Brain Health and Aphasia Recovery

大脑健康和失语症恢复

基本信息

批准号：
10094381
负责人：
Leonardo F Bonilha
金额：
$ 17.43万
依托单位：
UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA
依托单位国家：
美国
项目类别：
财政年份：
2016
资助国家：
美国
起止时间：
2016-04-01 至 2026-03-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10094381
关键词：
Acute Address Affect Aging Anatomy Aphasia Behavioral Blood Vessels Brain Brain Injuries Brain region Characteristics Chronic Clinical Cognitive Collaborations Data Diffusion Magnetic Resonance Imaging Elderly Exhibits Fiber Goals Guidelines Human Image Impairment Individual Injury International Language Language Disorders Lead Lesion Linguistics Literature Location Machine Learning Magnetic Resonance Imaging Measures Mediating Mediation Medical Metabolic Methods Microvascular Dysfunction Modeling Nervous System Trauma Neurobiology Neurologic Neurons Outcome Pathway interactions Predisposition Recovery Reporting Research Residual state Semantics Severities Stroke Structure Symptoms Testing Vascular blood supply Work acute symptom aphasia recovery base brain health brain tissue cardiovascular health cardiovascular risk factor cognitive reserve connectome experience innovation language impairment lexical loss of function multimodality network architecture neural network architecture neuroimaging novel persistent symptom phonology post stroke preservation resilience stroke recovery stroke-induced aphasia synergism white matter

项目摘要

Abstract Language impairments can vary considerably between individuals with aphasia. Our neurobiological models based on the stroke lesion can only partly explain the aphasic symptoms. We hypothesize that the integrity of the residual brain tissue outside the stroke lesion is an important, but not yet fully appreciated, determinant of aphasia severity and recovery. It is well recognized that cardiovascular risk factors lead to cumulative widespread brain damage through small vessel disease (SVD). Outside the aphasia literature, SVD has been strongly associated with poor cognitive reserve and reduced resiliency to various forms of neurological injury. Stroke survivors with aphasia typically have cardiovascular risk factors and they commonly exhibit SVD. However, the impact of SVD is not usually taken into account in our models of recovery, even though the residual brain tissue is responsible for overcoming the loss of function. It follows that higher degrees of SVD outside the lesion may lead to worse aphasic symptoms and less chances of recovery due to reduced capacity to compensate for the stroke injury. Our goal is to directly test this hypothesis. We propose to evaluate how aphasia is shaped by the stroke lesion in combination with residual brain integrity. Neuroimaging (brain MRI) is ideally suited to address this problem. SVD is composed of microangiopathic ischemic changes and microhemorrhages. The ischemic changes from SVD can be measured through white matter hyper intensities using T2-weighted and T2-FLAIR images, and the microhemorrhages can be assessed using susceptibility-weighted images. SVD preferentially affects white matter and diffusion MRI can provide additional measures of white matter microstructural integrity and their relationship with the whole brain neuronal networks architecture (the brain connectome). Using our experience with post-stroke lesion symptom mapping, white matter and connectome imaging we propose a comprehensive study of the neurobiology and impact of SVD in aphasia. Our project will build on international guidelines for SVD assessment (The STandards for ReportIng Vascular changes on nEuroimaging - STRIVE) and it will develop an innovative multimodal machine learning approach to fully assess brain integrity. Brain integrity and language measures will be assessed in the context of chronic (Project 1) and acute (Project 2) aphasia recovery. The behavioral and linguistic assessments will be guided by Project 4. With the neuroimaging core, we will develop and distribute a multimodal neuroimaging approach to quantify the severity and location of SVD. Specific Aim 1 will longitudinally assess the independent impact of SVD, controlling for the brain lesion, on acute and chronic symptoms, as well as acute and chronic language recovery. Specific Aim 2 will evaluate the mechanisms by which SVD leads to language impairments by assessing the impact of SVD and stroke lesions on connectome neural network architecture, loss of associative long-range white matter fibers and its relationship with semantic, lexical-semantic, lexical-phonological, phonological/phonetic deficits.

抽象的失语症患者之间的语言障碍可能存在很大差异。我们的神经生物学基于中风病变的模型只能部分解释失语症状。我们假设中风病灶外残留脑组织的完整性很重要，但尚未得到充分认识，失语严重程度和恢复的决定因素。众所周知，心血管危险因素会导致累积性广泛脑损伤通过小血管疾病（SVD）。在失语症文献之外，SVD 与以下疾病密切相关：认知储备能力差，对各种形式的神经损伤的弹性降低。中风幸存者失语症通常有心血管危险因素，并且通常表现出 SVD。然而，影响在我们的恢复模型中通常不考虑 SVD，即使残余脑组织负责克服功能丧失。由此可见，病灶外的 SVD 程度可能较高由于代偿能力降低，导致失语症症状更严重，恢复机会更小中风损伤。我们的目标是直接检验这个假设。我们建议结合脑残评估中风病变如何形成失语症正直。神经影像（脑部 MRI）非常适合解决这个问题。 SVD 的组成为微血管病变缺血性改变和微出血。 SVD 引起的缺血性改变可以是使用 T2 加权和 T2-FLAIR 图像通过白质高强度测量，以及可以使用磁敏感加权图像来评估微出血。 SVD 优先影响白色物质和扩散 MRI 可以提供白质微结构完整性及其相关性的额外测量与全脑神经元网络结构（大脑连接组）的关系。利用我们在中风后病变症状图谱、白质和连接组成像方面的经验我们建议对神经生物学和 SVD 对失语症的影响进行全面研究。我们的项目将建立在 SVD 评估国际指南（报告血管变化标准 nEuroimaging - STRIVE），它将开发一种创新的多模式机器学习方法，以充分评估大脑完整性。大脑完整性和语言测量将在慢性（项目 1）和急性的背景下进行评估（项目2）失语恢复。行为和语言评估将以项目 4 为指导。神经影像核心，我们将开发和分发多模式神经影像方法来量化严重程度和 SVD 的位置。具体目标 1 将纵向评估 SVD 的独立影响，控制脑损伤，关于急性和慢性症状，以及急性和慢性语言恢复。具体目标 2 将评估通过评估 SVD 和中风的影响，了解 SVD 导致语言障碍的机制连接组神经网络结构的损伤、关联性长程白质纤维的丧失及其与语义、词汇语义、词汇语音、语音/语音缺陷的关系。