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: 10377732
• 负责人: Emily Larsen Dennis
• 金额: $ 70.73万
• 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/10377732
• 关键词: Accounting; Address; Adolescent; Adolescent Development; Adult; Age; Algorithms; Anatomy; Atrophic; Attention; Brain; 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; Documentation; Education; Ensure; Future; General Population; Genetic; Goals; Gold; Heterogeneity; Image; Image Analysis; Imaging Device; Incidence; Individual; Injury; International; Lesion; Link; Location; 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; analysis pipeline; base; 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; 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.

项目摘要/摘要 儿童和青少年在一般人群中的创伤性脑损伤（TBI）率最高，但 当前检查MR数据的结构和功能缺陷的工具具有多个关键局限性。第一的， 没有用于考虑成像分析中病变的金标准程序，其次，现有工具 已建立在成年人口上。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，并将其使用该工作流程 确定与结果相关的因素。个性化病理概况（P3）将包括注册 适合年龄的模板和病变细分，允许进行体素病变症状映射， 作为包装的一部分，形态分析，形状分析和网络扩散建模，选项 也用于纵向分析。该工作流将包括和扩展新颖的管道。 voxelwise病变 症状图检查了病变位置和特定症状之间的对应关系，但已有 在现有应用程序中的能力不足。网络扩散建模使用来自健康的扩散MRI数据 个体来建模病理的传播。虽然目前用于长期受伤的患者 估计受伤的中心，在该提案中，将使用纵向数据来验证预测 病理传播。方面的统计分析类似地使用健康数据来预测 基于病变位置的断开连接。对称多元线性还原可降低高维度 成像，认知和临床数据到组件，揭示了破坏的模式。通过包括所有这些 跨多个站点的各个方法，P3将允许对TBI对影响的影响进行多模式检查 具有更大统计能力的儿科患者。在AIM 1中，我们将开发和测试P3的八个人群 站点。随着神经病学，康复，神经心理学，放射学和大脑的临床专家的投入 数学，计算机科学和神经影像学分析的发展和技术专长，我们 将确保P3在统计和计算上具有有效性和临床相关性。在AIM 2中，我们将提取 来自跨人群不同量表的常见神经心理学终点，并将这些措施与 P3生成的脑指标来确定与结果相关的因素并识别亚组 患者人数。在AIM 3中，我们将将P3分发给Beta测试站点网络，以便在本地运行，从而允许 进一步的改进和验证，并将P3传播给研究界。通过荟萃分析或 与大型分析配对的协调，我们将结合跨站点的效果并检查一致性 效果大小，位置和方向。教育将通过国家和国际教程进行 会议，现场访问以及通过书面文档。 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了解异质性 伤害后的结果为未来的治疗开发提供了信息。