Cohen Alexander D, Nencka Andrew S, Wang Yang
Department of Radiology, Medical College of Wisconsin, Milwaukee, Wisconsin, United States of America.
PLoS One. 2018 Feb 1;13(2):e0190427. doi: 10.1371/journal.pone.0190427. eCollection 2018.
Typical simultaneous blood oxygenation-level dependent (BOLD) and arterial spin labeling (ASL) sequences acquire two echoes, one perfusion-sensitive and one BOLD-sensitive. However, for ASL, spatial resolution and brain coverage are limited due to the T1 decay of the labeled blood. This study applies a sequence combining a multiband acquisition with four echoes for simultaneous BOLD and pseudo-continuous ASL (pCASL) echo planar imaging (MBME ASL/BOLD) for block-design task-fMRI. A multiband acceleration of four was employed to increase brain coverage and reduce slice-timing effects on the ASL signal. Multi-echo independent component analysis (MEICA) was implemented to automatically denoise the BOLD signal by regressing non-BOLD components. This technique led to increased temporal signal-to-noise ratio (tSNR) and BOLD sensitivity. The MEICA technique was also modified to denoise the ASL signal by regressing artifact and BOLD signals from the first echo time-series. The MBME ASL/BOLD sequence was applied to a finger-tapping task functional MRI (fMRI) experiment. Signal characteristics and activation were evaluated using single echo BOLD, combined ME BOLD, combined ME BOLD after MEICA denoising, perfusion-weighted (PW), and perfusion-weighted after MEICA denoising time-series. The PW data was extracted using both surround subtraction and high-pass filtering followed by demodulation. In addition, the CBF/BOLD response ratio and CBF/BOLD coupling were analyzed. Results showed that the MEICA denoising procedure significantly improved the BOLD signal, leading to increased BOLD sensitivity, tSNR, and activation statistics compared to conventional single echo BOLD data. At the same time, the denoised PW data showed increased tSNR and activation statistics compared to the non-denoised PW data. CBF/BOLD coupling was also increased using the denoised ASL and BOLD data. Our preliminary data suggest that the MBME ASL/BOLD sequence can be employed to collect whole-brain task-fMRI with improved data quality for both BOLD and PW time series, thus improving the results of block-design task fMRI.
典型的同时血氧水平依赖（BOLD）和动脉自旋标记（ASL）序列采集两个回波，一个对灌注敏感，一个对BOLD敏感。然而，对于ASL，由于标记血液的T1衰减，空间分辨率和脑覆盖范围有限。本研究应用一种将多频段采集与四个回波相结合的序列，用于同时进行BOLD和伪连续ASL（pCASL）回波平面成像（MBME ASL/BOLD）以进行组块设计任务功能磁共振成像（fMRI）。采用四倍数的多频段加速来增加脑覆盖范围并减少切片时间对ASL信号的影响。实施多回波独立成分分析（MEICA），通过回归非BOLD成分来自动去除BOLD信号的噪声。该技术提高了时间信噪比（tSNR）和BOLD敏感性。还对MEICA技术进行了改进，通过从第一个回波时间序列中回归伪影和BOLD信号来去除ASL信号的噪声。MBME ASL/BOLD序列应用于手指敲击任务功能磁共振成像（fMRI）实验。使用单回波BOLD、联合多回波BOLD、MEICA去噪后的联合多回波BOLD、灌注加权（PW）以及MEICA去噪后的灌注加权时间序列来评估信号特征和激活情况。PW数据通过环绕减法和高通滤波然后解调来提取。此外，分析了脑血流量（CBF）/BOLD反应比率和CBF/BOLD耦合。结果表明，与传统单回波BOLD数据相比，MEICA去噪程序显著改善了BOLD信号，导致BOLD敏感性、tSNR和激活统计量增加。同时，与未去噪的PW数据相比，去噪后的PW数据显示tSNR和激活统计量增加。使用去噪后的ASL和BOLD数据，CBF/BOLD耦合也增加了。我们的初步数据表明，MBME ASL/BOLD序列可用于采集全脑任务功能磁共振成像，提高BOLD和PW时间序列的数据质量，从而改善组块设计任务功能磁共振成像的结果。
