Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA.
Siemens Medical Solutions USA Inc., Malvern, Pennsylvania, USA.
Magn Reson Med. 2022 Apr;87(4):1784-1798. doi: 10.1002/mrm.29079. Epub 2021 Nov 16.
To develop an isotropic high-resolution stack-of-spirals UTE sequence for pulmonary imaging at 0.55 Tesla by leveraging a combination of robust respiratory-binning, trajectory correction, and concomitant-field corrections.
A stack-of-spirals golden-angle UTE sequence was used to continuously acquire data for 15.5 minutes. The data was binned to a stable respiratory phase based on superoinferior readout self-navigator signals. Corrections for trajectory errors and concomitant field artifacts, along with image reconstruction with conjugate gradient SENSE, were performed inline within the Gadgetron framework. Finally, data were retrospectively reconstructed to simulate scan times of 5, 8.5, and 12 minutes. Image quality was assessed using signal-to-noise, image sharpness, and qualitative reader scores. The technique was evaluated in healthy volunteers, patients with coronavirus disease 2019 infection, and patients with lung nodules.
The technique provided diagnostic quality images with parenchymal lung SNR of 3.18 ± 0.0.60, 4.57 ± 0.87, 5.45 ± 1.02, and 5.89 ± 1.28 for scan times of 5, 8.5, 12, and 15.5 minutes, respectively. The respiratory binning technique resulted in significantly sharper images (p < 0.001) as measured with relative maximum derivative at the diaphragm. Concomitant field corrections visibly improved sharpness of anatomical structures away from iso-center. The image quality was maintained with a slight loss in SNR for simulated scan times down to 8.5 minutes. Inline image reconstruction and artifact correction were achieved in <5 minutes.
The proposed pulmonary imaging technique combined efficient stack-of-spirals imaging with robust respiratory binning, concomitant field correction, and trajectory correction to generate diagnostic quality images with 1.75 mm isotropic resolution in 8.5 minutes on a high-performance 0.55 Tesla system.
通过结合稳健的呼吸分箱、轨迹校正和伴随场校正,开发一种用于 0.55T 肺部成像的各向同性高分辨率螺旋堆叠 UTE 序列。
使用螺旋式金角 UTE 序列连续采集 15.5 分钟的数据。根据上下读数自导航信号,将数据分箱到稳定的呼吸相位。在 Gadgetron 框架内在线执行轨迹误差和伴随场伪影校正以及共轭梯度 SENSE 图像重建。最后,数据进行回顾性重建以模拟 5、8.5 和 12 分钟的扫描时间。使用信噪比、图像锐度和定性读者评分评估图像质量。该技术在健康志愿者、新冠病毒 2019 感染患者和肺结节患者中进行了评估。
该技术提供了具有诊断质量的图像,实质肺 SNR 分别为 3.18±0.06、4.57±0.87、5.45±1.02 和 5.89±1.28,扫描时间分别为 5、8.5、12 和 15.5 分钟。呼吸分箱技术可显著提高图像锐度(p<0.001),以膈膜处的相对最大导数来衡量。伴随场校正明显改善了离等中心的解剖结构的清晰度。在模拟扫描时间降至 8.5 分钟时,图像质量保持不变,仅略有 SNR 损失。在线图像重建和伪影校正可在 5 分钟内完成。
该方法将高效的螺旋堆叠成像与稳健的呼吸分箱、伴随场校正和轨迹校正相结合,在高性能 0.55T 系统上 8.5 分钟内生成具有 1.75mm 各向同性分辨率的诊断质量图像。