Association Between the Severity of Diabetic Retinopathy and Optical Coherence Tomography Angiography Metrics.
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SUBMITTER: Xu B
PROVIDER: S-EPMC8702651 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:PurposeThe purpose of this study was to investigate whether optical coherence tomography angiography (OCTA) metrics are related to retinal vessel geometry parameters in diabetic retinopathy (DR).MethodsIn total, 119 eyes (119 patients) were included in this retrospective cross-sectional study. Retinal vessel geometry parameters were analyzed using semi-automated software. OCTA metrics were analyzed using automated manufacturer-provided algorithms. Associations between the severity of DR and retinal vessel geometry parameters and OCTA metrics were evaluated. Multivariable regression analyses were performed to evaluate associations between retinal vessel geometry parameters and OCTA metrics after adjusting for clinical characteristics and DR severity.ResultsDR severity was negatively associated with the following: arteriole-venular ratio (P = 0.039), arteriolar network fractal dimension (FDa; P = 0.003), arteriolar junctional exponent deviation (P = 0.037), venular junctional exponent deviation (P = 0.036), vessel area density (VAD) of the superficial capillary plexus (SCP) and deep capillary plexus (DCP; P < 0.001, both), vessel length density (VLD) of the SCP and DCP (P < 0.001, both), and foveal avascular zone (FAZ) circularity (P < 0.001). DR severity was positively associated with the central retinal venular equivalent caliber (P = 0.005), arteriolar branching coefficient (BCa; P = 0.010), venular branching coefficient (P = 0.007), and FAZ size (P = 0.002). In multivariable regression analyses, the following retinal vessel geometry parameters and OCTA metrics were associated: FDa with VAD of the SCP (β = 0.40, P < 0.001), FDa with VLD of the SCP (β = 0.01, P < 0.001), and BCa with FAZ circularity (β = -1.02, P = 0.001).ConclusionsIn DR, changes in retinal arteriolar geometry parameters were significantly associated with OCTA metrics, which reflect DR pathophysiology.
| S-EPMC8525825 | biostudies-literature
Project description:ImportanceStudies have not yet determined whether the distribution of lesions in the retinal periphery alters the association between the severity of diabetic retinopathy (DR) and macular vessel density.ObjectiveTo evaluate the association of DR lesion distribution with optical coherence tomography angiography (OCTA) metrics and DR severity.Design, setting, and participantsThis cross-sectional observational study was conducted at a tertiary care center for diabetic eye disease among 225 patients with type 1 or 2 diabetes who had undergone imaging between February 15, 2016, and December 31, 2019.ExposuresOptical coherence tomography angiography 3 × 3-mm macular scans and ultra-widefield color imaging.Main outcomes and measuresOptical coherence tomography angiography vessel density in the superficial capillary plexus, intermediate capillary plexus, and deep capillary plexus and choriocapillaris flow density. The severity of DR and the predominantly peripheral lesions (PPL) were evaluated from ultra-widefield color imaging.ResultsThe study evaluated 352 eyes (225 patients; 125 men [55.6%]; mean [SD] age, 52.1 [15.1] years), of which 183 eyes (52.0%) had mild nonproliferative diabetic retinopathy (NPDR), 71 eyes (20.2%) had moderate NPDR, and 98 eyes (27.8%) had severe NPDR or proliferative diabetic retinopathy (PDR). In eyes with no PPL (209 [59.4%]), the mean (SD) vessel density in the superficial capillary plexus (mild NPDR, 38.1% [4.7%]; moderate NPDR, 36.4% [4.6%]; severe NPDR or PDR, 34.1% [4.1%]; P < .001) and the deep capillary plexus (mild NPDR, 45.8% [3.0%]; moderate NPDR, 45.8% [2.2%]; severe NPDR or PDR, 44.5% [1.9%]; P = .002), as well as the mean (SD) choriocapillaris flow density (mild NPDR, 69.7% [6.2%]; moderate NPDR, 67.6% [5.6%]; severe NPDR or PDR, 67.1% [5.6%]; P = .01), decreased with increasing DR severity. These associations remained statistically significant even after correcting for age, signal strength index, spherical equivalent, duration of diabetes, type of diabetes, and correlation between eyes of the same patient. In eyes with PPL (143 [40.6%]), mean (SD) vessel density in the superficial capillary plexus (mild NPDR, 34.1% [4.1%]; moderate NPDR, 35.2% [4.1%]; severe NPDR or PDR, 36.0% [4.3%]; P = .42) and the deep capillary plexus (mild NPDR, 44.5% [1.7%]; moderate NPDR, 45.4% [1.4%]; severe NPDR or PDR, 44.9% [1.5%]; P = .81), as well as the mean (SD) choriocapillaris flow density (mild NPDR, 67.1% [5.6%]; moderate NPDR, 69.3% [4.6%]; severe NPDR or PDR, 68.3% [5.6%]; P = .49), did not appear to change with increasing DR severity.Conclusions and relevanceThese results suggest that central retinal vessel density is associated with DR severity in eyes without, but not with, PPL. These findings suggest a potential need to stratify future optical coherence tomography angiography studies of eyes with DR by the presence or absence of PPL. If DR onset and worsening are associated with the location of retinal nonperfusion, assessment of global retinal nonperfusion using widefield angiography may improve the ability to evaluate DR severity and risk of DR worsening over time.
| S-EPMC7596681 | biostudies-literature
Project description:PurposeTo investigate any associations between cigarette smoking and retinal microvascular changes in diabetic patients without visible retinopathy.DesignRetrospective, cross-sectional study.Participants1099 eyes from 1099 diabetic patients with no clinical evidence of diabetic retinopathy (DR) were included in this study.MethodsDiabetic patients underwent optical coherence tomography angiography (OCTA) scanning at Zuckerberg San Francisco General Hospital and Trauma Center between April 2018 and September 2019. Patient demographic and clinical information was collected. Standard bivariate statistics and multivariate linear regression were performed.Main outcome measuresOCTA parameters included metrics related to the foveal avascular zone (FAZ; area, perimeter, circularity), perfusion density (PD; full, center, inner), and vessel length density (VLD; full, center, inner).ResultsThe study population included 750 non-smokers and 349 smokers. FAZ perimeter was the only OCTA parameter that was significantly different between the two groups on uncontrolled analysis (P = 0.033). Multivariate regression analyses revealed significant associations between lower VLD full (β = -0.31, P = 0.048), lower VLD inner (β = -0.35, P = 0.046) and a history of smoking. No significant associations between cigarette smoking and either FAZ or PD were detected.ConclusionsOur results suggest that smoking is likely associated with deleterious changes in the retinal microvasculature of patients with a history of diabetes and no visible DR. Based on these findings, diabetic patients with a history of smoking may benefit from higher prioritization in terms of ophthalmic screening.
| S-EPMC8270137 | biostudies-literature
Project description:PurposeTo describe a new technique for mapping parafoveal intercapillary areas (PICAs) using optical coherence tomography angiography (OCTA), and demonstrate its utility for quantifying parafoveal nonperfusion in diabetic retinopathy (DR).MethodsNineteen controls, 15 diabetics with no retinopathy (noDR), 15 with nonproliferative diabetic retinopathy (NPDR), and 15 with proliferative diabetic retinopathy (PDR) were imaged with 10 macular OCTA scans. PICAs were automatically delineated on the averaged superficial OCTA images. Following creation of an eccentricity-specific reference database from the controls, all PICAs greater than 2 SD above the reference means for PICA area and minor axis length were identified as nonperfused areas. Regions of interest (ROI) at 300 ?m and 1000 ?m from the foveal avascular zone (FAZ) margin were analyzed. Percent nonperfused area was defined as summed nonperfused areas divided by ROI area. Values were compared using Kruskal-Wallis and post-hoc Mann-Whitney U tests.ResultsMedian values for total percent nonperfused area at the 300-?m ROI were 2.09, 2.44, 18.08, and 27.55 in the control, noDR, NPDR, and PDR groups, respectively. Median values at the 1000-?m ROI were 3.10, 3.31, 13.42, and 23.00. While there were no significant differences between the control and noDR groups, significant differences were observed between all other groups at both ROIs.ConclusionsPercent nonperfused area can quantify parafoveal nonperfusion in DR and can be calculated through automatic delineation of PICAs in an eccentricity-specific manner using a standard deviation mapping approach.Translational relevancePercent nonperfused area shows promise as a metric to measure disease severity in diabetic retinopathy.
| S-EPMC6042523 | biostudies-literature
Project description:PurposeThe purpose of this study was to evaluate the impact of image processing on quantitative metrics in optical coherence tomography angiography (OCTA) images and study conclusions in patients with diabetes.MethodsThis was a single center, retrospective cross-sectional study. OCTA imaging with the Cirrus HD-OCT 5000 AngioPlex of patients with diabetes was performed. The 8 × 8 mm superficial slab images underwent 4 different preprocessing methods (none, background subtraction [BGS], foveal avascular zone brightness adjustment, and contrast limited adaptive histogram equalization [CLAHE]) followed by 4 different binarization algorithms (global Huang, global Otsu, local Niblack, and local Phansalkar) in ImageJ. Vessel density (VD), skeletonized VD (SVD), and fractal dimension (FD) were calculated. Mixed-effect multivariate linear regressions were performed.ResultsTwo hundred eleven scans from 104 patients were included. Of these scans, 67 (31.8%) had no diabetic retinopathy (DR), 99 (46.9%) had nonproliferative DR (NPDR), and 45 (21.3%) had proliferative DR (PDR). Forty-eight of 211 (22.7%) scans had diabetic macular edema (DME). The image processing method used significantly impacted values of VD, SVD, and FD (all P -values < 0.001). On multivariate analysis, the image processing method changed the clinical variables significantly associated with VD, SVD, and FD. However, BGS and CLAHE yielded more consistent significant covariates across multiple binarization algorithms.ConclusionsThe image processing method can impact the conclusions of any given study analyzing quantitative OCTA metrics. Thus, caution is urged in the interpretation of such studies. Background subtraction or CLAHE may play a role in the standardization of image processing.Translational relevanceThis work proposes strategies to achieve robust and consistent analysis of OCTA imaging, which is especially important for clinical trials.
| S-EPMC9483236 | biostudies-literature
Project description:Purpose:To identify microvascular and neural parameters related to the severity of diabetic retinopathy (DR) by using optical coherence tomography angiography in patients with type 2 diabetes. Methods:This cross-sectional study included 110 eyes (63 patients) with no DR, 46 eyes (33 patients) with mild nonproliferative DR, 36 eyes (23 patients) with moderate nonproliferative DR, 36 eyes (22 patients) with severe nonproliferative DR, and 31 eyes (19 patients) with proliferative DR. The optical coherence tomography angiography images were processed to quantify the foveal avascular zone parameters, macular vessel density (VD), retinal thickness, peripapillary VD, retinal nerve fiber layer thickness, and ganglion cell complex thickness. A LASSO-based continuation ratio model was used to select the most clinically relevant parameters for predicting the stage of DR. Results:The regression model identified a set of regional parameters for each scanning pattern that identified the DR severity, including foveal avascular zone perimeter; FD-300; temporal perifoveal superficial capillary plexus VD and retinal thickness; temporal and nasal parafoveal deep capillary plexus VD; peripapillary VD in the temporal superior, nasal inferior, and temporal inferior sectors; temporal superior and nasal inferior retinal nerve fiber layer thickness; ganglion cell complex thickness; and FLV, which changed significantly with the progression of DR. Furthermore, two combined blocks exhibited different sensitive parameters to differentiate between the groups based on DR severity. Similar results were obtained in eyes without diabetic macular edema. Conclusions:We identified microvascular and neural parameters related to the severity of DR using optical coherence tomography angiography, suggesting their potential clinical application for better screening and staging of DR.
| S-EPMC7405728 | biostudies-literature
Project description:As the prevalence of diabetes increases, millions of people need to be screened for diabetic retinopathy (DR). Remarkable advances in technology have made it possible to use artificial intelligence to screen DR from retinal images with high accuracy and reliability, resulting in reducing human labor by processing large amounts of data in a shorter time. We developed a fully automated classification algorithm to diagnose DR and identify referable status using optical coherence tomography angiography (OCTA) images with convolutional neural network (CNN) model and verified its feasibility by comparing its performance with that of conventional machine learning model. Ground truths for classifications were made based on ultra-widefield fluorescein angiography to increase the accuracy of data annotation. The proposed CNN classifier achieved an accuracy of 91-98%, a sensitivity of 86-97%, a specificity of 94-99%, and an area under the curve of 0.919-0.976. In the external validation, overall similar performances were also achieved. The results were similar regardless of the size and depth of the OCTA images, indicating that DR could be satisfactorily classified even with images comprising narrow area of the macular region and a single image slab of retina. The CNN-based classification using OCTA is expected to create a novel diagnostic workflow for DR detection and referral.
| S-EPMC8626435 | biostudies-literature
Project description:PurposeTo develop an automated diabetic retinopathy (DR) staging system using optical coherence tomography angiography (OCTA) images with a convolutional neural network (CNN) and to verify the feasibility of the system.MethodsIn this retrospective cross-sectional study, a total of 918 data sets of 3 × 3 mm2 OCTA images and 917 data sets of 6 × 6 mm2 OCTA images were obtained from 1118 eyes. A deep CNN and four traditional machine learning models were trained with annotations made by a retinal specialist based on ultra-widefield fluorescein angiography. Separately, the same images of the test data sets were independently graded by two human experts. The results of the CNN algorithm were compared with those of traditional machine learning-based classifiers and human experts.ResultsThe proposed CNN achieved an accuracy of 0.728, a sensitivity of 0.675, a specificity of 0.944, an F1 score of 0.683, and a quadratic weighted κ of 0.908 for a six-level staging task, which were far superior to the results of traditional machine learning methods or human experts. The CNN algorithm showed a better performance using 6 × 6 mm2 rather than 3 × 3 mm2 sized OCTA images and using combined data rather than a separate OCTA layer alone.ConclusionsCNN-based classification using OCTA images can provide reliable assistance to clinicians for DR classification.Translational relevanceThis CNN algorithm can guide the clinical decision for invasive angiography or referrals to ophthalmology specialists, helping to create more efficient diagnostic workflow in primary care settings.
| S-EPMC8899862 | biostudies-literature
Project description:PurposeThe purpose of this study was to evaluate specifically in type 1 diabetes mellitus (DM) individuals the relationship between perifoveal superficial capillary plexus (SCP) parameters assessed by optical coherence tomography angiography (OCTA) and diabetic retinopathy (DR) grade.MethodsCross-sectional analysis of a large scale prospective OCTA trial cohort (ClinicalTrials.gov NCT03422965). A total of 1186 eyes (593 individuals), 956 type 1 DM eyes (478 patients), and 230 control eyes (115 healthy volunteers) were included in this study. DR stage was graded according to the International Classification. OCTA imaging was performed with a commercially available device (Cirrus HD-OCT). Vessel density (VD), perfusion density (PD), and foveal avascular zone (FAZ) area, perimeter and circularity measurements were quantified in the SCP and receiver operating characteristic (ROC) curves were constructed for each OCTA parameter.ResultsVD and PD (in both 3 × 3 and 6 × 6 mm captures) were inversely associated with DR stage (P < 0.001 in all cases) in a multiple regression analysis after controlling by age, gender, signal strength index, axial length, and DM duration. Greater FAZ area and perimeter and conversely lower circularity measurements were observed as DR severity increased in both scanning protocols (P < 0.05 in all cases).ConclusionsIn type 1 DM individuals, OCTA provides an objective, continuous, and reliable method for accurate quantification of VD, PD, and FAZ parameters in the SCP, which ultimately correlate with DR stages.Translational relevanceObjective OCTA measurements of the retinal microvasculature could substitute the clinical DR classification in patients with type 1 DM, identify patients at risk of DR progression, and inform treatment decisions to modify the evolution of the disease.
| S-EPMC7533741 | biostudies-literature
Project description:ImportanceMacular ischemia is a key feature of diabetic retinopathy (DR). Quantification of macular ischemia has potential as a biomarker for DR.ObjectiveTo assess the feasibility of automated quantification of capillary nonperfusion as a potential sign of macular ischemia using optical coherence tomography (OCT) angiography.Design, setting, and participantsAn observational study conducted in a tertiary, subspecialty, academic practice evaluated macular nonperfusion with 6 × 6-mm OCT angiography obtained with commercially available 70-kHz OCT and fluorescein angiography (FA). The study was conducted from January 22 to September 18, 2014. Data analysis was performed from October 1, 2014, to April 7, 2015. Participants included 12 individuals with normal vision serving as controls and 12 patients with various levels of DR.Main outcomes and measuresPreplanned primary measures were parafoveal and perifoveal vessel density, total avascular area, and foveal avascular zone as detected with 6 × 6-mm OCT angiography and analyzed using an automated algorithm. Secondary measures included the agreement of the avascular area between the OCT angiogram and FA.ResultsCompared with the 12 healthy controls (11 women; mean [SD] age, 54.2 [14.2] years), the 12 participants with DR (4 women; mean [SD] age, 55.1 [12.1] years) had reduced parafoveal and perifoveal vessel density by 12.6% (95% CI, 7.7%-17.5%; P < .001) and 10.4% (95% CI, 6.8%-14.1%; P < .001), respectively. Total avascular area and foveal avascular zone area were greater in eyes with DR by 0.82 mm2 (95% CI, 0.65-0.99 mm2; P = .02) and 0.16 mm2 (95% CI, 0.05-0.28 mm2; P < .001). The agreement between the vascular areas in the OCT angiogram and FA had a κ value of 0.45 (95% CI, 0.21-0.70; P < .001). Total avascular area in the central 5.5-mm-diameter area distinguished eyes with DR from control eyes with 100% sensitivity and specificity.Conclusions and relevanceAvascular area analysis with an automated algorithm using OCT angiography, although not equivalent to FA, detected DR reliably in this small pilot study. Further study is necessary to determine the usefulness of the automated quantification in clinical practice.
| S-EPMC4978127 | biostudies-literature