CARE4Kids: Imaging Biomarker Core

CARE4Kids：成像生物标志物核心

• 批准号: 10203601
• 负责人: PAUL M THOMPSON
• 金额: $ 23.01万
• 依托单位: UNIVERSITY OF CALIFORNIA LOS ANGELES
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-08 至 2026-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10203601
• 关键词: 3-Dimensional; Administrative Supplement; Adolescent; Affect; Anatomy; Biological Markers; Blood; Brain; Brain Concussion; Brain imaging; Brain scan; Calibration; Cerebrovascular Circulation; Child; Clinical; Clinical assessments; Collection; Common Data Element; Communities; Data; Data Adjustments; Data Analyses; Data Collection; Data Coordinating Center; Detection; Development; Diffusion Magnetic Resonance Imaging; Ensure; Feedback; Functional Magnetic Resonance Imaging; Funding; Genetic study; Geometry; Goals; Image; Individual; Inflammation; Information Theory; International; Machine Learning; Magnetic Resonance Imaging; Measurable; Measures; Methods; Modality; Modeling; Monitor; Motion; Multimodal Imaging; National Institute of Neurological Disorders and Stroke; Nervous System Trauma; Outcome; Outcome Measure; Participant; Perfusion; Phase; Post-Concussion Syndrome; Predisposition; Process; Prognosis; Protocols documentation; Quality Control; Recommendation; Research; Resolution; Rest; Running; Sample Size; Scanning; Site; Spin Labels; Standardization; Structure; Subgroup; Supervision; Testing; Time; Training; Travel; United States; United States National Institutes of Health; Universities; Utah; Validation; White Matter Hyperintensity; Work; base; biobank; blood perfusion; brain volume; cognitive development; cohort; combat; cost; data collection site; data exchange; data harmonization; data quality; design; endophenotype; experience; falls; functional outcomes; imaging biomarker; imaging facilities; imaging modality; imaging study; indexing; injured; innovation; mild traumatic brain injury; multimodality; neuroimaging; neuropathology; outcome prediction; patient population; patient subsets; phenotypic data; predict clinical outcome; tool; volunteer; white matter

PROJECT SUMMARY/ABSTRACT – Imaging Biomarker Core The CARE4Kids Center Without Walls Project aims to discover measurable biomarkers of persistent post- concussive symptoms (PPCS) and use these markers to characterize subgroups (endophenotypes) that will inform prognosis and potential treatment. Advanced neuroimaging offers great promise in revealing how concussion affects brain structure and function, but relatively small sample sizes have limited the reliability and generalizability of imaging studies to date. The overall goal of the Imaging Biomarker Core is to collect state-of- the-art multimodal brain imaging data that is maximally informative about outcomes in children and adolescents with concussion. Multimodal imaging will be collected in the Development Cohort, at baseline only, and used to develop and test models of outcome prediction that will be examined in the Validation Cohort. The neuroimaging protocol is designed to maximize data quality and minimize discomfort for our injured, younger patient population and is based on existing multi-site efforts (i.e., ABCD, UK Biobank) and NINDS imaging recommendations. The Imaging Biomarker Core has the following Specific Aims: Specific Aim 1: Discover which multimodal brain imaging measures best predict clinical outcomes in concussion (separately, and when combined with other biomarkers and clinical measures). Specific Aim 2: Neuroimaging site qualification and training – site qualification using pilot data and coordinated training will prepare sites to collect high-quality data. Specific Aim 3: Collect high-quality multimodal brain MRI – 360 participants will be scanned across 6 sites in the Development Cohort. Specific Aim 4: Ongoing data quality control – ongoing quality control through phantoms, volunteers, and data review will ensure high-quality data that is maximally comparable across sites. Specific Aim 5: Analyze Data: Transfer images and derived measures to the University of Utah Data Coordinating Center (U-DCC) to disseminate to the research community. We will use standardized, validated, publicly-available protocols to process the neuroimaging data. Measures of regional brain volumes, cortical geometry, white matter organization, functional connectivity, perfusion, and neuropathology (i.e., microbleeds and white matter hyperintensities) will be compared between groups and examined for correlation with outcome measures. In addition to these simpler approaches, working with the U-DCC, we will employ machine learning approaches to identify which combination of imaging, demographic, and clinical measures best predicts functional outcome.

项目摘要/摘要-成像生物标志物核心