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.

项目总结