Institute of Physical Chemistry, Polish Academy of Sciences, Warsaw, Poland.
Department of Biomedical Engineering, Wroclaw University of Science and Technology, Wroclaw, Poland.
Invest Ophthalmol Vis Sci. 2019 Jul 1;60(8):3197-3203. doi: 10.1167/iovs.19-26963.
We introduce a new approach to assess the properties of corneal microstructure in vivo of healthy control and keratoconus eyes, based on statistical modeling of light intensity distribution from Scheimpflug images.
Twenty participants (10 mild keratoconus and 10 control eyes) were included in this study. Corneal biomechanics was assessed with a commercial Scheimpflug camera technology. Sets of 140 images acquired per measurement were exported for further analysis. For each image, after corneal segmentation, the stromal pixel intensities were statistically modeled, leading to parametric time-series that characterizes distributional changes during the measurement. From those time series, a set of 10 newly introduced parameters (microscopic parameters) was derived to discriminate normal from keratoconic corneas and further compared against clinical parameters available from the same measuring device, including central corneal thickness, IOP, and deformation amplitude (macroscopic parameters).
Biomechanical microscopic parameters extracted from statistical modeling of light intensity distribution were good discriminators between mild keratoconus and control eyes (Mann-Whitney U test, P < 0.05/N [Bonferroni]). The combination of available macroscopic and novel microscopic parameters was the most successful tool to differentiate between keratoconus and control eyes with no misclassifications.
For the first time to our knowledge, a set of parameters related to corneal microstructure, acquired from statistical modeling of light intensity distribution of dynamic Scheimpflug image acquisition was introduced. This novel approach showed the potential of combining macroscopic and microscopic corneal properties derived from a single clinical device to discriminate successfully between mild keratoconus and control eyes.
我们介绍了一种新方法，通过对 Scheimpflug 图像的光强分布进行统计建模，来评估健康对照和圆锥角膜眼中角膜微观结构的特性。
本研究纳入了 20 名参与者（10 名轻度圆锥角膜和 10 名对照眼）。使用商业 Scheimpflug 相机技术评估角膜生物力学。每次测量获取 140 张图像，用于进一步分析。对于每张图像，在角膜分割后，对基质像素强度进行统计建模，得到描述测量过程中分布变化的参数时间序列。从这些时间序列中，得出了一组 10 个新引入的参数（微观参数），用于区分正常和圆锥角膜的角膜，并与来自同一测量设备的临床参数（包括中央角膜厚度、眼压和变形幅度[宏观参数]）进行比较。
从光强分布的统计建模中提取的生物力学微观参数是区分轻度圆锥角膜和对照眼的良好判别指标（Mann-Whitney U 检验，P < 0.05/N [Bonferroni]）。可用宏观参数和新微观参数的组合是区分圆锥角膜和对照眼的最成功工具，没有错误分类。
据我们所知，这是首次介绍了一组与角膜微观结构相关的参数，这些参数是从动态 Scheimpflug 图像采集的光强分布的统计建模中获得的。这种新方法显示了从单个临床设备中提取的宏观和微观角膜特性相结合的潜力，可成功区分轻度圆锥角膜和对照眼。
