Rapid Structure-Function MRI of the Lung for Post-COVID-19 Management
用于 COVID-19 后管理的肺部快速结构功能 MRI
基本信息
- 批准号:10831646
- 负责人:
- 金额:$ 108.34万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2021
- 资助国家:美国
- 起止时间:2021-09-03 至 2025-09-02
- 项目状态:未结题
- 来源:
- 关键词:
项目摘要
Project Summary
The pandemic of coronavirus disease 2019 (COVID-19) has presented an unprecedented crisis and challenge
to public health, with tremendous health care and economic burden to our society. Given the high morbidity of
this new disease and increasing findings on COVID-associated complications, it has emerged as an important
and urgent clinical need to investigate the sequelae in patients recovered from COVID-19 (post-COVID patients),
particularly with respect to residual long-term lung damage such as post-COVID decline of pulmonary function
and/or development of lung structure abnormality. This will ensure that the long-term outcomes of post-COVID
patients can be studied, better understood, and properly managed. At present, Computed Tomography (CT) is
the gold standard for imaging lung anatomy, but its radiation burden precludes frequent longitudinal evaluations.
Pulmonary function is currently evaluated by spirometry or plethysmography, which provide global measures of
function but this is inadequate for assessing the extent of disease heterogeneity. The overarching aim of this
application is to develop novel rapid free-breathing four-dimensional (4D=3D+motion) lung MRI techniques that
will enable frequent evaluation of lung anatomy and function in the longitudinal follow-ups of post-COVID patients.
These new methods will be based on a combination of compressed sensing and golden-angle radial acquisition,
with incorporation of the latest advances in deep learning, which are all pioneered by our research team.
Specifically, we propose to develop, optimize and evaluate a 10-minute free-breathing lung MRI protocol that
will enable one-stop-shop characterization of whole lung anatomy and spatially-resolved pulmonary function
without administration of contrast media. The overall hypothesis is that the proposed 4D MRI techniques can
serve as a potential radiation-free alternative to CT for longitudinal evaluation of lung structure change and a
better alternative to spirometry for deriving regional function parameters that could provide additional novel
insights into the heterogeneity of lung ventilation and associated lung diseases. Our proposal includes the
following three specific aims: (i) development of motion-resolved 4D UTE-MRI (MRI with ultra-shot echo times)
for submillimeter resolution free-breathing whole-lung imaging, (ii) development of deep breathing-based 4D
UTE-MRI for deriving global/regional pulmonary function parameters, and (iii) development of deep learning-
based lung segmentation for efficient and automated estimation of pulmonary function parameters. Successful
completion of this project will deliver non-invasive, non-contrast-enhanced, and free-breathing 4D MRI
techniques for rapid assessment of lung anatomy and pulmonary function. Given the overwhelming prevalence
of COVID-19 and the overall cumulative incidence in the United States, our novel imaging methods would provide
a unique opportunity to augment post-COVID care, particularly for identifying COVID-19-induced lung fibrosis in
a timely manner and for studying the longitudinal changes of lung anatomy and global/regional pulmonary
function. These methods could also be extended for evaluation of other pulmonary diseases.
项目摘要
2019年冠状病毒病大流行(新冠肺炎)带来了前所未有的危机和挑战
对公众健康造成了巨大的医疗保健和经济负担。鉴于……的高发病率
这种新的疾病和越来越多的发现与冠状病毒相关的并发症,它已经成为一个重要的
临床迫切需要调查新冠肺炎康复患者(冠状病毒感染后患者)的后遗症,
尤其是关于残存的长期肺损伤,如冠状病毒感染后肺功能下降
和/或发展为肺结构异常。这将确保冠状病毒感染后的长期结果
可以对患者进行研究、更好地理解和适当地管理。目前,计算机断层扫描(CT)是
肺解剖成像的黄金标准,但其辐射负担排除了频繁的纵向评估。
目前,肺功能的评估方法是肺活量测定法或体积描记法,它们提供了对
功能,但这不足以评估疾病异质性的程度。这样做的首要目标是
应用是开发新的快速自由呼吸四维(4D=3D+运动)肺MRI技术
将能够在COVID后患者的纵向随访中频繁地评估肺解剖和功能。
这些新方法将基于压缩传感和黄金角径向捕获的组合,
融合了深度学习领域的最新进展,这些都是我们的研究团队开创的。
具体地说,我们建议开发、优化和评估一种10分钟自由呼吸的肺部MRI方案,该方案
将实现对整个肺解剖和空间分辨肺功能的一站式表征
不使用造影剂。总体假设是,所提出的4D MRI技术可以
作为一种潜在的无辐射替代CT,用于纵向评估肺结构变化和
肺活量测定的更好的替代方法,用于得出区域功能参数,可以提供额外的新的
对肺通风的异质性和相关肺部疾病的洞察。我们的建议包括
以下三个具体目标:(I)开发运动分辨率4D UTE-MRI(具有超快射回波时间的MRI)
用于亚毫米分辨率自由呼吸全肺成像:(Ii)基于深呼吸的4D的发展
UTE-MRI用于得出全球/区域肺功能参数,以及(Iii)深度学习的发展-
基于肺分割的肺功能参数的高效和自动估计。成功
该项目的完成将提供非侵入性、非对比增强和自由呼吸的4D MRI
肺解剖和肺功能的快速评估技术。鉴于压倒性的流行率
新冠肺炎和美国的总累积发病率,我们的新成像方法将提供
一个独特的机会来加强COVID后的护理,特别是在识别新冠肺炎诱导的肺纤维化方面
及时研究肺解剖和全肺/局部肺的纵向变化
功能。这些方法也可推广应用于其他肺部疾病的评估。
项目成果
期刊论文数量(4)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Golden-Angle Radial MRI: Basics, Advances, and Applications.
- DOI:10.1002/jmri.28187
- 发表时间:2022-07
- 期刊:
- 影响因子:4.4
- 作者:Feng, Li
- 通讯作者:Feng, Li
Performance of spiral UTE-MRI of the lung in post-COVID patients.
- DOI:10.1016/j.mri.2022.12.002
- 发表时间:2023-02
- 期刊:
- 影响因子:2.5
- 作者:Fauveau, Valentin;Jacobi, Adam;Bernheim, Adam;Chung, Michael;Benkert, Thomas;Fayad, Zahi A.;Feng, Li
- 通讯作者:Feng, Li
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Li Feng其他文献
A Novel Web Service QoS Collaborative Prediction Approach with Biased Baseline
一种新颖的带偏差基线的 Web 服务 QoS 协作预测方法
- DOI:
- 发表时间:
2015 - 期刊:
- 影响因子:0
- 作者:
Shen Limin;Chen Zhen;Li Feng - 通讯作者:
Li Feng
Li Feng的其他文献
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{{ truncateString('Li Feng', 18)}}的其他基金
Rapid Motion-Robust and Easy-to-Use Dynamic Contrast-Enhanced MRI for Liver Perfusion Quantification
用于肝脏灌注定量的快速运动稳健且易于使用的动态对比增强 MRI
- 批准号:
10831643 - 财政年份:2023
- 资助金额:
$ 108.34万 - 项目类别:
3D Free-Breathing Fat and Iron Corrected T1 Mapping
3D 自由呼吸脂肪和铁校正 T1 映射
- 批准号:
10432272 - 财政年份:2022
- 资助金额:
$ 108.34万 - 项目类别:
3D Free-Breathing Fat and Iron Corrected T1 Mapping
3D 自由呼吸脂肪和铁校正 T1 映射
- 批准号:
10831651 - 财政年份:2022
- 资助金额:
$ 108.34万 - 项目类别:
Rapid Motion-Robust and Easy-to-Use Dynamic Contrast-Enhanced MRI for Liver Perfusion Quantification
用于肝脏灌注定量的快速运动稳健且易于使用的动态对比增强 MRI
- 批准号:
10430267 - 财政年份:2021
- 资助金额:
$ 108.34万 - 项目类别:
Rapid Motion-Robust and Easy-to-Use Dynamic Contrast-Enhanced MRI for Liver Perfusion Quantification
用于肝脏灌注定量的快速运动稳健且易于使用的动态对比增强 MRI
- 批准号:
10297597 - 财政年份:2021
- 资助金额:
$ 108.34万 - 项目类别:
Rapid Structure-Function MRI of the Lung for Post-COVID-19 Management
用于 COVID-19 后管理的肺部快速结构功能 MRI
- 批准号:
10181576 - 财政年份:2021
- 资助金额:
$ 108.34万 - 项目类别:
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