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

• 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
• 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' 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

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 该项目旨在释放我们最近收集的新生儿缺血性缺血的现有现有的临床报道数据 脑病（Hie）。 Hie影响1-5/1000年出生的新生儿，是早期的主要原因 死亡率和发病率。新生儿大脑磁共振成像（MRI）通常用于临床 照顾好。预计新生儿脑MRI会揭示不良结果的3D神经解剖机制 我们可以设计新的治疗方法，专门针对这些机制。新生儿大脑MRI也带有希望 确定那些有危险的新生儿在以后的生活中发展不良后果，以便早期干预 计划可以针对那些处于危险的新生儿，以获得最大的利益。尽管MRI在照顾Hie方面起着至关重要的作用 临床实践中的当前规范是通过专家神经放射科医生或神经科医生视觉阅读MRI。专家阅读， 但是，有许多局限性 - 主观，定性，不足以揭示机制，并且不足 预测结果。随着人工智能的兴起（AI），可能会对MRI进行客观和定量分析 在医学和神经影像信息方面。但是，一个主要限制是缺乏公开可用的数据 hie。我们的项目旨在通过存档和发布我们临床上的大规模（n = 231）和释放该空白，并 HIE的多站点（2家医院）数据。我们的数据是由NIH R01（2012-2017）和 基金会（2016-2020）。我们的数据是全面的，包括临床数据元素（来自母亲和 新生儿），新生儿脑MRI（结构和扩散序列），专家传记注释 新生儿脑MRI，NICU结果（死亡/生存，住院时间）和2岁的神经认知的区域 结果（正常/不利，是/否用于开发Dealy，是/否，听力/视觉/运动障碍，并且 是/否，用于脑瘫）。我们的数据也是代表性的，来自不同种族/种族的患者 来自不同MRI扫描仪（Siemens 3T或GE 1.5T）的患者，具有广泛结果的患者，具有 不同的成像协议和MRI在生活的不同日子进行了扫描。我们还将从现有的 数据。匿名（DE-SIDIED）数据将通过“受控”发布到NCBI DBGAP平台 访问”选项，需要IRB和数据使用协议（DUA）。将发布派生数据 “开放访问”选项，无需任何批准即可免费下载。两个发布选项都与 DBGAP上已经发布的其他临床和MRI数据。我们希望这个第一个全面数据 将促进AI自动​​识别MRI中的HIE病变的未来协作努力，并使AI准确地确定 预测整合临床和MRI信息的HIE结果。