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European Radiology

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11.02.2016 | Magnetic Resonance

Graph theoretical analysis reveals the reorganization of the brain network pattern in primary open angle glaucoma patients

verfasst von: Jieqiong Wang, Ting Li, Ningli Wang, Junfang Xian, Huiguang He

Erschienen in: European Radiology | Ausgabe 11/2016

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Abstract

Objectives

Most previous glaucoma studies with resting-state fMRI have focused on the neuronal activity in the individual structure of the brain, yet ignored the functional communication of anatomically separated structures. The purpose of this study is to investigate the efficiency of the functional communication change or not in glaucoma patients.

Methods

We applied the resting-state fMRI data to construct the connectivity network of 25 normal controls and 25 age-gender-matched primary open angle glaucoma patients. Graph theoretical analysis was performed to assess brain network pattern differences between the two groups.

Results

No significant differences of the global network measures were found between the two groups. However, the local measures were radically reorganized in glaucoma patients. Comparing with the hub regions in normal controls’ network, we found that six hub regions disappeared and nine hub regions appeared in the network of patients. In addition, the betweenness centralities of two altered hub regions, right fusiform gyrus and right lingual gyrus, were significantly correlated with the visual field mean deviation.

Conclusions

Although the efficiency of functional communication is preserved in the brain network of the glaucoma at the global level, the efficiency of functional communication is altered in some specialized regions of the glaucoma.

Key Points

• Global topological measures of brain network have no alterations in glaucoma patients.

• Local network measures are radically reorganized in glaucoma patients.

• The alterations of hub regions are found in the glaucoma.

• Betweenness centrality of altered hubs may reflect the glaucoma severity.

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Quigley HA, Broman AT (2006) The number of people with glaucoma worldwide in 2010 and 2020. Br J Ophthalmol 90:262–267CrossRefPubMedPubMedCentral

Whitmore AV, Libby RT, John SW (2005) Glaucoma: thinking in new ways-a role for autonomous axonal self-destruction and other compartmentalised processes? Prog Retin Eye Res 24:639–662CrossRefPubMed

Gupta V, Jha R, Rao A, Kong G, Sihota R (2009) The effect of different doses of intracameral bevacizumab on surgical outcomes of trabeculectomy for neovascular glaucoma. Eur J Ophthalmol 19:435–441PubMed

Duncan RO, Sample PA, Weinreb RN, Bowd C, Zangwill LM (2007) Retinotopic organization of primary visual cortex in glaucoma: Comparing fMRI measurements of cortical function with visual field loss. Prog Retin Eye Res 26:38–56CrossRefPubMed

Hui ES, Fu QL, So KF, Wu EX (2007) Diffusion tensor MR study of optic nerve degeneration in glaucoma. 2007 Annual International Conference of the Ieee Engineering in Medicine and Biology Society. 1–16:4312–4315

Garaci FG, Bolacchi F, Cerulli A et al (2009) Optic nerve and optic radiation neurodegeneration in patients with glaucoma: In vivo analysis with 3-T diffusion-tensor MR imaging. Radiology 252:496–501CrossRefPubMed

Engelhorn T, Michelson G, Waerntges S, Struffert T, Haider S, Doerfler A (2011) Diffusion tensor imaging detects rarefaction of optic radiation in glaucoma patients. Acad Radiol 18:764–769CrossRefPubMed

Zhang Y, Wan SH, Ge J, Zhang XL (2012) Diffusion tensor imaging reveals normal geniculocalcarine-tract integrity in acquired blindness. Brain Res 1458:34–39CrossRefPubMed

Wang J, Miao W, Li J et al (2015) Automatic segmentation of the lateral geniculate nucleus: Application to control and glaucoma patients. J Neurosci Methods 255:104–114CrossRefPubMed

10.

Chen WW, Wang N, Cai S et al (2013) Structural brain abnormalities in patients with primary open-angle glaucoma: a study with 3T MR imaging. Invest Ophthalmol Vis Sci 54:545–554CrossRefPubMed

11.

Gupta N, Yucel YH (2007) Glaucoma as a neurodegenerative disease. Curr Opin Ophthalmol 18:110–114CrossRefPubMed

12.

Liu Z, Xu C, Xu Y et al (2010) Decreased regional homogeneity in insula and cerebellum: a resting-state fMRI study in patients with major depression and subjects at high risk for major depression. Psychiatry Res 182:211–215CrossRefPubMed

13.

Greicius MD, Flores BH, Menon V et al (2007) Resting-state functional connectivity in major depression: abnormally increased contributions from subgenual cingulate cortex and thalamus. Biol Psychiatry 62:429–437CrossRefPubMedPubMedCentral

14.

Cherkassky VL, Kana RK, Keller TA, Just MA (2006) Functional connectivity in a baseline resting-state network in autism. Neuroreport 17:1687–1690CrossRefPubMed

15.

Paakki JJ, Rahko J, Long X et al (2010) Alterations in regional homogeneity of resting-state brain activity in autism spectrum disorders. Brain Res 1321:169–179CrossRefPubMed

16.

Liu Y, Yu C, Liang M et al (2007) Whole brain functional connectivity in the early blind. Brain 130:2085–2096CrossRefPubMed

17.

Wang D, Qin W, Liu Y, Zhang Y, Jiang T, Yu C (2014) Altered resting-state network connectivity in congenital blind. Hum Brain Mapp 35:2573–2581CrossRefPubMed

18.

Wang TY, Li Q, Guo MX et al (2014) Abnormal functional connectivity density in children with anisometropic amblyopia at resting-state. Brain Res 1563:41–51CrossRefPubMed

19.

Ding K, Liu Y, Yan X, Lin X, Jiang T (2013) Altered functional connectivity of the primary visual cortex in subjects with amblyopia. Neural Plast 2013(612086):8. doi:10.1155/2013/612086

20.

Lin X, Ding K, Liu Y, Yan X, Song S, Jiang T (2012) Altered spontaneous activity in anisometropic amblyopia subjects: revealed by resting-state fMRI. PLoS One 7(8):e43373. doi:10.1371/journal.pone.0043373

21.

Wang J, Hu L, Li W, Xian J, Ai L, He H (2014) Alternations of functional connectivity in amblyopia patients: a resting-state fMRI study. In: Proc. SPIE 9038, Medical Imaging 2014: Biomedical Applications in Molecular, Structural, and Functional Imaging, 903809 (March 13, 2014). doi:10.1117/12.2043424

22.

Song Y, Mu K, Wang J et al (2014) Altered spontaneous brain activity in primary open angle glaucoma: a resting-state functional magnetic resonance imaging study. PLoS One 9:e89493CrossRefPubMedPubMedCentral

23.

Li T, Liu Z, Li J et al (2015) Altered amplitude of low-frequency fluctuation in primary open-angle glaucoma: a resting-state FMRI study. Invest Ophthalmol Vis Sci 56:322–329CrossRef

24.

Zang Y, Jiang T, Lu Y, He Y, Tian L (2004) Regional homogeneity approach to fMRI data analysis. Neuroimage 22:394–400CrossRefPubMed

25.

Zang YF, He Y, Zhu CZ et al (2007) Altered baseline brain activity in children with ADHD revealed by resting-state functional MRI. Brain Dev 29:83–91CrossRefPubMed

26.

van den Heuvel MP, Hulshoff Pol HE (2010) Exploring the brain network: a review on resting-state fMRI functional connectivity. Eur Neuropsychopharmacol 20:519–534CrossRefPubMed

27.

Dai H, Morelli JN, Ai F et al (2013) Resting-state functional MRI: functional connectivity analysis of the visual cortex in primary open-angle glaucoma patients. Hum Brain Mapp 34:2455–2463CrossRefPubMed

28.

Shu N, Liu Y, Li J, Li Y, Yu C, Jiang T (2009) Altered anatomical network in early blindness revealed by diffusion tensor tractography. PLoS One 4:e7228CrossRefPubMedPubMedCentral

29.

Bola M, Gall C, Moewes C, Fedorov A, Hinrichs H, Sabel BA (2014) Brain functional connectivity network breakdown and restoration in blindness. Neurology 83:542–551CrossRefPubMed

30.

Gong GL, Rosa P, Carbonell F, Chen ZJ, He Y, Evans AC (2009) Age- and gender-related differences in the cortical anatomical network. J Neurosci 29:15684–15693CrossRefPubMedPubMedCentral

31.

Chen ZJ, He Y, Rosa-Neto P, Gong GL, Evans AC (2011) Age-related alterations in the modular organization of structural cortical network by using cortical thickness from MRI. Neuroimage 56:235–245CrossRefPubMed

32.

He Y, Chen Z, Evans A (2008) Structural insights into aberrant topological patterns of large-scale cortical networks in Alzheimer’s disease. J Neurosci 28:4756–4766CrossRefPubMed

33.

Supekar K, Menon V, Rubin D, Musen M, Greicius MD (2008) Network analysis of intrinsic functional brain connectivity in Alzheimer’s disease. PLoS Comput Biol 4:e1000100CrossRefPubMedPubMedCentral

34.

Buckner RL, Sepulcre J, Talukdar T et al (2009) Cortical hubs revealed by intrinsic functional connectivity: mapping, assessment of stability, and relation to Alzheimer’s disease. J Neurosci 29:1860–1873CrossRefPubMedPubMedCentral

35.

Lo CY, Wang PN, Chou KH, Wang JH, He Y, Lin CP (2010) Diffusion Tensor Tractography Reveals Abnormal Topological Organization in Structural Cortical Networks in Alzheimer’s Disease. J Neurosci 30:16876–16885CrossRefPubMed

36.

Yao Z, Zhang Y, Lin L, Zhou Y, Xu C, Jiang T et al. (2010) Abnormal cortical networks in mild cognitive impairment and Alzheimer’s Disease. PLoS Comput Biol 6(11):e1001006. doi:10.1371/journal.pcbi.1001006

37.

Zhou J, Gennatas ED, Kramer JH, Miller BL, Seeley WW (2012) Predicting regional neurodegeneration from the healthy brain functional connectome. Neuron 73:1216–1227CrossRefPubMedPubMedCentral

38.

Humphries MD, Gurney K, Prescott TJ (2006) The brainstem reticular formation is a small-world, not scale-free, network. Proc R Soc B Biol Sci 273:503–511CrossRef

39.

Latora V, Marchiori M (2001) Efficient behavior of small-world networks. Phys Rev Lett 87(19):198701. doi:10.1103/PhysRevLett.87.198701

40.

Watts DJ, Strogatz SH (1998) Collective dynamics of ‘small-world’ networks. Nature 393:440–442CrossRefPubMed

41.

Yan CG, Zang YF (2010) DPARSF: A MATLAB toolbox for “Pipeline” data analysis of resting-state fMRI. Front Syst Neurosci 4:13

42.

Tzourio-Mazoyer N, Landeau B, Papathanassiou D et al (2002) Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain. Neuroimage 15:273–289CrossRefPubMed

43.

Rubinov M, Sporns O (2010) Complex network measures of brain connectivity: uses and interpretations. Neuroimage 52:1059–1069CrossRefPubMed

44.

Achard S, Delon-Martin C, Vertes PE et al (2012) Hubs of brain functional networks are radically reorganized in comatose patients. Proc Natl Acad Sci U S A 109:20608–20613CrossRefPubMedPubMedCentral

45.

Sporns O, Honey CJ (2006) Small worlds inside big brains. Proc Natl Acad Sci U S A 103:19219–19220CrossRefPubMedPubMedCentral

46.

Achard S, Salvador R, Whitcher B, Suckling J, Bullmore E (2006) A resilient, low-frequency, small-world human brain functional network with highly connected association cortical hubs. J Neurosci 26:63–72CrossRefPubMed

47.

Hagmann P, Kurant M, Gigandet X et al (2007) Mapping human whole-brain structural networks with diffusion MRI. PLoS One 2:e597CrossRefPubMedPubMedCentral

48.

He Y, Chen ZJ, Evans AC (2007) Small-world anatomical networks in the human brain revealed by cortical thickness from MRI. Cereb Cortex 17:2407–2419CrossRefPubMed

49.

Iturria-Medina Y, Sotero RC, Canales-Rodriguez EJ, Aleman-Gomez Y, Melie-Garcia L (2008) Studying the human brain anatomical network via diffusion-weighted MRI and Graph Theory. Neuroimage 40:1064–1076CrossRefPubMed

50.

Liu Y, Liang M, Zhou Y et al (2008) Disrupted small-world networks in schizophrenia. Brain 131:945–961CrossRefPubMed

51.

Gong GL, He Y, Concha L et al (2009) Mapping anatomical connectivity patterns of human cerebral cortex using in vivo diffusion tensor imaging tractography. Cereb Cortex 19:524–536CrossRefPubMed

52.

Micheloyannis S, Pachou E, Stam CJ, Vourkas M, Erimaki S, Tsirka V (2006) Using graph theoretical analysis of multi channel EEG to evaluate the neural efficiency hypothesis. Neurosci Lett 402:273–277CrossRefPubMed

53.

Stam CJ, Jones BF, Nolte G, Breakspear M, Scheltens P (2007) Small-world networks and functional connectivity in Alzheimer’s disease. Cereb Cortex 17:92–99CrossRefPubMed

54.

Stam CJ, de Haan W, Daffertshofer A et al (2009) Graph theoretical analysis of magnetoencephalographic functional connectivity in Alzheimer’s disease. Brain 132:213–224CrossRefPubMed

55.

Wang QF, Su TP, Zhou Y et al (2012) Anatomical insights into disrupted small-world networks in schizophrenia. Neuroimage 59:1085–1093CrossRefPubMed

56.

Hanggi J, Wotruba D, Jancke L (2011) Globally altered structural brain network topology in grapheme-color synesthesia. J Neurosci 31:5816–5828CrossRefPubMed

57.

Caeyenberghs K, Leemans A, Heitger MH et al (2012) Graph analysis of functional brain networks for cognitive control of action in traumatic brain injury. Brain 135:1293–1307CrossRefPubMed

58.

Bullmore E, Sporns O (2009) Complex brain networks: graph theoretical analysis of structural and functional systems. Nat Rev Neurosci 10:186–198CrossRefPubMed

59.

Yuan W, Wade SL, Babcock L (2015) Structural connectivity abnormality in children with acute mild traumatic brain injury using graph theoretical analysis. Hum Brain Mapp 36(2):779–792

60.

Dehaene S, Le Clec HG, Poline JB, Le Bihan D, Cohen L (2002) The visual word form area: a prelexical representation of visual words in the fusiform gyrus. Neuroreport 13:321–325CrossRefPubMed

61.

Inman WS (1921) Emotion and eye symptoms. Br J Med Psychol 2:47–67CrossRef

62.

Schoenberg MJ (1940) Role of states of anxiety in the pathogenesis of primary glaucoma. Arch Ophthalmol 23:76–86CrossRef

63.

Sykes CS (1949) Role of emotion in glaucoma. Dis Nerv Syst 10:104–107PubMed

64.

Ripley HS, Wolff HG (1950) Life situations, emotions, and glaucoma. Psychosom Med 12:215–224CrossRefPubMed

65.

Yochim BP, Mueller AE, Kane KD, Kahook MY (2012) Prevalence of cognitive impairment, depression, and anxiety symptoms among older adults with glaucoma. J Glaucoma 21:250–254CrossRefPubMed

Titel: Graph theoretical analysis reveals the reorganization of the brain network pattern in primary open angle glaucoma patients
verfasst von: Jieqiong Wang
Ting Li
Ningli Wang
Junfang Xian
Huiguang He
Publikationsdatum: 11.02.2016
Verlag: Springer Berlin Heidelberg
Erschienen in: European Radiology / Ausgabe 11/2016
Print ISSN: 0938-7994
Elektronische ISSN: 1432-1084
DOI: https://doi.org/10.1007/s00330-016-4221-x

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Graph theoretical analysis reveals the reorganization of the brain network pattern in primary open angle glaucoma patients

Abstract

Objectives

Methods

Results

Conclusions

Key Points

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Springer Medizin

Abstract

Objectives

Methods

Results

Conclusions

Key Points

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