Abstract：Objective To summarize the research progress of magnetic resonance imaging in relation to children's brain development and neurodevelopmental disorders (NDDs). Methods The recent literatures in the database of CNKI, Wanfang data, Pubmed, and Web of Science were searched by using the keywords of "儿童脑发育" "神经发育障碍" "磁共振成像" "brain development" "neurodevelopmental disorders" "children" and "MRI" from January 1999 to January 2021. A total of 7 974 literatures were searched. The literatures that were inconsistent to the subject, had no full text, were of low quality, had low level of evidence, and were repeated studies were excluded. Finally, 49 literatures were analyzed and summarized. Results Multimodal brain imaging techniques, such as morphological, anatomical, and functional MRI, combined with current machine learning analysis techniques, such as brain age prediction and imaging genetics, can be used to map normal and atypical childhood brain development from the perspective of structure, function, and network, thereby promoting the understanding of the pathophysiological mechanisms of NDDs. Conclusions Quantitative analysis of multimodal MRI technology was performed to observe the changes of structural and functional brain parameters of children with NDDs. Results contribute to the elucidation of the mechanism of the disease and provide imaging biomarkers for the early diagnosis, classification, and prognosis of NDDs.
余倩倩, 张其锐, 张志强. 儿童脑发育及神经发育障碍的多模态MRI研究进展[J]. 中华解剖与临床杂志, 2022, 27(1): 54-59.
Yu Qianqian, Zhang Qirui, Zhang Zhiqiang. Research progress of magnetic resonance imaging on brain development and neurodevelopmental disorders in children. Chinese Journal of Anatomy and Clinics, 2022, 27(1): 54-59.
Meisler MH, Hill SF, Yu W.Author correction: sodium channelopathies in neurodevelopmental disorders[J]. Nat Rev Neurosci, 2021,22(4):256.DOI:10.1038/s41583-021-00449-5.
[2]
Song JM, Kang M, Park DH, et al.Pathogenic GRM7 mutations associated with neurodevelopmental disorders impair axon outgrowth and presynaptic terminal development[J]. J Neurosci, 2021,41(11):2344-2359. DOI: 10.1523/JNEUROSCI.2108-20.2021.
[3]
Casey BJ, Tottenham N, Liston C, et al.Imaging the developing brain: what have we learned about cognitive development?[J]. Trends Cogn Sci, 2005,9(3):104-110. DOI: 10.1016/j.tics.2005.01.011.
[4]
Lenroot RK, Giedd JN.Brain development in children and adolescents: insights from anatomical magnetic resonance imaging[J]. Neurosci Biobehav Rev, 2006, 30(6):718-729. DOI: 10.1016/j.neubiorev.2006.06.001.
[5]
Bhatt RR, Gupta A, Mayer EA, et al.Chronic pain in children: structural and resting-state functional brain imaging within a developmental perspective[J]. Pediatr Res, 2020,88(6):840-849. DOI: 10.1038/s41390-019-0689-9.
[6]
Forrest MP, Parnell E, Penzes P.Dendritic structural plasticity and neuropsychiatric disease[J]. Nat Rev Neurosci, 2018, 19(4): 215-234. DOI: 10.1038/nrn.2018.16.
[7]
Teeuw J, Brouwer RM, Koenis M, et al.Genetic influences on the development of cerebral cortical thickness during childhood and adolescence in a dutch longitudinal twin sample: the brainscale study[J]. Cereb Cortex, 2019, 29(3):978-993. DOI: 10.1093/cercor/bhy005.
[8]
Khundrakpam BS, Reid A, Brauer J, et al.Developmental changes in organization of structural brain networks[J]. Cereb Cortex, 2013, 23(9): 2072-2085. DOI: 10.1093/cercor/bhs187.
[9]
Collin G, van den Heuvel MP. The ontogeny of the human connectome: development and dynamic changes of brain connectivity across the life span[J]. Neuroscientist, 2013,19(6): 616-628. DOI: 10.1177/1073858413503712.
[10]
Wedeen VJ, Wang RP, Schmahmann JD, et al.Diffusion spectrum magnetic resonance imaging (DSI) tractography of crossing fibers[J]. Neuroimage, 2008, 41(4): 1267-1277. DOI: 10.1016/j.neuroimage.2008.03.036.
[11]
Lebel C, Beaulieu C.Longitudinal development of human brain wiring continues from childhood into adulthood[J]. J Neurosci, 2011, 31(30): 10937-10947.DOI:10.1523/JNEUROSCI.5302-10.2011.
[12]
Sowell ER, Peterson BS, Thompson PM, et al.Mapping cortical change across the human life span[J]. Nat Neurosci, 2003, 6(3): 309-315. DOI: 10.1038/nn1008.
[13]
Zhao T, Xu Y, He Y.Graph theoretical modeling of baby brain networks[J]. Neuroimage, 2019, 185: 711-727. DOI: 10.1016/j.neuroimage.2018.06.038.
[14]
Gurunandan K, Arnaez-Telleria J, Carreiras M, et al.Converging evidence for differential specialization and plasticity of language systems[J]. J Neurosci, 2020, 40(50):9715-9724. DOI: 10.1523/JNEUROSCI.0851-20.2020.
[15]
Niu X, Zhang F, Kounios J, et al.Improved prediction of brain age using multimodal neuroimaging data[J]. Hum Brain Mapp, 2020, 41(6): 1626-1643. DOI: 10.1002/hbm.24899.
[16]
Cole JH, Poudel R, Tsagkrasoulis D, et al.Predicting brain age with deep learning from raw imaging data results in a reliable and heritable biomarker[J]. Neuroimage, 2017,163: 115-124. DOI: 10.1016/j.neuroimage.2017.07.059.
[17]
Kang HJ, Kawasawa YI, Cheng F, et al.Spatio-temporal transcriptome of the human brain[J]. Nature, 2011,478(7370): 483-489. DOI: 10.1038/nature10523.
[18]
Pletikos M, Sousa AMM, Sedmak G, et al.Temporal specification and bilaterality of human neocortical topographic gene expression[J]. Neuron, 2014,81(2):321-332. DOI: 10.1016/j.neuron.2013.11.018.
[19]
Kochunov P, Jahanshad N, Marcus D, et al.Heritability of fractional anisotropy in human white matter: a comparison of Human Connectome Project and ENIGMA-DTI data[J]. Neuroimage, 2015, 111: 300-311. DOI: 10.1016/j.neuroimage.2015.02.050.
[20]
Vuoksimaa E, Panizzon MS, Hagler DJ, et al.Heritability of white matter microstructure in late middle age: a twin study of tract-based fractional anisotropy and absolute diffusivity indices[J]. Hum Brain Mapp, 2017, 38(4):2026-2036. DOI: 10.1002/hbm.23502.
[21]
Gao W, Elton A, Zhu H, et al.Intersubject variability of and genetic effects on the brain's functional connectivity during infancy[J]. J Neurosci, 2014, 34(34): 11288-11296. DOI: 10.1523/JNEUROSCI.5072-13.2014.
[22]
Hazlett HC, Gu H, Munsell BC, et al.Early brain development in infants at high risk for autism spectrum disorder[J]. Nature, 2017, 542(7641): 348-351. DOI:10.1038/nature21369.
[23]
Xia K, Zhang J, Ahn M, et al.Genome-wide association analysis identifies common variants influencing infant brain volumes[J]. Transl Psychiatry, 2017, 7(8): e1188. DOI: 10.1038/tp.2017.159.
[24]
Krishnan ML, Van Steenwinckel J, Schang AL, et al.Integrative genomics of microglia implicates DLG4 (PSD95) in the white matter development of preterm infants[J]. Nat Commun, 2017, 8(1): 428. DOI: 10.1038/s41467-017-00422-w.
[25]
Xia K, Zhang J, Ahn M, et al.Genome-wide association analysis identifies common variants influencing infant brain volumes[J]. Transl Psychiatry, 2017, 7(8): e1188. DOI: 10.1038/tp.2017.159.
[26]
Castellanos FX, Lee PP, Sharp W, et al.Developmental trajectories of brain volume abnormalities in children and adolescents with attention-deficit/hyperactivity disorder[J]. JAMA, 2002, 288(14): 1740-1748. DOI:10.1001/jama.288. 14.1740.
[27]
Aoki Y, Cortese S, Castellanos FX.Research review: diffusion tensor imaging studies of attention-deficit/hyperactivity disorder: meta-analyses and reflections on head motion[J]. J Child Psychol Psychiatry, 2018, 59(3):193-202. DOI: 10.1111/jcpp.12778.
[28]
Wu Y, Gau S S, Lo Y, et al.White matter tract integrity of frontostriatal circuit in attention deficit hyperactivity disorder: association with attention performance and symptoms[J]. Human Brain Mapping, 2014, 35(1): 199-212. DOI: 10.1002/hbm.22169.
[29]
Hart H, Radua J, Nakao T, et al.Meta-analysis of functional magnetic resonance imaging studies of inhibition and attention in attention-deficit/hyperactivity disorder: exploring task-specific, stimulant medication, and age effects[J]. JAMA Psychiatry, 2013, 70(2): 185-198. DOI:10.1001/jamapsychiatry.2013.277.
[30]
Wang M, Hu Z, Liu L, et al.Disrupted functional brain connectivity networks in children with attention-deficit/hyperactivity disorder: evidence from resting-state functional near-infrared spectroscopy[J]. Neurophotonics, 2020, 7(1): 1. DOI: 10.1117/1.NPh.7.1.015012.
[31]
Shappell HM, Duffy KA, Rosch KS, et al.Children with attention-deficit/hyperactivity disorder spend more time in hyperconnected network states and less time in segregated network states as revealed by dynamic connectivity analysis[J]. Neuroimage, 2021, 229: 117753. DOI: 10.1016/j.neuroimage.2021.117753.
[32]
Traut N, Beggiato A, Bourgeron T, et al.Cerebellar volume in autism: literature meta-analysis and analysis of the autism brain imaging data exchange cohort[J]. Biol Psychiatry, 2018, 83(7): 579-588. DOI: 10.1016/j.biopsych.2017.09.029.
[33]
Yu Q, Peng Y, Kang H, et al.Differential white matter maturation from birth to 8 years of age[J]. Cereb Cortex, 2020, 30(4): 2673-2689. DOI: 10.1093/cercor/bhz268.
[34]
Redcay E, Dodell-Feder D, Mavros PL, et al.Atypical brain activation patterns during a face-to-face joint attention game in adults with autism spectrum disorder[J]. Hum Brain Mapp, 2013,34(10):2511-2523. DOI: 10.1002/hbm.22086.
[35]
Di Martino A, Yan CG, Li Q, et al.The autism brain imaging data exchange: towards a large-scale evaluation of the intrinsic brain architecture in autism[J]. Mol Psychiatry, 2014, 19(6): 659-667. DOI: 10.1038/mp.2013.78.
[36]
Corps J, Rekik I.Morphological brain age prediction using multi-view brain networks derived from cortical morphology in healthy and disordered participants[J]. Sci Rep, 2019, 9(1): 9676. DOI: 10.1038/s41598-019-46145-4.
[37]
Shakeri M, Datta AN, Malfait D, et al.Sub-cortical brain morphometry and its relationship with cognition in rolandic epilepsy[J]. Epilepsy Res, 2017, 138: 39-45. DOI:10.1016/j.eplepsyres.2017.09.007.
[38]
Garcia-Ramos C, Jackson DC, Lin J J, et al.Cognition and brain development in children with benign epilepsy with centrotemporal spikes[J]. Epilepsia, 2015, 56(10): 1615-1622. DOI: 10.1111/epi.13125.
[39]
Ciumas C, Saignavongs M, Ilski F, et al.White matter development in children with benign childhood epilepsy with centro-temporal spikes[J]. Brain, 2014, 137(Pt 4):1095-1106. DOI: 10.1093/brain/awu039.
[40]
Pardoe HR, Berg AT, Archer JS, et al.A neurodevelopmental basis for BECTS: evidence from structural MRI[J]. Epilepsy Res, 2013, 105(1-2): 133-139. DOI: 10.1016/j.eplepsyres. 2012.11.008.
[41]
Bear J J, Chapman K E, Tregellas J R.The epileptic network and cognition: what functional connectivity is teaching us about the childhood epilepsies[J]. Epilepsia, 2019, 60(8): 1491-1507. DOI: 10.1111/epi.16098.
[42]
Adebimpe A, Bourel-Ponchel E, Wallois F.Identifying neural drivers of benign childhood epilepsy with centrotemporal spikes[J]. Neuroimage Clin, 2018, 17:739-750. DOI: 10.1016/j.nicl.2017.11.024.
[43]
Kim EH, Shim WH, Lee JS, et al.Altered structural network in newly onset childhood absence epilepsy[J]. J Clin Neurol, 2020, 16(4): 573-580. DOI: 10.3988/jcn.2020.16.4.573.
[44]
Li Q, Cao W, Liao X, et al.Altered resting state functional network connectivity in children absence epilepsy[J]. J Neurol Sci, 2015, 354(1-2): 79-85. DOI: 10.1016/j.jns.2015.04.054.
[45]
Xue K, Luo C, Zhang D, et al.Diffusion tensor tractography reveals disrupted structural connectivity in childhood absence epilepsy[J]. Epilepsy Res, 2014, 108(1): 125-138. DOI: 10.1016/j.eplepsyres.2013.10.002.
[46]
Liao W, Wu GR, Xu Q, et al.DynamicBC: a MATLAB toolbox for dynamic brain connectome analysis[J]. Brain Connect, 2014, 4(10): 780-790. DOI: 10.1089/brain.2014.0253.
[47]
Kanner A M, Scharfman H, Jette N, et al.Epilepsy as a network disorder (1): what can we learn from other network disorders such as autistic spectrum disorder and mood disorders?[J]. Epilepsy Behav, 2017, 77: 106-113. DOI: 10.1016/j.yebeh.2017.09.014.
[48]
Reh RK, Dias BG, Nelson CA, et al.Critical period regulation across multiple timescales[J]. Proc Natl Acad Sci USA, 2020, 117(38): 23242-23251. DOI: 10.1073/pnas. 1820836117.
[49]
Chen LC, Chen MH, Hsu JW, et al.Association of parental depression with offspring attention deficit hyperactivity disorder and autism spectrum disorder: a nationwide birth cohort study[J]. J Affect Disord, 2020, 277: 109-114. DOI: 10.1016/j.jad.2020.07.059.
2022, Vol. 27 
