Gabriella Moraes MD, MSc , Robbert Struyven MD , Siegfried K. Wagner BMBCh, FRCOphth , Timing Liu BA , David Chong MBBChir , Abdallah Abbas iBSc, MBBS , Reena Chopra BSc , Praveen J. Patel MD, FRCOphth , Konstantinos Balaskas MD , Tiarnan D.L. Keenan BM BCh, PhD , Pearse A. Keane MD, FRCOphth
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引用次数: 0
摘要
目的将人工智能(AI)应用于黄斑OCT扫描,以分割和量化玻璃体内治疗新生血管性年龄相关性黄斑变性(AMD)过程中解剖和病理特征的体积变化.设计对Moorfields眼科医院AMD数据库中的OCT图像进行回顾性分析.方法查询Moorfields眼科医院新生血管性AMD数据库中接受抗血管内皮生长因子治疗的第一只和第二只眼睛,并在基线和12个月时进行OCT扫描。将随访扫描结果输入 AI 系统,研究不同时间点的 OCT 变量体积,并与基线体积组进行比较。主要结果测量研究了以下变量的体积输出:视网膜内积液、视网膜下积液、色素上皮脱落(PED)、视网膜下超反光物质(SHRM)、超反光灶、神经感觉视网膜和视网膜色素上皮。结果分析特征的平均体积从基线到4个月和12个月都显著下降,在第一次治疗和第二次治疗的眼睛中都是如此。反映渗出的病理特征,包括纯液体成分(视网膜内液和视网膜下液)和含有液体和纤维血管组织的病理特征(PED 和 SHRM),在 12 个月的治疗中表现出相似的反应。PED 和 SHRM 的平均体积在最初 2 个月的下降并不明显,但也很显著,在加载阶段后达到平稳,12 个月后变化很小。随着时间的推移,神经感觉视网膜和视网膜色素上皮的体积也逐渐减少,但减少幅度不如渗出性特征大。多个时间点的横断面分析表明,基线 OCT 导出的分段特征与随访时生物标志物的体积之间存在显著关联。展示某些OCT生物标记物如何随治疗而进展,以及治疗前视网膜形态对不同结构体积的影响,可为疾病机制提供新的见解,并有助于个性化治疗。数据将在未来的研究中公开。财务信息披露:专有或商业信息披露请参见本文末尾的脚注和披露。
Quantifying Changes on OCT in Eyes Receiving Treatment for Neovascular Age-Related Macular Degeneration
Purpose
Application of artificial intelligence (AI) to macular OCT scans to segment and quantify volumetric change in anatomical and pathological features during intravitreal treatment for neovascular age-related macular degeneration (AMD).
Design
Retrospective analysis of OCT images from the Moorfields Eye Hospital AMD Database.
Participants
A total of 2115 eyes from 1801 patients starting anti-VEGF treatment between June 1, 2012, and June 30, 2017.
Methods
The Moorfields Eye Hospital neovascular AMD database was queried for first and second eyes receiving anti-VEGF treatment and had an OCT scan at baseline and 12 months. Follow-up scans were input into the AI system and volumes of OCT variables were studied at different time points and compared with baseline volume groups. Cross-sectional comparisons between time points were conducted using Mann–Whitney U test.
Main Outcome Measures
Volume outputs of the following variables were studied: intraretinal fluid, subretinal fluid, pigment epithelial detachment (PED), subretinal hyperreflective material (SHRM), hyperreflective foci, neurosensory retina, and retinal pigment epithelium.
Results
Mean volumes of analyzed features decreased significantly from baseline to both 4 and 12 months, in both first-treated and second-treated eyes. Pathological features that reflect exudation, including pure fluid components (intraretinal fluid and subretinal fluid) and those with fluid and fibrovascular tissue (PED and SHRM), displayed similar responses to treatment over 12 months. Mean PED and SHRM volumes showed less pronounced but also substantial decreases over the first 2 months, reaching a plateau postloading phase, and minimal change to 12 months. Both neurosensory retina and retinal pigment epithelium volumes showed gradual reductions over time, and were not as substantial as exudative features.
Conclusions
We report the results of a quantitative analysis of change in retinal segmented features over time, enabled by an AI segmentation system. Cross-sectional analysis at multiple time points demonstrated significant associations between baseline OCT-derived segmented features and the volume of biomarkers at follow-up. Demonstrating how certain OCT biomarkers progress with treatment and the impact of pretreatment retinal morphology on different structural volumes may provide novel insights into disease mechanisms and aid the personalization of care. Data will be made public for future studies.
Financial Disclosure(s)
Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.