Relationship between Glaucoma and the Three-Dimensional Optic Nerve Head Related Structure

项目摘要 青光眼是全球第二大致盲原因，其特征是视神经损伤 导致视网膜神经节细胞死亡，并伴有视野丧失。视神经头(ONH) 是视神经纤维损伤的部位，在青光眼的发病机制和诊断中起着核心作用。 传统上，青光眼的诊断是基于ONH的眼底检查，它提供了以下信息 ONH的表面轮廓。然而，视神经损伤发生在更深的层面。随着用于三维(3D)视网膜成像的光学相干断层扫描(OCT)技术的发展，参数 来源于3DONH相关结构(例如，Bruch膜开口最小边缘宽度，乳头状部周围 视网膜神经纤维层厚度、视盘倾斜度等)为了更好地了解青光眼的发病机制， 并用于补充临床诊断。此外，对ONH生物力学的研究也表明 ONH在任何给定眼压水平下的应变水平取决于ONH的3D几何形状 相关结构。高应变水平被认为是导致视网膜神经节细胞损伤的原因之一。以前的研究 提示3DONH相关结构与青光眼发病机制相关，并具有重要意义 对青光眼的诊断。然而，到目前为止，一项使用临床数据来确定 目前尚未对青光眼进行3D ONH相关结构的研究。 我们建议研究3D ONH相关结构与青光眼的关系。 包括图像处理、计算力学和机器学习在内的综合技术。本项目的具体目标是：(1)从3DONH相关结构中提取特征并研究其含义 关于VF损耗模式(K99相)。(2)研究ONH应变场模式对青光眼的影响 (K99阶段)。(3)研究3D ONH相关特征对OCT诊断参数(R00时相)的影响。 (4)3D ONH相关结构特征的模型中心视力损失(R00阶段)。总的来说，这些研究将为青光眼的结构-功能关系提供新的见解和视角，并建立 眼部解剖的视网膜神经纤维层轮廓的具体规范，将促进我们目前的理解 研究青光眼的发病机制，提高青光眼的诊断水平。我们的研究具有很高的临床相关性，可以 有可能转化为临床实践，以便更好地诊断、监测和治疗青光眼。 通过建议的研究和培训计划，申请者将建立坚实的眼科知识基础，并进一步提高他在数学建模和数据科学方面的专业知识。该项目将提供 关键的培训机会，进一步提高申请人的能力，成为一名独立的计算视觉科学家在眼科。

Project Summary Glaucoma is the second leading cause of blindness globally, and is characterized by optic nerve damage that leads to the death of retinal ganglion cells with accompanying visual field (VF) loss. The optic nerve head (ONH) is the site of injury to the optic nerve fibers and plays a central role in glaucoma pathogenesis and diagnosis. Traditionally, glaucoma is diagnosed based on fundus inspection of the ONH, which provides information about the surface contour of the ONH. However, the optic nerve damage occurs in the deeper layers. With the development of optical coherence tomography (OCT) techniques for three-dimensional (3D) retinal imaging, parameters derived from the 3D ONH related structure (e.g., Bruch's membrane opening minimum rim width, peripapillary retinal nerve fiber layer thickness, disc tilt etc.) have been studied to better understand glaucoma pathogenesis, and are used to supplement clinical diagnosis. In addition, studies of the ONH biomechanics have also shown that the strain level at the ONH at any given intraocular pressure level depends on the 3D geometry of the ONH related structure. A high strain level is hypothesized to contribute to retinal ganglion cell injury. Previous research has suggested that the 3D ONH related structure is correlated to glaucoma pathogenesis and critically important to glaucoma diagnosis. However, to date, a systematic study using clinical data to determine the impact of the 3D ONH related structure on glaucoma has not been conducted. We propose to study the relationship between the 3D ONH related structure and glaucoma with a diverse set of combined techniques including image processing, computational mechanics and machine learning. The specific aims of this project are to: (1) Derive features from the 3D ONH related structure and study their implications on VF loss patterns (K99 Phase). (2) Investigate the impact of the strain field patterns at the ONH on glaucoma (K99 Phase). (3) Study the effect of the 3D ONH related features on OCT diagnostic parameters (R00 Phase). (4) Model central vision loss from the 3D ONH related structural features (R00 Phase). Collectively, these studies will provide new insights and perspectives into the structure-function relationships in glaucoma and establish ocular anatomy specific norms of retinal nerve fiber layer profiles, which will advance our current understanding of glaucoma pathogenesis and improve glaucoma diagnosis. Our research is of high clinical relevance and can be potentially translated into clinical practice for better glaucoma diagnosis, monitoring and treatment. Through the proposed research and training plans, the applicant will build a solid knowledge base in ophthalmology and further improve his expertise in mathematical modeling and data science. This project will provide critical training opportunities to further enhance the applicant's capabilities to become an independent computational vision scientist in ophthalmology.