Improving rigor and reproducibility in adaptive optics ophthalmoscopy

项目总结 自适应光学(AO)眼底镜可通过以下方式非侵入性地显示显微视网膜结构 纠正每只眼睛独特的光学模糊，潜在地能够提高理解和 眼科疾病的管理。然而，缺乏标准化阻碍了这项技术在 多中心研究是测试新疗法的黄金标准。这件事的首要目标是 项目是提高AO眼底镜检查的严密性和重复性，以通过以下方式实现其潜力 三个具体目标： 目标1.开发、制造和分发校准的模型眼睛，允许图像的精确补偿 声光检眼镜的光学系统引起的失真和定标误差。这些模型眼睛将被设计成 可被其他人复制，并具有与普通人眼相似的光学特性。 目标2.开发使用全眼光学生物测量的成像协议和算法，以实现精确的 补偿由每只眼睛独特的光学系统引起的图像失真和定标误差。 目的3.收集无眼病受试者的光感受器马赛克图像的开放标准数据集， 并用它来检验两个假说。首先，杆状感光器以每年约1%的速度老化 视网膜的中央部分，在各种导致失明的情况下受到影响，如老年性黄斑 退化。第二，杆状感光器间距随着细胞损失而增加，抵消了密度的下降， 因此可用于检测疾病的早期征兆。图像的缩放和失真校正方法 来自AIMS 1和2的测试将提高我们执行这些测试的能力。 该项目的可交付成果将包括由AO视网膜成像社区提供的反馈和测试。 在这个项目结束时，AO眼底镜的用户将收到软件和校准的模型眼睛 精确的图像缩放和校正失真，以及在解剖上最真实和精确的缩放 光感受器标准数据集。建议的做法将促进视网膜成像的发展。 改善眼病早期诊断和管理的生物标记物，以及新疗法的测试。

PROJECT SUMMARY Adaptive optics (AO) ophthalmoscopy allows non-invasive visualization of microscopic retinal structures by correcting the optical blur that is unique to each eye, potentially enabling improving the understanding and management of eye disease. Lack of standardization, however, has hindered the adoption of this technology in the multi-center studies that are the gold standard for testing novel treatments. The overarching goal of this project is to improve rigor and reproducibility in AO ophthalmoscopy, in order to materialize its potential through three specific aims: Aim 1. To develop, build and distribute calibrated model eyes that allow precise compensation of image distortions and scaling errors caused by the optics of AO ophthalmoscopes. These model eyes will be designed to be reproducible by others and have similar optical properties to those of an average human eye. Aim 2. To develop imaging protocols and algorithms that use whole-eye optical biometry to allow precise compensation of image distortions and scaling errors caused by the unique optics of each eye. Aim 3. To collect an open normative dataset of photoreceptor mosaic images in subjects free of eye disease, and to use it to test two hypotheses. First, that rod photoreceptors are lost to aging at a rate of ~1% per year in the central portion of the retina that is affected in various leading blinding conditions, such as age-related macular degeneration. Second, that rod photoreceptor spacing increases with cell loss, offsetting the decline in density, and thus can be used for detecting early signs of disease. The image scaling and distortion correction methods from Aims 1 & 2 will improve our ability to perform these tests. The deliverables of this project will incorporate feedback and testing by the AO retinal imaging community. At this project’s conclusion, users of AO ophthalmoscopes will receive software and calibrated model eyes for precise image scaling and correction distortion, as well as the most anatomically truthful and accurately scaled photoreceptor normative dataset. The proposed practices will facilitate the development of retinal imaging biomarkers that improve early diagnosis and management of eye disease, as well as testing of novel therapies.