Headache Center, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
Tiantan Neuroimaging Center of Excellence, China National Clinical Research Center for Neurological Diseases, Beijing, China.
J Headache Pain. 2024 Nov 25;25(1):204. doi: 10.1186/s10194-024-01919-8.
To delineate the structural connectome alterations in patients with chronic migraine (CM), episodic migraine (EM), and healthy controls (HCs).
The pathogenesis of migraine chronification remains elusive, with structural brain network changes potentially playing a key role. However, there is a paucity of research employing graph theory analysis to explore changes in the whole brain structural networks in patients with CM and EM.
The individual structural brain connectome of 60 patients with CM, 34 patients with EM, and 39 healthy control participants were constructed by using deterministic diffusion-tensor tractography. Graph metrics including global efficiency, characteristic path length, local efficiency, clustering coefficient, and small-world parameters were evaluated to describe the topologic organization of the white matter structural networks. Additionally, nodal clustering coefficient and efficiency were considered to assess the regional characteristics of the brain connectome. A graph-based statistic was used to assess brain network properties across the groups.
Graph theory analysis revealed significant disruptions in the structural brain networks of CM patients, characterized by reduced global efficiency, local efficiency, and increased characteristic path length compared to HCs. Additionally, CM patients exhibited significantly lower local efficiency than EM patients. Notably, the CM group demonstrated marked reductions in local clustering coefficient and nodal local efficiency in the frontal and temporal regions compared with the healthy control group and EM group. Nodal local efficiency can effectively distinguish CM from EM and HCs. Moreover, the disrupted topologic efficiency was significantly associated with attack frequency and MIDAS score in patients with migraine after Bonferroni correction.
Decreased structural connectivity in the frontal and temporal regions may serve as a neuroimaging marker for migraine chronification and disease progression, providing valuable insights into the pathophysiology of chronic migraine.
描绘慢性偏头痛(CM)、阵发性偏头痛(EM)患者与健康对照(HC)的结构连接组改变。
偏头痛慢性化的发病机制仍不清楚,结构脑网络变化可能起着关键作用。然而,运用图论分析来探索 CM 和 EM 患者全脑结构网络变化的研究较少。
采用确定性弥散张量追踪技术构建 60 例 CM 患者、34 例 EM 患者和 39 例健康对照者的个体结构脑连接组。评估全局效率、特征路径长度、局部效率、聚类系数和小世界参数等图论指标,以描述白质结构网络的拓扑组织。此外,还考虑了节点聚类系数和效率,以评估脑连接组的区域特征。采用基于图的统计方法评估跨组的脑网络特性。
图论分析显示,CM 患者的结构脑网络存在显著破坏,与 HC 相比,全局效率、局部效率降低,特征路径长度增加。此外,CM 患者的局部效率明显低于 EM 患者。值得注意的是,与健康对照组和 EM 组相比,CM 组在额区和颞区的局部聚类系数和节点局部效率明显降低。节点局部效率可以有效地将 CM 与 EM 和 HC 区分开来。此外,经 Bonferroni 校正后,拓扑效率的破坏与偏头痛患者的发作频率和 MIDAS 评分显著相关。
额区和颞区结构连接的减少可能是偏头痛慢性化和疾病进展的神经影像学标志物,为慢性偏头痛的病理生理学提供了有价值的见解。