scholarly journals Association Between the Severity of Diabetic Retinopathy and Optical Coherence Tomography Angiography Metrics

2021 ◽  
Vol 12 ◽  
Author(s):  
Binxin Xu ◽  
Jiahui Chen ◽  
Shaohua Zhang ◽  
Shengli Shen ◽  
Xuan Lan ◽  
...  
Keyword(s):  
Risk Factors ◽  
Optical Coherence Tomography ◽  
Diabetic Retinopathy ◽  
Systemic Risk ◽  
Optical Coherence Tomography Angiography ◽  
Vessel Segmentation ◽  
Optical Coherence ◽  
Segmentation Method ◽  
The Relationship ◽  
Systemic Risk Factors

Diabetic retinopathy, the most serious ocular complication of diabetes, imposes a serious economic burden on society. Automatic and objective assessment of vessel changes can effectively manage diabetic retinopathy and prevent blindness. Optical coherence tomography angiography (OCTA) metrics have been confirmed to be used to assess vessel changes. The accuracy and reliability of OCTA metrics are restricted by vessel segmentation methods. In this study, a multi-branch retinal vessel segmentation method is proposed, which is comparable to the segmentation results obtained from the manual segmentation, effectively extracting vessels in low contrast areas and improving the integrity of the extracted vessels. OCTA metrics based on the proposed segmentation method were validated to be reliable for further analysis of the relationship between OCTA metrics and diabetes and the severity of diabetic retinopathy. Changes in vessel morphology are influenced by systemic risk factors. However, there is a lack of analysis of the relationship between OCTA metrics and systemic risk factors. We conducted a cross-sectional study that included 362 eyes of 221 diabetic patients and 1,151 eyes of 587 healthy people. Eight systemic risk factors were confirmed to be closely related to diabetes. After controlling these systemic risk factors, significant OCTA metrics (such as vessel complexity index, vessel diameter index, and mean thickness of retinal nerve fiber layer centered in the macular) were found to be related to diabetic retinopathy and severe diabetic retinopathy. This study provides evidence to support the potential value of OCTA metrics as biomarkers of diabetic retinopathy.

scholarly journals The effect of systemic factors on retinal blood flow in patients with carotid stenosis: an optical coherence tomography angiography study

GeroScience ◽  
2021 ◽  
Author(s):  
Lilla István ◽  
Cecilia Czakó ◽  
Fruzsina Benyó ◽  
Ágnes Élő ◽  
Zsuzsa Mihály ◽  
...  
Keyword(s):  
Risk Factors ◽  
Blood Flow ◽  
Optical Coherence Tomography ◽  
Carotid Artery ◽  
Systemic Risk ◽  
Carotid Artery Stenosis ◽  
Optical Coherence Tomography Angiography ◽  
Retinal Blood Flow ◽  
Systemic Factors ◽  
Systemic Risk Factors

AbstractCarotid artery stenosis (CAS) is among the leading causes of mortality and permanent disabilities in the Western world. CAS is a consequence of systemic atherosclerotic disease affecting the majority of the aging population. Optical coherence tomography angiography (OCTA) is a novel imaging technique for visualizing retinal blood flow. It is a noninvasive, fast method for qualitative and quantitative assessment of the microcirculation. Cerebral and retinal circulation share similar anatomy, physiology, and embryology; thus, retinal microvasculature provides a unique opportunity to study the pathogenesis of cerebral small vessel disease in vivo. In this study, we aimed to analyze the effect of systemic risk factors on retinal blood flow in the eyes of patients with significant carotid artery stenosis using OCT angiography. A total of 112 eyes of 56 patients with significant carotid stenosis were included in the study. We found that several systemic factors, such as decreased estimated glomerular filtration rate (eGFR), hypertension, and carotid occlusion have a significant negative effect on retinal blood flow, while statin use and carotid surgery substantially improve ocular microcirculation. Neither diabetes, clopidogrel or acetylsalicylic acid use, BMI, serum lipid level, nor thrombocyte count showed a significant effect on ocular blood flow. Our results demonstrate that a systematic connection does exist between certain systemic risk factors and retinal blood flow in this patient population. OCTA could help in the assessment of cerebral circulation of patients with CAS due to its ability to detect subtle changes in retinal microcirculation that is considered to represent changes in intracranial blood flow.

scholarly journals Diabeteses kisér-károsodás vizsgálata optikai koherencia tomográfián alapuló angiográfiával

2018 ◽  
Vol 159 (8) ◽  
pp. 320-326
Author(s):  
Cecília Czakó ◽  
Gábor László Sándor ◽  
Mónika Ecsedy ◽  
Zsuzsanna Szepessy ◽  
Ágnes Borbándy ◽  
...  
Keyword(s):  
Risk Factors ◽  
Optical Coherence Tomography ◽  
Diabetic Retinopathy ◽  
Optical Coherence Tomography Angiography ◽  
Retinal Vessel ◽  
Vessel Density ◽  
Diabetic Patients ◽  
Optical Coherence ◽  
Retinal Microvasculature ◽  
Retinal Vessel Density

Abstract: Introduction: Optical coherence tomography angiography is a non-invasive imaging technique that is able to visualize the different retinal vascular layers using motion contrast to detect blood flow without intravenous dye injection. This method might help to assess microangiopathy in diabetic retinopathy during screening and follow-up. Aim: To quantify retinal microvasculature alterations in both eyes of diabetic patients in relation to systemic risk factors using optical coherence tomography angiography. Method: Both eyes of 36 diabetic patients and 45 individuals without diabetes were examined. Duration of diabetes, insulin therapy, blood pressure, HbA1c, dyslipidemia, axial length and the presence of diabetic retinopathy were recorded. Retinal vessel density was measured by optical coherence tomography angiography. The effect of risk factors on vessel density and between-eye asymmetry was assessed using multivariable regression analysis. Results: Vessel density was significantly lower and between-eye difference was significantly higher in diabetic patients compared to controls (p<0.05). Both vessel density and between-eye asymmetry significantly correlated with diabetes duration (p<0.05) after controlling for the effect of risk factors. The between-eye asymmetry in vessel density was significantly higher in patients without clinically detectable diabetic retinopathy compared to control subjects (p<0.001). Conclusions: There is a decrease in retinal vessel density and an increase in between-eye asymmetry in patients with diabetes compared to healthy subjects. By using optical coherence tomography angiography, the detection of these microvascular alterations is possible before clinically detectable diabetic retinopathy and might serve as a useful tool in both screening and timing of treatment. Orv Hetil. 2018; 159(8): 320–326.

scholarly journals Foveal avascular zone segmentation in optical coherence tomography angiography images using a deep learning approach

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Reza Mirshahi ◽  
Pasha Anvari ◽  
Hamid Riazi-Esfahani ◽  
Mahsa Sardarinia ◽  
Masood Naseripour ◽  
...  
Keyword(s):  
Optical Coherence Tomography ◽  
Diabetic Retinopathy ◽  
Deep Learning ◽  
Healthy Subjects ◽  
Optical Coherence Tomography Angiography ◽  
Validation Dataset ◽  
Diabetic Patients ◽  
Dice Similarity Coefficient ◽  
Optical Coherence ◽  
Avascular Zone

AbstractThe purpose of this study was to introduce a new deep learning (DL) model for segmentation of the fovea avascular zone (FAZ) in en face optical coherence tomography angiography (OCTA) and compare the results with those of the device’s built-in software and manual measurements in healthy subjects and diabetic patients. In this retrospective study, FAZ borders were delineated in the inner retinal slab of 3 × 3 enface OCTA images of 131 eyes of 88 diabetic patients and 32 eyes of 18 healthy subjects. To train a deep convolutional neural network (CNN) model, 126 enface OCTA images (104 eyes with diabetic retinopathy and 22 normal eyes) were used as training/validation dataset. Then, the accuracy of the model was evaluated using a dataset consisting of OCTA images of 10 normal eyes and 27 eyes with diabetic retinopathy. The CNN model was based on Detectron2, an open-source modular object detection library. In addition, automated FAZ measurements were conducted using the device’s built-in commercial software, and manual FAZ delineation was performed using ImageJ software. Bland–Altman analysis was used to show 95% limit of agreement (95% LoA) between different methods. The mean dice similarity coefficient of the DL model was 0.94 ± 0.04 in the testing dataset. There was excellent agreement between automated, DL model and manual measurements of FAZ in healthy subjects (95% LoA of − 0.005 to 0.026 mm2 between automated and manual measurement and 0.000 to 0.009 mm2 between DL and manual FAZ area). In diabetic eyes, the agreement between DL and manual measurements was excellent (95% LoA of − 0.063 to 0.095), however, there was a poor agreement between the automated and manual method (95% LoA of − 0.186 to 0.331). The presence of diabetic macular edema and intraretinal cysts at the fovea were associated with erroneous FAZ measurements by the device’s built-in software. In conclusion, the DL model showed an excellent accuracy in detection of FAZ border in enfaces OCTA images of both diabetic patients and healthy subjects. The DL and manual measurements outperformed the automated measurements of the built-in software.

Detecting papillary neovascularization in proliferative diabetic retinopathy using optical coherence tomography angiography

2016 ◽  
Vol 96 (3) ◽  
pp. 321-323 ◽  
Author(s):  
Maria Cristina Savastano ◽  
Matteo Federici ◽  
Benedetto Falsini ◽  
Aldo Caporossi ◽  
Angelo Maria Minnella
Keyword(s):  
Optical Coherence Tomography ◽  
Diabetic Retinopathy ◽  
Proliferative Diabetic Retinopathy ◽  
Optical Coherence Tomography Angiography ◽  
Optical Coherence
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