Interoperable Software Platform for Reproducible Research and Clinical Translation of MRI

用于 MRI 可重复研究和临床转化的可互操作软件平台

• 批准号: 10491708
• 负责人: Michael Lustig
• 金额: $ 30.45万
• 依托单位: UNIVERSITY OF CALIFORNIA BERKELEY
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-21 至 2024-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10491708
• 关键词: Address; Advanced Development; Algorithms; Ally; Architecture; Back; Binding; Clinical; Clinical Research; Cloud Computing; Code; Communities; Complement; Computer software; Data; Development; Documentation; Ecosystem; Educational Materials; Educational workshop; Environment; Europe; Fostering; Funding Opportunities; Goals; Growth; High Performance Computing; Image; Industry; Infrastructure; Institution; International; Ionizing radiation; Libraries; Linux; MRI Scans; Magnetic Resonance Imaging; Maintenance; Memory; Methods; Modality; Modernization; Monitor; Motivation; Movement; Neurosciences Research; Operating System; Performance; Polishes; Publishing; Pythons; Renaissance; Reproducibility; Research; Resources; Scanning; Schedule; Science; Site; Software Framework; Software Tools; Standardization; Techniques; Technology; Testing; Time; Training Activity; Translating; United States; Update; Vendor; Visual; Work; X-Ray Computed Tomography; base; biomedical imaging; clinical practice; clinical translation; cloud based; cluster computing; computational platform; computerized data processing; data repository; experience; file format; graphical user interface; image reconstruction; imaging modality; improved; innovation; interest; interoperability; man; neuroimaging; non-invasive imaging; open source; parallel computer; parity; pre-clinical research; program dissemination; quality assurance; reconstruction; research clinical testing; response; soft tissue; software infrastructure; tool; usability; web page; web portal; webinar

Project Abstract Motivation: This proposal, titled Interoperable Software Platform for Reproducible Research and Clinical Translation of MRI, is in response to the U24 funding opportunity RFA-EB-18-002, Resources for Technology Dissemination. Magnetic resonance imaging (MRI) is non-invasive, non-ionizing, and offers superb soft tissue contrast, but is traditionally limited by long scan times. Recently, advances in numerical image reconstruction and availability of powerful hardware platforms have led to new MRI scanning techniques with dramatic reductions in scan times. However, the associated computational sophistication has posed a large barrier to reproducibil- ity and clinical translation. This proposal addresses this fundamental issue by establishing best practices and infrastructure for reproducible research in MRI. Initial work toward this goal spanning six years has led to the development of the BART software toolbox for computational MRI. BART implements advanced MRI reconstruction algorithms in an extensible manner so that new technological advances can build off of the collective progress in the field. Supported computational back- ends including multi-CPU and multi-GPU architectures afford efficient use in a clinical translation environment. Project dissemination has been met with strong interest from the international MRI research community, having grown a user-base spanning over 50 academic and industry sites. Nonetheless, current limitations in project in- frastructure and support have hindered more widespread dissemination. Therefore, the major emphasis here is expanding development to improve usability, creation of written and audio-visual educational material, integration with other tools, cloud-based support, and software reliability. This will (1) provide new users common ground for starting new projects, (2) allow them to use their existing workflows with BART, (3) move to more accessible computation platforms, and (4) reliably translate their work into clinical practice. Approach: The project will proceed with four interrelated aims, supported by user training activities. Aim 1 will focus on adding comprehensive documentation and creating example-based tutorials. Aim 2 will expand interop- erability with software platforms and vendor tools used by the MRI community. Aim 3 will complete infrastructure and backends for cloud and parallel computing. Aim 4 will improve software reliability and quality assurance. The work will be disseminated through online material, webinars and workshops. Significance: This work will enable development, creation and reproducibility of modern state-of-the art MRI reconstruction methods that rely on highly specialized data processing approaches. MRI development will be streamlined as new methods build off of reliable infrastructure and existing work. Improved sustainability and reliability will enable rapid dissemination of new work into clinical evaluation and practice while significantly reducing the technical burden normally associated with clinical translation.

项目摘要 动机：该建议，标题为可再现研究和临床的可互操作软件平台 MRI的翻译是回应U24资金机会RFA-EB-18-002，技术资源 传播。磁共振成像（MRI）是非侵入性的，非电离的，并且提供了精美的软组织 对比，但传统上受到长期扫描时期的限制。最近，数值图像重建和 功能强大的硬件平台的可用性导致了新的MRI扫描技术，并具有巨大的降低 在扫描时期。但是，相关的计算复杂已被定位为重核 - IT和临床翻译。该建议通过建立最佳实践和 MRI可再现研究的基础设施。 最初朝着六年迈向这一目标的工作导致了BART软件工具箱的开发 计算MRI。巴特以可扩展的方式实施高级MRI重建算法 新的技术进步可以基于领域的集体进步。支持的计算背面 - 包括多CPU和多GPU体系结构在内的末端在临床翻译环境中提供了有效的用途。 国际MRI研究社区的激烈兴趣已经充满了计划， 增长了一个跨越50多个学术和行业网站的用户基础。尽管如此，项目当前的局限性 铁路结构和支持阻碍了更大的传播。因此，这里的主要重点是 扩大发展以提高可用性，创建书面和视听教育材料，整合 使用其他工具，基于云的支持和软件可靠性。这将（1）为新用户提供共同点 为了开始新项目，（2）允许他们与Bart一起使用现有的工作流，（3）移至更容易访问的 计算平台和（4）可靠地将其工作转化为临床实践。 方法：该项目将以四个相互关联的目标进行，并得到用户培训活动的支持。目标1意志 专注于添加综合文档并创建基于示例的教程。 AIM 2将扩展互动 - MRI社区使用的软件平台和供应商工具的ERASIABLE。 AIM 3将完成基础架构 以及用于云和并行计算的后端。 AIM 4将提高软件可靠性和质量保证。这 工作将通过在线材料，网络研讨会和研讨会来传播。 意义：这项工作将使现代最先进的MRI的发展，创造和可重复性 重建方法依赖于高度专业的数据处理方法。 MRI开发将是 简化了随着新方法的基础，基于可靠的基础架构和现有工作。改善可持续性和 可靠性将使新作品的快速传播到临床评估和实践中，同时显着 减少通常与临床翻译相关的技术燃烧。