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通过心跳动态建模实现脑电-磁共振同时记录下心冲击图抑制。

Ballistocardiogram suppression in concurrent EEG-MRI by dynamic modeling of heartbeats.

机构信息

Physical Sciences Platform, Sunnybrook Research Institute, Toronto, Ontario, Canada.

Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada.

出版信息

Hum Brain Mapp. 2022 Oct 1;43(14):4444-4457. doi: 10.1002/hbm.25965. Epub 2022 Jun 13.

Abstract

The ballistocardiogram (BCG), the induced electric potentials by the head motion originating from heartbeats, is a prominent source of noise in electroencephalography (EEG) data during magnetic resonance imaging (MRI). Although methods have been proposed to suppress the BCG artifact, more work considering the variability of cardiac cycles and head motion across time and subjects is needed to provide highly robust correction. Here, a method called "dynamic modeling of heartbeats" (DMH) is proposed to reduce BCG artifacts in EEG data recorded inside an MRI system. The DMH method models BCG artifacts by combining EEG points at time instants with similar dynamics. The modeled BCG artifact is then subtracted from the EEG recording to suppress the BCG artifact. Performance of DMH was tested and specifically compared with the Optimal Basis Set (OBS) method on EEG data recorded inside a 3T MRI system with either no MRI acquisition (Inside-MRI), echo-planar imaging (EPI-EEG), or fast MRI acquisition using simultaneous multi-slice and inverse imaging methods (SMS-InI-EEG). In a steady-state visual evoked response (SSVEP) paradigm, the 15-Hz oscillatory neuronal activity at the visual cortex after DMH processing was about 130% of that achieved by OBS processing for Inside-MRI, SMS-InI-EEG, and EPI-EEG conditions. The DMH method is computationally efficient for suppressing BCG artifacts and in the future may help to improve the quality of EEG data recorded in high-field MRI systems for neuroscientific and clinical applications.

摘要

心动球描记图(BCG)是源自心跳的头部运动产生的感应电动势,是磁共振成像(MRI)期间脑电图(EEG)数据中的一个主要噪声源。虽然已经提出了抑制 BCG 伪影的方法,但需要更多考虑心脏周期和头部运动随时间和受试者变化的工作,以提供高度稳健的校正。在这里,提出了一种称为“心跳动态建模”(DMH)的方法,用于减少 MRI 系统内记录的 EEG 数据中的 BCG 伪影。DMH 方法通过结合具有相似动力学的 EEG 点来对 BCG 伪影进行建模。然后,从 EEG 记录中减去建模的 BCG 伪影以抑制 BCG 伪影。在具有无 MRI 采集(Inside-MRI)、平面回波成像(EPI-EEG)或使用同时多切片和反向成像方法的快速 MRI 采集(SMS-InI-EEG)的 3T MRI 系统内记录的 EEG 数据上测试了 DMH 的性能,并特别与最优基集(OBS)方法进行了比较。在稳态视觉诱发电位(SSVEP)范式中,经过 DMH 处理后视觉皮层的 15-Hz 振荡神经元活动大约是 OBS 处理 Inside-MRI、SMS-InI-EEG 和 EPI-EEG 条件下的 130%。DMH 方法在抑制 BCG 伪影方面具有计算效率,并且将来可能有助于提高用于神经科学和临床应用的高场 MRI 系统中记录的 EEG 数据的质量。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/664e/9435020/ed4be0b6e523/HBM-43-4444-g008.jpg

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