Glaucoma Service, Department of Ophthalmology and Visual Sciences, Federal University of São Paulo, São Paulo, Brazil,
Glaucoma Unit, Hospital Medicina dos Olhos, Osasco, Brazil,
Ophthalmic Res. 2021;64(1):108-115. doi: 10.1159/000508952. Epub 2020 May 26.
New technologies have been developed in order to decrease interpersonal influence and subjectivity during the glaucoma diagnosis process. Enhanced depth imaging spectral-domain OCT (EDI OCT) has turned up as a favorable tool for deep optic nerve head (ONH) structures assessment.
A prospective cross-sectional study was conducted to compare the diagnostic performance of different EDI OCT-derived parameters to discriminate between eyes with and without glaucoma.
The following ONH parameters were measured: lamina cribrosa (LC) thickness and area; prelaminar neural tissue (PLNT) thickness and area; average Bruch's membrane opening - minimum rim width (BMO-MRW), superior BMO-MRW, and inferior BMO-MRW. Peripapillary retinal nerve fiber layer (pRNFL) thickness was also obtained.
Seventy-three participants were included. There were no significant differences between AUCs for average BMO-MRW (0.995), PLNT area (0.968), and average pRNFL thickness (0.975; p ≥ 0.089). However, AUCs for each of these 3 parameters were significantly larger than LC area AUC (0.701; p ≤ 0.001). Sensitivities at 80% specificity were: PLNT area = 92.3%, average BMO-MRW = 97.4%, and average pRNFL thickness = 94.9%.
Comparing the diagnostic performance of different EDI OCT ONH parameters to discriminate between eyes with and without glaucoma, we found better results for neural tissue-based indexes (BMO-MRW and PLNT area) compared to laminar parameters. In this specific population, these neural tissue-based parameters (including PLNT area, which was investigated by the first time in the present study) had a diagnostic performance comparable to that of the conventional pRNFL thickness protocol.
为了减少青光眼诊断过程中的人际影响和主观性，已经开发出新技术。增强深度成像谱域 OCT（EDI OCT）已成为评估深层视神经头（ONH）结构的有利工具。
进行了一项前瞻性的横断面研究，以比较不同 EDI OCT 衍生参数区分青光眼眼和非青光眼眼的诊断性能。
测量了以下 ONH 参数：筛板（LC）厚度和面积；前层神经组织（PLNT）厚度和面积；平均 Bruch 膜开口-最小边缘宽度（BMO-MRW）、上 BMO-MRW 和下 BMO-MRW。还获得了视盘周围视网膜神经纤维层（pRNFL）厚度。
共纳入 73 名参与者。平均 BMO-MRW（0.995）、PLNT 面积（0.968）和平均 pRNFL 厚度（0.975；p≥0.089）的 AUC 之间无显著差异。然而，这些 3 个参数中的每一个的 AUC 都显著大于 LC 面积 AUC（0.701；p≤0.001）。在 80%特异性时的灵敏度为：PLNT 面积=92.3%，平均 BMO-MRW=97.4%，平均 pRNFL 厚度=94.9%。
比较不同 EDI OCT ONH 参数的诊断性能以区分青光眼眼和非青光眼眼，我们发现基于神经组织的指标（BMO-MRW 和 PLNT 面积）的结果优于基于层的参数。在这个特定人群中，这些基于神经组织的参数（包括 PLNT 面积，这是本研究首次进行研究）的诊断性能与传统的 pRNFL 厚度方案相当。
