3D RNFL Structure And High-Resolution Perimetry For Assessing Glaucomatous Damage

7. 项目概要摘要 青光眼是可预防性失明的主要原因之一，目前可用的治疗方法还不能 足以阻止许多患者的病情进展。虽然人们对青光眼的生物学了解很多， 新治疗形式的开发受到三个障碍的阻碍： 正常眼中的神经节细胞数量，青光眼患者视野检查的受试者内变异性较高，以及 疾病进展速度缓慢。拟议的研究整合了神经建模和临床 研究开发诊断青光眼和评估青光眼进展的改进方法 失明。研究结果旨在改进临床试验和持续患者护理的措施，同时 同时提高对青光眼病理生理学的基础科学认识并提供 疾病过程的生物学研究指南。临床设备的创新使用将指导测试 定制系统和统计分析将利用结构性措施和功能性措施之间的协同作用 青光眼损伤。视网膜神经纤维层 (RNFL) 的高分辨率视网膜成像将在 青光眼患者使用定制的先进自适应光学扫描激光检眼镜 (AOSLO) 作为 以及定制使用谱域光学相干断层扫描 (SD-OCT)。高分辨率视野检查将 使用抗光学的定制刺激在视野的相应区域进行 影响传统视野检查的伪影。具体目标 1 将确定神经节细胞功能障碍在 与临床观察到的反射率相对应的受试者之间视力丧失量的差异 缺陷，并评估纵向变化。具体目标 2 将利用结构和 开发与 RNFL 信息动态交互的视野算法的功能措施 结构。具体目标 3 将开发显着提高楔形缺陷检测能力的方法， 传统视野测量法的采样率很低。

7. Project Summary Abstract Glaucoma is one of the leading causes of preventable blindness, and currently available treatments are not sufficient to halt progression in many patients. While much has been learned about the biology of glaucoma, development of new forms of treatment has been stymied by three barriers: high between-subject variability in ganglion cell number in normal eyes, high within-subject variability for perimetry in patients with glaucoma, and the slow rate of progression of the disease. The proposed research integrates neural modeling and clinical research to develop improved methods for diagnosing glaucoma and for assessing progression towards blindness. The results are intended to improve measures for both clinical trials and ongoing patient care, while at the same time improving basic science understanding of the pathophysiology of glaucoma and providing guidance for biological studies of the disease process. Innovative uses of clinical devices will guide testing with custom systems, and statistical analyses will utilize the synergy between structural and functional measures of glaucomatous damage. High-resolution retinal imaging of retinal nerve fiber layer (RNFL) will be performed on patients with glaucoma using a custom advanced adaptive optics scanning laser ophthalmoscope (AOSLO) as well as custom use of spectral domain optical coherence tomography (SD-OCT). High-resolution perimetry will be performed in corresponding regions of the visual field, using custom stimuli that are resistant to optical artifacts that affect conventional perimetry. Specific Aim 1 will determine the role of ganglion cell dysfunction in between-subject differences in the amount of visual loss corresponding to clinically observed reflectance defects, and assess longitudinal changes. Specific Aim 2 will utilize the synergy between structural and functional measures to develop perimetric algorithms that interact dynamically with information about RNFL structure. Specific Aim 3 will develop methods that dramatically improve the ability to detect wedge defects that are poorly sampled by conventional perimetry.