School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom.
MR Research Collaborations, Siemens Healthcare Limited, Frimley, United Kingdom.
Magn Reson Med. 2018 Dec;80(6):2618-2629. doi: 10.1002/mrm.27208. Epub 2018 Apr 22.
To develop a robust and efficient reconstruction framework that provides high-quality motion-compensated respiratory-resolved images from free-breathing 3D whole-heart Cartesian coronary magnetic resonance angiography (CMRA) acquisitions.
Recently, XD-GRASP (eXtra-Dimensional Golden-angle RAdial Sparse Parallel MRI) was proposed to achieve 100% scan efficiency and provide respiratory-resolved 3D radial CMRA images by exploiting sparsity in the respiratory dimension. Here, a reconstruction framework for Cartesian CMRA imaging is proposed, which provides respiratory-resolved motion-compensated images by incorporating 2D beat-to-beat translational motion information to increase sparsity in the respiratory dimension. The motion information is extracted from interleaved image navigators and is also used to compensate for 2D translational motion within each respiratory phase. The proposed Optimized Respiratory-resolved Cartesian Coronary MR Angiography (XD-ORCCA) method was tested on 10 healthy subjects and 2 patients with cardiovascular disease, and compared against XD-GRASP.
The proposed XD-ORCCA provides high-quality respiratory-resolved images, allowing clear visualization of the right and left coronary arteries, even for irregular breathing patterns. Compared with XD-GRASP, the proposed method improves the visibility and sharpness of both coronaries. Significant differences (p < .05) in visible vessel length and proximal vessel sharpness were found between the 2 methods. The XD-GRASP method provides good-quality images in the absence of intraphase motion. However, motion blurring is observed in XD-GRASP images for respiratory phases with larger motion amplitudes and subjects with irregular breathing patterns.
A robust respiratory-resolved motion-compensated framework for Cartesian CMRA has been proposed and tested in healthy subjects and patients. The proposed XD-ORCCA provides high-quality images for all respiratory phases, independently of the regularity of the breathing pattern.
开发一种强大而高效的重建框架，从自由呼吸的 3D 全心脏笛卡尔冠状动脉磁共振血管造影（CMRA）采集提供高质量的运动补偿呼吸分辨图像。
最近，XD-GRASP（Extra-Dimensional Golden-angle RAdial Sparse Parallel MRI）被提出，通过利用呼吸维度的稀疏性，实现 100%的扫描效率，并提供呼吸分辨的 3D 径向 CMRA 图像。在这里，提出了一种笛卡尔 CMRA 成像的重建框架，通过将 2D 逐拍平移运动信息纳入其中，增加呼吸维度的稀疏性，提供呼吸分辨的运动补偿图像。运动信息从交错的图像导航器中提取，并用于补偿每个呼吸阶段内的 2D 平移运动。所提出的优化呼吸分辨笛卡尔冠状动脉磁共振血管造影（XD-ORCCA）方法在 10 名健康受试者和 2 名心血管疾病患者中进行了测试，并与 XD-GRASP 进行了比较。
所提出的 XD-ORCCA 提供了高质量的呼吸分辨图像，即使对于不规则的呼吸模式，也允许清楚地可视化右冠状动脉和左冠状动脉。与 XD-GRASP 相比，该方法提高了两条冠状动脉的可视性和清晰度。在这两种方法之间发现了可视血管长度和近端血管清晰度的显著差异（p<.05）。在没有相位内运动的情况下，XD-GRASP 方法提供了高质量的图像。然而，在 XD-GRASP 图像中，对于呼吸相位具有较大运动幅度和呼吸模式不规则的受试者，观察到运动模糊。
已经提出并在健康受试者和患者中测试了一种用于笛卡尔 CMRA 的强大的呼吸分辨运动补偿框架。所提出的 XD-ORCCA 为所有呼吸阶段提供了高质量的图像，而与呼吸模式的规则性无关。
