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 扩散MRI（dMRI）是一种领先的体内成像方法，用于研究细微的显微结构变化 在大脑的白色物质中，这通常需要多个站点协作进行数据收集。分散 处理方法正成为多站点数据收集的首选方法，因为它们支持 更好的个人数据保护和可扩展性。使用分散的方法，增强神经 通过Meta分析成像遗传学（ENIGMA）研究在不同的研究领域产生了开创性的发现。 紊乱然而，为分散的ENIGMA dMRI研究建立的dMRI管道不是自动的， 用户友好，并要求每个站点具有强大的编程和dMRI专业知识，而在 许多临床网站。该项目的目标是帮助减轻现场一级的技术负担， 通过增加更多的研究中心，促进分散研究。 需要分散的多站点研究，以严格和统计上稳健地识别细微的 神经系统的变化，但技术上的困难，使分散的dMRI分析高度资源- 密集，阻碍了研究网站的参与。技术上的困难包括安装 多个软件工具及其软件依赖性，包括多个脚本步骤的分析指令 这些步骤对于新手用户来说很难遵循，而质量控制（QC）步骤需要dMRI方面的专业知识。 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处理和QC：1）开发自动化dMRI 具有广泛数据QC步骤的处理管道;以及2）提供仪表板功能并将 渠道.在第一个目标下，各种神经成像和图像处理工具将被连接在一起， 自动化dMRI处理管道，同时估计广泛的QC措施，这些措施将被策划， 非dMRI专家帮助直观地了解数据质量。对于第二个目标，将建立一个网络服务器， 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。此外，所有 组件将被容器化为单个包，以便使用Docker更容易地分发和部署。 本申请中提出的创新方法将简化dMRI分析， 在安装和操作集装箱式 管道，并将促进直观的用户交互的仪表板。我们新的和实质上不同的方法 是重要的，因为它预计将解决阻碍合作的大部分技术负担， 以分散的方式调查大脑的变化，鼓励更多的研究中心参与多研究中心 dMRI研究。