An Integrated Software Platform for Accelerating Image-Driven Ophthalmic Research and Driving New Insights and Endpoints to the Clinic

一个集成软件平台，用于加速图像驱动的眼科研究并为临床带来新的见解和终点

• 批准号: 9908389
• 负责人: Eric L. Buckland
• 金额: $ 74.33万
• 依托单位: TRANSLATIONAL IMAGING INNOVATIONS, INC.
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-01 至 2022-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9908389
• 关键词: Address; Age related macular degeneration; Algorithms; Architecture; Artificial Intelligence; Automobile Driving; Biological Markers; Blindness; Clinic; Clinical; Clinical Research; Collection; Communication; Computer software; Consent; Data; Data Discovery; Data Science; Diabetic Retinopathy; Docking; Economics; Environment; Eye diseases; Foundations; Frustration; Funding; Glaucoma; Goals; Housing; Human Subject Research; Hybrids; Image; Imaging Device; Imaging technology; Influentials; Intervention; Investigation; Knowledge; Libraries; Mosaicism; Ontology; Ophthalmology; Ophthalmoscopy; Optical Coherence Tomography; Patients; Phase; Policies; Prevalence; Process; Reader; Research; Research Subjects; Savings; Science; Site; Small Business Innovation Research Grant; Speed; Strategic Planning; Structure; System; Technology; Translating; Translations; United States National Institutes of Health; Validation; Vision; Wisconsin; adaptive optics; algorithm development; algorithm training; application programming interface; biomarker development; biomarker discovery; clinical translation; cost; data access; data exchange; data integration; data sharing; data warehouse; deep learning; design; efficacy testing; experience; fighting; image processing; image reconstruction; imaging modality; imaging platform; imaging program; improved; innovation; insight; medical schools; microsystems; ocular imaging; process repeatability; programs; repository; retinal imaging; safety testing; software systems; structured data; tool; verification and validation; vision science

ABSTRACT More than 20 million patients suffer from age-related macular degeneration, diabetic retinopathy, or glaucoma. These degenerative eye diseases develop over decades, and their prevalence is increasing. Retinal imaging technologies such as optical coherence tomography and adaptive optics ophthalmoscopy are essential tools in the investigation and management of eye disease. New quantitative biomarkers derived from these and other imaging modalities are critical to the clinical translation of emerging ophthalmic innovations. However, biomarker development in the era of artificial intelligence requires large volumes of annotated images and transparent, reproducible processes, which places new demands on the management of living subjects research, data sharing, and algorithm development. Unfortunately, current software platforms are not effective in integrating these data in a manner that meets specific requirements in ophthalmology, Our goal in this Direct-to-Phase II SBIR, consistent with objectives of the NIH Strategic Plan for Data Science, is to create an integrated platform (PaaS) for the collection, curation, analysis, and sharing of ocular images and data. We will extend the capabilities of systems developed by the Advanced Ocular Imaging Program (AOIP), Medical College of Wisconsin (MCW), which include: (a) LATTICE - a software solution that reduces costs, reduces errors, and improves communications in the management of living-subjects research; (b) MOSAIC - an image processing platform and algorithm library with traditional and AI-trained algorithms; and (c) The AOIP Image Bank - a Repository that houses images and data on 1578 fully-consent human research subjects. To create the integrative platform, we will address four aims: (a) Extend LATTICE to meet the workflow requirements of academic and sponsored research in local and multisite environments, including the extensible direct integration of data relevant to ocular studies; (b) Design and implement a hybrid (local + cloud) REPOSITORY architecture, data schema, knowledge ontology, and query architecture for Owners and Readers of data.; (c) Integrate and demonstrate LATTICE, REPOSITORY and MOSAIC into a continuous ocular science workflow and (d) integrate and demonstrate Lattice, Repository and Mosaic into a continuous ocular science workflow. Our Integrated Translational Imaging platform will enable ophthalmic innovators to translate sight-saving insights and interventions to the clinic faster, with less frustration, and greater confidence. Our proposal fills an important technology gap in the field of ophthalmic data science and biomarker development. While the number and type of imaging devices continues to grow, the tools to develop and deploy new biomarkers and clinical endpoints using these exquisite imaging devices has not kept pace. With this program we will enable a new generation of image-driven innovation to find its way to the clinic.

抽象的 超过2000万患者患有与年龄相关的黄斑变性，糖尿病性视网膜病变或青光眼患者。这些 退化性眼部疾病几十年来发展起来，其患病率正在增加。视网膜成像技术，例如 光学相干断层扫描和自适应光学眼镜检查是研究的重要工具， 眼病的管理。从这些和其他成像方式得出的新的定量生物标志物对于 新兴眼科创新的临床翻译。但是，人造时代的生物标志物发展 智能需要大量带注释的图像和透明的可再现过程，这使得 对生活学科研究，数据共享和算法开发的管理要求。很遗憾， 当前的软件平台无法以满足特定要求的方式集成这些数据 眼科， 我们在这个直接到基础II SBIR中的目标，与NIH数据科学战略计划的目标一致 一个集成平台（PAAS），用于收集，策展，分析和眼部图像和数据。我们将扩展 威斯康星州医学院高级眼部成像计划（AOIP）开发的系统功能 （MCW），其中包括：（a）晶格 - 一种降低成本，降低错误并改善通信的软件解决方案 在生活受试者研究的管理中； （b）马赛克 - 带有图像处理平台和算法库 传统和AI训练算法； （c）AOIP图像库 - 一个存储库，该存储库在1578年包含图像和数据 完全愉快的人类研究主题。为了创建集成平台，我们将解决四个目标：（a）扩展晶格 满足在本地和多站点环境中的学术和赞助研究的工作流程要求，包括 与眼研究有关的数据的可扩展直接整合； （b）设计和实施混合动力车（本地 +云） 存储库体系结构，数据架构，知识本体论和查询架构，用于所有者和数据的读者。 （C） 将晶格，存储库和马赛克整合到连续的眼科学工作流程中，并且（d）整合 并将晶格，存储库和马赛克展示为连续的眼科学工作流程。我们的综合翻译 成像平台将使眼科创新者能够更快地将视力见解和干预转化为诊所， 减少挫败感和更大的信心。 我们的建议填补了眼科数据科学和生物标志物开发领域的重要技术差距。尽管 成像设备的数量和类型不断增长，开发和部署新生物标志物和临床的工具 使用这些精美的成像设备的端点尚未保持步伐。通过这个程序，我们将启用新一代 图像驱动的创新以找到通往诊所的方式。