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采用静息态 fMRI 的图论分析研究重性抑郁障碍的功能脑网络变化。

Investigating changes of functional brain networks in major depressive disorder by graph theoretical analysis of resting-state fMRI.

机构信息

Department of Biomedical Engineering, Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran.

Department of Biomedical Engineering, Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran.

出版信息

Psychiatry Res Neuroimaging. 2024 Oct;344:111880. doi: 10.1016/j.pscychresns.2024.111880. Epub 2024 Aug 24.

Abstract

BACKGROUND

Major Depressive Disorder (MDD), as a chronic mental disorder, causes changes in mood, thoughts, and behavior. The pathophysiology of the disorder and its treatment are still unknown. One of the most notable changes observed in patients with MDD through fMRI is abnormal functional brain connectivity.

METHODS

Preprocessed data from 60 MDD patients and 60 normal controls (NCs) were selected, which has been performed using the DPARSF toolbox. The whole-brain functional networks and topologies were extracted using graph theory-based methods. A two-sample, two-tailed t-test was used to compare the topological features of functional brain networks between the MDD and NCs groups using the DPABI-Net/Statistical Analysis toolbox.

RESULTS

The obtained results showed a decrease in both global and local efficiency in MDD patients compared to NCs, and specifically, MDD patients showed significantly higher path length values. Acceptable p-values were obtained with a small sample size and less computational volume compared to the other studies on large datasets. At the node level, MDD patients showed decreased and relatively decreased node degrees in the sensorimotor network (SMN) and the dorsal attention network (DAN), respectively, as well as decreased node efficiency in the SMN, default mode network (DMN), and DAN. Also, MDD patients showed slightly decreased node efficiency in the visual networks (VN) and the ventral attention network (VAN), which were reported after FDR correction with Q < 0.05.

LIMITATIONS

All participants were Chinese.

CONCLUSIONS

Collectively, increased path length, decreased global and local efficiency, and also decreased nodal degree and efficiency in the SMN, DAN, DAN, VN, and VAN were found in patients compared to NCs.

摘要

背景

重度抑郁症(MDD)作为一种慢性精神障碍,会导致情绪、思维和行为的变化。这种疾病的病理生理学及其治疗方法仍不清楚。通过 fMRI 观察到 MDD 患者最显著的变化之一是大脑功能连接异常。

方法

从 60 名 MDD 患者和 60 名正常对照组(NCs)中选择经过预处理的数据,这些数据是使用 DPARSF 工具箱完成的。使用基于图论的方法提取全脑功能网络和拓扑结构。使用 DPABI-Net/Statistical Analysis 工具箱,采用两样本两尾 t 检验比较 MDD 组和 NCs 组的功能脑网络拓扑特征。

结果

与 NCs 相比,MDD 患者的全局和局部效率均降低,尤其是 MDD 患者的路径长度值明显升高。与其他基于大型数据集的研究相比,该研究的样本量小、计算量少,结果的可接受 p 值也较高。在节点水平上,MDD 患者的感觉运动网络(SMN)和背侧注意网络(DAN)的节点度分别降低,且相对降低,DAN 的节点效率也降低。此外,SMN、默认模式网络(DMN)和 DAN 的节点效率也降低,VN 和腹侧注意网络(VAN)的节点效率略有降低,这些结果在 FDR 校正后 Q<0.05 时有报道。

局限性

所有参与者均为中国人。

结论

与 NCs 相比,MDD 患者的路径长度增加,全局和局部效率降低,SMN、DAN、DMN、VN 和 VAN 的节点度和效率降低。

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