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利用角膜前、后表面像差和厚度空间分布检测亚临床圆锥角膜。

Detection of subclinical keratoconus by using corneal anterior and posterior surface aberrations and thickness spatial profiles.

机构信息

Department of Ophthalmology, Goethe-University, Frankfurt am Main, Germany.

出版信息

Invest Ophthalmol Vis Sci. 2010 Jul;51(7):3424-32. doi: 10.1167/iovs.09-4960. Epub 2010 Feb 17.

Abstract

PURPOSE. To assess the suitability of corneal anterior and posterior surface aberrations and thickness profile data for discrimination between eyes with early keratoconus (KC), fellow eyes of eyes with early KC, and normal eyes. METHODS. Thirty-two eyes (group 1) of 25 patients were newly diagnosed with KC; 17 eyes of 17 patients (group 2) were asymptomatic fellow eyes without clinical signs of KC. One hundred twenty-three healthy eyes of 69 patients were negative control eyes (group 3). Zernike coefficients from anterior and posterior surfaces, data from corneal thickness spatial profiles, and output values of discriminant functions based on wavefront and pachymetry data were assessed by receiver operating characteristic (ROC) curve analysis for their usefulness in discriminating between KC (groups 1, 2) eyes and control eyes. RESULTS. Vertical coma (C(3)(-1)) from the anterior surface was the coefficient with the highest ability to discriminate between groups 2 and 3 (area under the ROC curve [A(z)ROC] = 0.980; cutoff, -0.2 microm). For posterior wavefront coefficients and pachymetry data, A(z)ROC values were lower. Constructing discriminant functions from Zernike coefficients increased A(z)ROC values. The function containing first-surface data reached an A(z)ROC of 0.993; the functions containing posterior surface or pachymetry data had lower A(z)ROC values (0.932 and 0.903, respectively). The function with anterior, posterior, and pachymetry data reached an A(z)ROC of 1.0. CONCLUSIONS. Corneal wavefront and pachymetry data enabled highly accurate distinction of eyes with subclinical keratoconus from normal eyes. Posterior aberrations and thickness spatial profile data did not markedly improve discriminative ability over that of anterior wavefront data alone.

摘要

目的。评估角膜前表面和后表面像差及厚度轮廓数据用于区分早期圆锥角膜(KC)眼、早期 KC 眼的对侧眼和正常眼的适宜性。

方法。32 只眼(第 1 组)的 25 例患者被新诊断为 KC;17 只眼(第 2 组)的 17 例患者为无症状的对侧眼,无 KC 的临床体征。123 只眼(第 3 组)的 69 例健康患者为阴性对照组。通过接收者操作特征(ROC)曲线分析评估来自前表面和后表面的泽尼克系数、角膜厚度空间轮廓数据以及基于波前和厚度数据的判别函数的输出值,以评估其在区分 KC(第 1 组、第 2 组)眼和对照组眼的有用性。

结果。前表面垂直彗差(C(3)(-1))是区分第 2 组和第 3 组的最佳系数(ROC 曲线下面积[A(z)ROC]为 0.980;截断值,-0.2 μm)。对于后表面波前系数和厚度数据,A(z)ROC 值较低。使用泽尼克系数构建判别函数增加了 A(z)ROC 值。仅包含前表面数据的函数达到了 A(z)ROC 的 0.993;包含后表面或厚度数据的函数的 A(z)ROC 值较低(分别为 0.932 和 0.903)。包含前、后表面和厚度数据的函数达到了 A(z)ROC 的 1.0。

结论。角膜波前和厚度数据能够高度准确地区分亚临床圆锥角膜眼与正常眼。后表面像差和厚度空间轮廓数据对前表面波前数据单独的区分能力没有明显改善。

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