Novel algorithm for improved contrast enhanced cardiac MRI

改进对比增强心脏 MRI 的新算法

基本信息

批准号：
8403755
负责人：
Mathews Jacob
金额：
$ 18.23万
依托单位：
UNIVERSITY OF IOWA
依托单位国家：
美国
项目类别：
财政年份：
2012
资助国家：
美国
起止时间：
2012-01-01 至 2014-11-30
项目状态：
已结题

项目摘要

Project Summary 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 ccfrom 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.

项目概要心肌首过灌注和晚期钆增强（LGE）方案是关键大多数临床心脏 MRI 检查的组成部分。当前 MRI 方案的局限性通常很难同时实现高时空分辨率，首过灌注 MRI 具有足够的空间覆盖范围和良好的图像质量，使其难以解释结果。同样，大量的屏气和长时间的屏气持续时间通常使 LGE 采集对许多患者来说具有挑战性，从而导致显着的运动伪影和患者吞吐量降低。在这种情况下，立即进行临床需要一种新颖的动态成像框架，可以实现自由呼吸的采集和显着提高时空分辨率和覆盖范围，而不会降低质量。该提案的主要目标是开发一种新颖的动态成像框架，该框架可以实现自由呼吸心脏 MRI，并以最小的伪影显着加速它。我们最近引入了一种新颖的正则化重建算法，以显着加速自由呼吸动态 MRI 数据。算法的初步验证展示了所提出的方案提供高达 11 倍加速度的能力折叠有小工件。该提案的主要重点是进一步改进k-t SLR 方案并用其实现高分辨率临床心肌灌注和自由呼吸 LGE 磁共振成像。拟议研究的成功完成将提供定量的结果灌注估计的时间分辨率为一次心跳，空间分辨率为来自整个心脏的 0.15x0.15x0.8 cc，比当前提高了四倍计划。同样，我们希望通过放松来显着提高患者的依从性屏气要求并减少 LGE MRI 数据的扫描时间。这些的发展是相当重要的，将大大提高现有技术的水平对比增强 CMRI。所提出的算法与经典算法截然不同依赖于 x-f 空间稀疏性的方法。此外，我们还引入了非凸谱先验并另外利用动态图像的稀疏性来进一步改进数据保真度和加速率。因此，所提出的方案具有很强的创新性，其影响预计将扩展到特定应用之外。我们的团队有能力胜任由于我们综合的专业知识范围和广度（包括信号/图像处理、MR 物理、放射学和心脏病学），以及广泛的初步数据。