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
• 负责人: Li Feng
• 金额: $ 37.04万
• 依托单位: ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-03 至 2023-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10181576
• 关键词: 3-Dimensional; 4D Imaging; 4D MRI; Adult Respiratory Distress Syndrome; Affect; Air; Anatomy; Breathing; COVID-19; COVID-19 monitoring; COVID-19 pandemic; COVID-19 patient; Caring; Chronic; Clinical; Contrast Media; Development; Diagnostic; Dimensions; Disease; Early identification; Economic Burden; Ensure; Evaluation; Foundations; Four-dimensional; Gold; Healthcare; Heterogeneity; Image; Imaging Techniques; Incidence; Inflammation; Investigation; Ionizing radiation; Lead; Longitudinal Studies; Lung; Lung Capacity; Lung diseases; Magnetic Resonance Imaging; Measures; Methods; Morbidity - disease rate; Motion; Outcome; Patients; Performance; Plethysmography; Prevalence; Protocols documentation; Public Health; Pulmonary Fibrosis; Pulmonary function tests; Radial; Radiation; Radiation exposure; Recording of previous events; Research; Residual state; Resolution; Respiratory Failure; Risk; Scanning; Societies; Spirometry; Structural defect; Structure; Time; United States; Variant; Viral Pneumonia; X-Ray Computed Tomography; base; care burden; chest computed tomography; clinical imaging; coronavirus disease; deep learning; disease heterogeneity; image reconstruction; imaging modality; insight; lung basal segment; lung development; lung imaging; lung injury; lung lobe; lung volume; novel; prevent; pulmonary function; pulmonary function decline; rapid technique; respiratory; soft tissue; ventilation; volunteer

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年冠状病毒病的大流行（Covid-19）提出了前所未有的危机和挑战 为公共卫生，给我们的社会带来巨大的医疗保健和经济负担。考虑到高发病 这种新疾病和关于共同相关并发症的发现的增加，它已成为重要的 紧急临床需要调查从1900（旋转后患者）中回收的患者的后遗症， 特别是关于残留的长期肺损伤，例如肺部功能后旋转后下降 和/或肺结构异常的发展。这将确保兴建后的长期结果 可以研究，更好地理解和适当管理患者。目前，计算机断层扫描（CT）为 成像肺解剖结构的金标准，但其辐射负担排除了频繁的纵向评估。 目前，通过肺活量法或散布物学评估肺功能 功能但这是评估疾病异质性程度的不足。总体目的 应用是开发新型的快速自由呼吸四维（4D = 3D+运动）肺MRI技术 将在旋转后患者的纵向随访中频繁评估肺解剖结构和功能。 这些新方法将基于压缩感应和金角径向采集的组合， 随着深度学习的最新进展，我们的研究团队都率先进行了启示。 具体而言，我们建议开发，优化和评估10分钟的自由呼吸肺MRI协议，该方案 将使整个肺解剖结构和空间分辨的肺功能一站式表征 没有对比媒体的管理。总体假设是提出的4D MRI技术可以 作为CT的潜在无辐射替代品，用于纵向评估肺结构变化和A 更好地替代肺活量测定法，以推导可提供其他新颖的区域功能参数 洞察肺通风和相关肺部疾病的异质性。我们的建议包括 以下三个具体目的：（i）运动分辨的4D UTE-MRI（具有超射击回波时间的MRI）的发展 对于亚毫米分辨率自由呼吸全肺成像，（ii）基于深呼吸的4D开发 用于得出全球/区域肺功能参数的UTE-MRI，以及（iii）深度学习的发展 - 基于肺部功能参数的有效和自动估计的基于肺部分割。成功的 该项目的完成将提供非侵入性，非对抗增强和自由呼吸4D MRI 快速评估肺解剖和肺功能的技术。考虑到压倒性的流行 covid-19和美国的整体累积发生率，我们的新成像方法将提供 增强杂化后护理的独特机会，特别是用于识别COVID-19诱导的肺纤维化 及时的方式，并研究肺解剖学和全球/区域肺的纵向变化 功能。这些方法也可以扩展以评估其他肺部疾病。