Ocular Blood Flow Imaging for Glaucoma Assessment

用于青光眼评估的眼血流成像

• 批准号: 10867973
• 负责人: Abhishek Rege
• 金额: $ 24.58万
• 依托单位: VASOPTIC MEDICAL, INC.
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-05-03 至 2025-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10867973
• 关键词: Administrative Supplement; Adult; Blindness; Blood flow; Clinic; Collection; Computer Vision Systems; Data; Data Analyses; Data Set; Diagnostic; Early Diagnosis; Eye; Future; Glaucoma; Goals; Hyperoxia; Image; Machine Learning; Myopia; Parents; Patients; Phase; Public Health; Refractive Errors; Research; Small Business Innovation Research Grant; Standardization; Techniques; Technology; Time; United States; biomarker identification; health goals; human subject; instrument; multimodality; parent grant; software development

ABSTRACT Our parent Phase II SBIR project seeks to develop effective diagnostic solutions for glaucoma, which is one of the leading causes of adult blindness in the United States and globally. Specific tasks undertaken are the collection of ocular blood flow data using our proprietary XyCAM technology from 150 human subjects in the glaucoma clinic at baseline and following hyperoxia, and the subsequent analysis of acquired data to identify biomarkers for early diagnosis of glaucoma. In particular, the plan is to evaluate the suitability of our approach in up to 30 subjects with a high degree of myopia (refractive error of more than 6 Diopters). We are requesting this administrative supplement to the parent grant to overcome certain data analysis challenges that have become apparent since we started the project. Notable among these is the need for registration of data acquired by the XyCAM to the data acquired by other instruments, and also to the data acquired by the XyCAM at other time points (such as post-hyperoxia) so that data analysis can be conducted at a regional level in a reliable and standardized manner. We propose to develop certain automated techniques by utilizing computer vision and machine learning approaches to support analyses of large volumes of data as will be collected during this study. In addition to these proposed activities facilitating project goals in the short term, we also anticipate that the developed software will prove useful more broadly in the future for multi-modal or longitudinal comparison of XyCAM-generated ocular blood flow data.

抽象的 我们的父阶段II SBIR项目旨在为青光眼开发有效的诊断解决方案， 这是美国和全球成人失明的主要原因之一。具体的 执行的任务是使用我们的专有Xycam收集眼血流数据 来自基线和高氧之后青光眼诊所中150名人类受试者的技术， 以及随后对获得的数据的分析，以识别生物标志物以早期诊断 青光眼。特别是，该计划是评估我们最多30个主题的方法的适用性 具有高度的近视度（超过6个屈光度的折射率）。我们要求这个 对父母赠款的行政补充，以克服某些数据分析挑战 自从我们启动该项目以来，已经变得显而易见。其中值得注意的是需要 XyCAM收购的数据注册到其他工具获得的数据，也是 XYCAM在其他时间点获得的数据（例如杂种后），以便数据 分析可以以可靠和标准化的方式在区域层面进行。我们建议 通过利用计算机视觉和机器学习来开发某些自动化技术 在本研究中将收集的大量数据分析的方法。在 除这些建议的活动外，还可以在短期内促进项目目标 未来开发的软件将在未来对多模式或 Xycam生成的眼流数据的纵向比较。