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基于病变部位的基于多变量机器学习的脑胶质瘤患者语言映射。

Multivariate machine learning-based language mapping in glioma patients based on lesion topography.

机构信息

Department of Neurosurgery, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Anhui, Hefei, China.

Glioma Surgery Division, Neurologic Surgery Department, Huashan Hospital, Fudan University, Shanghai, China.

出版信息

Brain Imaging Behav. 2021 Oct;15(5):2552-2562. doi: 10.1007/s11682-021-00457-0. Epub 2021 Feb 22.

DOI:10.1007/s11682-021-00457-0
PMID:33619646
Abstract

Diffusive and progressive tumor infiltration within language-related areas of the brain induces functional reorganization. However, the macrostructural basis of subsequent language deficits is less clear. To address this issue, lesion topography data from 137 preoperative patients with left cerebral language-network gliomas (81 low-grade gliomas and 56 high-grade gliomas), were adopted for multivariate machine-learning-based lesion-language mapping analysis. We found that tumor location in the left posterior middle temporal gyrus-a bottleneck where both dorsal and ventral language pathways travel-predicted deficits of spontaneous speech (cluster size = 1356 mm, false discovery rate corrected P < 0.05) and naming scores (cluster size = 1491 mm, false discovery rate corrected P < 0.05) in the high-grade glioma group. In contrast, no significant lesion-language mapping results were observed in the low-grade glioma group, suggesting a large functional reorganization. These findings suggest that in patients with gliomas, the macrostructural plasticity mechanisms that modulate brain-behavior relationships depend on glioma grade.

摘要

肿瘤在大脑语言相关区域的扩散和渐进性浸润会引起功能重组。然而,后续语言缺陷的宏观结构基础尚不明确。为解决这一问题,我们采用了 137 名术前左侧大脑语言网络胶质瘤(81 例低级别胶质瘤和 56 例高级别胶质瘤)患者的病变部位数据,进行了基于多元机器学习的病变-语言映射分析。我们发现,肿瘤位于左侧后颞中回——背侧和腹侧语言通路的瓶颈处——这预测了高级别胶质瘤组自发性言语(簇大小=1356mm,经假发现率校正 P<0.05)和命名得分(簇大小=1491mm,经假发现率校正 P<0.05)的缺陷。相比之下,低级别胶质瘤组没有观察到显著的病变-语言映射结果,表明存在较大的功能重组。这些发现表明,在胶质瘤患者中,调节大脑-行为关系的宏观结构可塑性机制取决于胶质瘤的级别。

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