Diagnosis and Monitoring of Glaucoma with Optical Coherence Tomography Angiography

项目摘要 光学相干断层扫描血管造影术（OCTA）是一种非侵入性的三维成像方法， 可视化和量化整个视网膜的微血管。拟议的研究评价了临床效用 OCTA测量值与视神经乳头（ONH）、视网膜 神经纤维层（RNFL）和黄斑使用当前临床成像标准测量，光谱域 光学相干断层扫描（OCT）用于预测和检测疑似青光眼患者的疾病进展， 青光眼患者。我们和其他人的研究表明，视网膜表面血管密度 ONH区域和黄斑中的血管密度（由血管组成的测量面积的比例）在开放性视网膜病变中较低。 角型青光眼（OAG）的眼睛比健康的眼睛。此外，诊断准确性随着增加而提高。 疾病严重程度。我们实验室的研究表明，血管密度的诊断准确性是 类似于OCT测量的RNFL厚度，并且视网膜区域中的血管密度降低 与局部视野（VF）缺陷相关。这些横截面结果强烈表明，OCTA 测量反映了与OAG的病理生理学相关的组织损伤。在一项纵向研究中， 黄斑血管密度的平均变化率在OAG眼中明显快于 青光眼怀疑或健康的眼睛。最后，最近的结果表明， OCTA测量的组合可以改善健康和青光眼眼睛的分类， 标准仪器测量，以及OCTA的深度学习分析。目前的研究 提供了一个独特的机会，以扩大纵向OCTA数据，已经收集了480 眼睛种族多样性的个人长达10年，以调查血管密度随时间的变化， 可疑青光眼和OAG眼，并将其与其他成像方式进行比较。本研究的目的是1） 为了更好地理解健康人群中OCTA和OCT测量值随时间的相对变化， 患病的眼睛，以更准确地识别真正的疾病相关的变化和2）提高我们的理解， 使用基于统计和深度学习的多因素分析， 模态OCTA和OCT测量。建议的研究将加强我们对年龄的了解， 血管密度和视网膜组织厚度的视网膜相关变化使我们能够预测和检测 更准确地改变，从而可能减缓进展速度，从而降低 视力相关的生活质量下降，包括失明。

Project Summary Optical coherence tomography angiography (OCTA) is a non-invasive, 3-dimensional imaging method to visualize and quantify microvasculature throughout the retina. The proposed study evaluates the clinical utility of OCTA measurements compared to standard structural measurements of the optic nerve head (ONH), retinal nerve fiber layer (RNFL) and macula measured using the current clinical imaging standard, spectral domain optical coherence tomography (OCT) to predict and detect progression of disease in glaucoma suspects and glaucoma patients. Our research, and that of others, has shown that superficial retinal vessel density (proportion of measured area composed of blood vessels) in the ONH region and macula is less dense in open angle glaucoma (OAG) eyes than in healthy eyes. Moreover, diagnostic accuracy is improved with increasing disease severity. Research from our laboratory suggests that the diagnostic accuracy of vessel density is similar to that of OCT-measured RNFL thickness, and that vessel density is reduced in retinal regions associated with localized visual field (VF) defects. These cross-sectional results strongly suggest that OCTA measurements reflect damage to tissues relevant to the pathophysiology of OAG. In a longitudinal study, the mean rate of change in macula vessel density was shown to be significantly faster in OAG eyes than in glaucoma suspect or healthy eyes. Finally, recent results indicate that shallow machine learning analyses of combinations of OCTA measurements can improve classification of healthy and glaucoma eyes compared to standard instrument measurements as can deep learning analyses of OCTA enface images. The current study provides a unique opportunity to extend the longitudinal OCTA data that has already been collected from 480 eyes racially diverse individuals for up to 10 years to investigate vessel density change over time in healthy, glaucoma suspect and OAG eyes, and to compare it to other imaging modalities. The aims of this study are 1) to improve our understandingof the relative change over time of OCTA and OCT measurements in healthy and diseased eyes to identify true disease-related change more accurately and 2) to improve our understanding of the risk of developing glaucomatous progression using statistical and deep learning-based analyses of multi- modal OCTA and OCT measurements. The proposed studies will enhance our understanding of age and glaucoma-related change in vessel density and retinal tissue thickness allowing us to predict and detect change more accurately, thus possibly slowing the rate of progression and consequently reducing the risk of reduction of vision related quality of life, including blindness.