UC Berkeley-UCSF Graduate Program in Bioengineering, University of California, Berkeley and University of California, San Francisco, California, USA.
Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, California, USA.
Magn Reson Med. 2018 Jun;79(6):2954-2967. doi: 10.1002/mrm.26958. Epub 2017 Oct 11.
To achieve motion robust high resolution 3D free-breathing pulmonary MRI utilizing a novel dynamic 3D image navigator derived directly from imaging data.
Five-minute free-breathing scans were acquired with a 3D ultrashort echo time (UTE) sequence with 1.25 mm isotropic resolution. From this data, dynamic 3D self-navigating images were reconstructed under locally low rank (LLR) constraints and used for motion compensation with one of two methods: a soft-gating technique to penalize the respiratory motion induced data inconsistency, and a respiratory motion-resolved technique to provide images of all respiratory motion states.
Respiratory motion estimation derived from the proposed dynamic 3D self-navigator of 7.5 mm isotropic reconstruction resolution and a temporal resolution of 300 ms was successful for estimating complex respiratory motion patterns. This estimation improved image quality compared to respiratory belt and DC-based navigators. Respiratory motion compensation with soft-gating and respiratory motion-resolved techniques provided good image quality from highly undersampled data in volunteers and clinical patients.
An optimized 3D UTE sequence combined with the proposed reconstruction methods can provide high-resolution motion robust pulmonary MRI. Feasibility was shown in patients who had irregular breathing patterns in which our approach could depict clinically relevant pulmonary pathologies. Magn Reson Med 79:2954-2967, 2018. © 2017 International Society for Magnetic Resonance in Medicine.
利用直接从成像数据中得出的新型动态 3D 图像导航器，实现运动稳健的高分辨率 3D 自由呼吸肺部 MRI。
使用具有 1.25 毫米各向同性分辨率的 3D 超短回波时间（UTE）序列采集 5 分钟的自由呼吸扫描。从该数据中，根据局部低秩（LLR）约束重建动态 3D 自导航图像，并使用两种方法之一进行运动补偿：一种是软门控技术，用于惩罚呼吸运动引起的数据不一致性；另一种是呼吸运动解析技术，用于提供所有呼吸运动状态的图像。
以 7.5 毫米各向同性重建分辨率和 300 毫秒的时间分辨率从所提出的动态 3D 自导航器得出的呼吸运动估计对于估计复杂的呼吸运动模式是成功的。与呼吸带和 DC 导航器相比，这种估计提高了图像质量。使用软门控和呼吸运动解析技术进行呼吸运动补偿，可以从志愿者和临床患者的高度欠采样数据中提供高质量的图像。
优化的 3D UTE 序列结合所提出的重建方法可以提供高分辨率的运动稳健肺部 MRI。在呼吸模式不规则的患者中，我们的方法可以显示临床相关的肺部病变，证明了其可行性。磁共振医学 79：2954-2967，2018。© 2017 国际磁共振学会。
