Department of Medical Imaging, Second Affiliated Hospital of Xi'an Jiaotong University, 157, Xi'wu Road, Xi'an, 710004, Shaanxi, China.
Neuroradiology. 2023 Oct;65(10):1483-1495. doi: 10.1007/s00234-023-03209-7. Epub 2023 Aug 22.
The aim of this study was to investigate alterations in the topological organization of whole-brain functional networks in patients with chronic low back pain (CLBP) and characterize the relationship of these alterations with pain characteristics.
Thirty-three CLBP patients and 34 matched healthy controls (HCs) underwent fMRI scans. A graph-theoretical approach was applied to identify brain network changes in patients suffering from chronic low back pain given its nonspecific etiology and complexity. Graph theory-based analysis was used to construct functional connectivity matrices and extract the features of small-world networks of the brain in both groups. Then, the whole-brain functional connectivity differences were characterized by network-based statistics (NBS) analysis, and the relationship between the altered brain features and clinical measures was explored.
At the global level, patients with CLBP showed significantly decreased gamma, sigma, global efficiency, and local efficiency and increased lambda and shortest path length compared with HCs. At the regional level, there were deficits in nodal efficiency within the default mode network and salience network. NBS analysis demonstrated that decreased functional connectivity was present in the CLBP patients, mainly in the frontolimbic circuit and temporal regions. Furthermore, aspects of topological dysfunctions in CLBP were correlated with pain severity.
This study highlighted the aberrant topological organization of functional brain networks in CLBP, which may shed light on the pathophysiology of CLBP and support the development of pain management approaches.
本研究旨在探讨慢性下背痛(CLBP)患者全脑功能网络拓扑组织的改变,并探讨这些改变与疼痛特征的关系。
33 例 CLBP 患者和 34 例匹配的健康对照组(HCs)接受 fMRI 扫描。鉴于慢性下背痛的非特异性病因和复杂性,我们采用了一种基于图论的方法来识别患者大脑网络的变化。基于图论的分析用于构建功能连接矩阵,并提取两组大脑小世界网络的特征。然后,通过基于网络的统计学(NBS)分析来描述全脑功能连接的差异,并探讨改变的大脑特征与临床指标之间的关系。
与 HCs 相比,CLBP 患者在全局水平上表现出明显的γ、σ、全局效率和局部效率降低,以及 λ和最短路径长度增加。在区域水平上,默认模式网络和突显网络内的节点效率存在缺陷。NBS 分析表明,CLBP 患者存在功能连接减少,主要集中在前额叶皮质和颞叶区域。此外,CLBP 患者的拓扑功能障碍与疼痛严重程度相关。
本研究强调了 CLBP 患者大脑功能网络拓扑结构的异常,这可能为 CLBP 的病理生理学提供了启示,并支持疼痛管理方法的发展。