Novel algorithm for improved contrast enhanced cardiac MRI

改进对比增强心脏 MRI 的新算法

• 批准号: 8243134
• 负责人: Mathews Jacob
• 金额: $ 23.61万
• 依托单位: UNIVERSITY OF IOWA
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-01-01 至 2013-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8243134
• 关键词: 3-Dimensional; Acceleration; Address; Algorithms; Bolus Infusion; Breathing; Cardiac; Cardiology; Clinical; Data; Databases; Defect; Development; Failure; Gadolinium; Goals; Health; Heart; Heart Diseases; Human; Image; Imaging problem; Kinetics; Learning; Magnetic Resonance Imaging; Measures; Methods; Minor; Modeling; Morphologic artifacts; Motion; Myocardial; Myocardial Ischemia; Myocardial perfusion; Patients; Performance; Perfusion; Peripheral Nerve Stimulation; Physics; Public Health; Qualifying; Quantitative Evaluations; Radiology Specialty; Research; Resolution; Risk; Scanning; Scheme; Signal Transduction; Slice; Structure; Techniques; Time; Validation; Variant; Weight; base; compliance behavior; computerized data processing; data sharing; data space; design; gadolinium oxide; heart motion; image processing; improved; innovation; novel; reconstruction; respiratory

DESCRIPTION (provided by applicant): Myocardial first-pass perfusion and late gadolinium enhancement (LGE) schemes are key components of most clinical cardiac MRI exams. The limitations of current MRI schemes often makes it challenging to simultaneously achieve high spatio-temporal resolution, sufficient spatial coverage, and good image quality in first-pass perfusion MRI, making it difficult to interpreting the results. Similarly, the large number of breath-holds and their long duration often makes LGE acquisitions challenging for many patients, resulting in significant motion artifacts and reduced patient throughput. In this context, there is an immediate clinical need for a novel dynamic imaging framework that can enable free-breathing acquisitions and considerably improve spatio-temporal resolution and coverage, without degrading the quality. The main objective of this proposal is to develop a novel dynamic imaging framework, which can enable free-breathing cardiac MRI and significantly accelerate it with minimal artifacts. We recently introduced a novel regularized reconstruction algorithm to significantly accelerate free-breathing dynamic MRI data. Preliminary validations of the algorithm demonstrated the ability of the proposed scheme to provide accelerations of up-to eleven fold with minor artifacts. The main focus of this proposal is to further improve the k-t SLR scheme and use it to realize high-resolution clinical myocardial perfusion and free-breathing LGE MRI. The successful completion of the proposed research will provide quantitative perfusion estimates with a temporal resolution of one heartbeat and spatial resolution of 0.15x0.15x0.8 cc from the entire heart, which is a four-fold improvement over current schemes. Similarly, we expect to considerably improve the patient compliance by relaxing the breath-holding requirement and reducing the scan time in LGE MRI data. These developments are quite significant and will considerably advance the state of the art in contrast-enhanced CMRI. The proposed algorithm is a radical departure from the classical approaches that rely on x-f space sparsity. In addition, we introduce non-convex spectral priors and additionally exploit the sparsity of the dynamic images to further improve the data fidelity and acceleration rate. Thus, the proposed scheme is highly innovative and its impact is expected to extend beyond the specific applications. Our team is well qualified to perform the proposed research because of our combined scope and breadth in expertise (including signal/image processing, MR physics, radiology, and cardiology), in addition to the extensive preliminary data. PUBLIC HEALTH RELEVANCE: The proposed project addresses the development of a novel acquisition and data-processing scheme to improve the performance of contrast enhance cardiac MRI. This research has relevance to public health since this scheme can significantly improve the interpretation of the data and improve patient compliance and comfort. In addition, a reduction in scan time will improve throughput. Thus, the findings are ultimately expected to be applicable to improve the health of human beings.

描述（由申请人提供）：心肌首过灌注和晚期钆增强（LGE）方案是大多数临床心脏MRI检查的关键组成部分。当前MRI方案的局限性通常使得在首过灌注MRI中同时实现高时空分辨率、足够的空间覆盖和良好的图像质量具有挑战性，使得难以解释结果。类似地，大量屏气及其长持续时间通常使LGE采集对许多患者具有挑战性，导致显著的运动伪影和降低的患者吞吐量。在这种情况下，有一个新的动态成像框架，可以使自由呼吸采集和大大提高时空分辨率和覆盖范围，而不会降低质量的直接临床需求。该提案的主要目标是开发一种新的动态成像框架，该框架可以实现自由呼吸心脏MRI，并以最小的伪影显著加速。我们最近引入了一种新的正则化重建算法，以显着加速自由呼吸动态MRI数据。算法的初步验证表明，所提出的计划，以提供高达11倍的加速度与轻微的文物的能力。该提案的主要重点是进一步改进k-t SLR方案，并将其用于实现高分辨率临床心肌灌注和自由呼吸LGE MRI。拟议研究的成功完成将提供定量灌注估计，整个心脏的时间分辨率为一次心跳，空间分辨率为0.15x0.15x0.8 cc，这是当前方案的四倍改进。同样，我们希望通过放宽屏气要求和减少LGE MRI数据的扫描时间来大大提高患者的依从性。这些发展是相当重要的，并将大大推进对比度增强CMRI的最新技术水平。所提出的算法是一个彻底的偏离依赖于x-f空间稀疏的经典方法。此外，我们引入非凸谱先验，并利用动态图像的稀疏性，以进一步提高数据保真度和加速率。因此，拟议的计划是高度创新的，其影响预计将超出具体的应用。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/图像处理，MR物理学，放射学和心脏病学）的综合范围和广度，以及广泛的初步数据。 公共卫生相关性：该项目旨在开发一种新的采集和数据处理方案，以提高对比增强心脏MRI的性能。这项研究与公共卫生相关，因为该方案可以显着改善数据的解释，提高患者的依从性和舒适度。此外，扫描时间的减少将提高吞吐量。因此，这些发现最终有望用于改善人类的健康。