Novel algorithm for improved contrast enhanced cardiac MRI

描述（由申请人提供）：心肌第一次灌注和晚期钆增强（LGE）方案是大多数临床心脏MRI检查的关键组成部分。目前MRI方案的局限性往往使得首遍灌注MRI难以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，从而给结果的解释带来困难。同样，大量的屏气和持续时间长，往往使许多患者难以获得LGE，导致明显的运动伪影和患者吞吐量降低。在这种情况下，临床迫切需要一种新的动态成像框架，它可以实现自由呼吸采集，并在不降低质量的情况下大大提高时空分辨率和覆盖范围。本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，并以最小的伪影显着加速它。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。该算法的初步验证表明，所提出的方案能够提供高达11倍的加速度，并且具有较小的伪影。本课题的主要研究重点是进一步完善k-t SLR方案，利用其实现高分辨率临床心肌灌注和自由呼吸LGE MRI。该研究的成功完成将提供一次心跳的时间分辨率和整个心脏的0.15x0.15x0.8 cc的空间分辨率的定量灌注估计，这是目前方案的四倍改进。同样，我们期望通过放松屏气要求和减少LGE MRI数据的扫描时间来显著提高患者的依从性。这些发展是相当重要的，并将大大推进对比增强CMRI的最新状态。所提出的算法与依赖于x-f空间稀疏性的经典方法完全不同。此外，我们引入了非凸谱先验，并利用动态图像的稀疏性进一步提高了数据保真度和加速速度。因此，拟议的方案具有高度创新性，其影响有望超出具体应用范围。由于我们的专业知识（包括信号/图像处理，MR物理，放射学和心脏病学）的范围和广度，以及广泛的初步数据，我们的团队完全有资格进行拟议的研究。

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.