Underlying Microstructure of Parapapillary Deep-Layer Capillary Dropout Identified by Optical Coherence Tomography Angiography.

Abstract

Purpose To characterize the microstructure underlying the parapapillary deep-layer microvasculature dropout (MvD) identified by optical coherence tomography (OCT) angiography (OCTA) in eyes with primary open-angle glaucoma (POAG). Methods Parapapillary MvD was defined as a focal sectoral capillary dropout without any visible microvascular network identified in deep-layer en face images obtained using swept-source OCTA. The peripapillary microstructure was characterized in 188 POAG patients with MvD in the parapapillary deep layer. Twelve radial optic nerve images were obtained using swept-source OCT to examine the peripapillary structure and measure the juxtapapillary choroidal thickness (JPCT). The JPCT was also measured in 72 age-matched POAG eyes having β-zone parapapillary atrophy (PPA) without an MvD (control group). Results Microvascular dropouts were observed within the areas with a PPA involving the β-zone, γ-zone, and a mixture of both zones in 72, 57, and 59 eyes, respectively. Choroid of noticeable thickness was observed without obvious thinning in the PPA area when the MvD was associated with the β-zone. The JPCT was comparable between eyes with MvD and control eyes. There was no distinguishable feature in the microstructure of the γ-zone, regardless of whether it was associated with MvD. Conclusions Optical coherence tomography angiography showed MvDs in the parapapillary deep layers that were associated with both β- and γ-zones within the PPAs. The microstructure of PPAs with MvDs was not distinguishable from that of PPAs not associated with MvDs.

DOI: 10.1167/iovs.17-21440

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Cite this paper

@article{Lee2017UnderlyingMO, title={Underlying Microstructure of Parapapillary Deep-Layer Capillary Dropout Identified by Optical Coherence Tomography Angiography.}, author={Eun Ji Lee and Tae-Woo Kim and Seung Hyen Lee and Jung Ah Kim}, journal={Investigative ophthalmology & visual science}, year={2017}, volume={58 3}, pages={1621-1627} }