Peripapillary retinal nerve fiber layer assessment of spectral domain optical coherence tomography and scanning laser polarimetry to diagnose preperimetric glaucoma

利用光谱域光学相干断层扫描和扫描激光偏振仪评估视乳头周围视网膜神经纤维层,以诊断视野缺损前期青光眼

阅读:2

Abstract

PURPOSE: To compare the abilities of peripapillary retinal nerve fiber layer (RNFL) parameters of spectral domain optical coherence tomograph (SDOCT) and scanning laser polarimeter (GDx enhanced corneal compensation; ECC) in detecting preperimetric glaucoma. METHODS: In a cross-sectional study, 35 preperimetric glaucoma eyes (32 subjects) and 94 control eyes (74 subjects) underwent digital optic disc photography and RNFL imaging with SDOCT and GDx ECC. Ability of RNFL parameters of SDOCT and GDx ECC to discriminate preperimetric glaucoma eyes from control eyes was compared using area under receiver operating characteristic curves (AUC), sensitivities at fixed specificities and likelihood ratios (LR). RESULTS: AUC of the global average RNFL thickness of SDOCT (0.786) was significantly greater (p<0.001) than that of GDx ECC (0.627). Sensitivities at 95% specificity of the corresponding parameters were 20% and 8.6% respectively. AUCs of the inferior, superior and temporal quadrant RNFL thickness parameters of SDOCT were also significantly (p<0.05) greater than the respective RNFL parameters of GDx ECC. LRs of outside normal limits category of SDOCT parameters ranged between 3.3 and 4.0 while the same of GDx ECC parameters ranged between 1.2 and 2.1. LRs of within normal limits category of SDOCT parameters ranged between 0.4 and 0.7 while the same of GDx ECC parameters ranged between 0.7 and 1.0. CONCLUSIONS: Abilities of the RNFL parameters of SDOCT and GDx ECC to diagnose preperimetric glaucoma were only moderate. Diagnostic abilities of the RNFL parameters of SDOCT were significantly better than that of GDx ECC in preperimetric glaucoma.

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。