摘要
目的利用弥散张量成像(diffusion tensor imaging,DTI)技术构建胶质瘤患者手术前后全脑结构网络和半脑结构网络,基于图论知识对脑网络参数进行定量研究及对比分析,探究胶质瘤及肿瘤切除手术对患者脑网络拓扑特性的影响。方法构建健康对照组、胶质瘤患者组手术前后全脑和半脑结构网络,定量分析两组大脑结构网络拓扑特性及网络参数,比较分析手术对患者全脑及半脑网络特性的影响。结果从全脑角度看,患者术后各全局网络参数较正常人均有所降低,但是小世界特性却有所增强,患者各全局参数在术前术后均无显著差异,患者术后的全脑局部参数明显低于术前;在半脑结构网络中,手术前后半脑全局参数无明显差异,而术后半脑全局参数明显低于术前。结论手术使得脑结构网络的局部脑区发生损伤,但并未对患者全脑及半脑全局参数造成显著影响,研究证实了人类大脑的代偿机制以及功能重组。该研究方法可对胶质瘤患者术后的疾病发展状况以及手术治疗效果评价提供帮助。
Objective This study aims to construct the anatomical brain networks( both whole brain and hemispheric brain networks) for glioma patients with healthy controls based on diffusion tensor imaging( DTI)before and after resective surgery. Then the characteristic parameters of these networks are compared and analyzed based on graph theory in order to explore the influences of glioma and resective surgery on the topological properties of the patients. Methods The whole brain and hemispheric brain networks of healthy controls and glioma patients( both preoperative group and postoperative group) were constructed. After that,we analyzed the parameters and topology properties of anatomical brain networks quantitatively to explore the influence of resective surgery on the patient's whole brain and hemispheric brain networks. Results From the perspective of the whole brain,the global parameters dropped after surgery compared with healthy controls,however,the small-world properties enhanced. There was no significant difference before or after surgery,in addition,the local parameters of postoperative group were significantly lower than preoperative group in the whole brain networks. From the perspective of hemispheric brain,there was no significant difference in the global parameters before or after surgery. Also,the global parameters of hemispheric brain of preoperative group were superior to postoperative group. Conclusions The surgery damages the local brain regions of the patient,while the surgery does not cause any significant impact on the globalparameters of whole brain and hemispheric brain,the results confirm the existence of the brain's compensation and re-organization mechanism. Moreover,this method can be applied in the prediction of recovery after surgery and the treatment evaluation.
出处
《北京生物医学工程》
2017年第2期139-145,共7页
Beijing Biomedical Engineering
基金
国家自然科学基金(61275199
61378092)
中央高校基本科研业务费专项(NS2015032
NP2015201)资助
关键词
弥散张量成像
胶质瘤
脑结构网络
切除手术
网络拓扑属性
diffusion tensor imaging
glioma
brain anatomical networks
surgical resection
network topology