New Techniques for Measuring Volumetric Structural Changes in Glaucoma

测量青光眼体积结构变化的新技术

• 批准号: 7871151
• 负责人: Madhusudhanan Balasubramanian
• 金额: $ 8.99万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN DIEGO
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-01-01 至 2012-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7871151
• 关键词: 3-Dimensional; Address; Advisory Committees; Affect; Architecture; Area; Biology; Blindness; Brain imaging; Bruch' s basal membrane structure; Cardiology; Clinic; Clinical; Complex; Computational Science; Computational Technique; Computer Vision Systems; Confocal Microscopy; Data; Data Set; Detection; Development; Diagnosis; Diagnostic; Disease Progression; Doctor of Philosophy; Educational workshop; Elements; Engineering; Eye; Functional disorder; Gastroenterology; Generations; Genetic screening method; Glaucoma; Goals; Gold; Grant; Health; Image; Interferometry; Lasers; Lead; Left; Mathematics; Measurement; Measures; Medicine; Membrane; Mentors; Methodology; Modeling; Monitor; National Eye Institute; National Institute of Biomedical Imaging and Bioengineering; Onset of illness; Ophthalmology; Ophthalmoscopes; Ophthalmoscopy; Optic Disk; Optical Coherence Tomography; Optics; Outcome; Patients; Performance; Phase; Principal Investigator; Recommendation; Research; Research Personnel; Research Training; Resolution; Retinal; Scanning; Science; Sensitivity and Specificity; Structure; Surface; Techniques; Technology; Time; Training; Treatment Effectiveness; Treatment Protocols; Validation; Vision; Vision research; Visit; analytical tool; base; bioimaging; blood flow measurement; cancer imaging; computer framework; computer science; cost; diagnostic accuracy; improved; instrument; medical specialties; multidisciplinary; optic nerve disorder; optical imaging; prevent; programs; retinal nerve fiber layer; symposium; time use

DESCRIPTION (provided by applicant) This K99/R00 application supports additional research training in computational mathematics and computer vision which will enable Dr. Madhusudhanan Balasubramanian-the applicant, to become an independent multidisciplinary investigator in computational ophthalmology. Specifically, in the K99 training phase of this grant, Dr. Balasubramanian will train at UC San Diego under the direction of Linda Zangwill PhD, an established glaucoma clinical researcher in the Department of Ophthalmology, as well as a team of co- mentors, including, Dr. Michael Holst from the Department of Mathematics and co-director for the Center for Computational Mathematics, and co-director of the Computational Science, Mathematics and Engineering and Dr. David Kriegman from Computer Science and Engineering. Training will be conducted via formal coursework, hands-on lab training, mentored research, and progress review by an advisory committee, visiting collaborating researchers and regular attendance at seminars and workshops. The subsequent R00 independent research phase involves applying Dr. Balasubramanian's newly acquired computational techniques to the difficult task of identifying glaucomatous change over time from optical images of the optic nerve head and retinal nerve fiber layer. A documented presence of progressive optic neuropathy is the best gold standard currently available for glaucoma diagnosis. Confocal Scanning Laser Ophthalmoscope (CSLO) and Spectral Domain Optical Coherence Tomography (SD-OCT) are two of the optical imaging instruments available for monitoring the optic nerve head health in glaucoma diagnosis and management. Currently, several statistical and computational techniques are available for detecting localized glaucomatous changes from the CSLO exams. SD-OCT is a new generation ophthalmic imaging instrument based on the principle of optical interferometry. In contrast to the CSLO technology, SDOCT can resolve retinal layers from the internal limiting membrane (ILM) through the Bruch's membrane and can capture the 3-D architecture of the optic nerve head at a very high resolution. These high-resolution, high-dimensional volume scans introduce a new level of data complexity not seen in glaucoma progression analysis before and therefore, powerful (high-performance) computational techniques are required to fully utilize the high precision retinal measurements for glaucoma diagnosis. The central focus of this application in the K99 mentored phase of the application will be in 1) developing computational and statistical techniques for detecting structural glaucomatous changes in various retinal layers from the SDOCT scans, and 2) developing a new avenue of research in glaucoma management where in strain in retinal layers will be estimated non-invasively to characterize glaucomatous progression. In the R00 independent phase, the specific aims focus on developing 1) statistical and computational techniques for detecting volumetric glaucomatous change over time using 3-D SD-OCT volume scans and 2) a computational framework to estimate full-field 3-D volumetric strain from the standard SD-OCT scans. PUBLIC HEALTH RELEVANCE: Detecting the onset and progression of glaucomatous changes in the eye is central to glaucoma diagnosis and management. This multidisciplinary project focuses on developing powerful (high-performance) computational, mathematical, and statistical techniques for detecting volumetric glaucomatous changes from the Confocal Scanning Laser Ophthalmoscopy (CSLO) scans and volumetric Spectral Domain Optical Coherence Tomography (SD-OCT) scans of the optic nerve head. In addition, the Principal Investigator of this proposal will receive extensive training in the areas of computational mathematics and computer vision to augment and strengthen his multidisciplinary expertise essential to execute the proposed specific aims.

描述（由申请人提供）此K99/R 00申请支持计算数学和计算机视觉方面的额外研究培训，这将使申请人Madhusudhanan Balasubramanian博士成为计算眼科学的独立多学科研究者。具体而言，在该补助金的K99培训阶段，Balasubramanian博士将在加州大学圣地亚哥分校接受培训，指导者是眼科系的青光眼临床研究员琳达·赞格威尔博士以及一个共同导师团队，包括数学系的迈克尔·霍尔斯特博士和计算数学中心的共同主任，以及计算科学的共同主任，数学与工程系的大卫克里格曼博士和计算机科学与工程系的。培训将通过正式的课程，动手实验室培训，指导研究，并由咨询委员会，访问合作研究人员和定期参加研讨会和讲习班的进展审查进行。随后的R 00独立研究阶段涉及将Balasubramanian博士新获得的计算技术应用于从视神经乳头和视网膜神经纤维层的光学图像中识别随时间推移的昏迷变化的艰巨任务。 目前青光眼诊断的最佳金标准是进行性视神经病变。共焦扫描激光检眼镜（CSL 0）和光谱域光学相干断层扫描（SD-OCT）是两种可用于青光眼诊断和治疗中监测视神经乳头健康的光学成像仪器。目前，有几种统计和计算技术可用于检测CSL 0检查的局部脑水肿变化。SD-OCT是基于光学干涉原理的新一代眼科成像仪器。与CSL 0技术相比，SDOCT可以分辨从内界膜（ILM）到布鲁赫膜的视网膜层，并且可以以非常高的分辨率捕获视神经乳头的3D结构。这些高分辨率、高维体积扫描引入了青光眼进展分析中前所未有的新水平的数据复杂性，因此，需要强大的（高性能）计算技术来充分利用高精度视网膜测量进行青光眼诊断。本申请在K99指导阶段的中心重点是：1）开发计算和统计技术，用于从SDOCT扫描中检测各种视网膜层中的结构性青光眼变化; 2）开发青光眼管理研究的新途径，其中将以非侵入性方式估计视网膜层中的应变，以表征青光眼进展。在R 00独立阶段，具体目标集中于开发1）使用3-D SD-OCT体积扫描检测体积性昏迷随时间变化的统计和计算技术，以及2）根据标准SD-OCT扫描估计全场3-D体积应变的计算框架。 公共卫生相关性：检测眼内青光眼变化的发生和进展是青光眼诊断和治疗的核心。这个多学科项目的重点是开发强大的（高性能）计算，数学和统计技术，用于检测从共焦扫描激光检眼镜（CSLO）扫描和体积光谱域光学相干断层扫描（SD-OCT）扫描视神经乳头的体积神经胶质瘤的变化。此外，该提案的主要研究者将接受计算数学和计算机视觉领域的广泛培训，以增加和加强其执行拟议具体目标所必需的多学科专业知识。