Advanced Stages Of Diabetic Retinopathy Research Articles

SUPERFICIAL AND DEEP VASCULAR COMPLEXES DAMAGED TO DIFFERENT EXTENTS IN ADVANCED STAGES OF DIABETIC RETINOPATHY.

To identify the extent of damage to the superficial vascular complex and deep vascular complex as the stage of diabetic retinopathy (DR) increases. Subjects were divided into four groups: patients with type 2 diabetes without DR (Group 1), those with mild-to-moderate nonproliferative DR (Group 2), those with severe-to-very severe nonproliferative DR (Group 3), and those with proliferative DR (Group 4). The vessel densities of the superficial vascular complex (superficial vessel density, SVD) and deep vascular complex (deep vessel density, DVD) and their ratios were compared. Linear regression analyses were used to identify factors associated with the SVD/DVD ratio. The SVDs were 25.5% ± 6.1%, 25.1% ± 7.0%, 24.5% ± 9.0%, and 21.6% ± 6.9% (P = 0.048); the DVDs 25.6% ± 5.3%, 23.0% ± 7.0%, 22.3% ± 8.8%, and 17.5% ± 5.0% (P < 0.001); and the SVD/DVD ratios 1.00 ± 0.16, 1.12 ± 0.20, 1.14 ± 0.33, and 1.24 ± 0.27 (P < 0.001) in Groups 1 to 4, respectively. In multivariate analysis, DR severity (B = 7.16, P < 0.001) and the HbA1c level (B = 1.57, P = 0.042) were significantly associated with the SVD/DVD ratio. Both the SVD and DVD tended to decrease in the advanced stages of DR, and the SVD/DVD ratio increased, indicating more severe damage to the deep vascular complex than the superficial vascular complex. The ratio was positively associated with the HbA1c level, indicating a significant relationship between that level and DVD rather than SVD damage.

Machine Learning Techniques used for Recognizing the Diabetic Retinopathy: A Survey

Diabetic Retinopathy (DR) is one of the major causes of blindness. DR mutilates the retinal blood vessels of a patient having diabetes. The DR has two major types: First one is Non- Proliferative Diabetic Retinopathy (NPDR) and second is Proliferative Diabetic Retinopathy (PDR). PDR is the advanced stage of DR which leads to neo vascularization, it is expected that the number of DR patients is to increase from 382 million to 592 million by 2028. In the early stages of the DR the patients were asymptomatic but in advanced stages, it leads to floaters, blurred vision, distortions, and progressive visual acuity loss. It is difficult but utmost important to detect the DR in early stages to avoid the worse effect of latter stages. The colour fundus images were used for the diagnosis of DR, the manual analysis could only be done by highly trained domain experts but it is bit expensive in terms of time and cost. Hence, it is important to use computer vision methods to automatically analyse the fundus images of Retina and assist the physicians/radiologists. The computer vision-based methods are divided into hand-on engineering and end-to-end learning. The hand-on engineering methods extract features using traditional approaches such as HoG, SIFT, LBP, Gabor filters, which failed to encode the variations in scale, rotation, and illumination. The end-to-end leaning automatically learns the hidden rich features and thus performs better classification.

Association of inflammation-related markers and diabetic retinopathy severity in the aqueous humor, but not serum of type 2 diabetic patients.

Diabetic retinopathy (DR) is a frequent microvascular complication of diabetes mellitus, and inflammatory pathways have been linked to its pathogenesis. In this retrospective, observational pilot study, we aimed to compare the concentrations of four inflammation-related proteins, ZAG, Reg-3a, elafin and RBP-4, in the serum and aqueous humor of healthy controls and diabetic patients with different stages of DR. The concentrations of VEGF-A, IL-8, IL-6 were determined in parallel as internal controls. In the serum, we did not find significant differences in the concentrations of target proteins. In the aqueous humor, higher levels of ZAG, RBP-4, Reg-3a and elafin were observed in advanced nonproliferative DR (NPDR)/ proliferative DR (PDR) compared to controls. The levels of ZAG and RBP-4 were also higher in advanced NPDR/PDR than in nonapparent DR. Normalization of target protein concentrations to the aqueous humor total protein demonstrates that a spill-over from serum due to breakage of the blood-retina barrier only partially accounts for increased inflammation related markers in later stages. In conclusion, we found elevated levels of Reg-3a, RBP-4, elafin and ZAG in advanced stages of diabetic retinopathy. Higher levels of pro-inflammatory proteins, Reg-3a and RBP-4, might contribute to the pathogenesis of diabetic retinopathy, as the parallel increased concentrations of anti-inflammatory molecules elafin and ZAG might indicate a compensatory mechanism.

Blocking Hemopexin With Specific Antibodies: A New Strategy for Treating Diabetic Retinopathy.

Hemopexin (HPX) is the best-characterized permeability factor in steroid-sensitive nephrotic syndrome. We have previously reported that HPX is overexpressed in the retina of patients with diabetes and induces the breakdown of the blood-retinal barrier invitro. Here, we report that intravitreal injection of anti-HPX antibodies significantly reduces vascular leakage, retinal neurodegeneration, and inflammation in diabetic murine models and that the immunoneutralization of HPX exerts a significant antiangiogenic effect invitro and in retinal explants. The blockade of HPX can be considered as a new therapy for advanced stages of diabetic retinopathy.

Early Retinal Microvascular Alterations in Young Type 1 Diabetic Patients without Clinical Retinopathy.

The purpose of this study is to identify and quantify preclinical changes with the help of optical coherence tomography angiography (OCTA) within the retinal microcirculation of young type 1 diabetes (T1D) patients without clinical signs of diabetic retinopathy (DR) and to compare these results with those obtained from healthy age-matched subjects. OCTA is currently used for monitoring diabetic retinopathy; however, there is no current consensus on which OCTA parameter alterations predict the first clinical signs of diabetic retinopathy. The main challenge that young patients with T1D face during the course of the disease is that they can rapidly progress to the development of DR, especially during adolescence. Moreover, they also present an increased risk of rapid progression toward advanced stages of DR and vision loss compared to type 2 diabetes patients, indicating the importance of early diagnosis and intervention. The limitations of the currently used screening procedures that led to the conceptualization of our study are the difficulties in performing fluorescein angiography tests for diagnosing the clinical signs of DR on young patients, namely the invasive procedure of dye injection, the risk of allergic reactions and the long duration of the examination. Moreover, given the long life expectancy of young T1D patients, it is essential to identify the preclinical changes in retinal microvasculature before reaching the first clinical signs quantifiable by FFA. The clinical study enrolled 119 subjects aged between 4 and 30 years old with a mean age of 13 years old, comprising 61 T1D patients with a mean duration of the disease of 4 years and 8 months and 58 healthy age-matched subjects for the control group. OCTA scans were performed using the RevoNX 130 OCTA device (Optopol) to evaluate the following retinal parameters: foveal avascular zone (FAZ) area, perimeter and circularity, overall foveal thickness, and superficial and deep vessel densities. Statistically significant differences between the two groups were identified for the following parameters: the FAZ area in the T1D group (0.42 ± 0.17) was larger than the control group (0.26 ± 0.080), the FAZ circularity (0.41 ± 0.11) was decreased compared to the control group (0.61 ± 0.08) and the FAZ perimeter was larger (3.63 ± 0.97) compared to the control group (2.30 ± 0.50). The overall foveal thickness was decreased in the T1D group (222.98 ± 17.33) compared to the control group (230.64 ± 20.82). The total vessel density of the superficial capillary plexus (SCP) on an investigated area of 6 X 6 mm centered around the fovea was decreased in the T1D group (37.4164 ± 2.14) compared to the control group (38.0241 ± 2.44). Our data suggest that specific imaging biomarkers such as FAZ perimeter, area and circularity, decreased overall foveal thickness and decreased vessel density in the SCP precede the clinical diagnosis of DR in young T1D patients and represent useful parameters in quantifying capillary nonperfusion in T1D patients without clinical signs of DR.

Data Diversity in Convolutional Neural Network Based Ensemble Model for Diabetic Retinopathy.

The medical and healthcare domains require automatic diagnosis systems (ADS) for the identification of health problems with technological advancements. Biomedical imaging is one of the techniques used in computer-aided diagnosis systems. Ophthalmologists examine fundus images (FI) to detect and classify stages of diabetic retinopathy (DR). DR is a chronic disease that appears in patients with long-term diabetes. Unattained patients can lead to severe conditions of DR, such as retinal eye detachments. Therefore, early detection and classification of DR are crucial to ward off advanced stages of DR and preserve the vision. Data diversity in an ensemble model refers to the use of multiple models trained on different subsets of data to improve the ensemble's overall performance. In the context of an ensemble model based on a convolutional neural network (CNN) for diabetic retinopathy, this could involve training multiple CNNs on various subsets of retinal images, including images from different patients or those captured using distinct imaging techniques. By combining the predictions of these multiple models, the ensemble model can potentially make more accurate predictions than a single prediction. In this paper, an ensemble model (EM) of three CNN models is proposed for limited and imbalanced DR data using data diversity. Detecting the Class 1 stage of DR is important to control this fatal disease in time. CNN-based EM is incorporated to classify the five classes of DR while giving attention to the early stage, i.e., Class 1. Furthermore, data diversity is created by applying various augmentation and generation techniques with affine transformation. Compared to the single model and other existing work, the proposed EM has achieved better multi-class classification accuracy, precision, sensitivity, and specificity of 91.06%, 91.00%, 95.01%, and 98.38%, respectively.

A Paradigm Shift in the Management Approaches of Proliferative Diabetic Retinopathy: Role of Anti-VEGF Therapy.

Diabetic retinopathy (DR) is considered one of the leading causes of vision loss globally. It principally causes upregulation of pro-angiogenic, proinflammatory, and vascular permeability factors such as vascular endothelial growth factor (VEGF), leading to neovascularisation. The advanced stage of DR or proliferative diabetic retinopathy (PDR) is of more concern, as it leads to vitreous haemorrhage and traction retinal detachment. Various risk factors associated with PDR include hyperglycemia, hypertension, neuropathy, dyslipidemia, anaemia, nephropathy, and retinal complications of drugs used for diabetes. Current management approaches for PDR have been stratified and involve pan-retinal photocoagulation, vitrectomy, and anti-VEGF agents. Given the emerging role of anti-VEGF agents as a favourable adjunct or alternative therapy, they have a critical role in the management of PDR. The review emphasises current management approaches for PDR focusing on anti-VEGF therapy. The review also highlights the risk/benefit evaluation of the various approaches employed for PDR management in various clinical scenarios.

Prevalence, characteristics and risk factors of diabetic retinopathy in type 2 diabetes mellitus patients in Jordan: a cross-sectional study.

ObjectivesTo measure the prevalence of diabetic retinopathy in patients with type 2 diabetes, to define their characteristics, and identify the associated risk factors.MethodsWe performed a cross sectional study of 1316 adult patients with type 2 diabetes mellitus who attended an ophthalmology clinic. Demographic, clinical, and laboratory data were analyzed. Diabetic retinopathy (DR) was diagnosed using a complete ophthalmic evaluation, including a fundic examination. Two regression models were constructed to identify the risk factors associated with DR and the parameters associated with the stage of retinopathy.ResultsMen accounted for 774 (58.8%) of the participants. The prevalence of DR was 28.2% (371 participants). DR was significantly more common in participants who were ≥60 years old, were women, had had diabetes for >10 years, were taking insulin, were not taking metformin, had a body mass index >30 kg/m2, were current smokers, or had a history of hypertension. Advanced stages of DR were more common in participants in the later stages of nephropathy and with albuminuria.ConclusionsPoor glycemic control, smoking, and advanced diabetic kidney disease are most closely associated with retinopathy. Further longitudinal studies are necessary to identify the mechanisms underlying these relationships and to guide community-based interventions.

INCIDENCE AND UPDATES MANAGEMENT OF DIABETIC RETINOPATHY

One of the biggest causes of vision loss in the globe is diabetic retinopathy (DR), a consequence of diabetes. Despite significant attempts to lower the prevalence of vision impairment, DR continues to grow. There is damage to the vascular endothelial cells as the first pathophysiology of DRcells and a decrease in pericytes. As a result of the hypoxic reactions that follow, vascular endothelialvascular endothelial growth factor (VEGF) The most effective treatment available right nowControlling blood sugar levels is the key to preventing diabetic retinopathy and diabetic macular edema (DME). Superior in every way Laser therapy, anti-VEGF therapy, steroid therapy, and vitrectomy are all necessary treatments in these situations. Photocoagulation of the retinal pigment epithelium There is strong evidence that non-proliferative diabetic retinopathy (NPDR) is a viable treatment option.results that can be used to keep DR from progressing further. Furthermore, laser therapy has proven to be effective.For example, grid and subthreshold diode laser micropulse photocoagulation (SDM) for DME has been used.reported. In cases of vitreous hemorrhage or tractional retinal detachment in PDR patients, vitrectomy has been undertaken. There has also been significant interest in the ability of anti-VEGF medication to slow the progression of PDR from DME patients. Even with these therapies, many individuals with DR are still at risk of losing their eyesight and developing potentially dangerous side effects.. In the most advanced stages of DR, laser photocoagulation and vitrectomy are effective treatments for preventing severe vision loss. Both approaches, however, have their limitations. Evidence from preclinical and clinical studies shows that targeting renin-angiotensin system inhibition, vascular endothelial growth factor, and renin-angiotensin system blockade can reduce cardiovascular disease risk.the growth hormone, corticosteroids and protein kinase C.DR may be treated with these methodsMethodsThe study between January 2017 and November 2020 total number of patients 2968, Retrospective three year analysis.ResultsIncidence of referable retinopathy was independently associated with known duration of diabetes, age at diagnosis, and use of insulin treatment. For participants needing insulin treatment with a duration of diabetes of 10 years or more, cumulative incidence of referable retinopathy at one and three years was 9.61 and 30.99 per 1000 people, respectively.

Serum Untargeted Metabolomics Reveal Potential Biomarkers of Progression of Diabetic Retinopathy in Asians.

Purpose: To reveal molecular mechanisms of diabetic retinopathy (DR) in Asians and facilitate the identification of new therapeutic targets through untargeted metabolomics. To determine the differences in serum metabolites and metabolic pathways between different stages of diabetic retinopathy in patients with type 2 diabetic mellitus (T2DM) and proliferative DR (PDR) and non-proliferative DR (NPDR) and identify differential metabolites between T2DM and DR (NPDR and PDR) patients. Methods: This prospective observational registration study described the differential metabolites between 45 T2DM patients and 15 control cases with no significant differences in clinical characteristics. Their biospecimens and clinical information were collected and recorded in their medical reports. DR phenotypes of the subjects were verified by retina specialists. Serum metabolites were analyzed using high-resolution mass spectrometry with liquid chromatography. Untargeted metabolomics was performed on serum samples from 15 T2DM patients, 15 non-proliferative diabetic retinopathy patients, 15 proliferative diabetic retinopathy patients, and 15 diabetic controls. Discriminatory metabolic features were identified through partial least squares discriminant analysis (PLS-DA), hierarchical clustering analysis (HCA), and generalized linear regression models. Result: Through untargeted metabolomics, 931 features (523 in positive and 408 in negative modes) with 102 common metabolites highly relevant to the presence of DR were detected. In the adjusted analysis, 67 metabolic features differed significantly between T2DM and NPDR patients. Pathway analysis revealed alterations in metabolisms of amino acids and fatty acids. Glutamate, phosphatidylcholine, and 13-hydroperoxyoctadeca-9,11-dienoic acid (13-PHODE) were key contributors to these pathway differences. A total of 171 features distinguished PDR patients from T2DM patients, and pathway analysis revealed alterations in amino acid metabolism, fatty acid metabolism, nitrogen metabolism, and tricarboxylic acid cycle. Aspartate, glutamate, glutamine, ornithine, N-acetyl-l-glutamate, N-acetyl-l-aspartate, citrate, succinate, N-(L-arginino)succinate, 2-oxoglutarate, 13-hydroperoxyoctadeca-9,11-dienoic acid, methionine, lysine, threonine, phenylalanine, N(pi)-methyl-l-histidine, phosphatidylcholine, and linoleate were major contributors to the pathway differences. Between NPDR patients and PDR patients, there were 79 significant differential metabolites. Enrichment pathway analysis showed changes in amino acid metabolism, fatty acid metabolism, pantothenate, and CoA biosynthesis. Aspartate, glutamine, N-acetyl-l-glutamate, N-acetyl-l-aspartate, pantothenate, dihomo-gamma-linolenate, docosahexaenoic acid, and icosapentaenoic acid were key factors for the differences of these pathways. Conclusion: This study demonstrated that the pathways of arginine biosynthesis metabolism, linoleic acid metabolism, alanine, aspartate, and glutamate metabolism, as well as d-glutamine and d-glutamate metabolism, were dysregulated in DR patients of the Asian population. Increased levels of glutamate, aspartate, glutamine, N-acetyl-l-glutamate, and N-acetyl-l-aspartate and decreased levels of dihomo-gamma-linolenate, docosahexaenoic, and icosapentaenoic were considered as the metabolic profile that could distinguish PDR from NPDR in Asians. Phosphatidylcholine and 13-PHODE were identified as two major novel metabolite markers in advanced stages of DR in our study.

Diabetic retinopathy screening in the emerging era of artificial intelligence.

Diabetic retinopathy is a frequent complication in diabetes and a leading cause of visual impairment. Regular eye screening is imperative to detect sight-threatening stages of diabetic retinopathy such as proliferative diabetic retinopathy and diabetic macular oedema in order to treat these before irreversible visual loss occurs. Screening is cost-effective and has been implemented in various countries in Europe and elsewhere. Along with optimised diabetes care, this has substantially reduced the risk of visual loss. Nevertheless, the growing number of patients with diabetes poses an increasing burden on healthcare systems and automated solutions are needed to alleviate the task of screening and improve diagnostic accuracy. Deep learning by convolutional neural networks is an optimised branch of artificial intelligence that is particularly well suited to automated image analysis. Pivotal studies have demonstrated high sensitivity and specificity for classifying advanced stages of diabetic retinopathy and identifying diabetic macular oedema in optical coherence tomography scans. Based on this, different algorithms have obtained regulatory approval for clinical use and have recently been implemented to some extent in a few countries. Handheld mobile devices are another promising option for self-monitoring, but so far they have not demonstrated comparable image quality to that of fundus photography using non-portable retinal cameras, which is the gold standard for diabetic retinopathy screening. Such technology has the potential to be integrated in telemedicine-based screening programmes, enabling self-captured retinal images to be transferred virtually to reading centres for analysis and planning of further steps. While emerging technologies have shown a lot of promise, clinical implementation has been sparse. Legal obstacles and difficulties in software integration may partly explain this, but it may also indicate that existing algorithms may not necessarily integrate well with national screening initiatives, which often differ substantially between countries.

Neuronal Dysfunction Is Linked to the Famine-Associated Risk of Proliferative Retinopathy in Patients With Type 2 Diabetes

Persons with type 2 diabetes born in the regions of famine exposures have disproportionally elevated risk of vision-threatening proliferative diabetic retinopathy (PDR) in adulthood. However, the underlying mechanisms are not known. In the present study, we aimed to investigate the plausible molecular factors underlying progression to PDR. To study the association of genetic variants with PDR under the intrauterine famine exposure, we analyzed single nucleotide polymorphisms (SNPs) that were previously reported to be associated with type 2 diabetes, glucose, and pharmacogenetics. Analyses were performed in the population from northern Ukraine with a history of exposure to the Great Ukrainian Holodomor famine [the Diagnostic Optimization and Treatment of Diabetes and its Complications in the Chernihiv Region (DOLCE study), n = 3,583]. A validation of the top genetic findings was performed in the Hong Kong diabetes registry (HKDR, n = 730) with a history of famine as a consequence of the Japanese invasion during WWII. In DOLCE, the genetic risk for PDR was elevated for the variants in ADRA2A, PCSK9, and CYP2C19*2 loci, but reduced at PROX1 locus. The association of ADRA2A loci with the risk of advanced diabetic retinopathy in famine-exposed group was further replicated in HKDR. The exposure of embryonic retinal cells to starvation for glucose, mimicking the perinatal exposure to famine, resulted in sustained increased expression of Adra2a and Pcsk9, but decreased Prox1. The exposure to starvation exhibited a lasting inhibitory effects on neurite outgrowth, as determined by neurite length. In conclusion, a consistent genetic findings on the famine-linked risk of ADRA2A with PDR indicate that the nerves may likely to be responsible for communicating the effects of perinatal exposure to famine on the elevated risk of advanced stages of diabetic retinopathy in adults. These results suggest the possibility of utilizing neuroprotective drugs for the prevention and treatment of PDR.

Nested U-Net for Segmentation of Red Lesions in Retinal Fundus Images and Sub-image Classification for Removal of False Positives.

Diabetic retinopathy is a pathological change of the retina that occurs for long-term diabetes. The patients become symptomatic in advanced stages of diabetic retinopathy resulting in severe non-proliferative diabetic retinopathy or proliferative diabetic retinopathy stages. There is a need of an automated screening tool for the early detection and treatment of patients with diabetic retinopathy. This paper focuses on the segmentation of red lesions using nested U-Net Zhou et al. (Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support, Springer, 2018)followed by removal of false positives based on the sub-image classification method. Different sizes of sub-images were studied for the reduction in false positives in the sub-image classification method. The network could capture semantic features and fine details due to dense convolutional blocks connected via skip connections in between down sampling and up sampling paths. False-negative candidates were very few and the sub-image classification network effectively reduced the falsely detected candidates. The proposed framework achieves a sensitivity of [Formula: see text], precision of [Formula: see text], and F1-Score of [Formula: see text] for the DIARETDB1 data set Kalviainen and Uusutalo (Medical Image Understanding and Analysis, Citeseer, 2007). It outperforms the state-of-the-art networks such as U-Net Ronneberger et al. (International Conference on Medical Image Computing and Computer-Assisted Intervention, Springer, 2015)and attention U-NetOktay et al. (Attention u-net: Learning where to look for the pancreas, 2018).

Altered oxylipin levels in human vitreous indicate imbalance in pro-/anti-inflammatory homeostasis in proliferative diabetic retinopathy

Proliferative diabetic retinopathy (PDR) is an advanced stage of diabetic retinopathy (DR), characterized by retinal neovascularization. It is a progressive fundus disease and a severe complication of diabetes that causes vision impairment. Hyperglycemia-induced persistent low-grade inflammation is a crucial factor underlying the pathogenesis of DR-associated damage and contributing to the progression of PDR. Highly enriched polyunsaturated fatty acids (PUFAs) in the retina are precursors to oxidized metabolites, namely, oxylipins, which exert pro-inflammatory or anti-inflammatory (resolving) effects under different pathological conditions and have been implicated in diabetes. To evaluate differences in oxylipin levels in the vitreous obtained from PDR and non-diabetic subjects, we performed a targeted assessment of oxylipins. A total of 41 patients with PDR and 22 non-diabetic control subjects were enrolled in this study. Vitreous humor obtained during routinely scheduled vitrectomy underwent a targeted but unbiased screening for oxylipins using mass spectrometry-based lipidomics. We found 21 oxylipins showing statistically significant differences in their levels between PDR and non-diabetic subjects (p < 0.05). Lipoxygenase (LOX)- and cytochrome P450 (CYP)- derived oxylipins were the most affected, while cyclooxygenase (COX) oxylipins were affected to a lesser extent. When categorized by their precursor PUFAs, ±19,20-EpDPE, a CYP product of docosahexaenoic acid (DHA) and 12S-HETE, a LOX product of arachidonic acid (ARA), were increased by the largest magnitude. Moreover, of these 21 oxylipins, 7 were considered as potential biomarkers for discriminating PDR patients from the non-diabetic controls. Our results indicate that altered oxylipin levels in the vitreous implicate an underlying imbalanced inflammation-resolution homeostasis in PDR.

Association Between Diabetic Retinopathy and Carotid Intima-Media Thickness.

IntroductionPatients with diabetes having advanced stage of diabetic retinopathy (DR) may predict future risk of coronary artery disease. To predict cardiovascular outcomes carotid intima-media thickness (CIMT) is utilized in diabetic patients. The aim of our study was the evaluation of the relationship between retinopathy and CIMT as two valuable non-invasive methods for early detection of micro- and macrovascular complication of diabetes.MethodsThis comparative cross-sectional study was conducted in the internal medicine ward of tertiary care hospital in Pakistan from November 2020 to January 2021. Three hundred patients with type 2 diabetes mellitus and 300 control subjects were enrolled in the study after taking informed consent. Ophthalmological examination was done to screen patients for DR. CIMT was evaluated by a Doppler ultrasound for both carotid arteries.ResultsCarotid artery intimal thickness was more in patients with retinopathy compared to patients without retinopathy in both right (0.77 ± 0.16 vs. 0.66 ± 0.12; p-value: <0.0001) and left carotid artery (0.77 ± 0.15 vs. 0.65 ± 0.11; p-value: <0.0001).ConclusionIn our study, there was a correlation between DR and CIMT. Screening for DR, which may be a potential early marker for complications, may help detect patients at risk of various macro and microvascular complications.

Study of awareness of diabetic retinopathy and its implications among diabetic patients visiting at a tertiary eye care center

The aim of this study was to assess the awareness of diabetic retinopathy among diabetic patients. A cross-sectional survey was conducted between from 2017 to 2019. The analysis was based on a representative sample of 624 adult subjects. Multivariable logistic analysis was used to examine socio-demographic factors associated with the levels of awareness, treatment and control of diabetes mellitus.In our study 624 participants interviewed, among them 62% were males. rest were females. Most of the study subjects were non-vegetarian (74%). and were illiterates (40%). In our study, 92% were of type 2 DM, among them nearly 44.7% were on multidrug treatment. About 31% were diagnosed with DM after developing systemic complications. On examination, it was found 44.1% had proliferative diabetic retinopathy (PDR), 22.1 % required surgical intervention due to vision-threatening complication. Awareness regarding separate eye treatment for diabetic retinopathy was not known among 55 % of the patients. The periodicity of follow-up once treated for eye disease was poor, 74.1% being unaware. In this study majority of patients were in the advanced stage of diabetic retinopathy and associated with systemic complications. Thus educating the patients about the diabetic disease, diet and multi-organ involvement and its complications and importance of regular follow-up and how to prevent significant ocular and systemic morbidity.

Large-cube 30\xb0\u2009\xd7\u200925\xb0 optical coherence tomography in diabetic macular edema

BackgroundTo evaluate the contribution of large-cube 30° × 25° optical coherence tomography (OCT) in the characterization of diabetic macular edema (DME) by assessing its extent and the presence of additional retinal edemas and to evaluate the factors that influenced their occurrence.MethodsThis retrospective study enrolled patients with diabetes who presented with retinal edema detected by horizontal large-cube 30° × 25° (8.7 × 7.3 mm) OCT. Two individualized areas were selected from the thickness map: the area within the 6-mm Early Treatment of Diabetic Retinopathy Study (ETDRS) grid, and that outside the ETDRS grid. Retinal edemas located within the ETDRS grid were designated as “main DME” and those located outside the ETDRS grid were designated as “peripheral retinal edemas.” For each area, OCT features were assessed while the extent of the main DME and the presence of peripheral retinal oedema were analysed in the area outside the ETDRS grid. Finally, part of included eyes was followed by the same protocol, of which a part benefited from intravitreal injections.ResultsPeripheral events were detected outside the ETDRS area in 279 eyes (74.4%) of the 375 eyes of the 218 patients included in this study: an extension of the main DME outside ETDRS grid in 177 eyes (47.2%) and/or the presence of peripheral retinal edemas in 207 eyes (55.2%). The analysis of associations between main DME and peripheral retinal edemas patterns did not find an association for retinal cyst localization (P = 0.42) while a week association was found fort cyst size (Cramer’s V = 0.188, p = 0.028). Nevertheless, a moderate association was found for the presence of microaneurysms (Cramer’s V = 0.247, p < 0.001) and strong association for hard exudates (Cramer’s V = 0.386, p < 0.001), The binary logistic regression analysis retained the following influencing factors of the occurrence of peripheral events: advanced DR stage (Odds ratio OR = 2.19, p = 0.03), diffuse DME (OR = 7.76, p < 0.001) and its location in outer fields (OR = 7.09, p = 0.006). Likewise, the extension of the main DME outside the ETDRS area in was influenced by the same factors in addition to CMT (OR = 0.98, p = 0.004) while the presence of peripheral retinal edema was influenced by the same factors except the outer location of the Main DME. Finally, from the 94 eyes treated by intravitreal injections, extension of the main DME outside the ETDRS grid was detected in 54 eyes (56.44%) at baseline visit and still remained detectable in 37 eyes (39.36%) after treatment initiation.ConclusionsLarge-cube 30° × 25° OCT allowed for more precise assessment of DME extension and better detection of retinal thickening mainly in the advanced stages of diabetic retinopathy with significant DME whether at the baseline visit or during follow-up. The combination of this protocol with a wider ETDRS grid would enhance DME detection and topography.

Detection of early diabetic retinopathy using visual electrophysiological tests

Detection of functional impairment of vision in pre-clinical stages helps early identification of diabetic retinopathy. We aimed to determine the functional integrity of retina and post retinal pathways using electro-oculography (EOG), pattern electroretinography (PERG) and pattern-reversal visual evoked potentials (PR-VEP) in newly diagnosed diabetic patients who have not developed fundoscopic features of diabetic retinopathy. Twenty-five adults with newly diagnosed diabetes mellitus without fundoscopic evidence of retinopathy and a control group of healthy adults were subjected to visual electrophysiological assessment. Retinal pigment epithelium (RPE)-photoreceptor interaction, photoreceptors and ganglion cells of the macula and post retinal pathways were assessed by EOG, PERG and PR-VEP, respectively. Fourteen of the 25 diabetic patients, i.e. 56% (95% confidence intervals 34.9%, 75.6%), had LP:DT (light peak to dark trough) ratio less than 1.7, to the cut-off defined by the International Society for Clinical Electrophysiology of Vision (ISCEV). All control group subjects had LP:DT ratios above 1.7. The median LP:DT ratio in diabetic group (1.62 ± IQR 0.27) was significantly lower than that of the controls (1.8 ± IQR 0.21). Four patients had prolonged PR-VEP P100 latencies, and seven had prolonged PERG P50 latencies as per the ISCEV cut-offs, whereas none of the control group had abnormal PERG or PR-VEP measures. With a limited sample, we found that 56% of newly diagnosed diabetic patients with normal fundoscopy had defective RPE-photoreceptor interaction. Further studies are needed to obtain more precise point estimates of these EOG abnormalities, and to determine the conversion rates into more advanced stages of diabetic retinopathy.

Classification of neovascularization on retinal images using extreme learning machine

AbstractProliferative diabetic retinopathy is the advanced stage of diabetic retinopathy (DR) resulting in the growth of abnormal vessels on the retinal surface termed as neovascularization. This article primarily deals with the timely detection and classification of retinal images into healthy, neovascularization on optic disc, and elsewhere using an extreme learning machine (ELM) classifier. Initially, a binary mask is employed to enhance the foreground pixels. The resultant image is processed for the extraction of a retinal vessel map using Hessian‐based Frangi filter. For the classification of retinal images, an optimal feature set of 14 features including seven‐moment invariant‐based features are extracted from the vascular map using sequential recursive feature elimination algorithm. Further, the training of the ELM classifier is carried out using the K‐fold cross‐validation technique to improve the performance of the classifier. The proposed method achieves an average accuracy of 98% and an average error rate of less than 0.005 when tested on different globally accessible datasets. Apart from the different statistical results like sensitivity, specificity, and area under curve are estimated as 98.5%, 100%, and 94.2%, respectively, for validating the algorithm. Comparison results reveal that the ELM classifier outperforms the SVM classifier in terms of accuracy and error rate.

Association of macular perfusion status with microvascular parameters up to the far periphery in diabetic retinopathy using multimodal imaging

BackgroundThe aim of our study was to investigate a possible association between macular perfusion status and retinal ischemia and leakage up to far peripheral retinal areas in eyes with early to advanced stages of diabetic retinopathy (DR).MethodsIn a retrospective, cross sectional analysis ultrawide field (UWF) color fundus photos (Optos, Optomap California) were graded for DR severity. Foveal avascular zone (FAZ) and vessel density from the superficial (SCP) and deep capillary plexus (DCP) were assessed on optical coherence tomography angiography (OCTA) scans (Topcon, DRI-OCT Triton). UWF angiography images were used to quantify leakage/ischemic index and number of microaneurysms (MA). Age, gender, disease duration, type of diabetes, HbA1C, hypertension, complications of diabetes and ocular history were recorded. Univariate mixed models and Spearman correlation analysis were used for statistical testing.Results24 eyes of 17 laser-naive diabetic patients with different stages of DR were analyzed. The mean age was 59.56 ± 8.46 years and the mean disease duration 19.65 ± 12.25 years. No statistically significant associations between FAZ size, macular vessel density of SCP/DCP and peripheral retinal ischemia, leakage and MA number were demonstrated. Higher stages of DR were associated with ischemic index (estimate [95% CI]: 13.04 [1.5; 24.5], p = 0.033) and MA count (estimate [95% CI]: 43.7 [15.6; 71.8], p = 0.01), but no association with leakage index was observed. Only weak correlations between DR severity and anamnestic data were found.ConclusionRetinal ischemic index and the amount of MAs assessed on UWFA up to peripheral areas are indicators of DR severity but not related to microvascular perfusion status in the macular region. Significance and timely sequence of macular vessel density in DR progression may need to be re-evaluated in future studies.