基于图论的胶质瘤患者脑结构网络分析

Graph theoretical analysis of structural brain network in patients with glioma

  • 摘要:
      背景  胶质瘤是颅内十分常见的恶性肿瘤,具有很强的侵袭性,既往研究表明胶质瘤的存在不仅会对病变周围造成损害,还会对肿瘤范围以外的其他远隔部位造成功能损害。对大脑网络的研究,可帮助临床医师对胶质瘤患者的手术预期及预后作出更精准的判断。
      目的  研究不同部位胶质瘤患者脑网络拓扑属性的改变,探讨由肿瘤病变引起与大脑功能变化相关的结构网络重塑。
      方法  纳入解放军总医院第一医学中心神经外科2018年1月 - 2020年12月收治的113例胶质瘤患者,采集所有受试者核磁共振扫描的弥散张量成像后,采用Mrtrix3软件对数据进行处理并构建大脑结构网络,通过GRETNA软件基于图论方法计算网络拓扑属性,观察不同位置肿瘤对脑结构网络的影响。
      结果  额叶、颞叶、顶叶胶质瘤三组间的全局最短路径长度(the shortest path length,Lp)、聚类系数(clustering coefficient,Cp)、全局网络效率(network efficiency,Eg)、局部效率(local efficiency,Eloc)表现出现统计学差异,与额叶、颞叶胶质瘤组相比,顶叶胶质瘤组的全局拓扑属性表现为升高(P<0.05),与其他脑区节点网络属性指标相比,肿瘤所在脑区的节点介数中心性(betweenness centrality,NBc)、度中心性(degree centrality,NDc)、全局效率(nodular global efficiency,NEg)升高,节点最短路径长度(nodular shortest path length,NLp)下降,差异有统计学意义(P<0.05)。
      结论  不同脑叶位置胶质瘤的网络拓扑属性发生了变化,全局属性和局部节点属性均表现出脑结构网络连接性改变。

     

    Abstract:
      Background  Glioma is the most common intracranial malignant tumor, which often shows strong invasiveness. Previous studies have shown that the existence of gliomas will not only cause damage around the lesions, but also distant sites outside the scope of the tumor. The study of structural brain network can help surgeons to make better judgment about the surgical expectation and prognosis for glioma patients.
      Objective  To investigate the changes of topological properties of brain network in patients with gliomas at different sites, and reveal the structural network remodeling related to brain function changes caused by tumor lesions.
      Methods  Totally 113 glioma patients were enrolled from 2018 to 2020 at the Department of Neurosurgery, Chinese PLA General Hospital. The diffusion tensor imaging data from MRI were processed by Mrtrix3 software and the brain structure network was constructed. The topological properties of the network were calculated by GRETNA software using graph theory. The effects of tumors in different locations on brain structural network were observed.
      Results  There were significant differences in global shortest path length (Lp), clustering coefficient (Cp), global network efficiency (Eg) and local efficiency (Eloc) among frontal lobe, temporal lobe and parietal lobe gliomas. The global topological property of parietal lobe glioma group was higher than that of frontal lobe and temporal lobe glioma group (P<0.05). Compared with other brain region node network attribute indexes, betweenness centrality (NBc), degree centrality (NDc), nodular global efficiency (NEg) increased and nodular shortest path length (NLp) decreased in the brain region where the tumor was located, and the difference was statistically significant (P< 0.05).
      Conclusion  The network topology attributes of glioma at different lobe locations have changed, and both the global attributes and local node attributes show changes in the connectivity of the brain structure network.

     

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