Optical coherence tomography angiography of retinal vascular diseases

2020 ◽  
pp. 269-283
Author(s):  
Rosa Lozada ◽  
Victor M. Villegas ◽  
Harry W. Flynn ◽  
Stephen G. Schwartz
2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Rodolfo Mastropasqua ◽  
Luca Di Antonio ◽  
Silvio Di Staso ◽  
Luca Agnifili ◽  
Angela Di Gregorio ◽  
...  

Purpose. To assess the ability of optical coherence tomography-angiography (OCT-A) to show and analyze retinal vascular patterns and the choroidal neovascularization (CNV) in retinal vascular diseases.Methods. Seven eyes of seven consecutive patients with retinal vascular diseases were examined. Two healthy subjects served as controls. All eyes were scanned with the SD-OCT XR Avanti (Optovue Inc, Fremont CA, USA). Split spectrum amplitude decorrelation angiography algorithm was used to identify the blood flow within the tissue. Fluorescein angiography (FA) and indocyanine green angiography (ICGA) with Spectralis HRA + OCT (Heidelberg Engineering GmbH) were performed.Results. In healthy subjects OCT-A visualized major macular vessels and detailed capillary networks around the foveal avascular zone. Patients were affected with myopic CNV (2 eyes), age-related macular degeneration related (2), branch retinal vein occlusion (BRVO) (2), and branch retinal artery occlusion (BRAO) (1). OCT-A images provided distinct vascular patterns, distinguishing perfused and nonperfused areas in BRVO and BRAO and recognizing the presence, location, and size of CNV.Conclusions. OCT-A provides detailed images of retinal vascular plexuses and quantitative data of pathologic structures. Further studies are warranted to define the role of OCT-A in the assessment of retinovascular diseases, with respect to conventional FA and ICG-A.


2020 ◽  
Author(s):  
Yih-Cherng Lee ◽  
Jian-Jiun Ding ◽  
Ling Yeung ◽  
Tay-Wey Lee ◽  
Chia-Jung Chang ◽  
...  

AbstractOptical coherence tomography angiography is a noninvasive imaging modality to establish the diagnosis of retinal vascular diseases. However, angiography images are significantly interfered if patients jitter or blink. In this study, a novel retinal image analysis method to accurately detect blood vessels and compensate the effect of interference was proposed. We call this the patch U-Net compensation (PUC) system, which is based on the famous U-Net. Several techniques, including a better training mechanism, direction criteria, area criteria, gap criteria, and probability map criteria, have been proposed to improve its accuracy. Simulations show that the proposed PUC achieves much better performance than state-of-art methods.


2017 ◽  
Vol 27 (4) ◽  
pp. e129-e133 ◽  
Author(s):  
Marco A. Gonzalez ◽  
Diana Shechtman ◽  
Jay M. Haynie ◽  
Leo Semes

Purpose Idiopathic macular telangiectasia type 2 (IMT2) is a bilateral acquired maculopathy, with a spectrum of clinical presentations associated with inner retinal telangiectatic vascular anomalies. Cases often are underdiagnosed or misdiagnosed. Current diagnostic modalities such as spectral-domain optical coherence tomography (SD-OCT) and fluorescein angiography (FA) are valuable to the understanding of the clinicopathology. More recently, optical coherence tomography angiography (OCTA), as an emerging noninvasive technology, has been shown to be particularly useful in the assessment and management of IMT2. Methods Three clinical cases of IMT2 are discussed. Clinical presentation, fundus photography, FA, SD-OCT, and OCTA are presented. Each case illustrates variable presentation, staging, and associated findings related to IMT2. Results Optical coherence tomography angiography provides additional value when paired with traditional multimodal imaging in the assessment and management of IMT2. Conclusions These cases present an opportunity to demonstrate the features of the OCTA in the evaluation of vascular diseases such as IMT2. Additionally, these examples emphasize the critical importance of OCTA in the clinical diagnosis and management of IMT2.


2018 ◽  
Vol 8 (2) ◽  
pp. 135-150 ◽  
Author(s):  
Anthony J. Deegan ◽  
Wendy Wang ◽  
Shaojie Men ◽  
Yuandong Li ◽  
Shaozhen Song ◽  
...  

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