Non-Invasive Imaging Markers to Elicit the Role of Vascular Involvement in Alzheimer’s Disease

非侵入性成像标记物可揭示血管受累在阿尔茨海默病中的作用

基本信息

  • 批准号:
    10370542
  • 负责人:
  • 金额:
    $ 60.82万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2022
  • 资助国家:
    美国
  • 起止时间:
    2022-02-15 至 2027-01-31
  • 项目状态:
    未结题

项目摘要

ABSTRACT Alzheimer's disease (AD) is the 6th leading cause of death in the United States and its prevalence continues to rise. AD has no clinically available curative treatments and findings from active clinical trials testing novel disease-modifying therapeutics have thus far been disappointing. There is, therefore, a growing urgency to identify early markers of AD, causative factors leading to dementia, and alternative treatment approaches for halting the global crisis posed by this debilitating condition. Cardiovascular disease, as well as cerebrovascular disease (CVD), has a strong link with both mild cognitive impairment and AD dementia; however, the question of whether CVD modulates underlying pathophysiology of AD has only recently begun receiving attention. To provide insights into AD relationships, non-invasive Magnetic Resonance Imaging (MRI) is being utilized in longitudinal studies of AD risk-enriched populations. The present project goes far beyond currently available MRI techniques which lack sensitivity and specificity to address key vascular hypotheses in AD. MRI methods commonly employed today such as fluid attenuation and susceptibility imaging only indirectly measure CVD and cannot inform on the dynamic vascular motion and hemodynamic phenomena that have been indicated in animal models to affect AD pathology. To address these gaps, the overarching objective of this project is to enable characterization of cerebrovascular involvement in AD through the development and study integration of a novel battery of non-invasive, MRI-based measures of cerebrovascular health. Building upon foundational studies at our institution, this work proposes innovative MRI technology to improve characterization of CVD in AD, specifically vascular stiffening and its relationship with cerebrovascular flow dynamics. We propose an ensemble of motion encoded MRI techniques which provide detailed depiction of autoregulatory flow dynamics and vascular stiffness in both the macro and micro vasculature. In this project, the novel methods will be technically developed harnessing deep learning from vast prior imaging data, validated with optical imaging, and characterized in healthy human subjects. We then will obtain key data characterizing cerebrovascular changes in a study of AD biomarker confirmed subjects with the overall goal of identifying the modifying effect of vascular disease on the symptom expression of cognitive impairment, AD biomarker accumulation, and neurodegeneration. Our pilot data suggest subjects with AD have a premature increase in arterial stiffness and decreased fluctuations in cerebral blood flow. Upon completion, this study will provide insights into which specific aspects of CVD are primary factors moderating AD interactions. Participants targeted for this study have extensive existing AD biomarker data and are being followed longitudinally through studies within the Wisconsin Alzheimer's Disease Research Center. The methodologies will be uniquely positioned for incorporation into large longitudinal cohort studies investigating AD mechanisms and evaluating putative risk and protective factors.
摘要

项目成果

期刊论文数量(0)
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Kevin Michael Johnson其他文献

Kevin Michael Johnson的其他文献

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{{ truncateString('Kevin Michael Johnson', 18)}}的其他基金

Optimizing MRI for Neurologic Screening using Radiologist Crowdsourcing
利用放射科医生众包优化 MRI 进行神经系统筛查
  • 批准号:
    10527680
  • 财政年份:
    2022
  • 资助金额:
    $ 60.82万
  • 项目类别:
Non-Invasive Imaging Markers to Elicit the Role of Vascular Involvement in Alzheimer’s Disease
非侵入性成像标记物可揭示血管受累在阿尔茨海默病中的作用
  • 批准号:
    10560465
  • 财政年份:
    2022
  • 资助金额:
    $ 60.82万
  • 项目类别:
MRI methods for high resolution imaging of the lung
用于肺部高分辨率成像的 MRI 方法
  • 批准号:
    10153865
  • 财政年份:
    2018
  • 资助金额:
    $ 60.82万
  • 项目类别:
MRI methods for high resolution imaging of the lung
用于肺部高分辨率成像的 MRI 方法
  • 批准号:
    9898434
  • 财政年份:
    2018
  • 资助金额:
    $ 60.82万
  • 项目类别:
Accelerated Neuro-MRA Using Compressed Sensing and Constrained Reconstruction
使用压缩感知和约束重建加速神经 MRA
  • 批准号:
    8964845
  • 财政年份:
    2010
  • 资助金额:
    $ 60.82万
  • 项目类别:

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