Dataset Information

Association of Optical Coherence Tomography Angiography of Collaterals in Retinal Vein Occlusion With Major Venous Outflow Through the Deep Vascular Complex.

ABSTRACT:

Importance

Analysis of collateral vessel formation following retinal vein occlusion may advance our understanding of the venous outflow anatomy in the macula.

Objective

To determine the location of collateral vessels with optical coherence tomography (OCT) angiography imaging.

Design, setting, and participants

Observational retrospective cohort study. Collateral vessel formation was studied with OCT angiography (OCTA) in patients with retinal vein occlusion (RVO). The study took place at 2 retinal practices (Vitreous Retina Macula Consultants of New York and Stein Eye Institute, University of California, Los Angeles), with patient records retrieved from March 2015 to August 2017. Data analysis was completed in November 2017.

Exposures

Collaterals identified with fundus photography and/or fluorescein angiography were analyzed with OCTA to determine their course through the superficial vascular plexus (SVP) and the deep vascular complex (DVC).

Main outcomes and measures

Collateral vessel pathways through the SVP and DVC were analyzed with cross-sectional and en face OCT and OCTA segmentation and color-coded volume renderings prepared from raw OCTA voxel data.

Results

From 23 eyes (22 branch and 1 hemispheric retinal vein occlusion ) of 23 patients (mean [SD] age, 73 [11] years), 101 collateral vessels were identified and analyzed (mean [SD], 4.4 [2.0]; range, 2-9 collateral per eye). On OCTA, the collaterals appeared as curvilinear dilated flow signals that connected veins across the horizontal raphe or veins on opposite sides of an occluded venous segment within the same retinal hemisphere. Of the 101 collaterals analyzed, all showed greater flow signal in the DVC, and all had some portion of their course identified within the DVC. No collaterals were found exclusively in the SVP. Volume renderings for 3 cases confirmed qualitatively that retinal collateral vessels course through the retina predominantly at the level of the DVC.

Conclusions and relevance

Based on a limited number of cases, all collateral vessels associated with retinal vein occlusion were found to course through the DVC. The absence of collaterals isolated to the SVP supports a serial arrangement of the SVP and DVC, with venous drainage predominantly coursing through the DVC.

SUBMITTER: Freund KB

PROVIDER: S-EPMC6248171 | biostudies-literature | 2018 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Association of Optical Coherence Tomography Angiography of Collaterals in Retinal Vein Occlusion With Major Venous Outflow Through the Deep Vascular Complex.

Freund K Bailey KB Sarraf David D Leong Belinda C S BCS Garrity Sean Thomas ST Vupparaboina Kiran K KK Dansingani Kunal K KK

JAMA ophthalmology 20181101 11

<h4>Importance</h4>Analysis of collateral vessel formation following retinal vein occlusion may advance our understanding of the venous outflow anatomy in the macula.<h4>Objective</h4>To determine the location of collateral vessels with optical coherence tomography (OCT) angiography imaging.<h4>Design, setting, and participants</h4>Observational retrospective cohort study. Collateral vessel formation was studied with OCT angiography (OCTA) in patients with retinal vein occlusion (RVO). The study ...[more]

PMID: 30352115

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Project description:PurposeTo examine whether deep-learning denoised optical coherence tomography angiography (OCTA) images could enhance automated macular ischemia quantification in branch retinal vein occlusion (BRVO).MethodsThis retrospective, single-center, cross-sectional study enrolled 74 patients with BRVO and 46 age-matched healthy subjects. The severity of macular ischemia was graded as mild, moderate, or severe. Denoised OCTA images were produced using a neural network model. Quantitative parameters derived from denoised images, including vessel density and nonperfusion area, were compared with those derived from the OCTA machine. The main outcome measures were correlations between quantitative parameters, and areas under receiver operating characteristic curves (AUCs) in classifying the severity of the macular ischemia.ResultsThe vessel density and nonperfusion area from denoised images were correlated strongly with the corresponding parameters from machine-derived images in control eyes and BRVO eyes with mild or moderate macular ischemia (all P < 0.001). However, no such correlation was found in eyes with severe macular ischemia. The vessel density and nonperfusion area from denoised images had significantly larger area under receiver operating characteristic curve than those derived from the original images in classifying moderate versus severe macular ischemia (0.927 vs 0.802 [P = 0.042] and 0.946 vs 0.797, [P = 0.022], respectively). There were no significant differences in the areas under receiver operating characteristic curve between the denoised images and the machine-derived parameters in classifying control versus BRVO, and mild versus moderate macular ischemia.ConclusionsA neural network model is useful for removing speckle noise on OCTA images and facilitating the automated grading of macular ischemia in eyes with BRVO.Translational relevanceDeep-learning denoised optical coherence tomography angiography images could enhance automated macular ischemia quantification.

Project description:BackgroundRetinal vein occlusion (RVO) is the second most common vision-threatening retinal vascular disease. Intravitreal dexamethasone implant has been applied to treat macular edema secondary to RVO (RVO-ME). However, the alteration of morphologic features detected with optical coherence tomography angiography (OCTA) has not been fully studied in RVO-ME patients before and after the treatment.ObjectiveThis study is aimed at identifying potential therapeutic targets in RVO with integrative bioinformatic analysis and compares the OCTA characteristics alterations in patients with RVO-ME receiving injection of dexamethasone intravitreal implant.MethodsBioinformatic analysis was analyzed in GSE101398 dataset from the Gene Expression Omnibus database. Multiple functional enrichment analyses were performed, and protein-protein interaction network was constructed to visualize the key node genes. Eleven eyes with RVO-ME were examined with OCTA before and after intravitreal dexamethasone implant. The OCTA parameters, including macular thickness, vessel density, foveal avascular zone parameters, the number of hyperreflective foci (HRF), area of cystoid edema, and subretinal fluid (SRF), were compared. The correlation was analyzed between best-corrected visual acuity (BCVA) and OCTA parameters.ResultsA total of 79 differentially expressed genes were identified. Functional enrichment analyses revealed the enriched inflammatory events in RVO. In RVO-ME, Pearson correlation revealed that baseline BCVA was positively correlated with the area of SRF and central macular thickness, while no correlation was detected between baseline BCVA and HRF number or the area of cystoid edema. The visual acuity improved, and the central macular thickness was decreased after intravitreal dexamethasone implant injection. Besides, the number of HRF, the area of cystoid edema, and SRF were significantly alleviated after dexamethasone intravitreal injection.ConclusionRetinal inflammation plays a crucial role in RVO pathogenesis. The imaging biomarkers of RVO including Müller glial intracellular edema, and retinal pigment epithelium dysfunction, could be assessed in OCTA and attenuated by intravitreal dexamethasone implant effectively.

Project description:PurposeTo determine the repeatability of superficial vessel density measurements using Spectral domain Ocular coherence tomography angiography(SD-OCTA) in patients diagnosed with retinal vein occlusion(RVO).DesignProspective observational study.SubjectsPatients who visited our retinal clinic from August 2017 to August 2018, diagnosed with RVO were recruited for the study.MethodsTwo consecutive 3×3 mm pattern scans were performed using the Cirrus HD-OCT 5000 along with AngioPlex software (Carl Zeiss Meditec) in each eye by single skilled examiner. All scans were analyzed using en face OCTA images to measure vessel density (VD) automatically. For further analysis of the effect of central macular thickness(CMT), eyes were divided into two groups according to CMT of 400μm (Group 1: CMT > 400μm, Group 2: CMT < 400μm). To identify factors affecting the repeatability of VD measurements, linear regression analyses were conducted for the coefficient of variation (CV) of VD by investigating demographics and ocular variables.Main outcome measuresThe intraclass correlation coefficient (ICC), coefficient of variation (CV) of VD measurements.ResultsA total of 57 eyes from 57 patients were examined: 35 eyes with BRVO and 22 eyes with CRVO. In all 57 eyes with RVO, the ICC and CV of the full VD(VD of 3mm diameter circle) were 0.800 and 10.61%, respectively. Univariate analyses showed that the mean CMT (B, 0.001; p<0.001) and mean ganglion cell-Inner plexiform layer (GC-IPL) thickness (B, -0.002; p = 0.020) were significant factors that affected the repeatability. Multivariate analyses of these two factors showed that only mean CMT was a significant factor. The ICC and CV of the full VD in group 1 (CMT > 400μm) were 0.348 and 22.55% respectively. In group 2 (CMT < 400μm), the ICC and CV of the full VD were 0.910 and 7.76%, respectively.ConclusionsThe repeatability of VD measurement in eyes with RVO was reasonably comparable to previous studies. Repeatability of VD measurement was significantly affected by central macular thickness.

Dataset Information

Association of Optical Coherence Tomography Angiography of Collaterals in Retinal Vein Occlusion With Major Venous Outflow Through the Deep Vascular Complex.

Importance

Objective

Design, setting, and participants

Exposures

Main outcomes and measures

Results

Conclusions and relevance

Publications

Association of Optical Coherence Tomography Angiography of Collaterals in Retinal Vein Occlusion With Major Venous Outflow Through the Deep Vascular Complex.

Similar Datasets

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