User-friendly Analysis Platform for Decentralized Multi-site Diffusion MRI Studies

用于分散式多站点扩散 MRI 研究的用户友好分析平台

• 批准号: 10724720
• 负责人: Kang Ik Cho
• 金额: $ 8.95万
• 依托单位: BRIGHAM AND WOMEN'S HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-07-06 至 2025-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10724720
• 关键词: Address; Antisocial Personality Disorder; Automatic Data Processing; Automation; Back; Bipolar Disorder; Brain; Brain Diseases; Collaborations; Computer software; Conduct Disorder; Consumption; Data; Data Collection; Data Pooling; Data Protection; Data Security; Data Set; Decentralization; Dependence; Development; Diffusion Magnetic Resonance Imaging; Digital Imaging and Communications in Medicine; Disease; Electronic Mail; Epilepsy; Etiology; Genetic; Goals; Heterogeneity; Human; Information Protection; Infrastructure; Instruction; Internet; Intervention; Intuition; Investigation; Knowledge; Link; Major Depressive Disorder; Manuals; Measures; Meta-Analysis; Methodology; Methods; Monitor; Nature; Neurologic; Operating System; Outcome; Outcome Measure; Output; Pathologic; Personally Identifiable Information; Post-Traumatic Stress Disorders; Process; Quality Control; Reporting; Reproducibility; Research; Resources; Running; Sample Size; Schizophrenia; Scientist; Seminal; Site; Sleep; Sleeplessness; Software Tools; Statistical Data Interpretation; Structure; System; Techniques; Time; Visualization; autism spectrum disorder; automated analysis; clinical center; clinical research site; computer infrastructure; computer science; computerized data processing; dashboard; data collection site; data quality; design; experience; image processing; improved; in vivo imaging; innovation; interest; nervous system disorder; neuroimaging; operation; response; skills; tool; user-friendly; web server; white matter; white matter change

Project Summary Diffusion MRI (dMRI) is a leading in-vivo imaging methodology for investigating subtle microstructural changes in the brain’s white matter, which often requires multi-site collaborations for data collection. Decentralized processing approaches are becoming the preferred approach for multi-site data collection because they support improved personal data protection and are scalable. Using a decentralized approach, The Enhancing Neuro Imaging Genetics through Meta Analysis (ENIGMA) studies produced seminal findings across different disorders. However, the dMRI pipeline established for decentralized ENIGMA dMRI studies is not automatic, not user friendly, and requires each site to have strong programming and dMRI expertise, which is not the case in many clinical sites. The goal of this project is to help alleviate the site-level technical burdens, which would promote decentralized studies by enabling the addition of more sites. Decentralized multi-site studies are needed for rigorous and statistically robust identification of subtle neurological changes, but the technical difficulties which make decentralized dMRI analysis highly resource- intensive, are impeding research sites from participating. The technical difficulties include the installation of multiple software tools and their software dependencies, analysis instructions that include multiple scripting steps that are hard to follow for novice users, and quality control (QC) steps that require expertise in dMRI. The central goal of this application is to develop a user-friendly dMRI analysis platform for decentralized studies which will facilitate the processing and QC by pursuing two specific aims: 1) develop an automated dMRI processing pipeline with extensive data QC steps; and 2) provide dashboard function and containerize the pipeline. Under the first aim, various neuroimaging and image processing utilities will be linked together to automatize the dMRI processing pipeline while estimating extensive QC measures, which will be curated for non-dMRI experts to help intuitively understand the data quality. For the second aim, a web-server will be developed to provide a dashboard that is used to interact with the pipeline and visualize the outputs. Also, all the components will be containerized as a single package for easier dissemination and deployment using docker. The innovative approaches proposed in this application will simplify the dMRI analysis, enable optimal user experience requiring minimal manual user-interventions in the installation and operation of the containerized pipeline, and will facilitate a dashboard for intuitive user interaction. Our new and substantively different approach is significant because it is expected to resolve much of the technical burden impeding the collaborative investigation of brain changes in a decentralized approach, encouraging more sites to participate in multi-site dMRI studies.

项目摘要 弥散磁共振成像(Dmri)是一种领先的体内成像方法，用于研究微小的微结构变化。 在大脑的白质中，这通常需要多个地点的协作来收集数据。去中心化 处理方法正在成为多站点数据采集的首选方法，因为它们支持 改进了个人数据保护，并且可扩展。使用分散的方法，增强的神经细胞 Meta分析成像遗传学(Enigma)研究在不同的不同领域产生了重大发现 精神错乱。然而，为分散的谜团dMRI研究建立的dMRI管道不是自动的，也不是 用户友好，并要求每个站点具有强大的编程和dMRI专业知识，但在 许多临床站点。该项目的目标是帮助减轻现场级别的技术负担，这将 通过增加更多的站点来促进分散研究。 需要分散的多点研究，以严格和统计稳健地识别细微的 神经变化，但使分散的dMRI分析具有高度资源的技术困难- 密集的，正在阻碍研究网站的参与。技术难点包括安装 多个软件工具及其软件依赖项，包括多个脚本步骤的分析说明 对于新手用户来说很难遵循的步骤，以及需要dMRI专业知识的质量控制(QC)步骤。 该应用程序的中心目标是为分散研究开发一个用户友好的dMRI分析平台 这将通过追求两个具体目标来促进加工和质量控制：1)开发自动化的dMRI 具有大量数据QC步骤的处理流水线；以及2)提供仪表板功能并将 输油管道。在第一个目标下，各种神经成像和图像处理实用程序将链接在一起，以 自动化dMRI处理流水线，同时评估广泛的QC措施，这将为 非dMRI专家帮助直观地了解数据质量。对于第二个目的，网络服务器将是 开发的目的是提供一个仪表板，用于与管道交互并可视化输出。另外，所有的 组件将被集装箱化为一个单独的包，以便于使用Docker进行分发和部署。 本应用中提出的创新方法将简化dMRI分析，使最佳用户 在集装箱的安装和操作中需要最少的手动用户干预的经验 流水线，并将促进直观的用户交互仪表板。我们新的和本质上不同的方法 意义重大，因为预计它将解决阻碍协作的大部分技术负担 以分散的方式调查大脑变化，鼓励更多的站点参与多站点 DMRI研究。