Assessing Photoreceptor Structure and Function in Normal and Diseased Retinae

抽象的。 视力丧失是一个重大的健康问题，既可能是遗传的，也可能是后天的。工具用于 对人类视网膜的非侵入性评估已经以令人难以置信的速度增长，现在提供了这个机会 单电池分辨率的探头结构和功能。这些工具是推动我们理解 人类视觉在健康和疾病方面的极限，以及提高我们开发和评估新奇事物的能力 视力丧失患者的治疗策略。我们研究计划的长期目标仍然是 开发和传播敏感、非侵入性、高分辨率的技术来评估光感受器 结构和功能。在过去的14年里，我们已经在健康的人身上做了这项工作，也在那些患有 各种视网膜和全身疾病。以前，我们的重点是遗传性视网膜结构 视网膜退行性变，这是由于对这些疾病的遗传基础和 出现了针对这些疾病的新的治疗方法。随着基于自适应光学(AO)的出现 评估视网膜功能的工具我们处于独特的位置，可以扩展我们的研究并探索交叉点 人类视网膜中的光感受器结构和功能之间的关系。因此，这笔赠款的两个主要目标 阶段是评估视网膜/光感受器结构，因为它应用于视力限制的治疗潜力 并量化光感受器马赛克的破坏和视觉分辨率之间的关系。 我们组建了一个多学科研究小组，通过以下具体目标实现这些目标： 目的1)确定蓝视锥患者黄斑中心凹残余细胞群的特性 单色性(BCM)，目标2)在连续和 破坏视锥细胞镶嵌，目标3)量化有黄斑变性病史的个体的中心凹结构和功能 早产。正在使用的不同方法将提供对中心凹解剖和 光感受器的结构和视觉行为。这项工作有望通过填充 文献中的关键差距，并提供了针对BCM临床治疗的增强框架 了解早产对视网膜结构和功能的影响。我们的提案涉及研究 《2021-2025年NEI战略规划》《展望未来》中概述的需求、差距和机遇： 探索和利用生物测量和视觉过程理论模型之间的联系， 进行仔细的临床表型分析，以确定疾病的可量化生物标志物，以便更准确地 随着时间的推移，诊断、风险预测和治疗效果评估，开发和验证成像 识别临床疾病生物标志物的方法；加强疾病诊断、分类和 预测；以及标准化不同设备之间的量化指标，“和”扩大激励，以 验证和共享代码，开发易于在云中共享和/或操作的工具，并开发最佳 算法验证、文档编制、代码构建和注释的实践指南。

ABSTRACT . Vision loss represents a major health issue and can have both inherited and acquired origins. Tools for noninvasive assessment of the human retina have grown at an incredible pace and now afford the opportunity probe structure and function with single-cell resolution. These tools are central to advancing our understanding of the limits of human vision in health and disease as well improving our ability to develop and evaluate novel therapeutic strategies for patients with vision loss. The long-term goal of our research program remains to develop and disseminate sensitive, noninvasive, high-resolution techniques to assess photoreceptor structure and function. Over the past 14 years we have done this in healthy individuals as well as those with a wide range of retinal and systemic diseases. Previously, our focus has been on retinal structure in inherited retinal degenerations, owing to improved understanding of the genetic basis of these conditions and the emergence of novel therapeutic approaches for these conditions. With the advent of adaptive optics (AO) based tools for assessing retinal function we are uniquely positioned to expand our studies and probe the intersection between photoreceptor structure and function in the human retina. As such, the two major goals for this grant period are to evaluate retinal/photoreceptor structure as it applies to therapeutic potential in vision-limiting pathology and quantify the relationship between disruptions in the photoreceptor mosaic and visual resolution. We have assembled a multidisciplinary research team to achieve these goals through the following specific aims: Aim 1) Determine the identity of the remnant cell population in the fovea of individuals with blue cone monochromacy (BCM), Aim 2) Probe the link between cone spacing and AO-corrected acuity in contiguous and disrupted cone mosaics, and Aim 3) Quantify foveal structure and function in individuals with a history of premature birth. The diverse approaches being utilized will provide insight into the link between foveal anatomy, photoreceptor topography, and visual behavior. This work is expected to have a positive clinical impact by filling critical gaps in the literature and providing an enhanced framework for targeting clinical therapies in BCM as well as understanding the impact of prematurity on retinal structure and function. Our proposal addresses research needs, gaps, and opportunities outlined in the 2021-2025 NEI Strategic Plan, “Vision for the Future”: “Explore and exploit connections between biological measurements and theoretical models of visual processes,” “Conduct careful clinical phenotyping to identify quantifiable biomarkers of disease to allow for more accurate diagnosis, risk prediction, and evaluation of treatment efficacy over time,” “Develop and validate imaging methods for identifying clinical disease biomarkers; for enhancing disease diagnosis, classification, and prediction; and for standardizing quantitative metrics among different devices,” and “Expand incentives to validate and share code, develop tools that are readily shared and/or operated in the cloud, and develop best practice guidelines for algorithm validation, documentation, code construction, and commenting.”