A harmonized vendor-agnostic environment for multi-site functional MRI studies

用于多站点功能 MRI 研究的与供应商无关的协调环境

• 批准号: 10483153
• 负责人: Jon-Fredrik Nielsen
• 金额: $ 92.67万
• 依托单位: UNIVERSITY OF MICHIGAN AT ANN ARBOR
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-15 至 2027-02-28
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10483153
• 关键词: 3-Dimensional; Active Sites; Adoption; Algorithms; Brain; Brain region; Clinical; Clinical Research; Cognition; Communities; Complex; Computer software; Data; Data Pooling; Development; Documentation; Education; Ensure; Environment; Fatty acid glycerol esters; Functional Magnetic Resonance Imaging; Future; Human; Image; Improve Access; Institution; Knowledge; Magnetic Resonance Imaging; Manufacturer; Maps; Measurement; Methods; Modeling; Motor; Multicenter Studies; Neurosciences Research; Performance; Physiologic pulse; Procedures; Protocols documentation; Pythons; Quality Control; Reproducibility; Research; Research Personnel; Resources; Rest; Scanning; Signal Transduction; Site; Structure; Techniques; Technology; Training; Travel; Variant; Vendor; cognitive task; computerized data processing; data acquisition; data quality; design; experimental study; file format; flexibility; image reconstruction; interest; invention; magnetic field; open source; open source library; portability; quality assurance; sustainable resource

Since its invention in the early 90s, functional magnetic resonance imaging (fMRI) has revolutionized our un- derstanding of the human brain. Functional MRI may be used to observe brain function during a specific motor or cognitive task, or at “rest” (resting-state fMRI). The latter produces so-called “functional connectivity” maps that may provide a new window into human cognition. There is currently a large, world-wide effort underway to discover potential research and clinical uses of such connectivity maps. A significant practical barrier in this effort, however, is the difficulty in ensuring that fMRI experiments are conducted in a consistent and reproducible manner across different centers. In particular, it is generally not possible to ensure identical execution of MR measurements (pulse sequences) across sites operating different MR scanners. Furthermore, even the image reconstruction and data processing methods can be difficult to harmonize, particularly across different MR ven- dors. This makes it challenging to directly compare results between sites, or “pool” data from multiple sites to increase statistical power and gain access to rare clinical conditions. We will assemble and disseminate a truly harmonized, cross-vendor, and flexible environment for fMRI re- search that ensures consistent data acquisition and image reconstruction across sites. Our framework is based on an open-source MR sequence development platform that allows any arbitrary MR pulse sequence to be de- signed “off-line” in Matlab or Python and exported to a vendor-independent file format, that can be ported directly to scanners from different manufacturers (at present, General Electric and Siemens are supported, but others may follow in the future). Due to this open pulse sequence structure it will also be possible to compose a unified image reconstruction environment based on current open-source libraries. Based on this technology, we will provide the fMRI research community with a complete and portable workflow for fMRI data acquisition and image reconstruction, backed up by integrated quality control procedures.

自从90年代初发生事故以来，功能性磁共振成像（fMRI）彻底改变了我们的局面 人类大脑的竞争。功能性MRI可用于观察特定电动机期间的大脑功能 或认知任务，或在“休息”（静止状态fMRI）。后者产生所谓的“功能连接”地图 这可能为人类认知提供了新的窗口。目前正在进行庞大的全球努力 发现这种连通图的潜在研究和临床用途。这是一个重要的实用障碍 然而，努力是确保fMRI实验以一致和繁殖进行的困难 跨不同中心的方式。特别是，通常不可能确保MR相同的执行 操作不同MR扫描仪的位点的测量（脉冲序列）。此外，即使是图像 重建和数据处理方法可能很难和协调，尤其是在不同的MR中 dors。这使得直接比较站点之间的结果或从多个站点的“池”数据与 增加统计能力并获得罕见的临床状况。 我们将组装并传播一个真正协调的，跨供应商和灵活的环境 搜索可确保跨站点的数据采集和图像重建。我们的框架是基于的 在开源MR序列开发平台上，该平台允许任何任意的MR脉冲序列被降低 在Matlab或Python中签名的“离线”，并导出到供应商独立的文件格式，可以直接移植 为了来自不同制造商的扫描仪（目前，通用电气和西门子得到了支持，但其他 将来可能会跟随）。由于这种开放的脉冲序列结构，也可以构成一个统一的 基于当前开源库的图像重建环境。基于这项技术，我们将 为fMRI研究社区提供fMRI数据获取和图像的完整和便携式工作流程 重建，由集成质量控制程序支持。

项目成果

Editorial: Autonomous magnetic resonance imaging.

• DOI: 10.3389/fnimg.2023.1277580
• 发表时间: 2023
• 期刊: Frontiers in neuroimaging
• 作者: Geethanath, Sairam;Nunes, Rita G;Nielsen, Jon-Fredrik
• 通讯作者: Nielsen, Jon-Fredrik

Open-source MR imaging and reconstruction workflow.

• DOI: 10.1002/mrm.29384
• 发表时间: 2022-12
• 期刊: MAGNETIC RESONANCE IN MEDICINE
• 影响因子: 3.3
• 作者: Veldmann, Marten;Ehses, Philipp;Chow, Kelvin;Nielsen, Jon-Fredrik;Zaitsev, Maxim;Stoecker, Tony
• 通讯作者: Stoecker, Tony