Novel Computational Framework for Free-Breathing & Ungated Dynamic MRI

自由呼吸的新颖计算框架

• 批准号: 9217649
• 负责人: Mathews Jacob
• 金额: $ 48.92万
• 依托单位: UNIVERSITY OF IOWA
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-04-01 至 2020-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9217649
• 关键词: 3-Dimensional; Abdomen; Address; Adult; Adverse effects; Algorithms; Breathing; Cardiac; Cardiopulmonary; Cardiovascular Diseases; Cardiovascular system; Child; Clinical Protocols; Comorbidity; Custom; Data; Data Set; Dependency; Development; Dimensions; Epidemic; Evaluation; Event; Fibrosis; Financial compensation; Formulation; Gadolinium; Goals; Image; Imagery; Joints; Learning; Lung; Magnetic Resonance Imaging; Measurement; Measures; Methods; Modeling; Motion; Myocardial perfusion; Obesity; Organ; Patients; Performance; Perfusion; Phase; Physics; Physiologic pulse; Physiological; Population; Prevalence; Protocols documentation; Public Health; Radiology Specialty; Recovery; Research; Resolution; Risk; Risk stratification; Sampling; Scanning; Scheme; Signal Transduction; Slice; Stress; Structure; Three-Dimensional Image; Three-Dimensional Imaging; Time; Variant; cardiovascular risk factor; cardiovascular visualization; computer framework; cost; flexibility; heart imaging; heart motion; high dimensionality; image reconstruction; imaging modality; improved; innovation; liver imaging; lung imaging; novel; perfusion imaging; public health relevance; reconstruction; respiratory; signal processing

 DESCRIPTION (provided by applicant): Obesity has reached global epidemic proportions in both adults and children. Obesity has a major impact on cardiovascular (CV) disorders because of its adverse effects on cardiac function, structure, and various CV risk factors. MR imaging has great potential in estimating these changes and stratifying obese subjects for risk of major advanced cardiac events. However, the physiological changes resulting from obesity and associated pulmonary comorbidities often make it difficult for many obese subject to comply with current clinical protocols that require several breath holds and long scan time. Short free breathing protocols are urgently needed for the cardiac evaluation of obese subjects. The main goal of this proposal is to develop a short 3-D free-breathing & un-gated cardiac imaging protocol to evaluate cardiac structure, function, perfusion, and fibrosis in obese subjects in around twenty minutes of scan time. This protocol is enabled by synergistic developments in novel ungated sequences and a novel manifold regularization framework. The reconstruction framework, which exploits the manifold structure of images and patches in the dataset, is ideally suited to harness the flexibility and high acquisition efficiency of ungated 3-D sequences. The main hypothesis is that the implicit motion compensated and motion resolved reconstruction scheme will provide good recovery of the datasets in the protocol from highly under sampled data. We will quantitatively determine the utility of the free-breathing & ungated framework to provide reconstructions that are equivalent to current breath-hold acquisitions. This framework is expected to significantly improve the compliance of obese subjects. In addition, this approach also provides co-registered 3-D volumes with different contrasts, which will greatly improve quantification, visualization, and radiologic interpretation. The manifold learning framework is powerful and highly innovative; it can be readily applied to a variety of dynamic applications beyond cardiac imaging (vocal tract imaging, liver imaging, lung imaging). Our team is well qualified to perform the proposed research because of our combined scope and breadth in expertise (including signal processing, MR physics, and radiology), in addition to the extensive preliminary data.

 描述（由申请人提供）：肥胖在成人和儿童中已达到全球流行病的比例。肥胖对心血管（CV）疾病有重大影响，因为它对心脏功能、结构和各种CV风险因素有不良影响。MR成像在估计这些变化和对肥胖受试者进行重大晚期心脏事件风险分层方面具有很大的潜力。然而，由肥胖和相关的肺部合并症引起的生理变化通常使得许多肥胖受试者难以遵守需要几次屏气和长扫描时间的当前临床方案。短期自由呼吸协议是迫切需要的心脏评估肥胖受试者。该提案的主要目标是开发一种短的3-D自由呼吸和非门控心脏成像协议，以在大约20分钟的扫描时间内评估肥胖受试者的心脏结构、功能、灌注和纤维化。该协议是通过新的非门控序列和新的流形正则化框架的协同发展实现的。重建框架，它利用了数据集中的图像和补丁的流形结构，非常适合利用非门控3-D序列的灵活性和高采集效率。主要假设是隐式运动补偿和运动分辨重建方案将从高度欠采样的数据中提供协议中的数据集的良好恢复。我们将定量地确定自由呼吸和非门控框架的效用，以提供相当于当前屏气采集的重建。预计该框架将显著改善肥胖受试者的依从性。此外，该方法还提供了具有不同对比度的共配准3D体积，这将大大改善量化、可视化和放射学解释。流形学习框架功能强大且具有高度创新性;它可以轻松应用于心脏成像以外的各种动态应用（声道成像，肝脏成像，肺部成像）。我们的团队完全有资格进行拟议的研究，因为我们的专业知识（包括信号处理，MR物理学和放射学）的综合范围和广度，以及广泛的初步数据。