 2.4%; and improved classification (NRI 3 between 9%). Microvascular changes in the retina are longitudinally associated with risk of DKD.

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.

Optical coherence tomography angiography reveals progressive worsening of retinal vascular geometry in diabetic retinopathy and improved geometry after panretinal photocoagulation

Purpose

To quantify vessel tortuosity and fractal dimension of the superficial capillary plexus (SCP) of the macula in different stages of diabetic retinopathy (DR), and following panretinal photocoagulation (PRP) using optical coherence tomography angiography (OCTA).

Methods

75 eyes of 75 subjects were divided into five groups; healthy controls, diabetes with no clinical DR, non-proliferative diabetic retinopathy (NPDR), proliferative diabetic retinopathy (PDR) and patients who received PRP for PDR (PDR+PRP).For vessel tortuosity, SCP slabs from 3x3 mm macular OCTA scans were processed using imageJ (NIH, USA), where large perifoveal vessels were traced and their length was measured with tortuosity calculated as the ratio between the actual length and the straight Euclidean length. For fractal dimension, SCP slabs were processed and imported to Fractalyse (ThéMA, France), where box-counting analyses produced fractal dimension values.

Results

We found a significant difference in vessel tortuosity and fractal dimension between the five groups (one-way ANOVA, p < 0.001both). NPDR and PDR had significantly more tortuous vessels and lower fractal dimension compared to healthy controls (Tukey HSD: p = 0.02, 0.015,0.015 and <0.001, respectively). Fractal dimension was also significantly lower in NPDR and PDR compared to eyes with no clinical DR (p <0.001 both), and in PDR compared to NPDR (p = 0.014). Following PRP, vessel tortuosity was significantly lower and fractal dimension was higher in PDR+PRP compared to PDR (p = 0.001 and 0.031, respectively).

Conclusions

We used macular OCTA scans to demonstrate significantly higher perifoveal large vessel tortuosity, and lower fractal dimension in NPDR and PDR compared to healthy controls. Vessel tortuosity shows more dramatic normalization than fractal dimension and could be explored as a sensitive marker for successful PRP.

Computer aided diabetic retinopathy detection based on ophthalmic photography: a systematic review and Meta-analysis

AIM

To ensure the diagnostic value of computer aided techniques in diabetic retinopathy (DR) detection based on ophthalmic photography (OP).

METHODS

PubMed, EMBASE, Ei village, IEEE Xplore and Cochrane Library database were searched systematically for literatures about computer aided detection (CAD) in DR detection. The methodological quality of included studies was appraised by the Quality Assessment Tool for Diagnostic Accuracy Studies (QUADAS-2). Meta-DiSc was utilized and a random effects model was plotted to summarize data from those included studies. Summary receiver operating characteristic curves were selected to estimate the overall test performance. Subgroup analysis was used to identify the efficiency of CAD in detecting DR, exudates (EXs), microaneurysms (MAs) as well as hemorrhages (HMs), and neovascularizations (NVs). Publication bias was analyzed using STATA.

RESULTS

Fourteen articles were finally included in this Meta-analysis after literature review. Pooled sensitivity and specificity were 90% (95%CI, 85%-94%) and 90% (95%CI, 80%-96%) respectively for CAD in DR detection. With regard to CAD in EXs detecting, pooled sensitivity, specificity were 89% (95%CI, 88%-90%) and 99% (95%CI, 99%-99%) respectively. In aspect of MAs and HMs detection, pooled sensitivity and specificity of CAD were 42% (95%CI, 41%-44%) and 93% (95%CI, 93%-93%) respectively. Besides, pooled sensitivity and specificity were 94% (95%CI, 89%-97%) and 87% (95%CI, 83%-90%) respectively for CAD in NVs detection. No potential publication bias was observed.

CONCLUSION

CAD demonstrates overall high diagnostic accuracy for detecting DR and pathological lesions based on OP. Further prospective clinical trials are needed to prove such effect.

OCT Angiography Metrics Predict Progression of Diabetic Retinopathy and Development of Diabetic Macular Edema: A Prospective Study

PURPOSE

To prospectively determine the relationship of OCT angiography (OCTA) metrics to diabetic retinopathy (DR) progression and development of diabetic macular edema (DME).

DESIGN

Prospective, observational study.

PARTICIPANTS

A total of 205 eyes from 129 patients with diabetes mellitus followed up for at least 2 years.

METHODS

All participants underwent OCTA with a swept-source OCT device (DRI-OCT Triton, Topcon, Inc, Tokyo, Japan). Individual OCTA images of superficial capillary plexus (SCP) and deep capillary plexus (DCP) were generated by IMAGEnet6 (Basic License 10). After a quality check, automated measurements of foveal avascular zone (FAZ) area, FAZ circularity, vessel density (VD), and fractal dimension (FD) of both SCP and DCP were then obtained.

MAIN OUTCOME MEASURES

Progression of DR and development of DME.

RESULTS

Over a median follow-up of 27.14 months (interquartile range, 24.16-30.41 months), 28 of the 205 eyes (13.66%) developed DR progression. Of the 194 eyes without DME at baseline, 17 (8.76%) developed DME. Larger FAZ area (hazard ratio [HR], 1.829 per SD increase; 95% confidence interval [CI], 1.332-2.512), lower VD (HR, 1.908 per SD decrease; 95% CI, 1.303-2.793), and lower FD (HR, 4.464 per SD decrease; 95% CI, 1.337-14.903) of DCP were significantly associated with DR progression after adjusting for established risk factors (DR severity, glycated hemoglobin, duration of diabetes, age, and mean arterial blood pressure at baseline). Lower VD of SCP (HR, 1.789 per SD decrease; 95% CI, 1.027-4.512) was associated with DME development. Compared with the model with established risk factors alone, the addition of OCTA metrics improved the predictive discrimination of DR progression (FAZ area of DCP, C-statistics 0.723 vs. 0.677, P < 0.001; VD of DCP, C-statistics 0.727 vs. 0.677, P = 0.001; FD of DCP, C-statistics 0.738 vs. 0.677, P < 0.001) and DME development (VD of SCP, C-statistics 0.904 vs. 0.875, P = 0.036).

CONCLUSIONS

The FAZ area, VD, and FD of DCP predict DR progression, whereas VD of SCP predicts DME development. Our findings provide evidence to support that OCTA metrics improve the evaluation of risk of DR progression and DME development beyond traditional risk factors.

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

Supplemental Digital Content is available in the text.

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.

Fully automated geometric feature analysis in optical coherence tomography angiography for objective classification of diabetic retinopathy

This study is to establish quantitative features of vascular geometry in optical coherence tomography angiography (OCTA) and validate them for the objective classification of diabetic retinopathy (DR). Six geometric features, including total vessel branching angle (VBA: θ), child branching angles (CBAs: α1 and α2), vessel branching coefficient (VBC), and children-to-parent vessel width ratios (VWR1 and VWR2), were automatically derived from each vessel branch in OCTA. Comparative analysis of heathy control, diabetes with no DR (NoDR), and non-proliferative DR (NPDR) was conducted. Our study reveals four quantitative OCTA features to produce robust DR detection and staging classification: (ANOVA, P<0.05), VBA, CBA1, VBC, and VWR1.

Prevalence of diabetic retinopathy, proliferative diabetic retinopathy and non-proliferative diabetic retinopathy in Asian T2DM patients: a systematic review and Meta-analysis

AIM

To investigate the pooled prevalence of diabetic retinopathy (DR), proliferative DR (PDR) and nonproliferative DR (NPDR) in Asian type 2 diabetes mellitus (T2DM) patients.

METHODS

We performed a systematic search online search using PubMed, EMBASE, Web of Science, the Cochrane Library, and China WeiPu Library to identify eligible studies that reported the prevalence of DR, PDR and NPDR in Asian T2DM patients. Effect size (ES) with 95% confidence interval (CI) was used to evaluate the prevalence of DR, PDR and NPDR in Asian T2DM patients, respectively.

RESULTS

There were 41 references and 48 995 T2DM patients involved in this study. The prevalence of DR, PDR, and NPDR was 28%, 6%, and 27% in T2DM patients, respectively; while the prevalence of PDR and NPDR in DR patients was 17% and 83%, respectively. Subgroup analysis showed that prevalence of DR in T2DM patients from Singaporean, Indian, South Korean, Malaysian, Asian, and Chinese was 33%, 42%, 16%, 35%, 21% and 25%, respectively. In T2DM patients with NPDR from Indian, South Korean, Malaysian, Asian, Chinese, higher prevalence was found than that in PDR patients (45% vs 17%, 13% vs 3%, 30% vs 5%, 23% vs 2% and 22% vs 3%), as well as in DR patients (74% vs 26%, 81% vs 19%, 86% vs 14%, 92% vs 8% and 85% vs 15%). The prevalence of PDR in T2DM from India was higher than patients from other locations of Asia, and the same results were also observed in NPDR patients.

CONCLUSION

In either T2DM Asian patients or DR patients, NPDR is more common than PDR. Based on our results, we should pay more attention to NPDR screening and management in T2DM patients, and we also recommend suitable interventions to prevent its progression.

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

PURPOSE

To examine associations between retinal vessel morphometry and cardiometabolic risk factors in older British men and women.

DESIGN

Retinal imaging examination as part of the European Prospective Investigation into Cancer-Norfolk Eye Study.

PARTICIPANTS

Retinal imaging and clinical assessments were carried out in 7411 participants. Retinal images were analyzed using a fully automated validated computerized system that provides novel measures of vessel morphometry.

METHODS

Associations between cardiometabolic risk factors, chronic disease, and retinal markers were analyzed using multilevel linear regression, adjusted for age, gender, and within-person clustering, to provide percentage differences in tortuosity and absolute differences in width.

MAIN OUTCOMES MEASURES

Retinal arteriolar and venular tortuosity and width.

RESULTS

In all, 279 802 arterioles and 285 791 venules from 5947 participants (mean age, 67.6 years; standard deviation [SD], 7.6 years; 57% female) were analyzed. Increased venular tortuosity was associated with higher body mass index (BMI; 2.5%; 95% confidence interval [CI], 1.7%-3.3% per 5 kg/m2), hemoglobin A1c (HbA1c) level (2.2%; 95% CI, 1.0%-3.5% per 1%), and prevalent type 2 diabetes (6.5%; 95% CI, 2.8%-10.4%); wider venules were associated with older age (2.6 μm; 95% CI, 2.2-2.9 μm per decade), higher triglyceride levels (0.6 μm; 95% CI, 0.3-0.9 μm per 1 mmol/l), BMI (0.7 μm; 95% CI, 0.4-1.0 per 5 kg/m2), HbA1c level (0.4 μm; 95% CI, -0.1 to 0.9 per 1%), and being a current smoker (3.0 μm; 95% CI, 1.7-4.3 μm); smoking also was associated with wider arterioles (2.1 μm; 95% CI, 1.3-2.9 μm). Thinner venules were associated with high-density lipoprotein (HDL) (1.4 μm; 95% CI, 0.7-2.2 per 1 mmol/l). Arteriolar tortuosity increased with age (5.4%; 95% CI, 3.8%-7.1% per decade), higher systolic blood pressure (1.2%; 95% CI, 0.5%-1.9% per 10 mmHg), in females (3.8%; 95% CI, 1.4%-6.4%), and in those with prevalent stroke (8.3%; 95% CI, -0.6% to 18%); no association was observed with prevalent myocardial infarction. Narrower arterioles were associated with age (0.8 μm; 95% CI, 0.6-1.0 μm per decade), higher systolic blood pressure (0.5 μm; 95% CI, 0.4-0.6 μm per 10 mmHg), total cholesterol level (0.2 μm; 95% CI, 0.0-0.3 μm per 1 mmol/l), and HDL (1.2 μm; 95% CI, 0.7-1.6 μm per 1 mmol/l).

CONCLUSIONS

Metabolic risk factors showed a graded association with both tortuosity and width of retinal venules, even among people without clinical diabetes, whereas atherosclerotic risk factors correlated more closely with arteriolar width, even excluding those with hypertension and cardiovascular disease. These noninvasive microvasculature measures should be evaluated further as predictors of future cardiometabolic disease.

Longitudinal Relationship Between Retinal Diabetic Neurodegeneration and Progression of Diabetic Retinopathy in Patients With Type 2 Diabetes

PURPOSE

To investigate the longitudinal relationship between diabetic retinal neurodegeneration and the progression of diabetic retinopathy (DR) by measuring macular ganglion cell-inner plexiform layer (mGCIPL) thickness in patients with type 2 diabetes (T2DM).

DESIGN

Retrospective cohort study.

METHODS

T2DM patients with no DR or mild nonproliferative DR (NPDR) followed up for ≥4 years were included in this study. DR was graded according to retinal photography, and mean parafoveal mGCIPL thickness was measured using optical coherence tomography with at least a 6-month interval from baseline. Hazard ratios (HR) for predicting 2-step progression and development of proliferative DR (PDR) were calculated using Cox proportional hazard modeling using baseline clinical factors.

RESULTS

Of 87 eyes of T2DM patients, 39 (44.8%) exhibited 2-step DR progression and 6 (6.9%) experienced progression to PDR. Patients with DR progression exhibited longer T2DM duration, thinner mGCIPL, greater mGCIPL thinning rate, severe cardiac autonomic neuropathy (CAN), lower peripheral nerve-conduction velocity, and higher glycated hemoglobin A1c level. Multivariate regression modeling revealed that baseline mGCIPL thickness (HR = 0.94), mGCIPL thinning rate (HR = 1.924), CAN score (HR = 1.248), and conduction velocity of peripheral nerves (HR = 0.894) were significant predictive factors for DR progression (area under the curve = 0.92).

CONCLUSION

Progressive loss of mGCIPL is an independent risk factor for progression in early-stage DR. Further assessment of autonomic and peripheral nerve functions can increase sensitivity in predicting aggravation of DR in patients with T2DM.

Microvascular Dysfunction and Hyperglycemia: A Vicious Cycle With Widespread Consequences

Microvascular and metabolic physiology are tightly linked. This Perspective reviews evidence that 1) the relationship between hyperglycemia and microvascular dysfunction (MVD) is bidirectional and constitutes a vicious cycle; 2) MVD in diabetes affects many, if not all, organs, which may play a role in diabetes-associated comorbidities such as depression and cognitive impairment; and 3) MVD precedes, and contributes to, hyperglycemia in type 2 diabetes (T2D) through impairment of insulin-mediated glucose disposal and, possibly, insulin secretion. Obesity and adverse early-life exposures are important drivers of MVD. MVD can be improved through weight loss (in obesity) and through exercise. Pharmacological interventions to improve MVD are an active area of investigation.

On ‘Asian’ Distinctiveness and Race as a Variable: The Case of Ophthalmic Epidemiology in Singapore

The notion that Singapore’s multi-ethnic population provides a unique and quintessentially ‘Asian’ asset for its biomedical sciences initiative has been part of the discourse in local and international media coverage of that sector. It has also been highlighted by scholars as a feature of Singapore’s political economy. This article discusses how ‘racial/ethnic difference’ was initially central but then became peripheral to one high-profile research programme: the Singapore Epidemiology of Eye Disease (SEED) Study Programme. The case study is offered as an example of the flexible deployment and situational enactment of racial/ethnic difference in biomedical science, by demonstrating how it gets entangled with and disentangled from the creation of scientific capital and legitimacy, as well as complicates the notion of ‘Asian’ science.

The Relationship of Retinal Vessel Geometric Characteristics to the Incidence and Progression of Diabetic Retinopathy

PURPOSE

To examine the relationships of retinal vessel geometric characteristics (RVGCs) to the incidence and progression of diabetic retinopathy (DR).

DESIGN

Observational, prospective cohort study.

PARTICIPANTS

Nine hundred ninety-six persons with type 1 diabetes mellitus (T1DM) and 1370 persons with type 2 diabetes mellitus (T2DM) seen at a baseline examination who were eligible for follow-up examinations at subsequent 5-year intervals. A total of 3846 person-interval data from these follow-up examinations are the basis for the analyses.

METHODS

Diabetic retinopathy and macular edema were assessed by grading of 30° stereoscopic color fundus photographs. Retinal vessel geometric characteristics were assessed using the Singapore I Vessel Assessment program from a digitized copy of 1 of the field 1 fundus photographs obtained at baseline and follow-up.

MAIN OUTCOME MEASURES

The 5-year incidence of any DR, progression of DR, and incidence of proliferative diabetic retinopathy (PDR) and clinically significant macular edema (CSME) in right eyes.

RESULTS

Incident DR occurred in 45%, progression in 32%, PDR in 10%, and CSME in 5%. While adjusting for glycated hemoglobin, duration of diabetes, and other factors, retinal arteriolar simple tortuosity was associated significantly with the incidence of any DR (odds ratio [OR], 1.17; 95% confidence interval [CI], 1.01-1.35). Retinal venular branching angle was associated significantly with progression of DR (OR, 1.18; 95% CI, 1.03-1.36), retinal venular curvature tortuosity was associated significantly with the incidence of PDR (OR, 1.15; 95% CI, 1.01-1.30), and retinal venular branching angle (OR, 1.41; 95% CI, 1.10-1.82) was associated significantly with the incidence of CSME. There were no significant associations of other RVGCs with any of the DR outcomes in the full multivariate model. Inclusion of all possible RVGCs did not improve the predictive value of the models that already included retinal vessel diameter and baseline DR severity level.

CONCLUSIONS

Retinal vessel geometric characteristics of the retinal venules were associated with progression of DR; however, most of the RVGCs measured from digitized fundus photographs added little to the assessment of risk of incidence and progression of DR when other risk factors were considered in T1DM and T2DM.