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手术后白质连接组的变化揭示了影响低级别胶质瘤患者辅助综合征恢复时间的因素。

The Variation of White Matter Connectome After Surgery Revealed Factors Affecting Supplementary Syndrome Recovery Time in Low-Grade Glioma Patients.

作者信息

Fang Shengyu, Li Yuzhe, Weng Shimeng, Dong Jiahan, Wang Jiangwei, Zhang Zhong, Fan Xing, Wang Yinyan, Ma Wenbin, Jiang Tao

机构信息

Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.

Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.

出版信息

CNS Neurosci Ther. 2025 May;31(5):e70426. doi: 10.1111/cns.70426.

DOI:10.1111/cns.70426
PMID:40346924
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12064937/
Abstract

OBJECTIVE

Supplementary motor area (SMA) syndrome is a common complication after SMA glioma resection. The compensatory mechanism of the structural sensorimotor network (SMN) and the factors influencing the recovery time of SMA syndrome have not been investigated.

METHODS

Pre- and postoperative diffusion tensor images of 42 low-grade glioma patients with SMA syndrome were processed to construct white matter connectomes. Patients were classified into fast and slow-recovery groups according to whether postoperative motor disorder recovers within 7 days. Fiber counts between nodes and graph theory topological properties were calculated. The shortest distance from the surgical region to the corticospinal tract (d) and the upper limb region of Brodmann area 4 (A4ul) was measured to find correlations with recovery time. Cox regressions were conducted to identify factors associated with SMA syndrome recovery time. A general linear model was formed using significant factors in multivariate Cox analysis to predict recovery time.

RESULTS

Decrease of fiber number between lesioned-hemispheric A4ul and contralateral SMN is correlated with prolongation of recovery time. Compared with the slow-recovery group, a higher increase of nodal degree centrality and nodal efficiency of ipsilateral A4ul was found in the fast-recovery group (nodal efficiency: left pre-op: 0.182 ± 0.009, left post-op: 0.231 ± 0.008, p < 0.0001; right pre-op: 0.157 ± 0.021, right post-op: 0.195 ± 0.018, p = 0.0011); (nodal degree centrality: left pre-op: 1.985 ± 0.166; left post-op: 3.195 ± 0.230, p < 0.0001; right pre-op: 1.620 ± 0.389; right post-op: 2.411 ± 0.452, p = 0.0005). Multivariate Cox analysis indicated that the increase in nodal efficiency of A4ul and d were protective factors for SMA syndrome recovery time. A significant negative correlation between the predict score and recovery time was found in the left lesion group (r = -0.756, p < 0.0001), and the same trend was found in the right lesion group (r = -0.531, p = 0.076).

CONCLUSIONS

This study revealed an increase in lesioned-hemispheric A4ul nodal efficiency and long d as protective factors in SMA syndrome recovery. A decrease in the number of interhemispheric fibers connecting lesioned-hemispheric A4ul to nodes on the contralateral hemisphere was correlated with the long recovery time of SMA syndrome.

摘要

目的

辅助运动区(SMA)综合征是SMA胶质瘤切除术后常见的并发症。结构感觉运动网络(SMN)的代偿机制以及影响SMA综合征恢复时间的因素尚未得到研究。

方法

对42例患有SMA综合征的低级别胶质瘤患者的术前和术后弥散张量图像进行处理,以构建白质连接组。根据术后运动障碍是否在7天内恢复,将患者分为快速恢复组和缓慢恢复组。计算节点间的纤维计数和图论拓扑属性。测量从手术区域到皮质脊髓束(d)和布罗德曼4区上肢区域(A4ul)的最短距离,以发现与恢复时间的相关性。进行Cox回归以确定与SMA综合征恢复时间相关的因素。使用多变量Cox分析中的显著因素形成一个通用线性模型来预测恢复时间。

结果

病变半球A4ul与对侧SMN之间纤维数量的减少与恢复时间的延长相关。与缓慢恢复组相比,快速恢复组同侧A4ul的节点度中心性和节点效率有更高的增加(节点效率:左侧术前:0.182±0.009,左侧术后:0.231±0.008,p<0.0001;右侧术前:0.157±0.021,右侧术后:0.195±0.018,p=0.0011);(节点度中心性:左侧术前:1.985±0.166;左侧术后:3.195±0.230,p<0.0001;右侧术前:1.620±0.389;右侧术后:2.411±0.452,p=0.0005)。多变量Cox分析表明,A4ul的节点效率增加和d是SMA综合征恢复时间的保护因素。在左侧病变组中发现预测评分与恢复时间之间存在显著负相关(r=-0.756,p<0.0001),在右侧病变组中也发现了相同趋势(r=-0.531,p=0.076)。

结论

本研究揭示病变半球A4ul节点效率的增加和d较长是SMA综合征恢复的保护因素。连接病变半球A4ul与对侧半球节点的半球间纤维数量减少与SMA综合征的恢复时间延长相关。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/246f/12064937/2aa5cd42c178/CNS-31-e70426-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/246f/12064937/dbd93ae3eba0/CNS-31-e70426-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/246f/12064937/0b8fbeb91843/CNS-31-e70426-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/246f/12064937/b2f8d26f78dd/CNS-31-e70426-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/246f/12064937/9b11c8494aa8/CNS-31-e70426-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/246f/12064937/90909a6002f9/CNS-31-e70426-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/246f/12064937/2aa5cd42c178/CNS-31-e70426-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/246f/12064937/dbd93ae3eba0/CNS-31-e70426-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/246f/12064937/0b8fbeb91843/CNS-31-e70426-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/246f/12064937/b2f8d26f78dd/CNS-31-e70426-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/246f/12064937/9b11c8494aa8/CNS-31-e70426-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/246f/12064937/90909a6002f9/CNS-31-e70426-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/246f/12064937/2aa5cd42c178/CNS-31-e70426-g005.jpg

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