Progressive Retinal Vasodilation in Patients With Type 1 Diabetes: A Longitudinal Study of Retinal Vascular Geometry

Three-Year Follow-Up Study Investigating Changes in Retinal Vascular Morphology and the Relationship with Diabetic Retinopathy in Children with Type 1 Diabetes Mellitus

INTRODUCTION

This study aimed to investigate changes in retinal microvascular morphology and associated factors, and their relationship with diabetic retinopathy (DR) in children with type 1 diabetes mellitus (T1DM).

METHODS

Thirty-eight children enrolled in this 3-year follow-up study underwent complete ophthalmic examinations including fundus photography. Retinal vascular parameters were measured automatically and compared between baseline and follow-up. Multiple linear regression was used to investigate factors affecting changes in vascular parameters. Binary logistic regression was used to analyze the relationship between retinal microvascular morphology and DR.

RESULTS

The caliber of all retinal vessels (within 1-1.5 papillary diameter [PD] from the center of the optic disc, p = 0.030; 1.5-2 PD, p = 0.003), arterioles, and venules (1.5-2 PD, p = 0.001) was narrower in nearly all regions in the follow-up group compared with the baseline group. Vascular tortuosity increased in the central part of the retina and decreased in the periphery. The density (1-1.5 PD, p = 0.030) and fractal dimension (p = 0.037) of retinal vessels were increased at the end of the follow-up compared with baseline. Retinal vascular caliber was independently correlated with DR (odds ratio 0.793 [95% confidence interval 0.633-0.993]; p = 0.044).

CONCLUSION

Retinal microvascular morphology in children with T1DM varied with the disease course. Narrower retinal vessels may be an independent risk factor for DR. Results of this study emphasized the importance of regular follow-up of fundus vascular morphology for the detection of early DR in children with T1DM.

Optimal Frequency of Retinopathy Screening in Adolescents With Type 1 Diabetes: Markov Modeling Approach Based on 30 Years of Data

OBJECTIVE

Current guidelines recommend biennial diabetic retinopathy (DR) screening commencing at the age of 11 years and after 2-5 years' duration of type 1 diabetes. Growing evidence suggests less frequent screening may be feasible.

RESEARCH DESIGN AND METHODS

Prospective data were collected from 2,063 youth with type 1 diabetes who were screened two or more times between 1990 and 2019. Baseline (mean ± SD) age was 13.3 ± 1.8 years, HbA1c was 8.6 ± 1.3% (70.1 ± 14.7 mmol/mol), diabetes duration was 5.6 ± 2.8 years, and follow-up time was 4.8 ± 2.8 years. DR was manually graded from 7-field retinal photographs using the Early Treatment Diabetic Retinopathy Study (ETDRS) scale. Markov chain was used to calculate probabilities of DR change over time and hazard ratio (HR) of DR stage transition.

RESULTS

The incidence of moderate nonproliferative DR (MNPDR) or worse was 8.6 per 1,000 patient-years. Probabilities of transition to this state after a 3-year interval were from no DR, 1.3%; from minimal DR, 5.1%; and from mild DR, 22.2%, respectively. HRs (95% CIs) for transition per 1% current HbA1c increase were 1.23 (1.16-1.31) from no DR to minimal NPDR, 1.12 (1.03-1.23) from minimal to mild NPDR, and 1.28 (1.13-1.46) from mild to MNPDR or worse. HbA1c alone explained 27% of the transitions between no retinopathy and MNPDR or worse. The addition of diabetes duration into the model increased this value to 31% (P = 0.03). Risk was also increased by female sex and higher attained age.

CONCLUSIONS

These results support less frequent DR screening in youth with type 1 diabetes without DR and short duration. Although DR progression to advanced stages is generally slow, higher HbA1c greatly accelerates it.

Thirty-Year Time Trends in Diabetic Retinopathy and Macular Edema in Youth With Type 1 Diabetes

OBJECTIVE

To examine trends in diabetic retinopathy (DR) and diabetic macular edema (DME) in adolescents with type 1 diabetes between 1990 and 2019.

RESEARCH DESIGN AND METHODS

We analyzed 5,487 complication assessments for 2,404 adolescents (52.7% female, aged 12-20 years, diabetes duration >5 years), stratified by three decades (1990-1999, 2000-2009, 2010-2019). DR and DME were graded according to the modified Airlie House classification from seven-field stereoscopic fundal photography.

RESULTS

Over three decades, the prevalence of DR was 40, 21, and 20% (P < 0.001) and DME 1.4, 0.5, and 0.9% (P = 0.13), respectively, for 1990-1999, 2000-2009, and 2010-2019. Continuous subcutaneous insulin infusion (CSII) use increased (0, 12, and 55%; P < 0.001); mean HbA1c was bimodal (8.7, 8.5, and 8.7%; P < 0.001), and the proportion of adolescents meeting target HbA1c <7% did not change significantly (8.3, 7.7, and 7.1%; P = 0.63). In multivariable generalized estimating equation analysis, DR was associated with 1-2 daily injections (odds ratio 1.88, 95% CI 1.42-2.48) and multiple injections in comparison with CSII (1.38, 1.09-1.74); older age (1.11, 1.07-1.15), higher HbA1c (1.19, 1.05-1.15), longer diabetes duration (1.15, 1.12-1.18), overweight/obesity (1.27, 1.08-1.49) and higher diastolic blood pressure SDS (1.11, 1.01-1.21). DME was associated with 1-2 daily injections (3.26, 1.72-6.19), longer diabetes duration (1.26, 1.12-1.41), higher diastolic blood pressure SDS (1.66, 1.22-2.27), higher HbA1c (1.28, 1.03-1.59), and elevated cholesterol (3.78, 1.84-7.76).

CONCLUSIONS

One in five adolescents with type 1 diabetes had DR in the last decade. These findings support contemporary guidelines for lower glycemic targets, increasing CSII use, and targeting modifiable risk factors including blood pressure, cholesterol, and overweight/obesity.

The Longitudinal Assessment of Vascular Parameters of the Retina and Their Correlations with Systemic Characteristics in Type 2 Diabetes-A Pilot Study

The aim of the study was to assess various retinal vessel parameters of diabetes mellitus (DM) patients and their correlations with systemic factors in type 2 DM. A retrospective exploratory study in which 21 pairs of baseline and follow-up images of patients affected by DM were randomly chosen from the Sankara Nethralaya−Diabetic Retinopathy Study (SN DREAMS) I and II datasets. Patients’ fundus was photographed, and the diagnosis was made based on Klein classification. Vessel thickness parameters were generated using a web-based retinal vascular analysis platform called VASP. The thickness changes between the baseline and follow-up images were computed and normalized with the actual thicknesses of baseline images. The majority of parameters showed 10~20% changes over time. Vessel width in zone C for the second vein was significantly reduced from baseline to follow-up, which showed positive correlations with systolic blood pressure and serum high-density lipoproteins. Fractal dimension for all vessels in zones B and C and fractal dimension for vein in zones A, B and C showed a minimal increase from baseline to follow-up, which had a linear relationship with diastolic pressure, mean arterial pressure, serum triglycerides (p < 0.05). Lacunarity for all vessels and veins in zones A, B and C showed a minimal decrease from baseline to follow-up which had a negative correlation with pulse pressure and positive correlation with serum triglycerides (p < 0.05). The vessel widths for the first and second arteries significantly increased from baseline to follow-up and had an association with high-density lipoproteins, glycated haemoglobin A1C, serum low-density lipoproteins and total serum cholesterol. The central reflex intensity ratio for the second artery was significantly decreased from baseline to follow-up, and positive correlations were noted with serum triglyceride, serum low-density lipoproteins and total serum cholesterol. The coefficients for branches in zones B and C artery and the junctional exponent deviation for the artery in zone A decreased from baseline to follow-up showed positive correlations with serum triglycerides, serum low-density lipoproteins and total serum cholesterol. Identifying early microvascular changes in diabetic patients will allow for earlier intervention, improve visual outcomes and prevent vision loss.

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.

Development and validation of a predictive risk model based on retinal geometry for an early assessment of diabetic retinopathy

AIMS

This study aimed to develop and validate a risk nomogram prediction model based on the retinal geometry of diabetic retinopathy (DR) in patients with type 2 diabetes mellitus (T2DM) and to investigate its clinical application value.

METHODS

In this study, we collected the clinical data of 410 patients with T2DM in the Second Affiliated Hospital of Chongqing Medical University between October 2020 and March 2022. Firstly, the patients were randomly divided into a development cohort and a validation cohort in a ratio of 7:3. Then, the modeling factors were selected using the least absolute shrinkage and selection operator (LASSO). Subsequently, a nomogram prediction model was built with these identified risk factors. Two other models were constructed with only retinal vascular traits or only clinical traits to confirm the performance advantage of this nomogram model. Finally, the model performances were assessed using the area under the receiver operating characteristic curve (AUC), calibration plot, and decision curve analysis (DCA).

RESULTS

Five predictive variables for DR among patients with T2DM were selected by LASSO regression from 33 variables, including fractal dimension, arterial tortuosity, venular caliber, duration of diabetes mellitus (DM), and insulin dosage (P< 0.05). A predictive nomogram model based on these selected clinical and retinal vascular factors presented good discrimination with an AUC of 0.909 in the training cohort and 0.876 in the validation cohort. By comparing the models, the retinal vascular parameters were proven to have a predictive value and could improve diagnostic sensitivity and specificity when combined with clinical characteristics. The calibration curve displayed high consistency between predicted and actual probability in both training and validation cohorts. The DCA demonstrated that this nomogram model led to net benefits in a wide range of threshold probability and could be adapted for clinical decision-making.

CONCLUSION

This study presented a predictive nomogram that might facilitate the risk stratification and early detection of DR among patients with T2DM.

Computational investigation of blood cell transport in retinal microaneurysms

Microaneurysms (MAs) are one of the earliest clinically visible signs of diabetic retinopathy (DR). MA leakage or rupture may precipitate local pathology in the surrounding neural retina that impacts visual function. Thrombosis in MAs may affect their turnover time, an indicator associated with visual and anatomic outcomes in the diabetic eyes. In this work, we perform computational modeling of blood flow in microchannels containing various MAs to investigate the pathologies of MAs in DR. The particle-based model employed in this study can explicitly represent red blood cells (RBCs) and platelets as well as their interaction in the blood flow, a process that is very difficult to observe in vivo. Our simulations illustrate that while the main blood flow from the parent vessels can perfuse the entire lumen of MAs with small body-to-neck ratio (BNR), it can only perfuse part of the lumen in MAs with large BNR, particularly at a low hematocrit level, leading to possible hypoxic conditions inside MAs. We also quantify the impacts of the size of MAs, blood flow velocity, hematocrit and RBC stiffness and adhesion on the likelihood of platelets entering MAs as well as their residence time inside, two factors that are thought to be associated with thrombus formation in MAs. Our results show that enlarged MA size, increased blood velocity and hematocrit in the parent vessel of MAs as well as the RBC-RBC adhesion promote the migration of platelets into MAs and also prolong their residence time, thereby increasing the propensity of thrombosis within MAs. Overall, our work suggests that computational simulations using particle-based models can help to understand the microvascular pathology pertaining to MAs in DR and provide insights to stimulate and steer new experimental and computational studies in this area.

The natural history of emerging diabetic retinopathy and microalbuminuria from prepuberty to early adulthood in Type 1 diabetes: A 19-year prospective clinical follow-up study

OBJECTIVE

To evaluate the impact of long-term glycaemic control and glycaemic variability on microvascular complications in adolescents and young adults with childhood-onset Type 1 diabetes.

METHODS

Twenty-six participants took part in a prospective follow-up study. We used univariate generalised estimating equations (GEE) analysis with first-order autoregressive AR(1) covariance structure for repeated measurements to evaluate the relationship between emerging diabetic retinopathy (DR) and each single explanatory variable, namely age at developmental stages from late prepuberty until early adulthood, duration of diabetes and long-term HbA_1c . Thereafter, the simultaneous effect of these three explanatory variables to DR was analysed in a multivariate model.

RESULTS

Twenty-five participants developed DR by early adulthood after a median diabetes duration of 16.2 years (range 6.3-24.0). No participants had DR during prepuberty. Each of the three variables was independently associated with emerging DR: age (OR 1.47, 95% CI to 1.25 to 1.74, p < 0.001) stronger than diabetes duration (OR 1.42, 95% CI 1.23 to 1.63, p < 0.001) and HbA_1c (OR 1.02, 95% CI 1.001 to 1.05, p = 0.041) in this population. In the multivariate analysis of these three explanatory variables, only age was associated with DR (adjusted OR 1.52, 95% CI 1.10 to 2.10, p = 0.012).

CONCLUSIONS

The emergence of DR during adolescence and early adulthood is not rare and increases with age in patients with deteriorating metabolic control during puberty and thereafter. This underpins the need to prevent deterioration of glycaemic control from taking place during puberty-seen again in this follow-up study-in children with diabetes.

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.

Long-term complications of type 1 diabetes: what do we know and what do we need to understand?

Long-term complications of type 1 diabetes (T1D) include microvascular complications and macrovascular disease. Despite the important advances in the treatment of T1D of the last decades, these complications still represent the leading cause of morbidity and mortality in patients with T1D. Extensive evidence indicates that structural and functional alterations of the kidney, retina, nerves and large arteries occur already in the first years after the onset of diabetes. We performed a comprehensive review of the available evidence on screening, diagnosis, prevention and treatment of vascular complications of T1D. In particular, we focused on three major challenges related to long-term complications of T1D: 1) finding of new biomarkers and diagnostic methods able to identify early signs of complications; 2) identifying specific risk factors for the development of these complications; 3) identifying and implementing new therapeutic strategies able to prevent the development and progression of vascular complications.

Retinal vascular geometry detection as a biomarker in diabetes mellitus

OBJECTIVE

To compare the vessel geometry characteristics of color fundus photographs in normal control and diabetes mellitus (DM) patients and to find potential biomarkers for early diabetic retinopathy (DR) based on a neural network vessel segmentation system and automated vascular geometry parameter analysis software.

METHODS

A total of 102 consecutive patients with type 2 DM (T2DM) and 132 healthy controls were recruited. All participants underwent general ophthalmic examinations, and retinal fundus photographs were taken with a digital fundus camera without mydriasis. Color fundus photographs were input into a dense-block generative adversarial network (D-GAN)-assisted retinal vascular segmentation system (http://www.gdcerc.cn:8081/#/login) to obtain binary images. These images were then analyzed by customized software (ocular microvascular analysis system V2.9.1) for automatic processing of vessel geometry parameters, including the monofractal dimension (D_box), multifractal dimension (D₀), vessel area ratio (R), max vessel diameter (d_max), average vessel diameter (d_ave), arc-chord ratio (A/C), and tortuosity (τ_n). Geometric differences between the healthy subjects and DM patients were analyzed. Then, regression analysis and receiver operating characteristic (ROC) curve analysis were performed to evaluate the diagnostic efficiency of the vascular geometry parameters.

RESULTS

No significant differences were observed between the baseline characteristics of each group. DM patients had lower D_box and D₀ values (1.330 ± 0.041; 1.347 ± 0.038) than healthy subjects (1.343 ± 0.048, p < 0.05; 1.362 ± 0.042, p < 0.05) and showed increasing values of d_max, d_ave, A/C, and τ_n compared with normal controls, although only the differences in d_ave and τ_n between the groups were statistically significant. In the regression analysis, d_ave and τ_n showed a good correlation with diabetes (d_ave, OR 1.765, 95% CI 1.319-2.362, p < 0.001; τ_n, OR 9.323, 95% CI 1.492-58.262, p < 0.05).

CONCLUSIONS

We demonstrated the relationship between retinal vascular geometry and the process in DM patients, showing that D_box, D₀, d_ave, and τ_n may be indicators of morphological changes in retinal vessels in DM patients and can be early biomarkers of DR.

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 vascular caliber changes after laser photocoagulation in diabetic retinopathy

BACKGROUND Diabetic retinopathy causes vascular dilatation caused by hypoxia, whereas oxygen tension improvement leads to retinal vessels narrowing. Given that laser photocoagulation aims to increase the oxygen tension in the retina, we hypothesized that the narrowing of vessel caliber after the treatment could be possibly demonstrated. This study aimed to assess the changes in the caliber of retinal vessels before and after laser photocoagulation in diabetic retinopathy. METHODS This research was a prospective cohort study on the treatment of diabetic retinopathy by laser photocoagulation, and it was conducted at Universitas Hasanuddin Hospital, Makassar, Indonesia between November 2017–April 2018. Retinal vascular caliber changes were analyzed before and 6–8 weeks after photocoagulation in 30 diabetic eyes. Central retinal arteriolar equivalent (CRAE) and central retinal venular equivalent (CRVE) were measured using the vessel assessment and measurement platform software for images of the retina (VAMPIRE) manual annotation tool. RESULTS A significant decrease of CRVE was observed after laser photocoagulation (p<0.001), but CRAE was not reduced significantly (p = 0.067). No difference was recorded between CRVE and CRAE post-laser photocoagulation (p = 0.14), implying a reduction in vein caliber toward normal in the treated eyes. CONCLUSIONS Laser photocoagulation decreases the CRVE in diabetic retinopathy despite the absence of changes in the grade of diabetic retinopathy.

Predicting High Coronary Artery Calcium Score From Retinal Fundus Images With Deep Learning Algorithms

Purpose

To evaluate high accumulation of coronary artery calcium (CAC) from retinal fundus images with deep learning technologies as an inexpensive and radiation-free screening method.

Methods

Individuals who underwent bilateral retinal fundus imaging and CAC score (CACS) evaluation from coronary computed tomography scans on the same day were identified. With this database, performances of deep learning algorithms (inception-v3) to distinguish high CACS from CACS of 0 were evaluated at various thresholds for high CACS. Vessel-inpainted and fovea-inpainted images were also used as input to investigate areas of interest in determining CACS.

Results

A total of 44,184 images from 20,130 individuals were included. A deep learning algorithm for discrimination of no CAC from CACS >100 achieved area under receiver operating curve (AUROC) of 82.3% (79.5%–85.0%) and 83.2% (80.2%–86.3%) using unilateral and bilateral fundus images, respectively, under a 5-fold cross validation setting. AUROC increased as the criterion for high CACS was increased, showing a plateau at 100 and losing significant improvement thereafter. AUROC decreased when fovea was inpainted and decreased further when vessels were inpainted, whereas AUROC increased when bilateral images were used as input.

Conclusions

Visual patterns of retinal fundus images in subjects with CACS > 100 could be recognized by deep learning algorithms compared with those with no CAC. Exploiting bilateral images improves discrimination performance, and ablation studies removing retinal vasculature or fovea suggest that recognizable patterns reside mainly in these areas.

Translational Relevance

Retinal fundus images can be used by deep learning algorithms for prediction of high CACS.

Predictive modelling of thrombus formation in diabetic retinal microaneurysms

Microaneurysms (MAs) are one of the earliest clinically visible signs of diabetic retinopathy (DR). Vision can be reduced at any stage of DR by MAs, which may enlarge, rupture and leak fluid into the neural retina. Recent advances in ophthalmic imaging techniques enable reconstruction of the geometries of MAs and quantification of the corresponding haemodynamic metrics, such as shear rate and wall shear stress, but there is lack of computational models that can predict thrombus formation in individual MAs. In this study, we couple a particle model to a continuum model to simulate the platelet aggregation in MAs with different shapes. Our simulation results show that under a physiologically relevant blood flow rate, thrombosis is more pronounced in saccular-shaped MAs than fusiform-shaped MAs, in agreement with recent clinical findings. Our model predictions of the size and shape of the thrombi in MAs are consistent with experimental observations, suggesting that our model is capable of predicting the formation of thrombus for newly detected MAs. This is the first quantitative study of thrombosis in MAs through simulating platelet aggregation, and our results suggest that computational models can be used to predict initiation and development of intraluminal thrombus in MAs as well as provide insights into their role in the pathophysiology of DR.

Hemoglobin A1c and retinal arteriolar narrowing in children with type 1 diabetes: the diagnostics of early atherosclerosis risk in kids study

BACKGROUND/OBJECTIVE

Microvascular alterations play a key role in the development of diabetes complications. Retinal vessel analysis is a unique method to examine microvascular changes in brain-derived vessels.

METHODS

Sixty-seven pediatric and adolescent type 1 diabetes patients and 58 healthy control persons (mean age 12.4 ± 2.9 years) underwent non-mydriatic retinal photography of both eyes. Central retinal arteriolar and central retinal venular (CRVE) diameter equivalents as well as the arteriolar-to-venular ratio were calculated using a semiautomated software. All anthropometric and laboratory parameters were measured according to standardized procedures for children.

RESULTS

Retinal vessel diameter did not differ between type 1 diabetic children and healthy controls. However, there was an independent association of higher hemoglobin A1c (HbA1c) levels with arteriolar narrowing. Arteriolar narrowing of 5.4 μm was observed with each percent increase in HbA1c. Longer duration of diabetes was associated with wider retinal arterioles. CRVE was not associated with diabetes duration or HbA1c.

CONCLUSIONS

Microvascular arteriolar alterations are already present in childhood and may indicate subclinical atherosclerosis and increased risk of diabetes complications later in life. Future research will have to investigate the potential use of retinal vessel diameters for treatment monitoring and guidance of therapy in children.

Towards Accurate Segmentation of Retinal Vessels and the Optic Disc in Fundoscopic Images with Generative Adversarial Networks

Automatic segmentation of the retinal vasculature and the optic disc is a crucial task for accurate geometric analysis and reliable automated diagnosis. In recent years, Convolutional Neural Networks (CNN) have shown outstanding performance compared to the conventional approaches in the segmentation tasks. In this paper, we experimentally measure the performance gain for Generative Adversarial Networks (GAN) framework when applied to the segmentation tasks. We show that GAN achieves statistically significant improvement in area under the receiver operating characteristic (AU-ROC) and area under the precision and recall curve (AU-PR) on two public datasets (DRIVE, STARE) by segmenting fine vessels. Also, we found a model that surpassed the current state-of-the-art method by 0.2 - 1.0% in AU-ROC and 0.8 - 1.2% in AU-PR and 0.5 - 0.7% in dice coefficient. In contrast, significant improvements were not observed in the optic disc segmentation task on DRIONS-DB, RIM-ONE (r3) and Drishti-GS datasets in AU-ROC and AU-PR.

Dynamic changes in retinal vessel diameter during acute hyperglycemia in type 1 diabetes

AIMS

To investigate changes in retinal vessel diameter during acute hyperglycemia in patients with type 1 diabetes.

METHODS

We conducted a study on 11 subjects with type 1 diabetes. Euglycemia was maintained for 3h followed by induction of hyperglycemia and simultaneous bolus of rapid acting insulin. Two fundus photos were captured during euglycemia and five fundus photos, blood glucose and blood pressure were taken every 30min for 2.5h post-prandial. Central retinal artery equivalent (CRAE) and central retinal vein equivalent (CRVE) were measured over the study visit and examined using generalized linear mixed models.

RESULTS

In a multivariate mixed model, mean CRAE and CRVE were reduced at 90min post-prandial in both zones B and C. In repeated measures analysis, arterioles exhibited a significant association with change in vessel caliber per change in blood glucose. Inconsistent effects of blood pressure on vessel diameter were also measured.

CONCLUSIONS

We document a change in retinal vessel diameter during acute hyperglycemia in persons with type 1 diabetes. Larger controlled studies are required to further investigate this phenomenon and to more accurately assess if hyperglycemia has direct effects on retinal vessel diameter.