Diagnostic Performance for Detection of Glaucomatous Structural Damage Using Pixelwise Analysis of Retinal Thickness Measurements.

IF 5 2区 医学 Q1 OPHTHALMOLOGY
Hongli Yang, Juan Reynaud, Glen P Sharpe, Dawn Jennings, Cindy Albert, Trinity Holthausen, Xiue Jiang, Shaban Demirel, Steven L Mansberger, Marcelo T Nicolela, Stuart K Gardiner, Balwantray C Chauhan, Claude F Burgoyne, Brad Fortune
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Abstract

Purpose: To compare the diagnostic accuracy of thickness measurements of individual and combined macular retinal layers to discriminate 188 glaucomatous and 148 glaucoma suspect eyes from 362 healthy control (HC) eyes on a pixel-by-pixel basis.

Methods: For this retrospective study, we manually corrected the segmentations of posterior pole optical coherence tomography (OCT) scans to determine the thickness of the nerve fiber layer (NFL), ganglion cell layer (GCL), inner plexiform layer (IPL), the ganglion cell complex (GCC), and the total neural retina (TR). For each eye, the total number of pixels with thickness values less than the fifth percentile of the HC distribution was used to create a receiver operating characteristic (ROC) curve for each layer and for layer combinations.

Results: Using total abnormal pixel count criteria to discriminate glaucoma from HC eyes, the individual layers with the highest area under the ROC curve (AUC) were the NFL and GCL; IPL performance was significantly lower (P < 0.05). GCC had a significant higher AUC (94.3%) than individual the AUC of the NFL (92.3%) (P = 0.0231) but not higher than AUC of the GCL (93.4%) (P = 0.3487). The highest AUC (95.4%) and sensitivity (85.1%) at 95% specificity was found for the Boolean combination of NFL or GCL. The highest AUC is not significantly higher (P = 0.0882) than the AUC of the GCC but the highest sensitivity is significantly higher than the sensitivity of the GCC. This pattern was similar for discriminating between suspect and HC eyes (P = 0.0356).

Conclusions: Using pixel-based methods, the diagnostic accuracy of NFL and GCL exceeded that of IPL and TR. GCC had equivalent performance as NFL and GCL. The specific spatial locations within the posterior pole that exhibit best performance vary depending on which layer is being assessed. Recognizing this dependency highlights the importance of considering multiple layers independently, as they offer complementary information for effective and comprehensive diagnosis.

利用视网膜厚度测量的像素分析检测青光眼结构损伤的诊断性能。
目的:比较单个黄斑视网膜层和组合黄斑视网膜层厚度测量的诊断准确性,以逐个像素为基础从362只健康对照(HC)眼中区分出188只青光眼眼和148只青光眼疑似眼:在这项回顾性研究中,我们手动校正了后极光学相干断层扫描(OCT)的分割,以确定神经纤维层(NFL)、神经节细胞层(GCL)、内丛膜层(IPL)、神经节细胞复合体(GCC)和总神经视网膜(TR)的厚度。对于每只眼睛,厚度值小于 HC 分布第五百分位数的像素总数被用来创建每层和各层组合的接收者操作特征曲线(ROC):使用异常像素总数标准来区分青光眼和HC眼,ROC曲线下面积(AUC)最高的单层是NFL和GCL;IPL的表现明显较低(P<0.05)。GCC 的 AUC(94.3%)明显高于 NFL 的 AUC(92.3%)(P = 0.0231),但不高于 GCL 的 AUC(93.4%)(P = 0.3487)。在 95% 的特异性条件下,NFL 或 GCL 的布尔组合的 AUC(95.4%)和灵敏度(85.1%)最高。最高的 AUC 并未明显高于 GCC 的 AUC(P = 0.0882),但最高的灵敏度却明显高于 GCC 的灵敏度。这种模式在区分可疑眼和 HC 眼时也类似(P = 0.0356):结论:使用基于像素的方法,NFL 和 GCL 的诊断准确性超过了 IPL 和 TR。GCC 的性能与 NFL 和 GCL 相当。后极部表现出最佳性能的特定空间位置因所评估的层而异。认识到这种依赖性突出了独立考虑多层的重要性,因为它们为有效和全面的诊断提供了互补信息。
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来源期刊
CiteScore
6.90
自引率
4.50%
发文量
339
审稿时长
1 months
期刊介绍: Investigative Ophthalmology & Visual Science (IOVS), published as ready online, is a peer-reviewed academic journal of the Association for Research in Vision and Ophthalmology (ARVO). IOVS features original research, mostly pertaining to clinical and laboratory ophthalmology and vision research in general.
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