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中文摘要
翻译
项目摘要/摘要 在美国,冠状动脉疾病(CAD)是主要的死亡原因。临床黄金标准 诊断和指导冠心病患者的治疗是基于有创的基于导管的程序,如 如用于解剖评估的X-线冠状动脉造影术(XCA)或用于生理学的血流储备分数(FFR) 评估。然而,这种侵入性手术存在成本和风险。这样的担忧是 进一步突出的事实是,大型研究表明,近三分之二的患者在最初的治疗中被转介 选择性侵袭性XCA未发现明显狭窄。因此,更好的非侵入性诊断工具 都是需要的。 心脏磁共振成像(CMR)是唯一一种能够全面评估心脏疾病的无创性成像方法。 单次检查中的CAD,包括心肌灌注、心功能和存活能力的评估, 以及狭窄的血管造影评估,而不需要电离辐射。这些属性还允许 用于临床上可能显示的重复检测。然而,尽管它有巨大的潜力作为非 侵入性看门人昂贵的侵入性程序,漫长的检查时间阻碍了CMR 临床翻译。尽管已经提出了几种加速成像技术,但这些技术仍然需要 在覆盖范围、分辨率和信噪比之间进行权衡。在本提案中,我们将开发和验证 新的获取和重建策略能够实现高速高分辨率的全心CMR 在10分钟内参加CAD综合评估考试。我们将发展快而低效 吸收率外部体积抑制模块,以减少来自胸部的混叠伪影来源 在后面。这将使得在灌注和电影CMR中同时进行多层成像的速率更高, 以最小的噪声放大大幅提高覆盖范围。对于冠状动脉核磁共振和生存能力成像, CMR将引入同步多层板成像,促进高各向同性分辨率的采集 覆盖速度很快。这些收购将辅之以常规化的堵漏和耐心治疗。 特定的机器学习重建,以进一步消除伪影和噪音。最后,我们将实施和 在一组疑似CAD患者中验证所建议的快速全面CMR检查,比较我们的 采用常规临床cmr评估功能、血流灌注和生存能力的方法,以及 有创XCA在冠状动脉狭窄评估中的应用这个项目的成功完成具有潜力 将CMR转变为用于安全和准确诊断CAD的领先快速非侵入性工具,提高 每年为数百万有胸痛和其他冠心病症状的患者提供医疗保健。
英文摘要
PROJECT SUMMARY/ABSTRACT Coronary artery disease (CAD) is the leading cause of death in the United States. The clinical gold standards to diagnose and guide treatment of patients with CAD are based on invasive catheter-based procedures, such as x-ray coronary angiography (XCA) for anatomic assessment or fractional flow reserve (FFR) for physiologic assessment. However, there are costs and risks associated with such invasive procedures. Such concerns are further highlighted by the fact that large studies have shown nearly two-thirds of patients referred for their initial elective invasive XCA were found to have no significant stenoses. Thus, better non-invasive diagnostic tools are needed. Cardiac MRI (CMR) is the only non-invasive imaging modality that provides a comprehensive assessment of CAD in a single examination, including an assessment of myocardial perfusion, cardiac function and viability, as well as angiographic evaluation of stenoses, without requiring ionizing radiation. These properties also allow for repeat testing as may be clinically indicated. However, despite its great potential to serve as the non- invasive gatekeeper for costly invasive procedures, lengthy examination times have prevented CMR from clinical translation. Although several accelerated imaging techniques have been proposed, these still require trade-offs between coverage, resolution and signal-to-noise ratio. In this proposal, we will develop and validate novel acquisition and reconstruction strategies to enable a highly accelerated high-resolution whole heart CMR exam for comprehensive CAD assessment in under 10 minutes. We will develop fast and low specific absorption rate outer volume suppression modules to reduce the source of aliasing artifacts from the chest and the back. This will enable higher rates for simultaneous multi-slice imaging in perfusion and cine CMR, improving coverage substantially with minimal noise amplification. For coronary MRI and viability imaging, simultaneous multi-slab imaging will be introduced to CMR, facilitating high isotropic resolution acquisitions with fast coverage. These acquisitions will be supplemented with regularized leakage-blocking and patient- specific machine learning reconstructions for further artifact and noise removal. Finally, we will implement and validate the proposed rapid comprehensive CMR exam in a cohort of suspected CAD patients, comparing our approach with conventional clinical CMR for the assessment of function, perfusion, and viability, and with invasive XCA for the assessment of coronary stenosis. Successful completion of this project has the potential to transform CMR into a leading rapid non-invasive tool for safe and accurate diagnosis of CAD, improving the healthcare of several million patients with chest pain and other CAD symptoms annually.
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Robust and Efficient Learning of High-Resolution Brain MRI Reconstruction from Small Referenceless Data
  • 批准号:
    10584324
  • 项目类别:
  • 资助金额:
    $53.06万
  • 财政年份:
    2023
  • 负责人:
    Mehmet Akcakaya
  • 依托单位:
Rapid Comprehensive Cardiac MRI Exam for Diagnosis of Coronary Artery Disease
  • 批准号:
    10383694
  • 项目类别:
  • 资助金额:
    $51.04万
  • 财政年份:
    2020
  • 负责人:
    Mehmet Akcakaya
  • 依托单位:
Novel Quantitative MRI Techniques for the Assessment of Cardiac Fibrosis without Gadolinium Contrast
  • 批准号:
    10319011
  • 项目类别:
  • 资助金额:
    $22.72万
  • 财政年份:
    2020
  • 负责人:
    Mehmet Akcakaya
  • 依托单位:
Novel Quantitative MRI Techniques for the Assessment of Cardiac Fibrosis without Gadolinium Contrast
  • 批准号:
    9977670
  • 项目类别:
  • 资助金额:
    $18.73万
  • 财政年份:
    2020
  • 负责人:
    Mehmet Akcakaya
  • 依托单位:
海外基金