School of Optometry and Vision Science, University of Bradford, UK.
Ophthalmology Department, Leeds Teaching Hospitals NHS Trust, Leeds, UK.
Transl Vis Sci Technol. 2021 May 3;10(6):31. doi: 10.1167/tvst.10.6.31.
We present a subjective approach to detecting glaucomatous defects in enface images and assess its diagnostic performance. We also test the hypothesis that if reflectivity changes precede thickness changes in glaucoma there should be reduced correlation between the modalities in glaucoma compared to controls.
Twenty glaucoma participants and 20 age-matched controls underwent high-resolution OCT scans of one eye. 4 µm-thick enface slabs were constructed through the retina. Enface indices were depths of first gap in visible retinal nerve fiber bundles (RNFBs) and last visible bundle, subjectively evaluated in six sectors of a 3.5 mm circle around the optic disc. Retinal nerve fiber layer thickness (RNFLT) along the same circle was extracted at angles corresponding to enface indices. Between-group differences were tested by linear mixed models. Diagnostic performance was measured by partial receiver operating characteristic area (pAUC).
First gap and last visible bundle were closer to the inner limiting membrane in glaucoma eyes (both P < 0.0001). Enface indices showed excellent diagnostic performance (pAUCs 0.63-1.00), similar to RNFLT (pAUCs 0.63-0.95). Correlation between enface and RNFLT parameters was strong in healthy (r = 0.81-0.92) and glaucoma eyes (r = 0.73-0.80).
This simple subjective method reliably identifies glaucomatous defects in enface images with diagnostic performance at least as good as existing thickness indices. Thickness and reflectivity were similarly related in healthy and glaucoma eyes, providing no strong evidence of reflectivity loss preceding thinning. Objective analyses may realize further potential of enface OCT images in glaucoma.
Novel enface OCT indices may aid glaucoma diagnosis.
我们提出了一种在神经纤维层图像中检测青光眼缺陷的主观方法，并评估了其诊断性能。我们还测试了这样一个假设，即如果青光眼的反射率变化先于厚度变化，那么与对照组相比，青光眼患者的两种模态之间的相关性应该会降低。
20 名青光眼患者和 20 名年龄匹配的对照者接受了一只眼的高分辨率 OCT 扫描。通过视网膜构建了 4 µm 厚的神经纤维层图像。在视盘周围 3.5 mm 圆的六个扇区中主观评估可视视网膜神经纤维束（RNFB）的第一个间隙和最后一个可见束的深度。在相同的圆周上提取与神经纤维层图像指数相对应的神经纤维层厚度（RNFLT）。使用线性混合模型测试组间差异。通过部分接收器工作特征面积（pAUC）测量诊断性能。
在青光眼眼中，第一个间隙和最后一个可见束更接近内界膜（均 P < 0.0001）。神经纤维层图像指数表现出出色的诊断性能（pAUC 值为 0.63-1.00），与 RNFLT 相似（pAUC 值为 0.63-0.95）。在健康眼（r = 0.81-0.92）和青光眼眼中（r = 0.73-0.80），神经纤维层图像和 RNFLT 参数之间的相关性很强。
这种简单的主观方法可靠地识别了神经纤维层图像中的青光眼缺陷，其诊断性能至少与现有的厚度指数一样好。在健康眼和青光眼眼中，厚度和反射率之间的关系相似，这并没有提供反射率损失先于变薄的有力证据。客观分析可能会进一步挖掘神经纤维层 OCT 图像在青光眼诊断中的潜力。
