Electrical Engineering, Stanford University, Stanford, CA, United States.
Medical Biophysics, Western University, London, Ontario, Canada.
Magn Reson Imaging. 2023 May;98:140-148. doi: 10.1016/j.mri.2023.01.008. Epub 2023 Jan 14.
To develop a respiratory-resolved motion-compensation method for free-breathing, high-resolution coronary magnetic resonance angiography (CMRA) using a 3D cones trajectory.
To achieve respiratory-resolved 0.98 mm resolution images in a clinically relevant scan time, we undersample the imaging data with a variable-density 3D cones trajectory. For retrospective motion compensation, translational estimates from 3D image-based navigators (3D iNAVs) are used to bin the imaging data into four phases from end-expiration to end-inspiration. To ensure pseudo-random undersampling within each respiratory phase, we devise a phyllotaxis readout ordering scheme mindful of eddy current artifacts in steady state free precession imaging. Following binning, residual 3D translational motion within each phase is computed using the 3D iNAVs and corrected for in the imaging data. The noise-like aliasing characteristic of the combined phyllotaxis and cones sampling pattern is leveraged in a compressed sensing reconstruction with spatial and temporal regularization to reduce aliasing in each of the respiratory phases.
In initial studies of six subjects, respiratory motion compensation using the proposed method yields improved image quality compared to non-respiratory-resolved approaches with no motion correction and with 3D translational correction. Qualitative assessment by two cardiologists and quantitative evaluation with the image edge profile acutance metric indicate the superior sharpness of coronary segments reconstructed with the proposed method (P < 0.01).
We have demonstrated a new method for free-breathing, high-resolution CMRA based on a variable-density 3D cones trajectory with modified phyllotaxis ordering and respiratory-resolved motion compensation with 3D iNAVs.
开发一种基于 3D 圆锥轨迹的自由呼吸高分辨率冠状动脉磁共振血管造影(CMRA)呼吸分辨运动补偿方法。
为了在临床相关的扫描时间内实现 0.98mm 的呼吸分辨分辨率图像,我们使用变密度 3D 圆锥轨迹对成像数据进行欠采样。为了进行回顾性运动补偿,来自基于 3D 图像的导航器(3D iNAVs)的平移估计被用于将成像数据分为从呼气末到吸气末的四个相位。为了确保在每个呼吸相中伪随机欠采样,我们设计了一种基于稳态自由进动成像中涡流伪影的 Phyllotaxis 读出排序方案。在分箱之后,使用 3D iNAVs 计算每个相位内的剩余 3D 平移运动,并在成像数据中进行校正。利用 Phyllotaxis 和圆锥采样模式的组合的噪声样的混叠特征,在具有空间和时间正则化的压缩感知重建中,减少每个呼吸相中的混叠。
在对 6 名受试者的初步研究中,与无运动校正和 3D 平移校正的非呼吸分辨方法相比,使用所提出的方法进行呼吸运动补偿可提高图像质量。两位心脏病学家的定性评估和图像边缘轮廓锐利度指标的定量评估表明,所提出的方法重建的冠状动脉段具有更高的清晰度(P<0.01)。
我们已经证明了一种新的基于变密度 3D 圆锥轨迹的自由呼吸高分辨率 CMRA 方法,该方法具有改进的 Phyllotaxis 排序和基于 3D iNAVs 的呼吸分辨运动补偿。