脑肿瘤患者基于磁共振弥散成像的宏观和微观结构测量与皮质传递的联系
Towards linking diffusion MRI based macro- and microstructure measures with cortico-cortical transmission in brain tumor patients（脑肿瘤患者基于磁共振弥散成像的宏观和微观结构测量与皮质传递的联系）We aimed to link macro- and microstructure measures of brain white matter obtained from diffusion MRI with effective connectivity measures based on a propagation of cortico-cortical evoked potentials induced with intrasurgical
direct electrical stimulation. For this, we compared streamline lengths and log-transformed ratios of streamlines computed from presurgical diffusion-weighted images, and the delays and amplitudes of N1 peaks recorded intrasurgically with electrocorticography electrodes in a pilot study of 9 brain tumor patients. Our results showed positive correlation between these two modalities in the vicinity of the stimulation sites (Pearson coefficient 0.54±0.13 for N1 delays, and 0.47±0.23 for N1 amplitudes), which could correspond to the neural propagation via U-fibers. In addition, we reached high sensitivities (0.78±0.07) and very high specificities (0.93±0.03) in a binary variant of our comparison. Finally, we used the structural connectivity measures to predict the effective connectivity using a multiple linear regression model, and showed a significant role of brain microstructure-related indices in this relation.
Keywords: structural connectivity, brain white matter microstrucure, effective connectivity, cortico-cortical evoked potentials, direct electrical stimulation, tractography
我们的目的是将磁共振弥散成像获得的大脑白质的宏观和微观结构测量与基于术中诱导的皮质-皮质诱发电位传播的有效连通性测量联系起来直接电刺激。为此，我们对9例脑肿瘤患者进行了初步研究，比较了术前扩散加权图像计算的流线长度和对数变换率，以及术中皮质电极记录的N1峰的延迟和振幅。我们的结果显示，在刺激部位附近，这两种方式之间存在正相关（N1延迟的Pearson系数为0.54±0.13，N1振幅为0.47±0.23），这与通过U纤维进行神经传播相对应。此外，在我们比较的二元变量中，我们达到了高灵敏度（0.78±0.07）和非常高的特异性（0.93±0.03）。最后，我们利用结构连接性测度，运用多元线性回归模型预测有效连接性，并显示脑微结构相关指标在这一关系中的重要作用。
关键词：结构连通性、脑白质微结构、有效连通性、皮质诱发电位、直接电刺激、纤维束描记术
页:
[1]