权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

Diagnostic Innovations in Glaucoma Study (DIGS): Glaucoma and High Myopia

青光眼研究 (DIGS) 的诊断创新：青光眼和高度近视

基本信息

批准号：
10686341
负责人：
LINDA M ZANGWILL
金额：
$ 66.75万
依托单位：
UNIVERSITY OF CALIFORNIA, SAN DIEGO
依托单位国家：
美国
项目类别：
财政年份：
2017
资助国家：
美国
起止时间：
2017-03-01 至 2027-08-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10686341
关键词：
3-Dimensional Address Age Aging American Society of Clinical Oncology Anterior Atrophic Biomechanics Blindness Blood Vessels Bruch&apos s basal membrane structure Clinical Cohort Studies Communities Complex Data Databases Detection Diagnosis Diagnostic Disease Disease Management Dropout Eye Functional disorder Glaucoma Goals High Prevalence Image Individual Inner Plexiform Layer Japan Korea Lead Length Link Maps Measures Modeling Morphology Myopia Open-Angle Glaucoma Optic Disk Optic Nerve Optical Coherence Tomography Papillary Patients Pattern Persons Phenotype Population Predisposition Prevalence Research Retina Risk Scanning Science Scotoma Secure Statistical Methods Testing Texture Thick Thinness Vision research Visual Fields clinical biomarkers clinical care cloud based cohort data curation data pipeline data sharing deep learning deep learning algorithm deep learning model density design follow-up functional disability functional loss ganglion cell high risk improved innovation learning strategy macula model development multimodality novel patient oriented predictive modeling prevent retinal nerve fiber layer vascular factor

项目摘要

Project Summary The objective of this study, “Diagnostic Innovations in Glaucoma Study (DIGS): Glaucoma and High Myopia”, is to overcome barriers to the detection of open angle glaucoma (OAG) in individuals with high myopia (mypOAG). In 2010, there was an estimated 1.4 billion people worldwide with myopia and the prevalence is rapidly rising to an estimated 4.75 billion by 2050. Moreover, persons with high myopia are 2.5 times more likely to have OAG than those without high myopia. It is unclear why myopia increases the risk of OAG, but it is likely related at least in part to biomechanical factors; longer axial lengths in myopic eyes may result in deformation of the lamina cribrosa, temporal displacement of Bruch's membrane, parapapillary changes and vascular factors; these all lead to increased susceptibility of the optic nerve to OAG damage. Given the higher prevalence of tilted discs and peripapillary atrophy in myopic eyes, the structural and functional tests that usually guide treatment decisions are of diminished value. This proposal will provide essential follow-up to establish best practices for patient-centered detection of OAG progression in the challenging high myopia population. Specifically, this proposal will 1) identify optic nerve head (ONH) 3D morphologic parameters from optical coherence tomography (OCT) scans (segmented and unsegmented) to differentiate between myopia eyes with and without progressive OAG; 2) optimize change detection using novel OCT features (e.g. texture and microvasculature) from wide field of view (WFOV) maps merged from individual ONH and macula scans; and 3) develop novel longitudinal and multimodal deep learning (DL) models to predict OAG progression. Most importantly, we will improve our understanding of the complex temporal relationship between structural, functional and microvascular age- and OAG related changes in a diverse cohort across the range of myopia. Specifically, in Specific Aim 1 (To improve our understanding of the complex relationship between ONH morphology and structural, functional, and microvascular change in the aging and OAG eye), we address several hypotheses related to the characterization of myopic ONH morphology in healthy eyes with and without high myopia. We hypothesize that ONH morphology is predictive of age – and OAG related structural, functional and microvascular changes and that it is predictive of fast progression. In Specific Aim 2 (To improve detection of OAG progression in myopic eyes using WFOV maps, unsegmented 3D volumes, ONH morphology), we address several hypotheses designed to detect and predict OAG progression using novel DL approaches. In Specific Aim 3, we will establish a cloud-based pipeline for data curation and computation that will facilitate secure DL model development and extensive data sharing with the vision research community.

项目摘要这项研究的目的是“青光眼诊断创新研究（DIGS）：青光眼和高度近视”，目的是克服高度近视患者开角型青光眼（OAG）检测的障碍（mypOAG）. 2010年，全球估计有14亿人患有近视，患病率为到2050年将迅速上升到47.5亿。此外，高度近视的人是其他人的2.5倍。高度近视组发生OAG的可能性高于非高度近视组。目前还不清楚为什么近视会增加OAG的风险，但它是可能至少部分与生物力学因素有关;近视眼的眼轴长度较长可能导致筛板变形、Bruch膜暂时移位、乳头旁改变和血管因素;这些都导致视神经对OAG损伤的易感性增加。鉴于较高的近视眼中椎间盘倾斜和视乳头周围萎缩的患病率，通常指导治疗决定的价值降低。这项建议将提供必要的后续行动，建立以患者为中心检测挑战性高度近视患者OAG进展的最佳实践人口具体地，该提议将1）从以下各项中识别视神经乳头（ONH）3D形态参数：光学相干断层扫描（OCT）扫描（分段和未分段）以区分近视具有和不具有渐进式OAG的眼睛; 2）使用新颖的OCT特征（例如纹理）优化变化检测和微脉管系统）的图像; 以及3）开发新的纵向和多模态深度学习（DL）模型来预测OAG进展。最重要的是，我们将提高我们对结构，在不同近视范围内的不同队列中，功能和微血管年龄和OAG相关变化。具体而言，在具体目标1中（为了提高我们对ONH与形态和结构，功能，和微血管的变化，在老化和OAG的眼睛），我们解决几个假设相关的表征近视ONH形态在健康的眼睛和没有高度近视。我们假设ONH形态是年龄和OAG相关结构的预测，功能和微血管变化，并且它是快速进展的预测。具体目标2（改善使用WFOV图、未分割3D体积、ONH检测近视眼的OAG进展形态学），我们提出了几个假设，旨在检测和预测OAG的进展，使用新的DL 接近。在具体目标3中，我们将建立一个基于云的数据管理和计算管道，将促进安全的DL模型开发和与视觉研究社区的广泛数据共享。