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

摘要 超过2000万患者患有年龄相关性黄斑变性、糖尿病视网膜病变或青光眼。这些 退行性眼病发展了几十年，并且其流行率正在增加。视网膜成像技术，如 光学相干断层扫描和自适应光学检眼镜是研究中的重要工具， 眼科疾病的管理。从这些和其他成像方式中获得的新的定量生物标志物对于 新兴眼科创新的临床转化。然而，生物标志物的发展在人工智能时代， 智能需要大量的注释图像和透明的、可重复的过程， 对活体研究的管理、数据共享和算法开发的需求。不幸的是， 当前的软件平台不能有效地以满足特定需求的方式集成这些数据 眼科学， 我们在这个直接到第二阶段SBIR的目标，与NIH数据科学战略计划的目标一致，是创建 一个用于收集、管理、分析和共享眼部图像和数据的集成平台（PaaS）。我们将扩展 由威斯康星州医学院高级眼部成像计划（AOIP）开发的系统的能力 (MCW)包括：（a）LATTICE -一种降低成本、减少错误和改善通信的软件解决方案 （B）MOSAIC -一个图像处理平台和算法库， 传统和人工智能训练的算法;以及（c）AOIP图像库-一个存储1578图像和数据的存储库 完全同意的人类研究对象为了创建集成平台，我们将实现四个目标：（a）扩展LATTICE 满足本地和多站点环境中学术和赞助研究的工作流程要求，包括 （B）设计和实现混合（本地+云） 数据库体系结构、数据模式、知识本体和数据所有者和读取者的查询体系结构。（c）第（1）款 将LATTICE、REPOSITORY和MOSAIC集成并展示为一个连续的眼科科学工作流程，以及（d）集成 并将Lattice、Repository和Mosaic演示为一个连续的视觉科学工作流程。我们的综合翻译 成像平台将使眼科创新者能够更快地将拯救视力的见解和干预措施转化为临床， 更少的挫折，更大的信心。 我们的提案填补了眼科数据科学和生物标志物开发领域的重要技术空白。而 成像设备的数量和类型持续增长，开发和部署新的生物标志物和临床应用的工具 使用这些精致的成像设备的终端没有跟上步伐。通过这项计划，我们将使新一代的 图像驱动的创新，以找到它的方式到诊所。

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.