我们提出了大脑肿瘤患者的网络拓扑结构可能发生改变的观点。然而，关于这些改变的模式没有共识，并且对潜在驱动因素的证据不足。我们旨在通过分析胶质性脑肿瘤（GBTs）和脑转移瘤（BMs）中结构性癫痫的存在来表征神经肿瘤患者的网络拓扑结构。我们研究了从2019年2月至2021年3月符合条件的患者。我们计算了六个频段的整个大脑（WB）连接性，网络拓扑参数（节点度、平均最短路径长度、局部聚类系数），并进行了分层分析，找出了功率上的差异。我们使用了Fieldtrip、Brain Connectivity MATLAB工具包和内部编写的脚本进行数据分析。我们收纳了41名患者（21名男性），平均年龄为60.1岁（范围23-82岁），其中GBTs（n = 23），BMs（n = 14）和其他组织学类型（n = 4）。统计分析表明，与对照组相比，患者的WB节点度在每个频段都显著降低（p1-30Hz = 0.002，pγ = 0.002，pβ = 0.002，pα = 0.002，pθ = 0.024和pδ = 0.002）。在描述性水平上，我们发现患者与对照组相比，WB局部聚类系数显著增加（p1-30Hz = 0.031，pδ = 0.013），但未经过虚拟发现率校正。没有发现GBTs与BMs的网络差异。然而，我们发现PSEs与PNSEs相比，WB局部聚类系数显著增加（pθ = 0.048），WB节点度显著降低（pα = 0.039），尚未经过校正。我们的数据暗示大脑肿瘤患者的网络拓扑结构发生改变。然而，单纯的组织学可能不会影响，但与肿瘤相关的癫痫似乎会影响大脑的功能网络。为了证实这些发现，需要进行长期研究和分析可能的混杂因素。©作者（们），2023年。

It was proposed that network topology is altered in brain tumor patients. However, there is no consensus on the pattern of these changes and evidence on potential drivers is lacking.We aimed to characterize neurooncological patients' network topology by analyzing glial brain tumors (GBTs) and brain metastases (BMs) with respect to the presence of structural epilepsy.Network topology derived from resting state magnetoencephalography was compared between (1) patients and controls, (2) GBTs and BMs, and (3) patients with (PSEs) and without structural epilepsy (PNSEs). Eligible patients were investigated from February 2019 to March 2021. We calculated whole brain (WB) connectivity in six frequency bands, network topological parameters (node degree, average shortest path length, local clustering coefficient) and performed a stratification, where differences in power were identified. For data analysis, we used Fieldtrip, Brain Connectivity MATLAB toolboxes, and in-house built scripts.We included 41 patients (21 men), with a mean age of 60.1 years (range 23-82), of those were: GBTs (n = 23), BMs (n = 14), and other histologies (n = 4). Statistical analysis revealed a significantly decreased WB node degree in patients versus controls in every frequency range at the corrected level (p1-30Hz = 0.002, pγ = 0.002, pβ = 0.002, pα = 0.002, pθ = 0.024, and pδ = 0.002). At the descriptive level, we found a significant augmentation for WB local clustering coefficient (p1-30Hz = 0.031, pδ = 0.013) in patients compared to controls, which did not persist the false discovery rate correction. No differences regarding networks of GBTs compared to BMs were identified. However, we found a significant increase in WB local clustering coefficient (pθ = 0.048) and decrease in WB node degree (pα = 0.039) in PSEs versus PNSEs at the uncorrected level.Our data suggest that network topology is altered in brain tumor patients. Histology per se might not, however, tumor-related epilepsy seems to influence the brain's functional network. Longitudinal studies and analysis of possible confounders are required to substantiate these findings.© The Author(s), 2023.