Kinany Nawal, Pirondini Elvira, Mattera Loan, Martuzzi Roberto, Micera Silvestro, Van De Ville Dimitri
Department of Radiology and Medical Informatics, Campus Biotech, University of Geneva, Chemin des Mines 9, Geneva 1211, Switzerland; Medical Image Processing Laboratory, Center for Neuroprosthetics, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne (EPFL), Geneva 1202, Switzerland; Bertarelli Foundation Chair in Translational Neuroengineering, Center for Neuroprosthetics, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne (EPFL), Geneva 1202, Switzerland.
Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA, USA; Department of BioEngineering, University of Pittsburgh, PA, USA; Rehabilitation Neural Engineering Laboratories, University of Pittsburgh, Pittsburgh, PA, USA.
Neuroimage. 2022 Apr 15;250:118964. doi: 10.1016/j.neuroimage.2022.118964. Epub 2022 Feb 3.
Functional magnetic resonance imaging (fMRI) has revolutionized the investigation of brain function. Similar approaches can be translated to probe spinal mechanisms. However, imaging the spinal cord remains challenging, notably due to its size and location. Technological advances are gradually tackling these issues, though there is yet no consensus on optimal acquisition protocols. In this study, we assessed the performance of three sequences during a simple motor task and at rest, in 15 healthy humans. Building upon recent literature, we selected three imaging protocols: a sequence integrating outer volume suppression (OVS) and two sequences implementing inner field-of-view imaging (ZOOMit) with different spatial and temporal resolutions. Images acquired using the OVS sequence appeared more prone to breathing-induced signal fluctuations, though they exhibited a higher temporal signal-to-noise ratio than ZOOMit sequences. Conversely, the spatial signal-to-noise ratio was higher for the two ZOOMit schemes. In spite of these differences in signal properties, all sequences yielded comparable performance in detecting group-level task-related activity, observed in the expected spinal levels. Nevertheless, our results suggest a superior sensitivity and robustness of patterns imaged using the OVS acquisition scheme. To analyze the data acquired at rest, we deployed a dynamic functional connectivity framework, SpiCiCAP, and we evaluated the ability of the three acquisition schemes to disentangle intrinsic spinal signals. We demonstrated that meaningful subdivisions of the spinal cord's functional architecture could be uncovered for all three sequences, with similar spatio-temporal properties across acquisition parameters. Cleaner and more stable components were, however, obtained using ZOOMit sequences. This study emphasizes the potential of fMRI as a robust tool to image spinal activity in vivo and it highlights specificities and similarities of three acquisition methods. This represents a key step towards the establishment of standardized spinal cord fMRI protocols.
功能磁共振成像(fMRI)彻底改变了脑功能的研究方式。类似的方法可用于探究脊髓机制。然而,对脊髓进行成像仍然具有挑战性,尤其是因其尺寸和位置。尽管在最佳采集协议上尚未达成共识,但技术进步正在逐步解决这些问题。在本研究中,我们评估了15名健康受试者在简单运动任务及静息状态下三种序列的性能。基于近期文献,我们选择了三种成像协议:一种整合了外容积抑制(OVS)的序列以及两种采用不同空间和时间分辨率的内视野成像(ZOOMit)序列。使用OVS序列采集的图像似乎更容易受到呼吸引起的信号波动影响,不过其时间信噪比高于ZOOMit序列。相反,两种ZOOMit方案的空间信噪比更高。尽管信号特性存在这些差异,但所有序列在检测预期脊髓节段的组水平任务相关活动方面表现相当。然而,我们的结果表明,使用OVS采集方案成像的模式具有更高的灵敏度和稳健性。为了分析静息状态下采集的数据,我们采用了一种动态功能连接框架SpiCiCAP,并评估了这三种采集方案解析脊髓固有信号的能力。我们证明,对于所有三种序列都能揭示脊髓功能结构的有意义细分,且不同采集参数下具有相似的时空特性。然而,使用ZOOMit序列获得的成分更清晰、更稳定。本研究强调了fMRI作为一种强大工具在体内对脊髓活动进行成像的潜力,并突出了三种采集方法的特异性和相似性。这是朝着建立标准化脊髓fMRI协议迈出的关键一步。