Delayed brain development of Rolandic epilepsy profiled by deep learning-based neuroanatomic imaging.
Biomarkers
Deep learning
Magnetic resonance imaging
Neurodevelopmental disorders
Rolandic epilepsy
Journal
European radiology
ISSN: 1432-1084
Titre abrégé: Eur Radiol
Pays: Germany
ID NLM: 9114774
Informations de publication
Date de publication:
Dec 2021
Dec 2021
Historique:
received:
21
12
2020
accepted:
05
05
2021
revised:
30
03
2021
pubmed:
22
5
2021
medline:
17
11
2021
entrez:
21
5
2021
Statut:
ppublish
Résumé
Although Rolandic epilepsy (RE) has been regarded as a brain developmental disorder, neuroimaging studies have not yet ascertained whether RE has brain developmental delay. This study employed deep learning-based neuroanatomic biomarker to measure the changed feature of "brain age" in RE. The study constructed a 3D-CNN brain age prediction model through 1155 cases of typically developing children's morphometric brain MRI from open-source datasets and further applied to a local dataset of 167 RE patients and 107 typically developing children. The brain-predicted age difference was measured to quantitatively estimate brain age changes in RE and further investigated the relevancies with cognitive and clinical variables. The brain age estimation network model presented a good performance for brain age prediction in typically developing children. The children with RE showed a 0.45-year delay of brain age by contrast with typically developing children. Delayed brain age was associated with neuroanatomic changes in the Rolandic regions and also associated with cognitive dysfunction of attention. This study provided neuroimaging evidence to support the notion that RE has delayed brain development. • The children with Rolandic epilepsy showed imaging phenotypes of delayed brain development with increased GM volume and decreased WM volume in the Rolandic regions. • The children with Rolandic epilepsy had a 0.45-year delay of brain-predicted age by comparing with typically developing children, using 3D-CNN-based brain age prediction model. • The delayed brain age was associated with morphometric changes in the Rolandic regions and attentional deficit in Rolandic epilepsy.
Identifiants
pubmed: 34018056
doi: 10.1007/s00330-021-08048-9
pii: 10.1007/s00330-021-08048-9
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
9628-9637Subventions
Organisme : National Natural Scientific Foundation of China
ID : 81701680
Organisme : National Natural Scientific Foundation of China
ID : 81871345
Organisme : National Natural Scientific Foundation of China
ID : 81790653
Organisme : National Natural Scientific Foundation of China
ID : 81790650
Organisme : National Key Research& Development Program of Ministry of Science& Technology of PR. China
ID : 2018YFA0701703
Organisme : grants of the key talent project in Jiangsu province
ID : ZDRCA2016093
Organisme : Natural scientific foundation-social development
ID : BE2016751
Informations de copyright
© 2021. European Society of Radiology.
Références
Beaussart M (1972) Benign epilepsy of children with Rolandic (centro-temporal) paroxysmal foci. A clinical entity. Study of 221 cases. Epilepsia 13:795–811
doi: 10.1111/j.1528-1157.1972.tb05164.x
Lima EM, Rzezak P, Dos Santos B et al (2018) The relevance of attention deficit hyperactivity disorder in self-limited childhood epilepsy with centrotemporal spikes. Epilepsy Behav 82:164–169
doi: 10.1016/j.yebeh.2018.03.017
Bektaş G, Tekin U, Yıldız EP, Aydınlı N, Çalışkan M, Özmen M (2019) Autism spectrum disorder and attention-deficit/hyperactivity disorder-related symptoms in benign childhood epilepsy with centrotemporal spikes: a prospective case-control study. Epilepsy Behav 95:61–64
doi: 10.1016/j.yebeh.2019.03.044
Kim EH, Yum MS, Kim HW, Ko TS (2014) Attention-deficit/hyperactivity disorder and attention impairment in children with benign childhood epilepsy with centrotemporal spikes. Epilepsy Behav 37:54–58
doi: 10.1016/j.yebeh.2014.05.030
Panayiotopoulos CP, Michael M, Sanders S, Valeta T, Koutroumanidis M (2008) Benign childhood focal epilepsies: assessment of established and newly recognized syndromes. Brain 131:2264–2286
doi: 10.1093/brain/awn162
Paolicchi JM (2013) The timing of pediatric epilepsy syndromes: what are the developmental triggers? Ann N Y Acad Sci 1304:45–51
doi: 10.1111/nyas.12307
Baumer FM, Pfeifer K, Fogarty A et al (2020) Cortical excitability, synaptic plasticity, and cognition in benign epilepsy with centrotemporal spikes: a pilot TMS-EMG-EEG study. J Clin Neurophysiol 37:170–180
doi: 10.1097/WNP.0000000000000662
Wilent WB, Contreras D (2005) Dynamics of excitation and inhibition underlying stimulus selectivity in rat somatosensory cortex. Nat Neurosci 8:1364–1370
doi: 10.1038/nn1545
Lenroot RK, Giedd JN (2006) Brain development in children and adolescents: insights from anatomical magnetic resonance imaging. Neurosci Biobehav Rev 30:718–729
doi: 10.1016/j.neubiorev.2006.06.001
Qiu A, Mori S, Miller MI (2015) Diffusion tensor imaging for understanding brain development in early life. Annu Rev Psychol 66:853–876
doi: 10.1146/annurev-psych-010814-015340
Gogtay N, Giedd JN, Lusk L et al (2004) Dynamic mapping of human cortical development during childhood through early adulthood. Proc Natl Acad Sci U S A 101:8174–8179
doi: 10.1073/pnas.0402680101
Pardoe HR, Berg AT, Archer JS, Fulbright RK, Jackson GD (2013) A neurodevelopmental basis for BECTS: evidence from structural MRI. Epilepsy Res 105:133–139
doi: 10.1016/j.eplepsyres.2012.11.008
Kim EH, Yum MS, Shim WH, Yoon HK, Lee YJ, Ko TS (2015) Structural abnormalities in benign childhood epilepsy with centrotemporal spikes (BCECTS). Seizure 27:40–46
doi: 10.1016/j.seizure.2015.02.027
Luo C, Zhang Y, Cao W et al (2015) Altered structural and functional feature of striato-cortical circuit in benign epilepsy with centrotemporal spikes. Int J Neural Syst 25:1550027
doi: 10.1142/S0129065715500276
Ciumas C, Saignavongs M, Ilski F et al (2014) White matter development in children with benign childhood epilepsy with centro-temporal spikes. Brain 137:1095–1106
doi: 10.1093/brain/awu039
Xiao F, Chen Q, Yu X et al (2014) Hemispheric lateralization of microstructural white matter abnormalities in children with active benign childhood epilepsy with centrotemporal spikes (BECTS): a preliminary DTI study. J Neurol Sci 336:171–179
doi: 10.1016/j.jns.2013.10.033
Garcia-Ramos C, Jackson DC, Lin JJ et al (2015) Cognition and brain development in children with benign epilepsy with centrotemporal spikes. Epilepsia 56:1615–1622
doi: 10.1111/epi.13125
Jonsson BA, Bjornsdottir G, Thorgeirsson TE et al (2019) Brain age prediction using deep learning uncovers associated sequence variants. Nat Commun 10:5409
doi: 10.1038/s41467-019-13163-9
Cole JH, Poudel RPK, Tsagkrasoulis D et al (2017) Predicting brain age with deep learning from raw imaging data results in a reliable and heritable biomarker. Neuroimage 163:115–124
Cole JH, Franke K (2017) Predicting age using neuroimaging: innovative brain ageing biomarkers. Trends Neurosci 40:681–690
doi: 10.1016/j.tins.2017.10.001
Kaufmann T, van der Meer D, Doan NT et al (2019) Common brain disorders are associated with heritable patterns of apparent aging of the brain. Nat Neurosci 22:1617–1623
doi: 10.1038/s41593-019-0471-7
Beheshti I, Nugent S, Potvin O, Duchesne S (2019) Bias-adjustment in neuroimaging-based brain age frameworks: a robust scheme. Neuroimage Clin 24:102063
doi: 10.1016/j.nicl.2019.102063
Schnack HG, van Haren NE, Nieuwenhuis M, Hulshoff Pol HE, Cahn W, Kahn RS (2016) Accelerated brain aging in schizophrenia: a longitudinal pattern recognition study. Am J Psychiatry 173:607–616
doi: 10.1176/appi.ajp.2015.15070922
Franke K, Gaser C, Manor B, Novak V (2013) Advanced brain AGE in older adults with type 2 diabetes mellitus. Front Aging Neurosci 5:90
doi: 10.3389/fnagi.2013.00090
Pardoe HR, Cole JH, Blackmon K, Thesen T, Kuzniecky R, Human Epilepsy Project Investigators (2017) Structural brain changes in medically refractory focal epilepsy resemble premature brain aging. Epilepsy Res 133:28–32
Sone D, Beheshti I, Maikusa N et al (2019) Neuroimaging-based brain-age prediction in diverse forms of epilepsy: a signature of psychosis and beyond. Mol Psychiatry. https://doi.org/10.1038/s41380-019-0446-9
Qu T, Yue Y, Zhang Q et al (2020) BAENET: a brain age estimation network with 3D skipping and outlier constraint loss 17th IEEE International Symposium on Biomedical Imaging, ISBI, Iowa City, IA, USA, April 3–7, pp 399–403
Berg AT, Berkovic SF, Brodie MJ et al (2010) Revised terminology and concepts for organization of seizures and epilepsies: report of the ILAE Commission on Classification and Terminology, 2005-2009. Epilepsia 51:676–685
doi: 10.1111/j.1528-1167.2010.02522.x
Fang Y, Han D, Luo H (2019) A virtual reality application for assessment for attention deficit hyperactivity disorder in school-aged children. Neuropsychiatr Dis Treat 15:1517–1523
doi: 10.2147/NDT.S206742
Alexander LM, Escalera J, Ai L et al (2017) An open resource for transdiagnostic research in pediatric mental health and learning disorders. Sci Data 4:170181
doi: 10.1038/sdata.2017.181
Di Martino A, Yan CG, Li Q et al (2014) The autism brain imaging data exchange: towards a large-scale evaluation of the intrinsic brain architecture in autism. Mol Psychiatry 19:659–667
doi: 10.1038/mp.2013.78
Erus G, Battapady H, Satterthwaite TD et al (2015) Imaging patterns of brain development and their relationship to cognition. Cereb Cortex 25:1676–1684
doi: 10.1093/cercor/bht425
Brown TT, Kuperman JM, Chung Y et al (2012) Neuroanatomical assessment of biological maturity. Curr Biol 22:1693–1698
doi: 10.1016/j.cub.2012.07.002
Whelan CD, Altmann A, Botia JA et al (2018) Structural brain abnormalities in the common epilepsies assessed in a worldwide ENIGMA study. Brain 141:391–408
doi: 10.1093/brain/awx341
Weng Y, Lariviere S, Caciagli L et al (2020) Macroscale and microcircuit dissociation of focal and generalized human epilepsies. Commun Biol 3:244
doi: 10.1038/s42003-020-0958-5
Aronica E, Muhlebner A (2017) Neuropathology of epilepsy. Handb Clin Neurol 145:193–216
doi: 10.1016/B978-0-12-802395-2.00015-8
Park JT, Shahid AM, Jammoul A (2015) Common pediatric epilepsy syndromes. Pediatr Ann 44:e30–e35
pubmed: 25658216
Sanchez-Carpintero R, Neville BG (2003) Attentional ability in children with epilepsy. Epilepsia 44:1340–1349
doi: 10.1046/j.1528-1157.2003.16403.x
Castellanos FX, Sonuga-Barke EJ, Milham MP, Tannock R (2006) Characterizing cognition in ADHD: beyond executive dysfunction. Trends Cogn Sci 10:117–123
doi: 10.1016/j.tics.2006.01.011
Lai MC, Lombardo MV, Baron-Cohen S (2014) Autism. Lancet 383:896–910
doi: 10.1016/S0140-6736(13)61539-1
Baglietto MG, Battaglia FM, Nobili L et al (2001) Neuropsychological disorders related to interictal epileptic discharges during sleep in benign epilepsy of childhood with centrotemporal or Rolandic spikes. Dev Med Child Neurol 43:407–412
doi: 10.1017/S0012162201000755
Blakemore SJ, Choudhury S (2006) Development of the adolescent brain: implications for executive function and social cognition. J Child Psychol Psychiatry 47:296–312
doi: 10.1111/j.1469-7610.2006.01611.x
Synnes A, Hicks M (2018) Neurodevelopmental outcomes of preterm children at school age and beyond. Clin Perinatol 45:393–408
doi: 10.1016/j.clp.2018.05.002