Studying models and mechanisms of optic nerve diseases.

研究视神经疾病的模型和机制。

• 批准号: 8035065
• 负责人: DONALD C. HOOD
• 金额: $ 41.37万
• 依托单位: COLUMBIA UNIV NEW YORK MORNINGSIDE
• 依托单位国家: 美国
• 财政年份: 1977
• 资助国家: 美国
• 起止时间: 1977-08-01 至 2015-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8035065
• 关键词: Algorithms; Anatomy; Axon; Behavioral; Blindness; Data; Defect; Detection; Disease; Doctor of Medicine; Doctor of Philosophy; Early Diagnosis; Effectiveness; Eye; Frequencies; Funding; Ganglion Cell Layer; Glaucoma; Goals; Grant; Heart; Human; Individual; Iowa; Light; Linear Models; Measurement; Measures; Modeling; Nature; Nerve Fibers; Ophthalmologist; Optic Nerve; Optical Coherence Tomography; Patients; Perimetry; Procedures; Publishing; Relative (related person); Research; Retina; Retinal; Retinal Ganglion Cells; Structure; Study Section; Study models; Techniques; Technology; Testing; Thick; Uncertainty; Universities; Vision; Visual; Visual Fields; Visual evoked cortical potential; Work; base; behavior test; design; glaucoma test; improved; in vivo; macula; new technology; optic nerve disorder; programs; retinal nerve fiber layer; visual performance

DESCRIPTION (provided by applicant): Glaucoma is the second leading cause of blindness in the world, but, with proper treatment, blindness can be avoided in 90% of individuals with glaucoma. Proper treatment begins with the detection of glaucoma. Our long-term goal is to improve the detection of early glaucomatous damage, as well as the detection of progression of such damage. In this proposal, we focus in particular on the macular region, the most important retinal region for everyday visual performance. To better understand glaucomatous damage to the macula, as part of Aim 1, we test the hypothesis that early macular visual defects have a particular, arcuate, form when tested with behavioral tests [i.e. standard automated perimetry (SAP)]. We propose an anatomical framework to understand the basis of these macular arcuate defects. Based upon this framework, specific structural (anatomical) hypotheses are generated to understand the type of patients who may be susceptible to these defects. These hypotheses are tested using SAP, multifocal visual evoked potentials, and a relatively new noninvasive technique for in vivo measurement of the anatomy of the human retina and optic nerve, called frequency domain optical coherence tomography (fdOCT). Glaucoma damages retinal ganglion cells (RGC) and their axons. Most of the in vivo anatomical studies in humans have focused on the retinal nerve fiber layer (RNFL), which is made up of axon of the RGCs. As part of Aim 2, we focus on measuring RGC thickness directly using fdOCT technology. In particular, we test a simple linear model, which relates local SAP field loss to RGC loss. In addition, we test the hypothesis that RGC loss is a more sensitive measure than peripapillary RNFL thickness for detecting macular damage Finally, in Aim 3 we use our linear structure-function model to improve our ability to detect glaucomatous damage and its progression. In particular, we use the model to predict the progression of structural and functional damage in patients with glaucoma and to predict the relative effectiveness of different tests for detecting glaucoma. Further, our theoretical framework allows us to test hypotheses about why different tests of glaucoma may or may not agree. PUBLIC HEALTH RELEVANCE: Glaucoma is the second leading cause of blindness in the world, but, with early detection and proper treatment, blindness can be avoided in 90% of individuals with glaucoma. We seek to improve our ability to detect and understand early damage to the most important region of the eye for everyday functions, the macula.

描述（由申请人提供）：青光眼是世界上第二大失明原因，但是，通过适当的治疗，90% 的青光眼患者可以避免失明。正确的治疗始于青光眼的检测。我们的长期目标是改进早期青光眼损伤的检测以及此类损伤进展的检测。在这项提案中，我们特别关注黄斑区域，这是日常视觉表现最重要的视网膜区域。 为了更好地了解青光眼对黄斑的损害，作为目标 1 的一部分，我们测试了这样的假设：早期黄斑视觉缺陷在通过行为测试进行测试时具有特定的弓形形式[即标准自动视野检查（SAP）]。我们提出了一个解剖框架来理解这些黄斑弓形缺陷的基础。基于此框架，生成特定的结构（解剖）假设，以了解可能易受这些缺陷影响的患者类型。这些假设通过 SAP、多焦点视觉诱发电位以及一种相对较新的非侵入性技术（称为频域光学相干断层扫描 (fdOCT)）进行了测试，用于体内测量人类视网膜和视神经的解剖结构。 青光眼会损害视网膜神经节细胞 (RGC) 及其轴突。大多数人体体内解剖学研究都集中在视网膜神经纤维层 (RNFL)，它由 RGC 的轴突组成。作为目标 2 的一部分，我们专注于使用 fdOCT 技术直接测量 RGC 厚度。特别是，我们测试了一个简单的线性模型，该模型将局部 SAP 场损失与 RGC 损失联系起来。此外，我们测试了这样的假设：RGC 损失是比视盘周围 RNFL 厚度更敏感的测量方法，用于检测黄斑损伤。最后，在目标 3 中，我们使用线性结构函数模型来提高检测青光眼损伤及其进展的能力。特别是，我们使用该模型来预测青光眼患者结构和功能损伤的进展，并预测检测青光眼的不同测试的相对有效性。此外，我们的理论框架使我们能够检验关于为什么不同的青光眼测试可能一致或不一致的假设。 公众健康相关性：青光眼是世界上第二大失明原因，但是，通过早期发现和适当治疗，90% 的青光眼患者可以避免失明。我们寻求提高检测和了解眼睛日常功能最重要区域黄斑早期损伤的能力。