Nicolas J. Heckenlaible BS , Christopher B. Toomey MD, PhD , James T. Handa MD
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引用次数: 0
Abstract
Purpose
Automated retinal cell layer segmentation empowers OCT as a precise tool for characterizing morphologic features of retinal health throughout age-related macular degeneration (AMD) progression, particularly in advance of more visible biomarkers such as drusen and macular pigmentary changes. Few studies have examined OCT changes in eyes progressing from early to intermediate disease, or combined examinations of cell layer thickness, reflectivity, and heterogeneity. Therefore, this study analyzed OCTs from eyes progressing from early to intermediate AMD to identify changes in retinal morphology and reflectivity that may serve as biomarkers of early progression.
Design
Retrospective cohort study.
Participants
Patients ≥50 years with a diagnosis of AMD and with high-quality ipsilateral OCTs in both early and intermediate stage disease.
Methods
Fifty OCTs from 25 patients were automatically segmented using a previously validated artificial intelligence-driven algorithm. Changes in the mean and standard deviation of cell layer thickness and reflectivity with progression through stages were calculated for 90 retinal volumes with the help of a novel Python-based analysis tool.
Main Outcome Measures
The primary outcomes were significant changes to cell layer thickness, reflectivity, and heterogeneity with progression of AMD.
Results
With progression from early to intermediate disease, photoreceptor outer segments diffusely thinned. Within the ellipsoid zone, the fovea and parafovea were thinned with a simultaneous increase in thickness variability and a decrease in parafoveal reflectivity. The retinal pigment epithelium-Bruch’s membrane complex underwent diffuse thickening and increased thickness variability alongside a decrease in foveal and parafoveal reflectivity.
Conclusions
These findings correlate with the known histopathology of early AMD and identify measurable OCT trends through the earliest stages of disease.
Financial Disclosures
Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.
目的 自动视网膜细胞层分割使 OCT 成为一种精确的工具,用于描述老年性黄斑变性(AMD)进展过程中视网膜健康的形态特征,特别是在更明显的生物标志物(如色素沉着和黄斑色素变化)出现之前。很少有研究对从早期病变发展到中期病变的眼睛的 OCT 变化进行检查,或对细胞层厚度、反射率和异质性进行综合检查。因此,本研究分析了从早期AMD进展到中期AMD的眼睛的OCT,以确定视网膜形态和反射率的变化,这些变化可作为早期进展的生物标志物。方法使用先前验证过的人工智能驱动算法自动分割25名患者的50幅OCT。在基于 Python 的新型分析工具的帮助下,计算了 90 个视网膜体积的细胞层厚度和反射率的平均值和标准偏差随病程进展的变化。在椭圆区内,眼窝和眼窝旁变薄,同时厚度变异性增加,眼窝旁反射率下降。视网膜色素上皮-布氏膜复合体发生弥漫性增厚,厚度变异性增加,同时眼窝和眼底旁反射率下降。结论这些发现与已知的早期 AMD 组织病理学相关,并确定了疾病最早阶段可测量的 OCT 趋势。