Personalized Profiles of Pathology in Pediatric Traumatic Brain Injury

小儿创伤性脑损伤的个性化病理学概况

• 批准号: 10542834
• 负责人: Emily Larsen Dennis
• 金额: $ 63.81万
• 依托单位: UNIVERSITY OF UTAH
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-01-01 至 2026-11-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10542834
• 关键词: Accounting; Address; Adolescent; Adolescent Development; Adult; Age; Algorithms; Anatomy; Atrophic; Attention; Brain; Brain region; Cause of Death; Characteristics; Child; Childhood; Childhood Injury; Chronic; Clinical; Clinical Data; Cognitive; Communities; Consensus; Craniocerebral Trauma; Data; Data Set; Developed Countries; Development; Diffuse; Diffusion; Diffusion Magnetic Resonance Imaging; Disparate; Documentation; Education; Ensure; Exclusion; Future; General Population; Genetic; Goals; Heterogeneity; Image; Image Analysis; Imaging Device; Incidence; Individual; Injury; International; Lesion; Link; Location; Maps; Mathematics; Measures; Meta-Analysis; Modeling; Monitor; Morphology; Nerve Degeneration; Neurology; Neuropsychology; Outcome; Outcome Measure; Pathology; Patients; Pattern; Pediatric Radiology; Physical Medicine; Population; Positioning Attribute; Procedures; Process; Prognosis; Public Health; Radiology Specialty; Recovery; Rehabilitation therapy; Research; Research Personnel; Resources; Running; Sample Size; Severities; Site; Site Visit; Statistical Data Interpretation; Subgroup; Symptoms; Technical Expertise; Techniques; Testing; Thick; Time; Traumatic Brain Injury; Validation; Work; Writing; analysis pipeline; brain volume; clinically relevant; cohort; computational neuroscience; computer science; cost effective; disability; experience; high dimensionality; improved; injured; interest; longitudinal analysis; morphometry; multidisciplinary; multimodality; neurodevelopment; neuroimaging; novel; outcome prediction; patient population; patient subsets; pediatric patients; pediatric traumatic brain injury; personalized medicine; psychologic; sex; shape analysis; software development; structural imaging; symposium; therapy development; tool; tractography; web site; working group

Project summary/abstract Children and adolescents have the highest rate of traumatic brain injury (TBI) in the general population, but current tools for examining structural and functional deficits from MR data have several key limitations. First, there is no gold standard procedure for considering lesions in imaging analysis, and second, existing tools have been built on adult populations. We propose to develop a workflow that addresses both of these issues and supports the extension of novel tools for advanced, multimodal analysis, and to use that workflow to identify factors associated with outcome. Personalized Profiles of Pathology (P3) will include registration to age-appropriate templates and lesion segmentation, allowing for voxelwise lesion symptom mapping, morphometric analyses, shape analysis, and network diffusion modeling as part of the package, with options for longitudinal analysis as well. This workflow will include and extend novel pipelines. Voxelwise lesion symptom mapping examines the correspondence between lesion location and specific symptoms, but has been underpowered in existing applications. Network diffusion modeling uses diffusion MRI data from healthy individuals to model the spread of pathology. While this is currently used on chronically injured patients to estimate the epicenter of injury, in this proposal, longitudinal data will be used to validate predictions of pathology spread. Tract-wise statistical analysis similarly uses healthy data to predict the degree of disconnection based on lesion location. Symmetric multivariate linear reduction reduces high dimensional imaging, cognitive, and clinical data to components, revealing patterns of disruption. By including all of these individual approaches across multiple sites, P3 will allow for multi-modal examination of the impact of TBI on pediatric patients with greater statistical power. In Aim 1, we will develop and test P3 on cohorts from eight sites. With input from clinical experts in neurology, rehabilitation, neuropsychology, radiology, and brain development, and technical expertise from mathematics, computer science, and neuroimaging analytics, we will ensure that P3 is statistically and computationally valid and clinically relevant. In Aim 2, we will extract common neuropsychological endpoints from disparate scales across cohorts and use these measures with brain metrics generated by P3 to determine factors associated with outcome and identify subgroups within the patient population. In Aim 3, we will distribute P3 to a network of beta-testing sites to run locally, allowing for further improvement and validation, and disseminate P3 to the research community. Through meta-analysis or harmonization paired with mega-analysis, we will combine effects across sites and examine consistency in effect size, location, and direction. Education will occur through tutorials at national and international conferences, site visits, and through written documentation. P3 will be made available online, with continuing support from the development team. The ultimate goal of P3 is to better understand heterogeneity in post-injury outcome to inform future treatment development.

项目概要/摘要 在一般人群中，儿童和青少年的创伤性脑损伤 (TBI) 发生率最高，但 目前用于检查 MR 数据结构和功能缺陷的工具有几个关键局限性。第一的， 在影像分析中没有考虑病变的黄金标准程序，其次，现有工具 是建立在成年人口的基础上的。我们建议开发一个解决这两个问题的工作流程 并支持扩展用于高级多模式分析的新颖工具，并使用该工作流程 确定与结果相关的因素。个性化病理学档案 (P3) 将包括注册 适合年龄的模板和病变分割，允许进行体素病变症状映射， 形态测量分析、形状分析和网络扩散建模作为软件包的一部分，并带有选项 也可用于纵向分析。该工作流程将包括并扩展新颖的管道。体素损伤 症状图检查病变位置和特定症状之间的对应关系，但有 在现有应用中动力不足。网络扩散建模使用健康人的扩散 MRI 数据 个人来模拟病理学的传播。虽然目前该方法用于慢性损伤患者 估计伤害的震中，在本提案中，纵向数据将用于验证预测 病理传播。区域统计分析同样使用健康数据来预测 根据病变位置断开连接。对称多元线性约简降低高维 将成像、认知和临床数据转化为组件，揭示破坏模式。通过包括所有这些 跨多个地点的单独方法，P3 将允许对 TBI 对 TBI 的影响进行多模式检查 儿科患者具有更强的统计功效。在目标 1 中，我们将在 8 个队列中开发和测试 P3 网站。听取了神经病学、康复、神经心理学、放射学和脑科临床专家的意见 开发以及来自数学、计算机科学和神经影像分析的技术专业知识，我们 将确保 P3 在统计和计算上有效且具有临床相关性。在目标 2 中，我们将提取 不同人群中不同尺度的常见神经心理学终点，并使用这些措施 P3 生成的大脑指标可确定与结果相关的因素并识别结果中的亚组 患者群体。在目标 3 中，我们将把 P3 分发到 Beta 测试站点网络以在本地运行，从而允许 进一步改进和验证，并将P3传播给研究界。通过荟萃分析或 协调与大型分析相结合，我们将结合各个站点的影响并检查一致性 影响的大小、位置和方向。教育将通过国内和国际的教程进行 会议、实地考察以及书面文件。 P3 将在线提供，并继续 开发团队的支持。 P3的最终目标是更好地理解异质性 受伤后的结果为未来的治疗发展提供信息。