Automatic skull segmentation from MR images for realistic volume conductor models of the head: Assessment of the state-of-the-art
Automatic skull segmentation from MR images for realistic volume conductor models of the head: Assessment of the state-of-the-art
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DOI：
10.1016/j.neuroimage.2018.03.001
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发表时间：
2018-07-01
期刊：
影响因子：
5.7
通讯作者：
Thielscher, Axel
中科院分区：
文献类型：
--
作者：
Nielsen, Jesper D.;Madsen, Kristoffer H.;Thielscher, Axel
解剖学上真实的人体头部体积导体模型对于经颅脑刺激（TBS）、脑电图（EEG）和脑磁图（MEG）过程中电场的准确正演建模非常重要。特别是，颅骨隔室由于其低电导率而对场分布产生强烈影响，这表明需要准确地表示其几何形状。然而，从结构磁共振（MR）图像中自动重建颅骨是困难的，因为致密骨在磁共振成像（MRI）中具有非常低的信号。本文对FSL BET2、扩展空间组织先验的SPM12统一分割程序和BrainSuite的颅骨搜索工具三种颅骨分割方法进行了评价。据我们所知，这项研究是第一个严格评估这些最先进的工具的准确性，通过与一组10个受试者的基于ct的颅骨分割进行比较。我们展示了提高分割质量的几个关键因素，包括多对比MRI数据的使用、MR序列的优化和分割方法参数的自适应。我们得出结论，FSL和SPM12比BrainSuite实现更好的颅骨分割。前两种方法在使用t1和t2加权图像组合作为输入时，对颅骨上半部分得到了合理的结果。基于spm12的结果可以通过简单的形态学操作来修复局部缺陷。与FSL BET2相比，基于spm12的分割具有扩展的空间组织先验和基于brainsuite的分割提供了椎骨的粗重建，从而能够构建包括颈部在内的体积传导模型。我们举例证明，扩展模型能够更准确地估计涉及脑外电极蒙太奇的经颅直流电刺激（tDCS）期间的电场分布。FSL和SPM12提供的方法集成到管道中，用于基于四面体网格的逼真头部模型的自动生成，这些模型作为开源软件包SimNIBS的一部分分发，用于经颅脑刺激的现场计算。
Anatomically realistic volume conductor models of the human head are important for accurate forward modeling of the electric field during transcranial brain stimulation (TBS), electro- (EEG) and magnetoencephalography (MEG). In particular, the skull compartment exerts a strong influence on the field distribution due to its low conductivity, suggesting the need to represent its geometry accurately. However, automatic skull reconstruction from structural magnetic resonance (MR) images is difficult, as compact bone has a very low signal in magnetic resonance imaging (MRI). Here, we evaluate three methods for skull segmentation, namely FSL BET2, the unified segmentation routine of SPM12 with extended spatial tissue priors, and the skullfinder tool of BrainSuite. To our knowledge, this study is the first to rigorously assess the accuracy of these state-of-the-art tools by comparison with CT-based skull segmentations on a group of ten subjects. We demonstrate several key factors that improve the segmentation quality, including the use of multi-contrast MRI data, the optimization of the MR sequences and the adaptation of the parameters of the segmentation methods. We conclude that FSL and SPM12 achieve better skull segmentations than BrainSuite. The former methods obtain reasonable results for the upper part of the skull when a combination of T1-and T2-weighted images is used as input. The SPM12-based results can be improved slightly further by means of simple morphological operations to fix local defects. In contrast to FSL BET2, the SPM12-based segmentation with extended spatial tissue priors and the BrainSuite-based segmentation provide coarse reconstructions of the vertebrae, enabling the construction of volume conductor models that include the neck. We exemplarily demonstrate that the extended models enable a more accurate estimation of the electric field distribution during transcranial direct current stimulation (tDCS) for montages that involve extraencephalic electrodes. The methods provided by FSL and SPM12 are integrated into pipelines for the automatic generation of realistic head models based on tetrahedral meshes, which are distributed as part of the open-source software package SimNIBS for field calculations for transcranial brain stimulation.