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Accelerated Neuro-MRA Using Compressed Sensing and Constrained Reconstruction

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
负责人:
Kevin Michael Johnson
金额:
$32.94万
依托单位国家:
美国
项目类别:
财政年份:
2010
资助国家:
美国
项目状态:
已结题
起止时间:
2010-05-01 至 2019-05-31

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英文摘要
 DESCRIPTION (provided by applicant): The enormous economic and social burden of stroke demands better tools to assess the cerebrovascular system. Magnetic Resonance Imaging (MRI) is widely used in the evaluation and management of patients presenting with symptoms of stroke and is standard of care for most diagnostic neurological imaging. In the case of intact aneurysms and atherosclerotic plaques, MRI offers unique contrast mechanisms unavailable from competing technologies. In both these diseases, an interaction of the endothelial wall with hemodynamic forces exerted by blood has been established. The exact relationship between forces and subsequent vascular pathogenesis is uncertain; however, flow conditions that predispose subjects to stenosis and aneurysm formation have been identified. MRI with flow encoding (4D flow), holds potential to non-invasively probe potentially hostile hemodynamic conditions. Furthermore, endothelial status can be probed with MRI utilizing black blood imaging to visualize the uptake of exogenous contrasts. Recent MRI studies suggest a link between post-contrast arterial wall enhancement (AWE) and lesion instability, potentially indicating AWE as a measure of active inflammation and remodeling. The simultaneous depiction of hemodynamics and inflammation holds tremendous potential to improve the in-vivo characterization of diseases involving vessel wall dysfunction or active remodeling. Unfortunately, current MRI methods often suffer from signal loss due complex and turbulent flow, inadequate coverage, and limitations in spatial resolution. Furthermore, many unique MRI contrast mechanisms, such as 4D flow, are not practical for clinical imaging due to extended scan times with required resolutions for accurate quantification. This proposal suggests a next generation of accelerated imaging technology for the comprehensive evaluation of intracranial stenoses and aneurysms that will rival and surpass computed tomography (CT) through the symbiotic development of new image acquisition and constrained reconstruction methods. In particular, we aim to develop methods for robust quantitative MRA (qMRA), a multi-contrast high resolution vascular imaging paradigm. In order to achieve the required combinations of artifact reduction, spatial resolution and signal-to-noise ratio, we harness acquisition strategies utilizin novel ultra-short echo time acquisition techniques in combination with robust model based reconstruction techniques. By acquiring data more rapidly and in a more efficient manor, these strategies allow improved spatial resolution while mitigating diagnostic obscuring artifacts from the complex flow. We aim to harness these advances to into a synergistic combination of angiographic MRI with highly accelerated 4D-flow and vessel wall imaging to investigate the interactions between vascular remodeling, inflammation, and hemodynamics in intact intracranial aneurysms and atherosclerotic lesions. The ultimate goal is to observed correlations between hostile hemodynamic conditions and arterial wall enhancement utilizing non-invasive imaging, which may provide new clinical treatment paradigms and improve the management of a broad array of neurovascular diseases.
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Non-Invasive Imaging Markers to Elicit the Role of Vascular Involvement in Alzheimer’s Disease
  • 批准号:
    10370542
  • 项目类别:
  • 资助金额:
    $60.82万
  • 财政年份:
    2022
  • 负责人:
    Kevin Michael Johnson
  • 依托单位:
Optimizing MRI for Neurologic Screening using Radiologist Crowdsourcing
  • 批准号:
    10527680
  • 项目类别:
  • 资助金额:
    $41.43万
  • 财政年份:
    2022
  • 负责人:
    Kevin Michael Johnson
  • 依托单位:
Non-Invasive Imaging Markers to Elicit the Role of Vascular Involvement in Alzheimer’s Disease
  • 批准号:
    10560465
  • 项目类别:
  • 资助金额:
    $69.06万
  • 财政年份:
    2022
  • 负责人:
    Kevin Michael Johnson
  • 依托单位:
MRI methods for high resolution imaging of the lung
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