Towards Patient-Tailored Perimetry: Automated Perimetry Can Be Improved by Seeding Procedures With Patient-Specific Structural Information
Towards Patient-Tailored Perimetry: Automated Perimetry Can Be Improved by Seeding Procedures With Patient-Specific Structural Information
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DOI：
10.1167/tvst.2.4.3
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发表时间：
2013-04-01
影响因子：
3
通讯作者：
Turpin, Andrew
中科院分区：
文献类型：
--
作者：
Denniss, Jonathan;McKendrick, Allison M.;Turpin, Andrew
目的：探讨患者特异性先验信息的性能，例如，从结构成像，在改善周边手术。方法：采用计算机模拟方法确定序列检验（ZEST）的误差分布和呈现次数。序列检验是一种贝叶斯方法，其先验分布以结构的阈值预测为中心。Structure-ZEST （SZEST）在单一位置进行了试验，真实阈值和预测阈值的组合在1到35 dB之间，并与瑞典交互式阈值算法（SITA） （Full-Threshold， FT）的变异性相似的标准程序进行了比较。青光眼视野的临床试验（n = 163，中位平均偏差-1.8 dB， 90%范围+2.1至-22.6 dB）也比较了两种技术。结果：对于单个位置，当结构预测在真实灵敏度的+/- 9 dB范围内时，SZEST通常优于FT，具体取决于响应误差。在受损部位，平均绝对误差降低了0.5 ~ 1.8 dB，阈值估计的SD降低了1.2 ~ 1.5 dB， SZEST的表现减少了2 ~ 4次（29% ~ 41%）。在整个视野范围内，增益较小（SZEST，平均绝对误差：降低0.5至1.2 dB，阈值估计SD：降低0.3至0.8 dB， 1[17%]减少呈现）。SZEST的90%复测限在动态范围内比ft的中位数窄1至3 dB，并且更加一致（四分位数范围窄2至8 dB）。结论：尽管对阈值的结构预测不精确，但在青光眼中植入贝叶斯视距测量程序可以减少视距测量的测试变异性。翻译相关性：结构数据可以减少当前周边测量技术的可变性。强结构-功能关系不是必需的，但是，为了实现增益，结构必须在+/- 9 dB内预测功能。
Purpose: To explore the performance of patient-specific prior information, for example, from structural imaging, in improving perimetric procedures.Methods: Computer simulation was used to determine the error distribution and presentation count for Structure-Zippy Estimation by Sequential Testing (ZEST), a Bayesian procedure with prior distribution centered on a threshold prediction from structure. Structure-ZEST (SZEST) was trialled for single locations with combinations of true and predicted thresholds between 1 to 35 dB, and compared with a standard procedure with variability similar to Swedish Interactive Thresholding Algorithm (SITA) (Full-Threshold, FT). Clinical tests of glaucomatous visual fields (n = 163, median mean deviation -1.8 dB, 90% range +2.1 to -22.6 dB) were also compared between techniques.Results: For single locations, SZEST typically outperformed FT when structural predictions were within +/- 9 dB of true sensitivity, depending on response errors. In damaged locations, mean absolute error was 0.5 to 1.8 dB lower, SD of threshold estimates was 1.2 to 1.5 dB lower, and 2 to 4 (29%-41%) fewer presentations were made for SZEST. Gains were smaller across whole visual fields (SZEST, mean absolute error: 0.5 to 1.2 dB lower, threshold estimate SD: 0.3 to 0.8 dB lower, 1 [17%] fewer presentation). The 90% retest limits of SZEST were median 1 to 3 dB narrower and more consistent (interquartile range 2-8 dB narrower) across the dynamic range than those for FT.Conclusion: Seeding Bayesian perimetric procedures with structural measurements can reduce test variability of perimetry in glaucoma, despite imprecise structural predictions of threshold.Translational Relevance: Structural data can reduce the variability of current perimetric techniques. A strong structure-function relationship is not necessary, however, structure must predict function within +/- 9 dB for gains to be realized.