Dataset Information

Accuracy and Reliability in Differentiating Retinal Arteries and Veins Using Widefield En Face OCT Angiography.

ABSTRACT: Purpose:To evaluate the accuracy and reliability in differentiating retinal arteries from veins using widefield optical coherence tomography angiography (OCTA). Methods:Ten healthy eyes and 12 eyes from diabetic patients were included. Foveal-centered swept-source OCTA images (12 × 12 mm) were obtained using the PLEX Elite 9000. Vessels were graded as arteries or veins by two independent, masked readers. Arteriovenous crossings were also evaluated in healthy eyes. The vessel identification gold standard was defined using color fundus photographs (CFP) for normal eyes and both CFP and fluorescein angiography for diabetic eyes. Grading accuracy was compared to the gold standard and reliability between readers assessed. Results:The study evaluated 538 vessels (119 first order, 110 second, 309 third) in healthy eyes and 645 vessels (184 first order, 159 second, 302 third). In healthy eyes, the average accuracies identifying all, first-, second-, and third-order vessels were 98.61%, 99.16%, 100%, and 98.06%, respectively. Cohen's ? between graders in all vessels was 0.948. In diabetic eyes, the average accuracies identifying vessels were 96.90%, 99.46%, 97.77%, and 94.85%, respectively. Cohen's ? between graders for all vessels was 0.888. For crossing identification, the average accuracy and Cohen's ? were low (60.71% and 0.659, respectively). Conclusions:En face OCTA allows for accurate and reliable artery and vein identification; for small branches and crossings, identification by en face OCTA alone may be less accurate and reliable. Translational Relevance:Arteries and veins can be differentiated on OCTA, assisting in clinically identifying pathology as arterial or venous side.

SUBMITTER: Ishibazawa A

PROVIDER: S-EPMC6602142 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature

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Accuracy and Reliability in Differentiating Retinal Arteries and Veins Using Widefield En Face OCT Angiography.

Ishibazawa Akihiro A Mehta Nihaal N Sorour Osama O Braun Phillip P Martin Sarah S Alibhai A Yasin AY Saifuddin Adnan A Arya Malvika M Baumal Caroline R CR Duker Jay S JS Waheed Nadia K NK

Translational vision science & technology 20190501 3

<h4>Purpose</h4>To evaluate the accuracy and reliability in differentiating retinal arteries from veins using widefield optical coherence tomography angiography (OCTA).<h4>Methods</h4>Ten healthy eyes and 12 eyes from diabetic patients were included. Foveal-centered swept-source OCTA images (12 × 12 mm) were obtained using the PLEX Elite 9000. Vessels were graded as arteries or veins by two independent, masked readers. Arteriovenous crossings were also evaluated in healthy eyes. The vessel ident ...[more]

PMID: 31316862

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Project description:IntroductionThere is a high and ever-increasing global prevalence of diabetic retinopathy (DR) and invasive imaging techniques are often required to confirm the presence of proliferative disease. The aim of this study was to explore the images of a rapid and non-invasive technique, widefield optical coherence tomography angiography (OCT-A), to study differences between patients with severe non-proliferative and proliferative DR (PDR).MethodsWe conducted an observational longitudinal study from November 2022 to March 2023. We recruited 75 patients who were classified into a proliferative group (28 patients) and severe non-proliferative group (47 patients). Classification was done by specialist clinicians who had full access to any multimodal imaging they required to be confident of their diagnosis, including fluorescein angiography. For all patients, we performed single-shot 4 × 4 and 10 × 10 mm (widefield) OCT-A imaging and when possible, the multiple images required for mosaic 17.5 × 17.5 mm (ultra widefield) OCT-A imaging. We assessed the frequency with which proliferative disease was identifiable solely from these OCT-A images and used custom-built MATLAB software to analyze the images and determine computerized metrics such as density and intensity of vessels, foveal avascular zone, and ischemic areas.ResultsOn clinically assessing the OCT-A 10 × 10 fields, we were only able to detect new vessels in 25% of known proliferative images. Using ultra-widefield mosaic images, however, we were able to detect new vessels in 100% of PDR patients. The image analysis metrics of 4 × 4 and 10 × 10 mm images did not show any significant differences between the two clinical groups. For mosaics, however, there were significant differences in the capillary density in patients with PDR compared to severe non-PDR (9.1% ± 1.9 in the PDR group versus 11.0% ± 1.9 for severe group). We also found with mosaics a significant difference in the metrics of ischemic areas; average area of ischemic zones (253,930.1 ± 108,636 for the proliferative group versus 149,104.2 ± 55,101.8 for the severe group.ConclusionsOur study showed a high sensitivity for detecting PDR using only ultra-widefield mosaic OCT-A imaging, compared to multimodal including fluorescein angiography imaging. It also suggests that image analysis of aspects such as ischemia levels may be useful in identifying higher risk groups as a warning sign for future conversion to neovascularization.

Project description:ImportanceImaging of the choriocapillaris in vivo is challenging with existing technology. Optical coherence tomography angiography (OCTA), if optimized, could make the imaging less challenging.ObjectiveTo investigate multiple en face image averaging on OCTA images of the choriocapillaris.Design, setting, and participantsObservational, cross-sectional case series at a referral institutional practice in Los Angeles, California. From the original cohort of 21 healthy individuals, 17 normal eyes of 17 participants were included in the study. The study dates were August to September 2016.ExposuresAll participants underwent OCTA imaging of the macula covering a 3 × 3-mm area using OCTA software (Cirrus 5000 with AngioPlex; Carl Zeiss Meditec). One eye per participant was repeatedly imaged to obtain 9 OCTA cube scan sets. Registration was first performed using superficial capillary plexus images, and this transformation was then applied to the choriocapillaris images. The 9 registered choriocapillaris images were then averaged. Quantitative parameters were measured on binarized OCTA images and compared with the unaveraged OCTA images.Main outcome and measureVessel caliber measurement.ResultsSeventeen eyes of 17 participants (mean [SD] age, 35.1 [6.0] years; 9 [53%] female; and 9 [53%] of white race/ethnicity) with sufficient image quality were included in this analysis. The single unaveraged images demonstrated a granular appearance, and the vascular pattern was difficult to discern. After averaging, en face choriocapillaris images showed a meshwork appearance. The mean (SD) diameter of the vessels was 22.8 (5.8) µm (range, 9.6-40.2 µm). Compared with the single unaveraged images, the averaged images showed more flow voids (1423 flow voids [95% CI, 967-1909] vs 1254 flow voids [95% CI, 825-1683], P < .001), smaller average size of the flow voids (911 [95% CI, 301-1521] µm2 vs 1364 [95% CI, 645-2083] µm2, P < .001), and greater vessel density (70.7% [95% CI, 61.9%-79.5%] vs 61.9% [95% CI, 56.0%-67.8%], P < .001). The distribution of the number vs sizes of the flow voids was skewed in both unaveraged and averaged images. A linear log-log plot of the distribution showed a more homogeneous distribution in the averaged images compared with the unaveraged images.Conclusions and relevanceMultiple en face averaging can improve visualization of the choriocapillaris on OCTA images, transforming the images from a granular appearance to a level where the intervascular spaces can be resolved in healthy volunteers.

Dataset Information

Accuracy and Reliability in Differentiating Retinal Arteries and Veins Using Widefield En Face OCT Angiography.

Publications

Accuracy and Reliability in Differentiating Retinal Arteries and Veins Using Widefield En Face OCT Angiography.

Similar Datasets

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