Developing Behavioral and Neuroimaging Predictors of Stroke Recovery

开发中风恢复的行为和神经影像预测因子

• 批准号: 10132735
• 负责人: ANDREW S KAYSER
• 金额: --
• 依托单位: VA NORTHERN CALIFORNIA HEALTH CARE SYS
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10132735
• 关键词: Acute; Address; Behavioral; Blood Vessels; Brain; Brain region; California; Caring; Chronic; Cognition; Cognitive; Cognitive deficits; Communities; Complement; Computing Methodologies; Data; Decision Making; Dependence; Development; Diffusion; Emotional; Etiology; Event; Evolution; Functional Magnetic Resonance Imaging; Future; Hospitals; Image; Impairment; Informed Consent; Injury; Lead; Lesion; Magnetic Resonance Imaging; Marshal; Measures; Methodology; Motor; Nervous System Physiology; Neurologist; Occupational; Outcome; Patients; Pharmaceutical Preparations; Phenotype; Recovery; Recovery of Function; Rehabilitation Centers; Rehabilitation therapy; Resources; Rest; Scanning; Science; Sentinel; Site; Speech; Statistical Methods; Stroke; Structure; System; Techniques; Technology; Testing; Time; Treatment Failure; Validation; Veterans; Work; acute care; analytical method; base; behavior measurement; cognitive control; cognitive disability; cognitive function; cognitive recovery; cost; design; disability; economic cost; graph theory; improved; indexing; individual patient; innovation; network dysfunction; neuroimaging; neurological recovery; noninvasive brain stimulation; novel strategies; personalized approach; post stroke; predictive marker; programs; prospective; recruit; stem; stroke event; stroke outcome; stroke patient; stroke recovery; stroke rehabilitation; stroke therapy; tractography; traditional therapy

Given the high personal and economic costs of stroke, significant resources have been devoted to rehabilitation efforts within the VA and elsewhere. Despite this emphasis, all too often recovery after stroke remains partial, and many patients do not respond to traditional therapies. The difficulties in improving recovery after stroke stem in part from the fact that traditional approaches to predicting the effects of stroke-related brain lesions on subsequent function are often imprecise, particularly so for higher cognitive functions. Recent advances have demonstrated, for example, that similar-appearing lesions may give rise to disparate phenotypes based upon the extent to which they disrupt specific large-scale brain networks. Thus, in this proposal we will take advantage of advances in MRI methodology and analytics, within the context of validated behavioral metrics and new statistical techniques, to develop new predictors of functional recovery after stroke. Over the course of the study, patients referred from acute care hospitals to the CREC in Martinez, California for rehabilitation after stroke will be recruited to participate within two weeks of their index event. Those who provide informed consent will undergo a battery of tests to assess cognitive, emotional, motor, and other neurological function. In parallel, they will undergo structural MRI, resting state functional MRI (rs-fMRI) and diffusion tractography imaging (DTI) from which connectivity metrics derived through graph theory and Granger causality will be determined. Both behavioral and neuroimaging data will be obtained at three time points: within two weeks of the sentinel event, at three months, and at twelve months. Following the acquisition of these behavioral and imaging metrics, advanced statistical methods will be used to search for validated predictors of cognitive, emotional, and other neurological recovery at three and twelve months after stroke. As such, this proposal takes advantage of (1) validated behavioral and cognitive measures; (2) a new connectivity brain science that permits the quantification of the integrity of brain networks and has given rise to hypotheses about their evolution after injury; (3) advanced statistical techniques; and (4) longitudinal assessments in order to identify markers that will help to predict recovery after stroke. This work hopefully represents the first step in a long-term program designed to address the significant personal and economic costs of stroke in veterans and others. In addition to permitting prospective validation of any predictors of cognitive recovery, these results may also form the basis for the assessment of future approaches to stroke treatment, including individualized medication trials and targeted non-invasive brain stimulation to enhance rehabilitation efforts.

鉴于中风的个人和经济成本很高，大量资源是 致力于弗吉尼亚州和其他地方的康复工作。尽管强调了，但经常 中风后的恢复仍然是部分的，许多患者对传统疗法没有反应。这 在传统方法的一部分事实中 预测与中风相关的脑病变对随后功能的影响通常不精确， 特别是对于更高的认知功能。例如，最近的进步表明， 类似的表现病变可能会根据它们的程度引起不同的表型 破坏特定的大型大脑网络。因此，在此提案中，我们将利用进步 在MRI方法论和分析中，在经过验证的行为指标和新的背景下 统计技术，开发中风后功能恢复的新预测指标。 在研究过程中，患者从急诊医院转介给CREC 加利福尼亚州马丁内斯的中风后康复，将在两周内参与 他们的索引活动。那些提供知情同意的人将经过一系列测试以评估 认知，情感，运动和其他神经功能。同时，它们将经历结构 MRI，静止状态功能性MRI（RS-FMRI）和扩散拖拉学成像（DTI） 通过图理论得出的连通性指标将被确定。两个都 行为和神经影像学数据将在三个时间点获得：在两周内 前哨事件，三个月，十二个月。在获得这些行为之后 和成像指标，高级统计方法将用于搜索验证的预测指标 中风后三个和十二个月，认知，情感和其他神经系统恢复。 因此，该提案利用了（1）验证的行为和认知措施； （2） 一种新的连通性脑科学，允许量化大脑网络的完整性和 已经提出了有关其受伤后其进化的假设； （3）高级统计技术；和 （4）纵向评估，以确定将有助于预测中风后恢复的标记。 希望这项工作代表了长期计划的第一步，旨在解决 退伍军人和其他人的中风的巨大个人和经济成本。除了允许 对认知恢复的任何预测指标的预期验证，这些结果也可能构成基础 评估未来的中风治疗方法，包括个性化的药物试验 并针对非侵入性大脑刺激以增强康复工作。