Department of Ophthalmology, University of Bonn, Ernst-Abbe-Str. 2, Bonn, Germany.
GRADE Reading Center, Ernst-Abbe-Str. 2, Bonn, Germany.
Sci Rep. 2019 Jul 31;9(1):11132. doi: 10.1038/s41598-019-47565-y.
Spatially-resolved mapping of rod- and cone-function may facilitate monitoring of macular diseases and serve as a functional outcome parameter. However, mesopic and dark-adapted two-color fundus-controlled perimetry (FCP, also called "microperimetry") constitute laborious examinations. We have devised a machine-learning-based approach to predict mesopic and dark-adapted (DA) retinal sensitivity in eyes with neovascular age-related macular degeneration (nAMD). Extensive psychophysical testing and volumetric multimodal retinal imaging data were acquired including mesopic, DA red and DA cyan FCP, spectral-domain optical coherence tomography and confocal scanning laser ophthalmoscopy infrared reflectance and fundus autofluorescence imaging. With patient-wise leave-one-out cross-validation, we have been able to achieve prediction accuracies of (mean absolute error, MAE [95% CI]) 3.94 dB [3.38, 4.5] for mesopic, 4.93 dB [4.59, 5.27] for DA cyan and 4.02 dB [3.63, 4.42] for DA red testing. Partial addition of patient-specific sensitivity data decreased the cross-validated MAE to 2.8 dB [2.51, 3.09], 3.71 dB [3.46, 3.96], and 2.85 dB [2.62, 3.08]. The most important predictive feature was outer nuclear layer thickness. This artificial intelligence-based analysis strategy, termed "inferred sensitivity", herein, enables to estimate differential effects of retinal structural abnormalities on cone- and rod-function in nAMD, and may be used as quasi-functional surrogate endpoint in future clinical trials.
空间分辨的杆状和锥状功能定位可能有助于监测黄斑疾病，并作为功能结果参数。然而，中值和暗适应双色眼底控制视野检查（FCP，也称为“微视野检查”）构成了费力的检查。我们已经设计了一种基于机器学习的方法来预测患有新生血管性年龄相关性黄斑变性（nAMD）的眼睛的中值和暗适应（DA）视网膜敏感性。获得了广泛的心理物理学测试和容积多模态视网膜成像数据，包括中值、暗适应红和暗适应蓝 FCP、光谱域光学相干断层扫描和共焦扫描激光检眼镜红外反射和眼底自发荧光成像。通过患者逐个的留一交叉验证，我们能够实现中值预测精度为 3.94 dB [3.38, 4.5]，暗适应蓝为 4.93 dB [4.59, 5.27]，暗适应红为 4.02 dB [3.63, 4.42]。部分添加患者特定的敏感性数据将交叉验证的 MAE 降低至 2.8 dB [2.51, 3.09]、3.71 dB [3.46, 3.96]和 2.85 dB [2.62, 3.08]。最重要的预测特征是外核层厚度。这种基于人工智能的分析策略，称为“推断敏感性”，可以估计视网膜结构异常对 nAMD 中锥状和杆状功能的差异影响，并可作为未来临床试验中的准功能替代终点。
