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Multimodal Neuroimaging: Advanced Tracking of Longitudinal Aphasia Recovery

Multimodal Neuroimaging: Advanced Tracking of Longitudinal Aphasia Recovery
多模态神经影像:纵向失语症恢复的高级跟踪
批准号:
9888972
负责人:
Venkatagiri Krishnamurthy
金额:
$0.0万
依托单位国家:
美国
项目类别:
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-04-01 至 2024-03-31

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中文摘要
翻译
中风后恢复的最初几个月是语言自发变化的关键时期, 功能和潜在的神经过程进行观察。在这段时间内对大脑变化进行成像可能会有所帮助 临床医生确定神经过程的恢复,但必须以不受中风混淆的方式进行, 引起脑血管变化。这一点很重要,因为有证据表明,脑血管损伤会引起 在中风后恢复的最初几个月,一系列的变化导致血管重塑。这 CDA 2提案通过开发一套集成的多模态神经成像解决了这一差距 方法分离神经和血管的变化,在恢复语言功能,从早期亚, 失语症患者的急性期(卒中后2-6周)至晚期亚急性期(卒中后12-16周)。 在第一个目标中,我们将确定是否从任务血氧中回归出血管信号(CVR和CBF) 每个时间点(早期和晚期)的水平依赖(BOLD)功能性MRI(fMRI)活动将改善 任务-BOLD活动的变化与词汇判断行为变化之间的关系。我们的方法 将是跟踪任务BOLD功能磁共振成像活动,从早期到晚期亚急性期,而病人参加了一个 听觉词识别任务(词汇决策)在这两个阶段。我们将把我们的宣传计划应用于 使血管信号退化BOLD振幅的变化(从敏化和未敏化/标准 任务BOLD功能磁共振成像活动),然后将与词汇决策行为的变化。我们希望看到这一点 神经敏感任务BOLD fMRI活动与词汇判断测量有较强的相关性 比未致敏的/标准的BOLD功能磁共振成像信号。在第二个目标中,我们将确定是否删除 静息态BOLD(rs-BOLD)血管信号,在每个时间点从剩余语言网络获得 点(早期和晚期阶段)将改善rs-BOLD网络测量的变化与 语言(特定领域和一般领域)措施的变化。我们的方法将是收购rs-BOLD 失语症患者早期和晚期亚急性期的fMRI扫描。然后我们将进行一次全面的 大脑体素网络分析(即模块化)从剩余语言中选择先验种子ROI, 相关脑区为了使rs-BOLD功能磁共振成像信号对神经连接敏感,我们将进行同样的实验。 在体素水平上的敏化方案(如目标1中所述)。然后我们将识别语言网络的变化 测量(来自致敏和未致敏/标准rs-BOLD fMRI),并将其与语言相关联 行为(域特定和域一般)。在完成目标2后,我们希望拟议的 敏化方案增强了rs-BOLD网络测量对脑网络重组的敏感性, 语言特异性和非语言特异性认知域。在第三个目标中,我们将确定血管 早期测量(CBF和CVR)可以预测语言行为的变化(西方失语症成套测验 理解力和费城测验。我们的方法是招募 失语症的早期亚急性期,并测量他们的血管和行为恢复在早期和晚期 时间点。具体来说,我们将在早期时间点获得体素方面的CBF和CVR测量,并使用 采用多元回归方法,我们将对血管指标进行建模,以预测临床相关指标的变化。 语言行为在完成目标3后,我们期望获得临床可翻译的数据 驱动的(基于血管生理学的)预测模型,可用于识别必须 改变以支持语言行为的改进。本CDA 2的预期成果是整合 多模式神经成像工具,以更准确地预测亚语言功能的纵向恢复, 急性失语症患者。长期目标是确定如何最好地使用神经成像工具, 提供准确的个性化语言恢复轨迹并预测治疗结果。
英文摘要
The first few months of post-stroke recovery is a critical time period where spontaneous changes in language functions and underlying neural processes are observed. Imaging brain changes during this time may help clinicians identify the recovery of neural processes, but must be done in a way that is not confounded by stroke- induced cerebrovascular changes. This is important, as evidence suggests that cerebrovascular insult will elicit a cascade of changes that leads to vascular remodeling in the first few months of post-stroke recovery. This CDA2 proposal addresses this gap through development of a set of integrated multi-modal neuroimaging methodologies to dissociate neural and vascular changes during recovery of language functions from early sub- acute (2-6 weeks post-stroke) to late sub-acute phase (12-16 weeks post-stroke) in patients with aphasia. In the first aim, we will determine if regressing out the vascular signals (CVR and CBF) from task Blood Oxygen Level Dependent (BOLD) functional MRI (fMRI) activity at each time point (early and late phase) will improve the relationship between change in task-BOLD activity and change in lexical decision behavior. Our approach will be to track task-BOLD fMRI activity from early to late sub-acute phase while the patients participate in an auditory word recognition task (lexical decision) in both phases. We will apply our sensitization scheme for regressing out vascular signals. The change in BOLD amplitude (from sensitized and unsensitized/standard task BOLD fMRI activity) will then be related to changes in the lexical decision behavior. We expect to see that the neuro-sensitized task BOLD fMRI activity will have a stronger correlation with lexical decision measures than the unsensitized/standard BOLD fMRI signal. In the second aim, we will determine if removing the vascular signals from resting state BOLD (rs-BOLD) acquired from residual language network at each time point (early and late phase) will improve the relationship between change in rs-BOLD network measures and change in language (domain specific and domain general) measures. Our approach will be to acquire rs-BOLD fMRI scans during the early and late sub-acute phase in patients with aphasia. We will then carry out a whole brain voxel-wise network analysis (i.e. modularity) choosing apriori seed ROI from the residual language- related brain areas. To sensitize the rs-BOLD fMRI signals to neural connections, we will carry out the same sensitization scheme (as described in Aim 1) at a voxel level. We will then identify changes in language network measures (from sensitized and unsensitized/standard rs-BOLD fMRI) and correlate them with language behavior (domain specific and domain general). After completing Aim 2, it is our expectation that the proposed sensitization scheme enhances the sensitivity of rs-BOLD network measures to brain network reorganization in language specific and language-nonspecific cognitive domains. In the third aim, we will determine if vascular measures (CBF and CVR) from early phase can predict change in language behavior (Western Aphasia Battery measure of comprehension and Philadelphia Naming Test. Our approach will be to recruit patients with aphasia in the early sub-acute phase and measure their vascular and behavioral recovery at both early and late time points. Specifically, we will acquire voxel-wise CBF and CVR measures at the early time point, and using multiple regression approach, we will model the vascular measures to predict change in clinically-relevant language behavior. After completing Aim 3, it is our expectation that we will have a clinically translatable data driven (vascular physiology-based) prediction model that can be used to identify brain regions that must change to support improvements in language behavior. The expected outcome of this CDA2 is an integration of multimodal neuroimaging tools to more accurately predict longitudinal recovery of language functions in sub- acute patients with aphasia. The long-term goal is to determine how neuroimaging tools can best be used to provide accurate individualized language recovery trajectories and predict treatment outcome.
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Multimodal Neuroimaging: Advanced Tracking of Longitudinal Aphasia Recovery
  • 批准号:
    10574497
  • 项目类别:
  • 资助金额:
    $0.0万
  • 财政年份:
    2019
  • 负责人:
    Venkatagiri Krishnamurthy
  • 依托单位:
Multimodal Neuroimaging: Advanced Tracking of Longitudinal Aphasia Recovery
  • 批准号:
    10385713
  • 项目类别:
  • 资助金额:
    $0.0万
  • 财政年份:
    2019
  • 负责人:
    Venkatagiri Krishnamurthy
  • 依托单位:
Multimodal Neuroimaging: Advanced Tracking of Longitudinal Aphasia Recovery
  • 批准号:
    10132738
  • 项目类别:
  • 资助金额:
    $0.0万
  • 财政年份:
    2019
  • 负责人:
    Venkatagiri Krishnamurthy
  • 依托单位:
海外基金