Sustaining the Integrative Imaging Informatics for Cancer Research (I3CR) Center

维持癌症研究综合成像信息学 (I3CR) 中心

• 批准号: 10187782
• 负责人: Daniel Scott Marcus
• 金额: $ 77万
• 依托单位: WASHINGTON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-04-06 至 2026-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10187782
• 关键词: Academia; Academy; Address; Administrator; Adopted; Adoption; Advanced Development; Area; Artificial Intelligence; Automation; Clinical; Clinical Data; Cloud Computing; Cloud Service; Communities; Data; Data Aggregation; Data Analyses; Data Commons; Data Scientist; Data Set; Database Management Systems; Development; Digital Imaging and Communications in Medicine; Disease; Ecosystem; Education; Educational Curriculum; Educational workshop; Engineering; Ensure; Environment; Event; FAIR principles; Funding; Grant; Health; High Performance Computing; Human Biology; Image; Image Analysis; Industry; Informatics; Information Resources Management; Information Systems; International; Knowledge; Lead; Malignant Neoplasms; Medical Imaging; Methods; Multi-Institutional Clinical Trial; NCI Center for Cancer Research; National Cancer Institute; Natural Language Processing; Online Systems; Outreach Research; Pathway interactions; Patient Care; Patients; Persons; Phase; Play; Radiology Information Systems; Request for Applications; Research; Research Personnel; Resources; Role; Series; Services; Structure; System; Technology; The Cancer Imaging Archive; Training Programs; Visualization; Work; anticancer research; application programming interface; base; cancer imaging; clinical translation; cohort; community engaged research; community engagement; computerized data processing; computing resources; data dissemination; data management; data sharing; deep learning; education resources; feature extraction; imaging informatics; improved; indexing; informatics tool; large datasets; open source; outreach; preclinical imaging; reconstruction; response; sharing platform; success; symposium; tool; trend; web services

Abstract Artificial intelligence (AI) and other computationally intensive methods have the potential to revolutionize cancer imaging research and patient care. The broad adoption of these technologies depends on the availability development of imaging informatics tools to assist users in managing massive data sets, generating well-curated annotations, and accessing scalable computing resources. The Integrative Imaging Informatics for Cancer Research (I3CR) Center has played a lead role in implementing cancer imaging informatics technology, with a focus on expanding the widely used open source XNAT informatics platform to better support computational workflows in cancer imaging. I3CR has also developed knowledge management tools to better track data processing and analysis, including tools for orchestrating and tracking container-based computing pipelines. As result of this work, XNAT has emerged as the most widely used imaging informatics platform in cancer research. It is deployed in over 200 organizations across academia and industry and has been adopted across a wide range of research contexts, including preclinical imaging, multi-site clinical trials, and clinical translation. As the I3CR informatics platform has matured and been widely adopted, the Center is now evolving to the next phase of development to more broadly sustain the platform. In the work proposed here, we will sustain the I3CR’s ongoing engineering initiatives and expand its outreach efforts. The Center’s sustainment activities will build on and extend the I3CR platform’s expansive set of data and knowledge management capabilities, with a focus on addressing key emergent needs within our user base. In Aim 1, we will continue to develop the XNAT-based data management platform, including adding standards-based clinical interfaces, developing a cohort discovery service with natural language processing support, implementing a task automation service, and extending its container-based computing service to support high performance computing and cloud computing environments. In Aim 2, we will implement a suite of integrations with complementary image analysis and data sharing platforms, including The Cancer Image Archive and the NCI Imaging Data Commons. In Aim 3, we will expand the I3CR’s outreach initiatives to ensure broad and effective adoption of the I3CR informatics platforms. The Center’s training program will utilize the XNAT Academy education platform to host a series of online training programs directed at specific audiences including developers, data scientists, integrators, and system administrators. A suite of supporting cloud services will be implemented assist the community in adopting and developing on the I3CR platform.

抽象的 人工智能 (AI) 和其他计算密集型方法有潜力 这些技术的广泛采用彻底改变了癌症成像研究和患者护理。 技术取决于成像信息学工具的可用性开发来协助 用户管理海量数据集、生成精心策划的注释以及访问 可扩展的计算资源。癌症研究综合成像信息学 (I3CR) 中心在癌症影像信息学技术的应用方面发挥了主导作用，拥有 专注于扩展广泛使用的开源XNAT信息学平台以更好地支持 I3CR 还开发了癌症成像的计算工作流程。 更好地跟踪数据处理和分析的工具，包括编排和跟踪工具 由于这项工作，XNAT 已成为最重要的计算管道。 在癌症研究中广泛使用的成像信息学平台已部署在 200 多个国家。 学术界和工业界的组织，并已被广泛采用 研究背景，包括临床前成像、多中心临床试验和临床转化。 随着I3CR信息学平台的成熟和广泛采用，该中心现已 发展到下一阶段，以更广泛地维持该平台的工作。 在此提议，我们将维持 I3CR 正在进行的工程计划并扩大其 该中心的维持工作活动将以 I3CR 为基础并加以扩展。 平台广泛的数据和知识管理功能，重点关注 满足我们用户群中的关键紧急需求 在目标 1 中，我们将继续开发 基于XNAT的数据管理平台，包括添加基于标准的临床界面， 开发具有自然语言处理支持的队列发现服务，实施 任务自动化服务，并扩展其基于容器的计算服务以支持高 在目标 2 中，我们将实现一个套件。 与互补的图像分析和数据共享平台的集成，包括 在目标 3 中，我们将扩展癌症图像档案和 NCI 成像数据共享。 I3CR 的外展计划确保 I3CR 信息学得到广泛而有效的采用 该中心的培训计划将利用 XNAT Academy 教育平台。 举办一系列针对特定受众（包括开发人员）的在线培训计划， 数据科学家、集成商和系统管理员将提供一套支持云服务。 实施协助社区在 I3CR 平台上采用和开发。