Automated Beta Zone Parapapillary Area Measurement to Differentiate Between Healthy and Glaucoma Eyes

自动测量视盘旁β区面积以区分健康眼和青光眼

阅读:1

Abstract

PURPOSE: To evaluate whether automated assessment of beta zone parapapillary atrophy (βPPA) area can differentiate between glaucomatous and healthy eyes of varying axial lengths (AL). DESIGN: Cross-sectional study. METHODS: βPPA was automatically identified in glaucoma and healthy eyes with enhanced-depth imaging optical coherence tomography (OCT) optic nerve head (ONH) radial B-scans. Associations with AL and the presence of glaucoma were assessed. Manually delineated βPPA on individual OCT ONH B-scans of 35 eyes from the Diagnostic Innovations in Glaucoma Study served to validate the automated method. RESULTS: One hundred fifty-three glaucoma eyes (mean ± standard deviation) (visual field mean deviation, -5.0 ± 6.4 dB and mean AL, 25.1 ± 1.1 mm) and 73 healthy eyes (visual field mean deviation, 0.1 ± 1.4 dB and mean AL, 24.1 ± 1.1 mm) were included. In multivariable analysis, larger βPPA area was significantly associated with a diagnosis of glaucoma after controlling for age, central corneal thickness, and AL. Moreover, in multivariable analysis, the odds of having glaucoma were doubled for each 0.2 mm(2) larger βPPA area. The age- and AL-adjusted area under the receiver operating characteristic curve (95% confidence interval) of βPPA area for differentiating between glaucoma and healthy eyes was 0.75 (0.68-0.81). Agreement for the location of the Bruch membrane opening and the location of retinal pigment epithelium tips was stronger between the automated technique and each individual observer than it was between the 2 observers. CONCLUSIONS: Larger βPPA area, as determined by automated OCT assessment, is significantly associated with a diagnosis of glaucoma, even after adjusting for age and AL, and may aid in differentiating healthy from glaucomatous eyes.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。