Department of Radiology, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI 53226, United States.
GE Healthcare, Waukesha, WI, United States.
Neuroimage. 2021 Jan 15;225:117461. doi: 10.1016/j.neuroimage.2020.117461. Epub 2020 Oct 16.
Recent advances in functional MRI techniques include multiband (MB) imaging and multi-echo (ME) imaging. In MB imaging multiple slices are acquired simultaneously leading to significant increases in temporal and spatial resolution. Multi-echo imaging enables multiple echoes to be acquired in one shot, where the ME images can be used to denoise the BOLD time series and increase BOLD sensitivity. In this study, resting state fMRI (rs-fMRI) data were collected using a combined MBME sequence and compared to an MB single echo sequence. In total, 29 subjects were imaged, and 18 of them returned within two weeks for repeat imaging. Participants underwent one MBME scan with three echoes and one MB scan with one echo. Both datasets were processed using standard denoising and advanced denoising. Advanced denoising included multi-echo independent component analysis (ME-ICA) for the MBME data and ICA-AROMA for the MB data. Resting state functional connectivity (RSFC) was evaluated using both selective seed-based and whole grey matter (GM) region-of-interest (ROI) based approaches. The reproducibility of connectivity metrics was also analyzed in the repeat subjects. In addition, functional connectivity density (FCD), a data-driven approach that counts the number of significant connections, both within a local cluster and globally, with each voxel was analyzed. Regardless of the standard or advanced denoising technique, all seed-based RSFC was significantly higher for MBME compared to MB. Much more GM ROI combinations showed significantly higher RSFC for MBME vs. MB. Reproducibility, evaluated using the dice coefficient was significantly higher for MBME relative to MB data. Finally, FCD was also higher for MBME vs. MB data. This study showed higher RSFC for MBME vs. MB data using selected seed-based, whole GM ROI-based, and data-driven approaches. Reproducibility found also higher for MBME data. Taken together, these results indicate that MBME is a promising technique for rs-fMRI.
近期功能磁共振成像技术的进展包括多带宽（MB）成像和多回波（ME）成像。在 MB 成像中，同时采集多个切片，从而显著提高了时间和空间分辨率。多回波成像可以在一次拍摄中采集多个回波，其中 ME 图像可用于对 BOLD 时间序列进行去噪并提高 BOLD 灵敏度。在这项研究中，使用组合的 MBME 序列采集静息态功能磁共振成像（rs-fMRI）数据，并与 MB 单回波序列进行比较。总共对 29 名受试者进行了成像，其中 18 名在两周内返回进行重复成像。参与者接受了一次带三个回波的 MBME 扫描和一次带一个回波的 MB 扫描。两个数据集都使用标准去噪和高级去噪进行处理。高级去噪包括 MBME 数据的多回波独立成分分析（ME-ICA）和 MB 数据的 ICA-AROMA。使用选择性种子和整个灰质（GM）感兴趣区（ROI）的方法评估静息状态功能连接（RSFC）。还对重复受试者的连接度量的可重复性进行了分析。此外，还分析了一种数据驱动的方法，即功能连接密度（FCD），该方法计算每个体素与局部簇内和全局范围内的显著连接数。无论使用标准还是高级去噪技术，MBME 的所有基于种子的 RSFC 均明显高于 MB。与 MBME 相比，更多的 GM ROI 组合显示出更高的 RSFC。使用骰子系数评估的可重复性也明显高于 MB 数据。最后，FCD 也高于 MB 数据。这项研究表明，与 MB 数据相比，MBME 在选定的基于种子的、整个 GM ROI 基于的和数据驱动的方法中具有更高的 RSFC。也发现 MBME 数据的可重复性更高。综上所述，这些结果表明 MBME 是 rs-fMRI 的一种很有前途的技术。
