Topological Alterations in White Matter Structural Networks in Blepharospasm.
blepharospasm
diffusion tensor imaging
graph theoretical analysis
hemifacial spasm
white matter structural networks
Journal
Movement disorders : official journal of the Movement Disorder Society
ISSN: 1531-8257
Titre abrégé: Mov Disord
Pays: United States
ID NLM: 8610688
Informations de publication
Date de publication:
12 2021
12 2021
Historique:
received:
12
04
2021
accepted:
03
07
2021
pubmed:
29
7
2021
medline:
17
3
2022
entrez:
28
7
2021
Statut:
ppublish
Résumé
Accumulating evidence indicates regional structural changes in the white matter (WM) of brains in patients with blepharospasm (BSP); however, whether large-scale WM structural networks undergo widespread reorganization in these patients remains unclear. We investigated topology changes and global and local features of large-scale WM structural networks in BSP patients compared with hemifacial spasm (HFS) patients or healthy controls (HCs). This cross-sectional study applied graph theoretical analysis to assess deterministic diffusion tensor tractography findings in 41 BSP patients, 41 HFS patients, and 41 HCs. WM structural connectivity in 246 cortical and subcortical regions was assessed, and topological parameters of the resulting graphs were calculated. Networks were compared among BSP, HFS, and HCs groups. Compared to HCs, both BSP and HFS patients showed alterations in network integration and segregation characterized by increased global efficiency and modularity and reduced shortest path length. Moreover, increased nodal efficiency in multiple cortical and subcortical regions was found in BSP and HFS patients compared with HCs. However, these differences were not found between BSP and HFS patients. Whereas all participants showed highly similar hub distribution patterns, BSP patients had additional hub regions not present in either HFS patients or HCs, which were located in the primary head and face motor cortex and basal ganglia. Our findings suggest that the large-scale WM structural network undergoes an extensive reorganization in BSP, probably due to both dystonia-specific abnormalities and facial hyperkinetic movements. © 2021 International Parkinson and Movement Disorder Society.
Sections du résumé
BACKGROUND
Accumulating evidence indicates regional structural changes in the white matter (WM) of brains in patients with blepharospasm (BSP); however, whether large-scale WM structural networks undergo widespread reorganization in these patients remains unclear.
OBJECTIVE
We investigated topology changes and global and local features of large-scale WM structural networks in BSP patients compared with hemifacial spasm (HFS) patients or healthy controls (HCs).
METHODS
This cross-sectional study applied graph theoretical analysis to assess deterministic diffusion tensor tractography findings in 41 BSP patients, 41 HFS patients, and 41 HCs. WM structural connectivity in 246 cortical and subcortical regions was assessed, and topological parameters of the resulting graphs were calculated. Networks were compared among BSP, HFS, and HCs groups.
RESULTS
Compared to HCs, both BSP and HFS patients showed alterations in network integration and segregation characterized by increased global efficiency and modularity and reduced shortest path length. Moreover, increased nodal efficiency in multiple cortical and subcortical regions was found in BSP and HFS patients compared with HCs. However, these differences were not found between BSP and HFS patients. Whereas all participants showed highly similar hub distribution patterns, BSP patients had additional hub regions not present in either HFS patients or HCs, which were located in the primary head and face motor cortex and basal ganglia.
CONCLUSIONS
Our findings suggest that the large-scale WM structural network undergoes an extensive reorganization in BSP, probably due to both dystonia-specific abnormalities and facial hyperkinetic movements. © 2021 International Parkinson and Movement Disorder Society.
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
2802-2810Informations de copyright
© 2021 International Parkinson and Movement Disorder Society.
Références
Hassell TJW, Charles D. Treatment of blepharospasm and oromandibular dystonia with botulinum toxins. Toxins 2020;12:269.
Defazio G, Hallett M, Jinnah HA, Conte A, Berardelli A. Blepharospasm 40 years later. Mov Disord 2017;32:498-509.
Baker RS, Andersen AH, Morecraft RJ, Smith CD. A functional magnetic resonance imaging study in patients with benign essential blepharospasm. J Neuroophthalmol 2003;23:11-15.
Dresel C, Haslinger B, Castrop F, Wohlschlaeger AM, Ceballos-Baumann AO. Silent event-related fMRI reveals deficient motor and enhanced somatosensory activation in orofacial dystonia. Brain 2006;129:36-46.
Jochim A, Li Y, Gora-Stahlberg G, et al. Altered functional connectivity in blepharospasm/orofacial dystonia. Brain Behav 2017;8:e00894.
Ni MF, Huang XF, Miao YW, Liang ZH. Resting state fMRI observations of baseline brain functional activities and connectivities in primary blepharospasm. Neurosci Lett 2017;660:22-28.
Etgen T, Mühlau M, Gaser C, Sander D. Bilateral grey-matter increase in the putamen in primary blepharospasm. J Neurol Neurosurg Psychiatry 2006;77:1017-1020.
Obermann M, Yaldizli O, De Greiff A, et al. Morphometric changes of sensorimotor structures in focal dystonia. Mov Disord 2007;22:1117-1123.
Horovitz SG, Ford A, Najee-Ullah MA, Ostuni JL, Hallett M. Anatomical correlates of blepharospasm. Transl Neurodegener 2012;1:12.
Liu J, Li L, Chen L, et al. Grey matter changes in Meige syndrome: a voxel-based morphology analysis. Sci Rep 2020;10:14533.
Zhou B, Wang J, Huang Y, Yang Y, Gong Q, Zhou D. A resting state functional magnetic resonance imaging study of patients with benign essential blepharospasm. J Neuroophthalmol 2013;33:235-240.
Battistella G, Termsarasab P, Ramdhani RA, Fuertinger S, Simonyan S. Isolated focal dystonia as a disorder of large-scale functional networks. Cereb Cortex 2017;27:1203-1215.
Huang XF, Zhu MR, Shan P, et al. Multiple neural networks malfunction in primary blepharospasm: an independent components analysis. Front Hum Neurosci 2017;11:235.
Chirumamilla VC, Dresel C, Koirala N, et al. Structural brain network fingerprints of focal dystonia. Ther Adv Neurol Disord 2019;12:1756286419880664.
Ramdhani RA, Kumar V, Velickovic M, Frucht SJ, Tagliati M, Simonyan K. What's special about task in dystonia? A voxel-based morphometry and diffusion weighted imaging study. Mov Disord 2014;29:1141-1150.
Guo Y, Peng K, Ou Z, et al. Structural brain changes in blepharospasm: a cortical thickness and diffusion tensor imaging study. Front Neurosci 2020;14:543802.
Lehéricy S, Tijssen MA, Vidailhet M, Kaji R, Meunier S. The anatomical basis of dystonia: current view using neuroimaging. Mov Disord 2013;28:944-957.
Albanese A, Bhatia K, Bressman SB, et al. Phenomenology and classification of dystonia: a consensus update. Mov Disord 2013;28:863-873.
Hamilton M. The assessment of anxiety states by rating. Br J Med Psychol 1959;32:50-55.
Jankovic J, Kenney C, Grafe S, Goertelmeyer R, Comes G. Relationship between various clinical outcome assessments in patients with blepharospasm. Mov Disord 2009;24:407-413.
Wabbels B, Roggenkämper P. Botulinum toxin in hemifacial spasm: the challenge to assess the effect of treatment. J Neural Transm 2012;119:963-980.
Cui Z, Zhong S, Xu P, He Y, Gong G. PANDA: a pipeline toolbox for analyzing brain diffusion images. Front Hum Neurosci 2013;7:42.
Fan L, Li H, Zhuo J, et al. The human brainnetome atlas: a new brain atlas based on connectional architecture. Cereb Cortex 2016;26:3508-3526.
Mori S, Crain BJ, Chacko VP, van Zijl PC. Three-dimensional tracking of axonal projections in the brain by magnetic resonance imaging. Ann Neurol 1999;45:265-269.
Donahue CJ, Sotiropoulos SN, Jbabdi S, et al. Using diffusion tractography to predict cortical connection strength and distance: a quantitative comparison with tracers in the monkey. J Neurosci 2016;36:6758-6770.
Zhao C, Yang L, Xie S, Zhang Z, Pan H, Gong G. Hemispheric module-specific influence of the X chromosome on white matter connectivity: evidence from girls with Turner syndrome. Cereb Cortex 2019;29:4580-4594.
Wang J, Wang X, Xia M, Liao X, Evans A, He Y. GRETNA: a graph theoretical network analysis toolbox for imaging connectomics. Front Hum Neurosci 2015;9:386.
Çelik ZÇ, Çolak Ç, Di Biase MA, et al. Structural connectivity in adolescent synthetic cannabinoid users with and without ADHD. Brain Imaging Behav 2020;14:505-514.
Cao Q, Shu N, An L, et al. Probabilistic diffusion tractography and graph theory analysis reveal abnormal white matter structural connectivity networks in drug-naive boys with attention deficit/hyperactivity disorder. J Neurosci 2013;33:10676-10687.
Bi Q, Wang W, Niu N, et al. Relationship between the disrupted topological efficiency of the structural brain connectome and glucose hypometabolism in normal aging. Neuroimage 2021;226:117591.
Zhang J, Wang L, Ding H, et al. Abnormal large-scale structural rich club organization in Leber's hereditary optic neuropathy. Neuroimage Clin 2021;30:102619.
Hagmann P, Kurant M, Gigandet X, et al. Mapping human whole-brain structural networks with diffusion MRI. PLoS One 2007;2:e597.
Gong G, He Y, Concha L, et al. Mapping anatomical connectivity patterns of human cerebral cortex using in vivo diffusion tensor imaging tractography. Cereb Cortex 2009;19:524-536.
Gong G, Rosa-Neto P, Carbonell F, Chen ZJ, He Y, Evans AC. Age- and gender-related differences in the cortical anatomical network. J Neurosci 2009;29:15684-15693.
van den Heuvel MP, Sporns O. Rich-club organization of the human connectome. J Neurosci 2011;31:15775-15786.
Iturria-Medina Y, Canales-Rodríguez EJ, Melie-García L, et al. Characterizing brain anatomical connections using diffusion weighted MRI and graph theory. Neuroimage 2007;36:645-660.
Achard S, Bullmore E. Efficiency and cost of economical brain functional networks. PLoS Comput Biol 2007;3:e17.
Supekar K, Musen M, Menon V. Development of large-scale functional brain networks in children. PLoS Biol 2009;7:e1000157.
Neychev VK, Fan X, Mitev VI, Hess EJ, Jinnah HA. The basal ganglia and cerebellum interact in the expression of dystonic movement. Brain 2008;131:2499-2509.
Jinnah HA, Berardelli A, Comella C, et al. The focal dystonias: current views and challenges for future research. Mov Disord 2013;28:926-943.
Yang J, Luo C, Song W, et al. Diffusion tensor imaging in blepharospasm and blepharospasm-oromandibular dystonia. J Neurol 2014;261:1413-1424.
Berman BD, Honce JM, Shelton E, Sillau SH, Nagae LM. Isolated focal dystonia phenotypes are associated with distinct patterns of altered microstructure. Neuroimage Clin 2018;19:805-812.
Vitek JL. Pathophysiology of dystonia: a neuronal model. Mov Disord 2002;17(Suppl 3):S49-S62.
Balint B, Mencacci NE, Valente EM, et al. Dystonia. Nat Rev Dis Primers 2018;4:25.
Rinnerthaler M, Benecke C, Bartha L, Entner T, Poewe W, Mueller J. Facial recognition in primary focal dystonia. Mov Disord 2006;21:78-82.
Alemán GG, de Erausquin GA, Micheli F. Cognitive disturbances in primary blepharospasm. Mov Disord 2009;24:2112-2120.
Romano R, Bertolino A, Gigante A, Martino D, Livrea P, Defazio G. Impaired cognitive functions in adult-onset primary cranial cervical dystonia. Parkinsonism Relat Disord 2014;20:162-165.
Lange F, Seer C, Dengler R, Dressler D, Kopp B. Cognitive flexibility in primary dystonia. J Int Neuropsychol Soc 2016;22:662-670.
Mori S, van Zijl PC. Fiber tracking: principles and strategies - a technical review. NMR Biomed 2002;15:468-480.
Behrens TE, Woolrich MW, Jenkinson M, et al. Characterization and propagation of uncertainty in diffusion-weighted MR imaging. Magn Reson Med 2003;50:1077-1088.