Multi-Site Clinical Data to Power MRI Biomarker of Neonatal Brain Injury

多部位临床数据为新生儿脑损伤的 MRI 生物标志物提供动力

基本信息

批准号：
10194889
负责人：
Yangming Ou
金额：
$ 9.49万
依托单位：
BOSTON CHILDREN'S HOSPITAL
依托单位国家：
美国
项目类别：
财政年份：
2021
资助国家：
美国
起止时间：
2021-04-12 至 2023-03-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10194889
关键词：
2 year old 3-Dimensional Address Affect Age Agreement Alzheimer&apos s Disease Archives Artificial Intelligence Atlases Authorization documentation Biological Markers Brain Brain Injuries Brain Neoplasms Caring Cerebral Palsy Cessation of life Child Health Clinical Clinical Data Clinical Trials Collection Consensus Consumption Data Data Element Data Set Databases Detection Development Diagnosis Diffusion Diffusion Magnetic Resonance Imaging Disease Early Intervention Ethnic group Foundations Frequencies Funding Future Grant Hearing Hospitals Human Development Image Informatics Injury Institutional Review Boards International Knowledge Length of Stay Lesion Life Link MRI Scans Magnetic Resonance Imaging Maps Medical Medical Imaging Metadata Morbidity - disease rate Mothers Motor National Institute of Child Health and Human Development Neonatal Neonatal Brain Injury Neonatal Intensive Care Units Neurocognitive Neurocognitive Deficit Neurologist Outcome Outcome Measure Patient-Focused Outcomes Patients Pattern Population Prognosis Protocols documentation Race Reader Reporting Research Risk Role Sample Size Signal Transduction Site Standardization Structure Study of magnetics Therapeutic Time Treatment outcome United States National Institutes of Health Visual adverse outcome base clinical care clinical practice clinical research site cohort cranium data access data de-identification database of Genotypes and Phenotypes design early childhood improved improved outcome intervention program magnetic resonance imaging biomarker meetings mortality motor impairment natural hypothermia neonatal brain neonatal hypoxic-ischemic brain injury neonatal outcome neonate neuroimaging novel outcome prediction patient registry response sex success symposium targeted treatment visual motor

项目摘要

Abstract This project aims to release our recently gathered existing clinically-acquired data for neonatal hypoxic ischemic encephalopathy (HIE). HIE affects 1-5/1000 term-born neonates and is a major cause of early-childhood mortality and morbidity. Neonatal brain magnetic resonance imaging (MRI) is acquired routinely for the clinical care of HIE. Neonatal brain MRI is expected to reveal 3D neuroanatomic mechanisms of adverse outcomes so that we can design new treatments specifically target those mechanisms. Neonatal brain MRI also carries hope to identify those neonates who are at risk to develop adverse outcomes later in life, so that early intervention program can target those at-risk neonates for maximum benefit. Despite MRI's vital role in caring for HIE, the current norm in clinical practice is to read MRI visually by expert neuroradiologist or neurologist. Expert reads, however, has many limitations – subjective, qualitative, insufficient to reveal mechanisms, and inadequate to predict outcomes. Objective and quantitative analysis of MRI is possible with the rise of artificial intelligence (AI) in medical and neuroimaging informatics. A major limitation, however, is the lack of publicly-available data on HIE. Our project aims to fill this gap, by archiving and releasing our clinically-acquired, large-scale (N=231), and multi-site (2 hospitals) data on HIE. Our data was acquired partly funded by NIH R01 (2012-2017) and foundations (2016-2020). Our data is comprehensive, including clinical data elements (from both mothers and neonates), neonatal brain MRI (structural and diffusion sequences), expert-consensus annotation of lesion regions in neonatal brain MRI, NICU outcome (death/survival, length of stay), and 2-year-old neurocognitive outcomes (normal/adverse, yes/no for development dealy, yes/no for the hearing/visual/motor impairment, and yes/no for cerebral palsy). Our data is also representative, coming from patients with different racial/ethnicity groups, in patients with a wide range of outcomes, from different MRI scanners (Siemens 3T or GE 1.5T), with different imaging protocols, and MRI scanned on different days of life. We will also derive new data from existing data. The anonymized (de-identified) data will be released to the NCBI dbGaP platform with the “Controlled Access” option, requiring IRB and data use agreement (DUA). The derived data will be released to dbGaP with the “Open Access” option, freely downloadable without any approval. Both release options are consistent with other clinical and MRI data that have already been released on dbGaP. We hope this first comprehensive data will boost future collaborative efforts for AI to automatically identify HIE lesions in MRI, and for AI to accurately predict HIE outcome integrating clinical and MRI information.

抽象的该项目旨在发布我们最近收集的新生儿缺氧缺血的现有临床数据脑病 (HIE) 影响 1-5/1000 的足月新生儿，是幼儿期的主要原因。新生儿脑部磁共振成像 (MRI) 是临床常规采集的数据。 HIE 的护理有望揭示不良后果的 3D 神经解剖学机制。我们可以设计专门针对这些机制的新疗法，这也带来了希望。识别那些有可能在以后的生活中出现不良后果的新生儿，以便早期干预尽管 MRI 在 HIE 护理中发挥着重要作用，但该计划可以针对高危新生儿以获得最大益处。目前临床实践中的规范是由神经放射科医生或神经科医生目视读取 MRI，然而，它有很多局限性——主观的、定性的、不足以揭示机制、也不足以随着人工智能 (AI) 的兴起，对 MRI 进行客观定量分析成为可能。然而，医学和神经影像信息学的一个主要限制是缺乏公开的数据。 HIE。我们的项目旨在通过归档和发布我们的临床获得的大规模（N = 231）和 HIE 的多站点（2 家医院）数据我们的数据部分由 NIH R01 (2012-2017) 资助和我们的数据很全面，包括临床数据元素（来自母亲和母亲）。新生儿）、新生儿脑 MRI（结构和扩散序列）、病变的专家共识注释新生儿脑 MRI 区域、NICU 结果（死亡/生存、住院时间）和 2 岁神经认知结果（正常/不良，发育情况是/否，听力/视觉/运动障碍是/否，以及脑瘫是/否）我们的数据也具有代表性，来自不同种族/民族的患者。来自不同 MRI 扫描仪（Siemens 3T 或 GE 1.5T）的具有各种结果的患者组，不同的成像方案，以及生命中不同日子的 MRI 扫描，我们还将从现有数据中获取新数据。匿名（去识别化）数据将通过“受控”发布到 NCBI dbGaP 平台。 Access”选项，需要 IRB 和数据使用协议（DUA）导出的数据将随 dbGaP 一起发布。 “开放获取”选项，无需任何批准即可免费下载。两种发布选项都是一致的。其他临床和 MRI 数据已经在 dbGaP 上发布，我们希望这是第一个全面的数据。将推动人工智能未来的合作努力，自动识别 MRI 中的 HIE 病变，并准确地识别结合临床和 MRI 信息预测 HIE 结果。