留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

基于图论的胶质瘤患者脑结构网络分析

刘明航 攸娜 杨晨轩 赵恺 赵悦 许百男

刘明航, 攸娜, 杨晨轩, 赵恺, 赵悦, 许百男. 基于图论的胶质瘤患者脑结构网络分析[J]. 解放军医学院学报, 2023, 44(5): 481-488. doi: 10.3969/j.issn.2095-5227.2023.05.008
引用本文: 刘明航, 攸娜, 杨晨轩, 赵恺, 赵悦, 许百男. 基于图论的胶质瘤患者脑结构网络分析[J]. 解放军医学院学报, 2023, 44(5): 481-488. doi: 10.3969/j.issn.2095-5227.2023.05.008
LIU Minghang, YOU Na, YANG Chenxuan, ZHAO Kai, ZHAO Yue, XU Bainan. Graph theoretical analysis of structural brain network in patients with glioma[J]. ACADEMIC JOURNAL OF CHINESE PLA MEDICAL SCHOOL, 2023, 44(5): 481-488. doi: 10.3969/j.issn.2095-5227.2023.05.008
Citation: LIU Minghang, YOU Na, YANG Chenxuan, ZHAO Kai, ZHAO Yue, XU Bainan. Graph theoretical analysis of structural brain network in patients with glioma[J]. ACADEMIC JOURNAL OF CHINESE PLA MEDICAL SCHOOL, 2023, 44(5): 481-488. doi: 10.3969/j.issn.2095-5227.2023.05.008

基于图论的胶质瘤患者脑结构网络分析

doi: 10.3969/j.issn.2095-5227.2023.05.008
详细信息
    作者简介:

    刘明航,男,在读硕士。研究方向:神经外科学。Email: liumhdoctor@163.com

    通讯作者:

    许百男,男,博士,主任医师,学术主任。Email: xubn301@aliyun.com

  • 中图分类号: R739.4

Graph theoretical analysis of structural brain network in patients with glioma

More Information
  • 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。

     

  • 图  1  额叶胶质瘤、颞叶胶质瘤、顶叶胶质瘤三组间全局参数比较(组别1:顶叶胶质瘤组;组别2:颞叶胶质瘤组;组别3:额叶胶质瘤组)

    A:三组间聚类系数指标比较;B:三组间最短路径长度比较;C:三组间全局效率比较;D:三组间局部效率比较

    Figure  1.  Comparison of global parameters among frontal lobe glioma, temporal lobe glioma and parietal lobe glioma (Group 1: parietal lobe glioma group; Group 2: temporal lobe glioma group; Group 3: frontal lobe glioma group)

    A: cluster coefficient index comparison among the three groups; B: shortest path length comparison among the three groups; C: global efficiency comparison among the three groups; D: local efficiency comparison among the three groups

    图  2  额叶胶质瘤、颞叶胶质瘤、顶叶胶质瘤三组间节点的介数中心性比较(红色小球表示组间比较升高的脑区,绿色小球表示组间比较降低的脑区。小球越大,表示升高或降低越显著;小球间连接线越粗,表示两节点间连接强度越强)

    A:额叶胶质瘤组与颞叶胶质瘤组的比较;B:额叶胶质瘤组与顶叶胶质瘤组的比较;C:颞叶胶质瘤组与顶叶胶质瘤组的比较

    Figure  2.  Comparison of the centrality of nodes among frontal lobe glioma, temporal lobe glioma and parietal lobe glioma (The red ball represents the elevated brain area of comparison between the groups, and the green ball indicates the decreased brain area of comparison between the groups. The larger the ball, the more obvious it is to rise or decrease. The thicker the connection line between the balls, the stronger the connection between the two nodes)

    A: comparison between frontal lobe glioma group and temporal lobe glioma group; B: comparison between frontal lobe glioma group and parietal lobe glioma group; C: comparison between temporal lobe glioma group and parietal lobe glioma group

    图  3  额叶胶质瘤、颞叶胶质瘤、顶叶胶质瘤三组间节点的度中心性比较(红色小球表示组间比较升高的脑区,绿色小球表示组间比较降低的脑区。小球越大,表示升高或降低越显著;小球间连接线越粗,表示两节点间连接强度越强)

    A:额叶胶质瘤组与颞叶胶质瘤组的比较;B:额叶胶质瘤组与顶叶胶质瘤组的比较;C:颞叶胶质瘤组与顶叶胶质瘤组的比较

    Figure  3.  Comparison of degree centrality of nodes among frontal lobe glioma, temporal lobe glioma and parietal lobe glioma (The red ball represents the elevated brain area of comparison between the groups, and the green ball indicates the decreased brain area of comparison between the groups. The larger the ball, the more obvious it is to rise or decrease. The thicker the connection line between the balls, the stronger the connection between the two nodes)

    A: comparison between frontal lobe glioma group and temporal lobe glioma group; B: comparison between frontal lobe glioma group and parietal lobe glioma group; C: comparison between temporal lobe glioma group and parietal lobe glioma group

    图  4  额叶胶质瘤、颞叶胶质瘤、顶叶胶质瘤三组间节点的全局效率比较(红色小球表示组间比较升高的脑区,绿色小球表示组间比较降低的脑区。小球越大,表示升高或降低越显著;小球间连接线越粗,表示两节点间连接强度越强)

    A:额叶胶质瘤组与颞叶胶质瘤组的比较;B:额叶胶质瘤组与顶叶胶质瘤组的比较;C:颞叶胶质瘤组与顶叶胶质瘤组的比较

    Figure  4.  Comparison of global efficiency of nodes among frontal lobe glioma, temporal lobe glioma and parietal lobe glioma (The red ball represents the elevated brain area of comparison between the groups, and the green ball indicates the decreased brain area of comparison between the groups. The larger the ball, the more obvious it is to rise or decrease. The thicker the connection line between the balls, the stronger the connection between the two nodes)

    A: comparison between frontal lobe glioma group and temporal lobe glioma group; B: comparison between frontal lobe glioma group and parietal lobe glioma group; C: comparison between temporal lobe glioma group and parietal lobe glioma group

    图  5  额叶胶质瘤、颞叶胶质瘤、顶叶胶质瘤三组间节点的最短路径长度比较(红色小球表示组间比较升高的脑区,绿色小球表示组间比较降低的脑区。小球越大,表示升高或降低越显著;小球间连接线越粗,表示两节点间连接强度越强)

    A:额叶胶质瘤组与颞叶胶质瘤组的比较;B:额叶胶质瘤组与顶叶胶质瘤组的比较;C:颞叶胶质瘤组与顶叶胶质瘤组的比较

    Figure  5.  Comparison of the shortest path length among frontal lobe glioma, temporal lobe glioma and parietal lobe glioma (The red ball represents the elevated brain area of comparison between the groups, and the green ball indicates the decreased brain area of comparison between the groups. The larger the ball, the more obvious it is to rise or decrease. The thicker the connection line between the balls, the stronger the connection between the two nodes)

    A: comparison between frontal lobe glioma group and temporal lobe glioma group; B: comparison between frontal lobe glioma group and parietal lobe glioma group; C: comparison between temporal lobe glioma group and parietal lobe glioma group

    表  1  全局拓扑属性比较

    Table  1.   Comparison of global topology attribute

    全局参数额叶肿瘤组颞叶肿瘤组顶叶肿瘤组FP
    聚类系数0.638 ± 0.0130.636 ± 0.0170.652 ± 0.00914.4000.001
    最短路径长度1.541 ± 0.0321.548 ± 0.0261.546 ± 0.01515.5320.001
    全局效率0.649 ± 0.0120.646 ± 0.0100.647 ± 0.00615.5820.001
    局部效率0.818 ± 0.0070.816 ± 0.0090.825 ± 0.00515.3990.001
    λ1.015 ± 0.0091.017 ± 0.0071.018 ± 0.0051.4590.237
    γ1.612 ± 0.1301.581 ± 0.0691.595 ± 0.0431.0420.356
    σ1.587 ± 0.1101.555 ± 0.0621.566 ± 0.0391.6490.197
    下载: 导出CSV
  • [1] Weller M,van den Bent M,Tonn JC,et al. European Association for Neuro-Oncology (EANO) guideline on the diagnosis and treatment of adult astrocytic and oligodendroglial gliomas[J]. Lancet Oncol,2017,18(6): e315-e329. doi: 10.1016/S1470-2045(17)30194-8
    [2] Zhang HS,Ille S,Sogerer L,et al. Elucidating the structural-functional connectome of language in glioma-induced aphasia using nTMS and DTI[J]. Hum Brain Mapp,2022,43(6): 1836-1849. doi: 10.1002/hbm.25757
    [3] Duffau H. Introducing the concept of brain metaplasticity in glioma:how to reorient the pattern of neural reconfiguration to optimize the therapeutic strategy[J]. J Neurosurg,2021,136(2): 613-617.
    [4] Melgarejo da Rosa M. Communication of Glioma cells with neuronal plasticity:what is the underlying mechanism?[J]. Neurochem Int,2020,141: 104879. doi: 10.1016/j.neuint.2020.104879
    [5] Almairac F,Duffau H,Herbet G. Contralesional macrostructural plasticity of the insular cortex in patients with glioma:a VBM study[J]. Neurology,2018,91(20): e1902-e1908. doi: 10.1212/WNL.0000000000006517
    [6] Lizarazu M,Gil-Robles S,Pomposo I,et al. Spatiotemporal dynamics of postoperative functional plasticity in patients with brain tumors in language areas[J]. Brain Lang,2020,202: 104741. doi: 10.1016/j.bandl.2019.104741
    [7] Cirillo S, Caulo M, Pieri V, et al. Role of functional imaging techniques to assess motor and language cortical plasticity in glioma patients: a systematic review[J/OL]. https://doi.org/10.1155/2019/4056436.
    [8] Li DL,Patel CB,Xu GF,et al. Visualization of diagnostic and therapeutic targets in glioma with molecular imaging[J]. Front Immunol,2020,11: 592389. doi: 10.3389/fimmu.2020.592389
    [9] Luo T, Li YL. Research and analysis of brain glioma imaging based on deep learning[J/OL]. https://doi.org/10.1155/2021/3426080.
    [10] Li GZ,Li L,Li YM,et al. An MRI radiomics approach to predict survival and tumour-infiltrating macrophages in gliomas[J]. Brain,2022,145(3): 1151-1161. doi: 10.1093/brain/awab340
    [11] Carrete LR,Young JS,Cha S. Advanced imaging techniques for newly diagnosed and recurrent gliomas[J]. Front Neurosci,2022,16: 787755. doi: 10.3389/fnins.2022.787755
    [12] Assaf Y,Pasternak O. Diffusion tensor imaging (DTI)-based white matter mapping in brain research:a review[J]. J Mol Neurosci,2008,34(1): 51-61. doi: 10.1007/s12031-007-0029-0
    [13] Chang XB,Jia XY,Wang YL,et al. Alterations of cerebellar white matter integrity and associations with cognitive impairments in schizophrenia[J]. Front Psychiatry,2022,13: 993866. doi: 10.3389/fpsyt.2022.993866
    [14] Lowry E,Puthusseryppady V,Johnen AK,et al. Cognitive and neuroimaging markers for preclinical vascular cognitive impairment[J]. Cereb Circ Cogn Behav,2021,2: 100029.
    [15] Niu C,Zhang M,Min ZG,et al. Motor network plasticity and low-frequency oscillations abnormalities in patients with brain gliomas:a functional MRI study[J]. PLoS One,2014,9(5): e96850. doi: 10.1371/journal.pone.0096850
    [16] Molendowska M,Matuszewski J,Kossowski B,et al. Temporal dynamics of brain white matter plasticity in sighted subjects during tactile Braille learning:a longitudinal diffusion tensor imaging study[J]. J Neurosci,2021,41(33): 7076-7085. doi: 10.1523/JNEUROSCI.2242-20.2021
    [17] Han K,Chapman SB,Krawczyk DC. Cognitive training reorganizes network modularity in traumatic brain injury[J]. Neurorehabil Neural Repair,2020,34(1): 26-38. doi: 10.1177/1545968319868710
    [18] Freundlieb N,Philipp S,Drabik A,et al. Ipsilesional motor area size correlates with functional recovery after stroke:a 6-month follow-up longitudinal TMS motor mapping study[J]. Restor Neurol Neurosci,2015,33(2): 221-231.
    [19] Bourgeron T. From the genetic architecture to synaptic plasticity in autism spectrum disorder[J]. Nat Rev Neurosci,2015,16(9): 551-563. doi: 10.1038/nrn3992
    [20] Rohlfs Domínguez P. Promoting our understanding of neural plasticity by exploring developmental plasticity in early and adult life[J]. Brain Res Bull,2014,107: 31-36. doi: 10.1016/j.brainresbull.2014.05.006
    [21] Sale A. Molecular mechanisms of neural plasticity:from basic research to implications for visual functional rescue[J]. Int J Mol Sci,2022,23(21): 13183. doi: 10.3390/ijms232113183
    [22] Frizzell TO,Phull E,Khan M,et al. Imaging functional neuroplasticity in human white matter tracts[J]. Brain Struct Funct,2022,227(1): 381-392. doi: 10.1007/s00429-021-02407-4
    [23] Jiao YM,Lin FX,Wu J,et al. Plasticity in language cortex and white matter tracts after resection of dominant inferior parietal lobule arteriovenous malformations:a combined fMRI and DTI study[J]. J Neurosurg,2020,134(3): 953-960.
    [24] Caria A,Dalboni da Rocha JL,Gallitto G,et al. Brain-machine interface induced Morpho-functional remodeling of the neural motor system in severe chronic stroke[J]. Neurotherapeutics,2020,17(2): 635-650. doi: 10.1007/s13311-019-00816-2
    [25] Sinke MR,Otte WM,van Meer MP,et al. Modified structural network backbone in the contralesional hemisphere chronically after stroke in rat brain[J]. J Cereb Blood Flow Metab,2018,38(9): 1642-1653. doi: 10.1177/0271678X17713901
    [26] Baldock AL,Yagle K,Born DE,et al. Invasion and proliferation kinetics in enhancing gliomas predict IDH1 mutation status[J]. Neuro-oncology,2014,16(6): 779-786. doi: 10.1093/neuonc/nou027
    [27] Slegers RJ,Blumcke I. Low-grade developmental and epilepsy associated brain tumors:a critical update 2020[J]. Acta Neuropathol Commun,2020,8(1): 27. doi: 10.1186/s40478-020-00904-x
    [28] Cunha MLVD,Maldaun MVC. Metastasis from glioblastoma multiforme:a meta-analysis[J]. Rev Assoc Med Bras (1992),2019,65(3): 424-433. doi: 10.1590/1806-9282.65.3.424
    [29] Buklina SB,Pitskhelauri DI,Beshplav ST. Clinical and neuropsychological survey of patients with glioma of the corpus callosum[J]. Zh Vopr Neirokhir Im N N Burdenko,2022,86(2): 80-88. doi: 10.17116/neiro20228602180
    [30] Angeli S,Emblem KE,Due-Tonnessen P,et al. Towards patient-specific modeling of brain tumor growth and formation of secondary nodes guided by DTI-MRI[J]. Neuroimage Clin,2018,20: 664-673. doi: 10.1016/j.nicl.2018.08.032
    [31] Yan JL,Li C,van der Hoorn A,et al. A neural network approach to identify the peritumoral invasive areas in glioblastoma patients by using MR radiomics[J]. Sci Rep,2020,10(1): 9748. doi: 10.1038/s41598-020-66691-6
    [32] Zhong LM,Li TF,Shu H,et al. (TS)2WM:tumor segmentation and tract statistics for assessing white matter integrity with applications to glioblastoma patients[J]. NeuroImage,2020,223: 117368. doi: 10.1016/j.neuroimage.2020.117368
    [33] Kocher M,Jockwitz C,Caspers S,et al. Role of the default mode resting-state network for cognitive functioning in malignant glioma patients following multimodal treatment[J]. Neuroimage Clin,2020,27: 102287. doi: 10.1016/j.nicl.2020.102287
    [34] Mair DB,Ames HM,Li R. Mechanisms of invasion and motility of high-grade gliomas in the brain[J]. Mol Biol Cell,2018,29(21): 2509-2515. doi: 10.1091/mbc.E18-02-0123
    [35] D'Souza S,Ormond DR,Costabile J,et al. Fiber-tract localized diffusion coefficients highlight patterns of white matter disruption induced by proximity to glioma[J]. PLoS One,2019,14(11): e0225323. doi: 10.1371/journal.pone.0225323
    [36] Ormond DR,D'Souza S,Thompson JA. Global and targeted pathway impact of gliomas on white matter integrity based on lobar localization[J]. Cureus,2017,9(9): e1660.
    [37] Larsen S,Kikinis R,Talos IF,et al. Quantitative comparison of functional MRI and direct electrocortical stimulation for functional mapping[J]. Int J Med Robot,2007,3(3): 262-270. doi: 10.1002/rcs.149
    [38] Yang J,Gohel S,Zhang Z,et al. Glioma-induced disruption of resting-state functional connectivity and amplitude of low-frequency fluctuations in the salience network[J]. AJNR Am J Neuroradiol,2021,42(3): 551-558. doi: 10.3174/ajnr.A6929
    [39] Maniar YM,Peck KK,Jenabi M,et al. Functional MRI shows altered deactivation and a corresponding decrease in functional connectivity of the default mode network in patients with gliomas[J]. AJNR Am J Neuroradiol,2021,42(8): 1505-1512. doi: 10.3174/ajnr.A7138
    [40] Duffau H. Functional mapping before and after low-grade glioma surgery:a new way to decipher various spatiotemporal patterns of individual neuroplastic potential in brain tumor patients[J]. Cancers,2020,12(9): 2611. doi: 10.3390/cancers12092611
    [41] Nelson CJ,Bonner S. Neuronal graphs:a graph theory primer for microscopic,functional networks of neurons recorded by calcium imaging[J]. Front Neural Circuits,2021,15: 662882. doi: 10.3389/fncir.2021.662882
    [42] Xin ZL,Chen XM,Zhang Q,et al. Alteration in topological properties of brain functional network after 2-year high altitude exposure:a panel study[J]. Brain Behav,2020,10(10): e01656.
    [43] Duffau H. Awake surgery for incidental WHO grade II gliomas involving eloquent areas[J]. Acta Neurochir,2012,154(4): 575-584. doi: 10.1007/s00701-011-1216-x
    [44] Kong NW, Gibb WR, Tate MC. Neuroplasticity: Insights from Patients Harboring Gliomas[J/OL]. https://doi.org/10.1155/2016/2365063.
    [45] Sihvonen AJ,Soinila S,Särkämö T. Post-stroke enriched auditory environment induces structural connectome plasticity:secondary analysis from a randomized controlled trial[J]. Brain Imaging Behav,2022,16(4): 1813-1822. doi: 10.1007/s11682-022-00661-6
    [46] Tavazzi E,Bergsland N,Pirastru A,et al. MRI markers of functional connectivity and tissue microstructure in stroke-related motor rehabilitation:a systematic review[J]. Neuroimage Clin,2022,33: 102931. doi: 10.1016/j.nicl.2021.102931
    [47] Zastron T,Kessner SS,Hollander K,et al. Structural connectivity changes within the basal Ganglia after 8 weeks of sensory-motor training in individuals with chronic stroke[J]. Ann Phys Rehabil Med,2019,62(3): 193-197. doi: 10.1016/j.rehab.2019.02.002
    [48] Southwell DG,Hervey-Jumper SL,Perry DW,et al. Intraoperative mapping during repeat awake craniotomy reveals the functional plasticity of adult cortex[J]. J Neurosurg,2016,124(5): 1460-1469. doi: 10.3171/2015.5.JNS142833
    [49] Sarubbo S,Le Bars E,Moritz-Gasser S,et al. Complete recovery after surgical resection of left Wernicke’s area in awake patient:a brain stimulation and functional MRI study[J]. Neurosurg Rev,2012,35(2): 287-292. doi: 10.1007/s10143-011-0351-4
    [50] Cui WG,Wang YY,Ren JX,et al. Personalized fMRI delineates functional regions preserved within brain tumors[J]. Ann Neurol,2022,91(3): 353-366. doi: 10.1002/ana.26303
  • 加载中
图(5) / 表(1)
计量
  • 文章访问数:  75
  • HTML全文浏览量:  27
  • PDF下载量:  6
  • 被引次数: 0
出版历程
  • 收稿日期:  2022-09-19
  • 网络出版日期:  2023-05-09
  • 刊出日期:  2023-05-28

目录

    /

    返回文章
    返回