C.J. Gorter Center for High Field MRI, Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands.
Center for image sciences, University Medical Centre Utrecht, Utrecht, the Netherlands.
Magn Reson Med. 2021 Nov;86(5):2441-2453. doi: 10.1002/mrm.28879. Epub 2021 Jun 9.
Multislice arterial spin labeling (ASL) MRI acquisitions are currently challenging in skeletal muscle because of long transit times, translating into low-perfusion SNR in distal slices when large spatial coverage is required. However, fiber type and oxidative capacity vary along the length of healthy muscles, calling for multislice acquisitions in clinical studies. We propose a new variant of flow alternating inversion recovery (FAIR) that generates sufficient ASL signal to monitor exercise-induced perfusion changes in muscle in two distant slices.
Label around and between two 7-cm distant slices was created by applying the presaturation/postsaturation and selective inversion modules selectively to each slice (split-label multislice FAIR). Images were acquired using simultaneous multislice EPI. We validated our approach in the brain to take advantage of the high resting-state perfusion, and applied it in the lower leg muscle during and after exercise, interleaved with a single-slice FAIR as a reference.
We show that standard multislice FAIR leads to an underestimation of perfusion, while the proposed split-label multislice approach shows good agreement with separate single-slice FAIR acquisitions in brain, as well as in muscle following exercise.
Split-label FAIR allows measuring muscle perfusion in two distant slices simultaneously without losing sensitivity in the distal slice.
由于较长的传输时间,多层面动脉自旋标记(ASL)MRI 采集在骨骼肌中目前具有挑战性,这导致在需要大空间覆盖时,远切片中的低灌注 SNR。然而,纤维类型和氧化能力沿着健康肌肉的长度变化,因此在临床研究中需要进行多层面采集。我们提出了一种新的流动交替反转恢复(FAIR)变体,该变体可产生足够的 ASL 信号,以监测两块远切片中运动引起的肌肉灌注变化。
通过选择性地将预饱和/后饱和和选择性反转模块应用于每个切片,在两个 7 厘米远的切片周围和之间创建标签(分割标签多层面 FAIR)。使用同时多层面 EPI 采集图像。我们在大脑中验证了我们的方法,利用高静息状态灌注的优势,并在运动期间和之后应用于小腿肌肉,同时作为参考进行单次层面 FAIR 交替。
我们表明,标准的多层面 FAIR 导致灌注的低估,而提出的分割标签多层面方法在大脑中以及运动后的肌肉中与单独的单次层面 FAIR 采集具有良好的一致性。
分割标签 FAIR 允许在不损失远切片灵敏度的情况下同时测量两块远切片中的肌肉灌注。