Annu Int Conf IEEE Eng Med Biol Soc. 2017 Jul;2017:4479-4482. doi: 10.1109/EMBC.2017.8037851.
Pre-surgical mapping of sensorimotor and language functions is crucial to reduce neurological deficits in epilepsy and tumor resection surgery. As non-invasive mapping, both resting-state and task-evoked functional MRI has been explored in pre-surgical mapping. In lack of standardized test paradigm, the reliability of fMRI mapping is still a concern for clinical use. In this study, to improve the reliability of fMRI based mapping, task fMRI data from all available task paradigms (motor movement, word repeating and picture naming) were low-pass filtered in the band of resting-state fMRI (0.01-0.08Hz) and concatenated to get more time points. With K-means clustering, it was shown that the sensorimotor network could be reliably parcellated into hand and tongue sub-regions. The resulted parcellations were further verified with invasive ECoG and ECS mapping. Both the accuracy and specificity were better than using the motor-task fMRI only. Especially, for those patients who failed in task fMRI mapping, our method was able to provide accurate mapping as well. Our results also indicate that cortical sensorimotor network pattern is intrinsic and always present during various tasks, which supports the physiological link between the spontaneous and the task-evoked BOLD signals.
术前对感觉运动和语言功能进行图谱绘制对于减少癫痫和肿瘤切除手术中的神经功能缺损至关重要。作为非侵入性图谱绘制方法，静息态和任务诱发功能磁共振成像（fMRI）都已在术前图谱绘制中得到探索。由于缺乏标准化的测试范式，fMRI图谱绘制的可靠性在临床应用中仍然是一个问题。在本研究中，为了提高基于fMRI的图谱绘制的可靠性，来自所有可用任务范式（运动、单词重复和图片命名）的任务fMRI数据在静息态fMRI频段（0.01 - 0.08Hz）进行低通滤波，并连接以获得更多时间点。通过K均值聚类，结果表明感觉运动网络可以可靠地划分为手部和舌部子区域。所得分区通过侵入性脑皮层电图（ECoG）和脑皮层刺激（ECS）图谱进一步验证。准确性和特异性均优于仅使用运动任务fMRI的情况。特别是对于那些在任务fMRI图谱绘制中失败的患者，我们的方法也能够提供准确的图谱。我们的结果还表明，皮层感觉运动网络模式是内在的，并且在各种任务期间始终存在，这支持了自发和任务诱发的血氧水平依赖（BOLD）信号之间的生理联系。
