Yamada N, Mills R P, Leen M M, Emond M J, Reynolds A C, Stanford D C
Department of Ophthalmology, University of Washington, Seattle 98195-6485, USA.
J Glaucoma. 1997 Oct;6(5):279-87.
The purpose of this study was to identify areas of the optic disc showing high variability of repeated depth measurements, and to minimize the effect of baseline variability in interpretation of possible change over time using the Glaucoma-Scope.
Seventy-four eyes from 70 subjects were analyzed with the Glaucoma-Scope. Three images were obtained on each of two separate sessions during the same day. At each location, the mean depth of the three images for each session was calculated to create a "baseline image." A contour map of standard deviation (SD) values at each topographic location was created for each subject reflecting local variability at different parts of the disc. The contour map and disc photograph were compared to determine what photographic features predicted high variability. A modified two-sample t-test was used at each topographic location to obtain p-values for the likelihood that a difference in mean depth between sessions was attributable to measurement variability alone.
Contour plots of SD for most subject eyes showed high variability in steeply sloped areas of the disc and along large blood vessels, with low variability near the cup center. The use of probability plots for significance of depth changes between test sessions automatically accounted for increased pointwise variability. The proportion of topographic locations showing statistically significant change but attributable to chance variation when no true change has occurred approximated the predicted proportion based on our modified t-test model.
A contour map of standard deviations of depth based on Glaucoma-Scope baseline images can identify areas of the disc with high variability. Statistical methods such as probability maps that account for local variability in the baseline image may be helpful in distinguishing true change from artefactual change over time.
本研究的目的是识别视盘上重复深度测量显示出高变异性的区域，并在使用青光眼镜解释随时间可能发生的变化时，尽量减少基线变异性的影响。
使用青光眼镜对70名受试者的74只眼睛进行分析。在同一天的两个不同时间段，每个时间段获取三张图像。在每个位置，计算每个时间段三张图像的平均深度，以创建一个“基线图像”。为每个受试者创建每个地形位置的标准差（SD）值的等高线图，反映视盘不同部位的局部变异性。将等高线图和视盘照片进行比较，以确定哪些照片特征预示着高变异性。在每个地形位置使用改良的双样本t检验，以获得各时间段平均深度差异仅归因于测量变异性的可能性的p值。
大多数受试者眼睛的SD等高线图显示，视盘陡坡区域和大血管沿线变异性高，杯中心附近变异性低。使用概率图来检验测试时间段之间深度变化的显著性，自动考虑了逐点变异性的增加。在没有真正变化时，显示出统计学显著变化但归因于偶然变异的地形位置比例接近基于我们改良t检验模型预测的比例。
基于青光眼镜基线图像的深度标准差等高线图可以识别视盘上变异性高的区域。考虑基线图像中局部变异性的统计方法，如概率图，可能有助于区分随时间的真正变化和人为变化。
