Thalamic nuclei volumes and network in juvenile myoclonic epilepsy.
epilepsy
network
thalamus
volume
Journal
Acta neurologica Scandinavica
ISSN: 1600-0404
Titre abrégé: Acta Neurol Scand
Pays: Denmark
ID NLM: 0370336
Informations de publication
Date de publication:
Apr 2020
Apr 2020
Historique:
received:
31
07
2019
revised:
13
10
2019
accepted:
15
11
2019
pubmed:
21
11
2019
medline:
21
7
2020
entrez:
21
11
2019
Statut:
ppublish
Résumé
The aim of this study was to investigate the alterations of thalamic nuclei volumes and intrinsic thalamic networks in patients with juvenile myoclonic epilepsy (JME) compared to healthy controls. We enrolled 50 patients with JME and 42 healthy controls. We obtained structural volumes of the individual thalamic nuclei based on T1-weighted imaging and performed intrinsic thalamic network analysis using graph theoretical analysis. We analyzed the differences of thalamic nuclei volumes and intrinsic thalamic networks between the patients with JME and healthy controls. In the patients with JME, there were significant alterations of thalamic nuclei volumes compared to healthy controls. Right laterodorsal and left suprageniculate nuclei volumes were significantly increased (0.0019% vs 0.0014%, P < .0001; 0.0011% vs 0.0008%, P = .0006, respectively), whereas left ventral posterolateral, left ventromedial, and left pulvinar inferior nuclei volumes (0.0572% vs 0.0664%, P = .0001; 0.0013% vs 0.0015%, P = .0002; 0.0120% vs 0.0140%, P < .0001, respectively) were decreased in the patients with JME. Furthermore, the intrinsic thalamic network of the patients with JME was significantly different from that of the healthy controls. The modularity in the patients with JME was significantly increased over that in healthy controls (0.0785 vs 0.0212, P = .039). We found that there were significant alterations of thalamic nuclei volumes and intrinsic thalamic networks in patients with JME compared to healthy controls. These findings might contribute to the underlying pathogenesis of in JME.
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
271-278Informations de copyright
© 2019 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
Références
Baykan B, Wolf P. Juvenile myoclonic epilepsy as a spectrum disorder: a focused review. Seizure. 2017;49:36-41.
Hauser WA. The prevalence and incidence of convulsive disorders in children. Epilepsia. 1994;35(Suppl 2):S1-S6.
Zifkin B, Andermann E, Andermann F. Mechanisms, genetics, and pathogenesis of juvenile myoclonic epilepsy. Curr Opin Neurol. 2005;18:147-153.
von Podewils F, Runge U, Kruger S, et al. Diffusion tensor imaging abnormalities in photosensitive juvenile myoclonic epilepsy. Eur J Neurol. 2015;22:1192-1200.
Cao B, Tang Y, Li J, Zhang X, Shang HF, Zhou D. A meta-analysis of voxel-based morphometry studies on gray matter volume alteration in juvenile myoclonic epilepsy. Epilepsy Res. 2013;106:370-377.
Kim JH, Kim JB, Suh SI. Alteration of cerebello-thalamocortical spontaneous low-frequency oscillations in juvenile myoclonic epilepsy. Acta Neurol Scand. 2019;140(4):252-258.
Caeyenberghs K, Powell HW, Thomas RH, et al. Hyperconnectivity in juvenile myoclonic epilepsy: a network analysis. Neuroimage Clin. 2015;7:98-104.
Lee HJ, Park KM. Structural and functional connectivity in newly diagnosed juvenile myoclonic epilepsy. Acta Neurol Scand. 2019;139:469-475.
Lin K, Jackowski AP, Carrete H Jr, et al. Voxel-based morphometry evaluation of patients with photosensitive juvenile myoclonic epilepsy. Epilepsy Res. 2009;86:138-145.
Woermann FG, Free SL, Koepp MJ, Sisodiya SM, Duncan JS. Abnormal cerebral structure in juvenile myoclonic epilepsy demonstrated with voxel-based analysis of MRI. Brain. 1999;122(Pt 11):2101-2108.
van Diessen E, Zweiphenning WJ, Jansen FE, Stam CJ, Braun KP, Otte WM. Brain Network Organization in Focal Epilepsy: a systematic review and meta-analysis. PLoS ONE. 2014;9:e114606.
Pedersen SB, Petersen KA. Juvenile myoclonic epilepsy: clinical and EEG features. Acta Neurol Scand. 1998;97:160-163.
Farahani FV, Karwowski W, Lighthall NR. Application of graph theory for identifying connectivity patterns in human brain networks: a systematic review. Front Neurosci. 2019;13:585.
Welton T, Kent DA, Auer DP, Dineen RA. Reproducibility of graph-theoretic brain network metrics: a systematic review. Brain Connect. 2015;5:193-202.
Gleichgerrcht E, Kocher M, Bonilha L. Connectomics and graph theory analyses: novel insights into network abnormalities in epilepsy. Epilepsia. 2015;56:1660-1668.
Song JL. Thalamus: Anatomy, Functions, and Disorders. Hauppauge, NY: Nova Science Publishers Inc; 2011.
Benedek G, Pereny J, Kovacs G, Fischer-Szatmari L, Katoh YY. Visual, somatosensory, auditory and nociceptive modality properties in the feline suprageniculate nucleus. Neuroscience. 1997;78:179-189.
Paroczy Z, Nagy A, Markus Z, Waleszczyk WJ, Wypych M, Benedek G. Spatial and temporal visual properties of single neurons in the suprageniculate nucleus of the thalamus. Neuroscience. 2006;137:1397-1404.
Eordegh G, Nagy A, Berenyi A, Benedek G. Processing of spatial visual information along the pathway between the suprageniculate nucleus and the anterior ectosylvian cortex. Brain Res Bull. 2005;67:281-289.
Appleton R, Beirne M, Acomb B. Photosensitivity in juvenile myoclonic epilepsy. Seizure. 2000;9:108-111.
Moeller F, Siebner HR, Wolff S, et al. Mapping brain activity on the verge of a photically induced generalized tonic-clonic seizure. Epilepsia. 2009;50:1632-1637.
Haines DE, Mihailoff GA. Fundamental Neuroscience for Basic and Clinical Applications, 5th edn. Philadelphia, PA: Elsevier; 2018.
Kim SH, Lim SC, Kim W, et al. Extrafrontal structural changes in juvenile myoclonic epilepsy: a topographic analysis of combined structural and microstructural brain imaging. Seizure. 2015;30:124-131.
Clemens B, Puskas S, Besenyei M, et al. Neurophysiology of juvenile myoclonic epilepsy: EEG-based network and graph analysis of the interictal and immediate preictal states. Epilepsy Res. 2013;106:357-369.
Bing G, Wang T, Zeng H, et al. Patterns of gray matter abnormalities in idiopathic generalized epilepsy: a meta-analysis of voxel-based morphology studies. PLoS ONE. 2017;12:e0169076.
Rubinov M, Sporns O. Complex network measures of brain connectivity: uses and interpretations. NeuroImage. 2010;52:1059-1069.
Paldino MJ, Zhang W, Chu ZD, Golriz F. Metrics of brain network architecture capture the impact of disease in children with epilepsy. Neuroimage Clin. 2017;13:201-208.
Baniqued PL, Gallen CL, Kranz MB, Kramer AF, D'Esposito M. Brain network modularity predicts cognitive training-related gains in young adults. Neuropsychologia. 2019;131:205-215.
Garcia-Ramos C, Dabbs K, Lin JJ, et al. Progressive dissociation of cortical and subcortical network development in children with new-onset juvenile myoclonic epilepsy. Epilepsia. 2018;59:2086-2095.
van Veenendaal TM, IJff DM, Aldenkamp AP, et al. Chronic antiepileptic drug use and functional network efficiency: a functional magnetic resonance imaging study. World J Radiol. 2017;9:287-294.
Jo HJ, Kenney-Jung DL, Balzekas I, et al. Relationship between seizure frequency and functional abnormalities in limbic network of medial temporal lobe epilepsy. Front Neurol. 2019;10:488.
Guo C, Ferreira D, Fink K, Westman E, Granberg T. Repeatability and reproducibility of FreeSurfer, FSL-SIENAX and SPM brain volumetric measurements and the effect of lesion filling in multiple sclerosis. Eur Radiol. 2019;29:1355-1364.
Iglesias JE, Insausti R, Lerma-Usabiaga G, et al. A probabilistic atlas of the human thalamic nuclei combining ex vivo MRI and histology. NeuroImage. 2018;183:314-326.
Seeley WW, Crawford RK, Zhou J, et al. Neurodegenerative diseases target large-scale human brain networks. Neuron. 2009;62:42-52.
Alexander-Bloch A, Giedd JN, Bullmore E. Imaging structural covariance between human brain regions. Nat Rev Neurosci. 2013;14:322-336.
Honey CJ, Sporns O, Cammoun L, et al. Predicting human resting-state functional connectivity from structural connectivity. Proc Natl Acad Sci USA. 2009;106:2035-2040.
Supekar K, Uddin LQ, Prater K, et al. Development of functional and structural connectivity within the default mode network in young children. NeuroImage. 2010;52:290-301.