Multi-scale image analysis and prediction of visual field defects after selective amygdalohippocampectomy.
Multi-scale image analysis and prediction of visual field defects after selective amygdalohippocampectomy.
复制标题
选择性杏仁核-海马区切除术后视野缺陷的多尺度图像分析与预测。
DOI：
10.1038/s41598-020-80751-x
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发表时间：
2021-01-14
影响因子：
4.6
通讯作者：
Rüber T
中科院分区：
文献类型：
--
作者：
David B;Eberle J;Delev D;Gaubatz J;Prillwitz CC;Wagner J;Schoene-Bake JC;Luechters G;Radbruch A;Wabbels B;Schramm J;Weber B;Surges R;Elger CE;Rüber T
选择性杏仁核切除术是治疗难治性颞叶癫痫的有效方法，但可能引起视野缺损（VFD）。在这里，我们的目的是描述组织特异性术前和术后成像相关的VFD严重程度使用全脑分析从体素到网络水平。对28例颞叶癫痫患者术前、术后行MRI（T1-MP3和弥散张量成像）检查，并按Goldmann标准行动态视野检查。我们探讨了全脑灰质（GM）和白色物质（WM）VFD的相关性，分别使用基于体素的形态测量和基于轨迹的空间统计。我们还重建了单个结构连接体，并进行了局部和全局网络分析。双侧颞中回的两个群集表明，随着VFD严重程度的增加，术后GM体积减少（FWE校正p < 0.05）。单个WM簇显示，随着同侧视辐射中VFD严重程度的增加，各向异性分数降低（FWE校正p < 0.05）。此外，有VFD的患者（与无VFD的患者相比）术后局部连通性变化的数量更高。在GM、WM和网络指标中，我们都没有发现VFD严重程度的术前相关性。尽管如此，在探索性分析中，人工神经网络元分类器可以基于高于机会水平的术前连接体预测VFD的发生。
Selective amygdalohippocampectomy is an effective treatment for patients with therapy-refractory temporal lobe epilepsy but may cause visual field defect (VFD). Here, we aimed to describe tissue-specific pre- and postoperative imaging correlates of the VFD severity using whole-brain analyses from voxel- to network-level. Twenty-eight patients with temporal lobe epilepsy underwent pre- and postoperative MRI (T1-MPRAGE and Diffusion Tensor Imaging) as well as kinetic perimetry according to Goldmann standard. We probed for whole-brain gray matter (GM) and white matter (WM) correlates of VFD using voxel-based morphometry and tract-based spatial statistics, respectively. We furthermore reconstructed individual structural connectomes and conducted local and global network analyses. Two clusters in the bihemispheric middle temporal gyri indicated a postsurgical GM volume decrease with increasing VFD severity (FWE-corrected p < 0.05). A single WM cluster showed a fractional anisotropy decrease with increasing severity of VFD in the ipsilesional optic radiation (FWE-corrected p < 0.05). Furthermore, patients with (vs. without) VFD showed a higher number of postoperative local connectivity changes. Neither in the GM, WM, nor in network metrics we found preoperative correlates of VFD severity. Still, in an explorative analysis, an artificial neural network meta-classifier could predict the occurrence of VFD based on presurgical connectomes above chance level.
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通讯作者：
Bzdok D
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