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Published in: BMC Pediatrics 1/2022

01-12-2022 | Central Nervous System Trauma | Research

Changes in a sensorimotor network, occipital network, and psychomotor speed within three months after focal surgical injury in pediatric patients with intracranial space-occupying lesions

Authors: Xue-Yi Guan, Wen-Jian Zheng, Kai-Yu Fan, Xu Han, Xiang Li, Zi-Han Yan, Zheng Lu, Jian Gong

Published in: BMC Pediatrics | Issue 1/2022

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Abstract

Background

Studies on cognition and brain networks after various forms of brain injury mainly involve traumatic brain injury, neurological disease, tumours, and mental disease. There are few related studies on surgical injury and even fewer pediatric studies. This study aimed to preliminarily explore the cognitive and brain network changes in children with focal, unilateral, well-bounded intracranial space-occupying lesions (ISOLs) in the short term period after surgery.

Methods

We enrolled 15 patients (6–14 years old) with ISOLs admitted to the Department of Pediatric Neurosurgery of the Beijing Tiantan Hospital between July 2020 and August 2021. Cognitive assessment and resting-state functional magnetic resonance imaging (rs-fMRI) were performed. Regional homogeneity (Reho), seed-based analysis (SBA) and graph theory analysis (GTA) were performed. Paired T-test was used for statistical analysis of cognitive assessment and rs-fMRI. Gaussian random-field theory correction (voxel p-value < 0.001, cluster p-value < 0.05) was used for Reho and SBA. False discovery rate correction (corrected p value < 0.05) for GTA.

Results

Our results showed that psychomotor speed decreased within three months after surgery. Further, rs-fMRI data analysis suggested that sensorimotor and occipital network activation decreased with low information transmission efficiency.

Conclusion

We prudently concluded that the changes in cognitive function and brain network within three months after surgery may be similar to ageing and that the brain is vulnerable during this period.
Appendix
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Literature
1.
go back to reference Subramanian S, Ahmad T: Childhood Brain Tumors. In: StatPearls. edn. Treasure Island (FL): StatPearls Publishing. Copyright © 2021, StatPearls Publishing LLC.; 2021. Subramanian S, Ahmad T: Childhood Brain Tumors. In: StatPearls. edn. Treasure Island (FL): StatPearls Publishing. Copyright © 2021, StatPearls Publishing LLC.; 2021.
2.
go back to reference Ostrom QT, Gittleman H, Fulop J, Liu M, Blanda R, Kromer C, Wolinsky Y, Kruchko C, Barnholtz-Sloan JS: CBTRUS Statistical Report: Primary Brain and Central Nervous System Tumors Diagnosed in the United States in 2008–2012. Neuro-oncology 2015, 17 Suppl 4(Suppl 4):iv1-iv62. Ostrom QT, Gittleman H, Fulop J, Liu M, Blanda R, Kromer C, Wolinsky Y, Kruchko C, Barnholtz-Sloan JS: CBTRUS Statistical Report: Primary Brain and Central Nervous System Tumors Diagnosed in the United States in 2008–2012. Neuro-oncology 2015, 17 Suppl 4(Suppl 4):iv1-iv62.
3.
go back to reference Bandopadhayay P, Bergthold G, London WB, Goumnerova LC, Morales La Madrid A, Marcus KJ, Guo D, Ullrich NJ, Robison NJ, Chi SN et al: Long-term outcome of 4,040 children diagnosed with pediatric low-grade gliomas: an analysis of the Surveillance Epidemiology and End Results (SEER) database. Pediatric blood & cancer 2014, 61(7):1173–1179. Bandopadhayay P, Bergthold G, London WB, Goumnerova LC, Morales La Madrid A, Marcus KJ, Guo D, Ullrich NJ, Robison NJ, Chi SN et al: Long-term outcome of 4,040 children diagnosed with pediatric low-grade gliomas: an analysis of the Surveillance Epidemiology and End Results (SEER) database. Pediatric blood & cancer 2014, 61(7):1173–1179.
4.
go back to reference Ostrom QT, Gittleman H, Truitt G, Boscia A, Kruchko C, Barnholtz-Sloan JS: CBTRUS Statistical Report: Primary Brain and Other Central Nervous System Tumors Diagnosed in the United States in 2011–2015. Neuro-oncology 2018, 20(suppl_4):iv1-iv86. Ostrom QT, Gittleman H, Truitt G, Boscia A, Kruchko C, Barnholtz-Sloan JS: CBTRUS Statistical Report: Primary Brain and Other Central Nervous System Tumors Diagnosed in the United States in 2011–2015. Neuro-oncology 2018, 20(suppl_4):iv1-iv86.
5.
go back to reference Hendrix P, Hans E, Griessenauer CJ, Simgen A, Oertel J, Karbach J. Neurocognitive Function Surrounding the Resection of Frontal WHO Grade I Meningiomas: A Prospective Matched-Control Study. World Neurosurgery. 2017;98:203–10.CrossRef Hendrix P, Hans E, Griessenauer CJ, Simgen A, Oertel J, Karbach J. Neurocognitive Function Surrounding the Resection of Frontal WHO Grade I Meningiomas: A Prospective Matched-Control Study. World Neurosurgery. 2017;98:203–10.CrossRef
6.
go back to reference Stam CJ. Modern network science of neurological disorders. Nat Rev Neurosci. 2014;15(10):683–95.CrossRef Stam CJ. Modern network science of neurological disorders. Nat Rev Neurosci. 2014;15(10):683–95.CrossRef
7.
go back to reference Bassett DS, Nelson BG, Mueller BA, Camchong J, Lim KO. Altered resting state complexity in schizophrenia. Neuroimage. 2012;59(3):2196–207.CrossRef Bassett DS, Nelson BG, Mueller BA, Camchong J, Lim KO. Altered resting state complexity in schizophrenia. Neuroimage. 2012;59(3):2196–207.CrossRef
8.
go back to reference Chen G, Ward BD, Xie C, Li W, Wu Z, Jones JL, Franczak M, Antuono P, Li SJ. Classification of Alzheimer disease, mild cognitive impairment, and normal cognitive status with large-scale network analysis based on resting-state functional MR imaging. Radiology. 2011;259(1):213–21.CrossRef Chen G, Ward BD, Xie C, Li W, Wu Z, Jones JL, Franczak M, Antuono P, Li SJ. Classification of Alzheimer disease, mild cognitive impairment, and normal cognitive status with large-scale network analysis based on resting-state functional MR imaging. Radiology. 2011;259(1):213–21.CrossRef
9.
go back to reference Kocher M, Jockwitz C, Caspers S, Schreiber J, Farrher E, Stoffels G, Filss C, Lohmann P, Tscherpel C, Ruge MI et al: Role of the default mode resting-state network for cognitive functioning in malignant glioma patients following multimodal treatment. Neuroimage-Clinical 2020, 27. Kocher M, Jockwitz C, Caspers S, Schreiber J, Farrher E, Stoffels G, Filss C, Lohmann P, Tscherpel C, Ruge MI et al: Role of the default mode resting-state network for cognitive functioning in malignant glioma patients following multimodal treatment. Neuroimage-Clinical 2020, 27.
10.
go back to reference Lv K, Fan YH, Xu L, Xu MS. Brain changes detected by functional magnetic resonance imaging and spectroscopy in patients with Crohn’s disease. World J Gastroenterol. 2017;23(20):3607–14.CrossRef Lv K, Fan YH, Xu L, Xu MS. Brain changes detected by functional magnetic resonance imaging and spectroscopy in patients with Crohn’s disease. World J Gastroenterol. 2017;23(20):3607–14.CrossRef
11.
go back to reference Xiong H, Guo RJ, Shi HW. Altered Default Mode Network and Salience Network Functional Connectivity in Patients with Generalized Anxiety Disorders: An ICA-Based Resting-State fMRI Study. Evid Based Complement Alternat Med. 2020;2020:4048916.PubMedPubMedCentral Xiong H, Guo RJ, Shi HW. Altered Default Mode Network and Salience Network Functional Connectivity in Patients with Generalized Anxiety Disorders: An ICA-Based Resting-State fMRI Study. Evid Based Complement Alternat Med. 2020;2020:4048916.PubMedPubMedCentral
12.
go back to reference Tuerk C, Degeilh F, Catroppa C, Dooley JJ, Kean M, Anderson V, Beauchamp MH. Altered resting-state functional connectivity within the developing social brain after pediatric traumatic brain injury. Hum Brain Mapp. 2020;41(2):561–76.CrossRef Tuerk C, Degeilh F, Catroppa C, Dooley JJ, Kean M, Anderson V, Beauchamp MH. Altered resting-state functional connectivity within the developing social brain after pediatric traumatic brain injury. Hum Brain Mapp. 2020;41(2):561–76.CrossRef
13.
go back to reference Falcon MI, Riley JD, Jirsa V, McIntosh AR, Elinor Chen E, Solodkin A: Functional Mechanisms of Recovery after Chronic Stroke: Modeling with the Virtual Brain. eneuro 2016, 3(2). Falcon MI, Riley JD, Jirsa V, McIntosh AR, Elinor Chen E, Solodkin A: Functional Mechanisms of Recovery after Chronic Stroke: Modeling with the Virtual Brain. eneuro 2016, 3(2).
14.
go back to reference Chao-Gan Y, Yu-Feng Z. DPARSF: A MATLAB Toolbox for “Pipeline” Data Analysis of Resting-State fMRI. Front Syst Neurosci. 2010;4:13.PubMedPubMedCentral Chao-Gan Y, Yu-Feng Z. DPARSF: A MATLAB Toolbox for “Pipeline” Data Analysis of Resting-State fMRI. Front Syst Neurosci. 2010;4:13.PubMedPubMedCentral
15.
go back to reference Yan CG, Wang XD, Zuo XN, Zang YF. DPABI: Data Processing & Analysis for (Resting-State) Brain Imaging. Neuroinformatics. 2016;14(3):339–51.CrossRef Yan CG, Wang XD, Zuo XN, Zang YF. DPABI: Data Processing & Analysis for (Resting-State) Brain Imaging. Neuroinformatics. 2016;14(3):339–51.CrossRef
16.
go back to reference Andersen SM, Rapcsak SZ, Beeson PM. Cost function masking during normalization of brains with focal lesions: still a necessity? Neuroimage. 2010;53(1):78–84.CrossRef Andersen SM, Rapcsak SZ, Beeson PM. Cost function masking during normalization of brains with focal lesions: still a necessity? Neuroimage. 2010;53(1):78–84.CrossRef
17.
go back to reference Rorden C, Karnath HO, Bonilha L. Improving lesion-symptom mapping. J Cogn Neurosci. 2007;19(7):1081–8.CrossRef Rorden C, Karnath HO, Bonilha L. Improving lesion-symptom mapping. J Cogn Neurosci. 2007;19(7):1081–8.CrossRef
18.
go back to reference Ashburner J. A fast diffeomorphic image registration algorithm. Neuroimage. 2007;38(1):95–113.CrossRef Ashburner J. A fast diffeomorphic image registration algorithm. Neuroimage. 2007;38(1):95–113.CrossRef
19.
go back to reference Friston KJ, Williams S, Howard R, Frackowiak RS, Turner R. Movement-related effects in fMRI time-series. Magn Reson Med. 1996;35(3):346–55.CrossRef Friston KJ, Williams S, Howard R, Frackowiak RS, Turner R. Movement-related effects in fMRI time-series. Magn Reson Med. 1996;35(3):346–55.CrossRef
20.
go back to reference Saad ZS, Gotts SJ, Murphy K, Chen G, Jo HJ, Martin A, Cox RW. Trouble at Rest: How Correlation Patterns and Group Differences Become Distorted After Global Signal Regression. Brain connectivity. 2012;2(1):25–32.CrossRef Saad ZS, Gotts SJ, Murphy K, Chen G, Jo HJ, Martin A, Cox RW. Trouble at Rest: How Correlation Patterns and Group Differences Become Distorted After Global Signal Regression. Brain connectivity. 2012;2(1):25–32.CrossRef
21.
go back to reference He H, Liu TT. A geometric view of global signal confounds in resting-state functional MRI. Neuroimage. 2012;59(3):2339–48.CrossRef He H, Liu TT. A geometric view of global signal confounds in resting-state functional MRI. Neuroimage. 2012;59(3):2339–48.CrossRef
22.
go back to reference Lv H, Wang Z, Tong E, Williams LM, Zaharchuk G, Zeineh M, Goldstein-Piekarski AN, Ball TM, Liao C, Wintermark M. Resting-State Functional MRI: Everything That Nonexperts Have Always Wanted to Know. AJNR Am J Neuroradiol. 2018;39(8):1390–9.PubMedPubMedCentral Lv H, Wang Z, Tong E, Williams LM, Zaharchuk G, Zeineh M, Goldstein-Piekarski AN, Ball TM, Liao C, Wintermark M. Resting-State Functional MRI: Everything That Nonexperts Have Always Wanted to Know. AJNR Am J Neuroradiol. 2018;39(8):1390–9.PubMedPubMedCentral
23.
go back to reference Dosenbach NU, Nardos B, Cohen AL, Fair DA, Power JD, Church JA, Nelson SM, Wig GS, Vogel AC, Lessov-Schlaggar CN, et al. Prediction of individual brain maturity using fMRI. Science. 2010;329(5997):1358–61.CrossRef Dosenbach NU, Nardos B, Cohen AL, Fair DA, Power JD, Church JA, Nelson SM, Wig GS, Vogel AC, Lessov-Schlaggar CN, et al. Prediction of individual brain maturity using fMRI. Science. 2010;329(5997):1358–61.CrossRef
24.
go back to reference Gualtieri C, Johnson L. Reliability and validity of a computerized neurocognitive test battery, CNS Vital Signs. Arch Clin Neuropsychol. 2006;21(7):623–43.CrossRef Gualtieri C, Johnson L. Reliability and validity of a computerized neurocognitive test battery, CNS Vital Signs. Arch Clin Neuropsychol. 2006;21(7):623–43.CrossRef
25.
go back to reference Ou X, Andres A, Pivik RT, Cleves MA, Snow JH, Ding Z, Badger TM. Voxel-Based Morphometry and fMRI Revealed Differences in Brain Gray Matter in Breastfed and Milk Formula-Fed Children. AJNR Am J Neuroradiol. 2016;37(4):713–9.CrossRef Ou X, Andres A, Pivik RT, Cleves MA, Snow JH, Ding Z, Badger TM. Voxel-Based Morphometry and fMRI Revealed Differences in Brain Gray Matter in Breastfed and Milk Formula-Fed Children. AJNR Am J Neuroradiol. 2016;37(4):713–9.CrossRef
26.
go back to reference Xia M, Wang J, He Y. BrainNet Viewer: a network visualization tool for human brain connectomics. PLoS ONE. 2013;8(7): e68910.CrossRef Xia M, Wang J, He Y. BrainNet Viewer: a network visualization tool for human brain connectomics. PLoS ONE. 2013;8(7): e68910.CrossRef
27.
go back to reference Li H, Zhao M, Wang S, Cao Y, Zhao J. Prediction of pediatric meningioma recurrence by preoperative MRI assessment. Neurosurg Rev. 2016;39(4):663–9.CrossRef Li H, Zhao M, Wang S, Cao Y, Zhao J. Prediction of pediatric meningioma recurrence by preoperative MRI assessment. Neurosurg Rev. 2016;39(4):663–9.CrossRef
28.
go back to reference Osawa T, Tosaka M, Nagaishi M, Yoshimoto Y. Factors affecting peritumoral brain edema in meningioma: special histological subtypes with prominently extensive edema. J Neurooncol. 2013;111(1):49–57.CrossRef Osawa T, Tosaka M, Nagaishi M, Yoshimoto Y. Factors affecting peritumoral brain edema in meningioma: special histological subtypes with prominently extensive edema. J Neurooncol. 2013;111(1):49–57.CrossRef
29.
go back to reference Lee MH, Smyser CD, Shimony JS. Resting-State fMRI: A Review of Methods and Clinical Applications. Am J Neuroradiol. 2013;34(10):1866–72.CrossRef Lee MH, Smyser CD, Shimony JS. Resting-State fMRI: A Review of Methods and Clinical Applications. Am J Neuroradiol. 2013;34(10):1866–72.CrossRef
30.
go back to reference Smitha KA, Akhil Raja K, Arun KM, Rajesh PG, Thomas B, Kapilamoorthy TR, Kesavadas C. Resting state fMRI: A review on methods in resting state connectivity analysis and resting state networks. Neuroradiol J. 2017;30(4):305–17.CrossRef Smitha KA, Akhil Raja K, Arun KM, Rajesh PG, Thomas B, Kapilamoorthy TR, Kesavadas C. Resting state fMRI: A review on methods in resting state connectivity analysis and resting state networks. Neuroradiol J. 2017;30(4):305–17.CrossRef
31.
go back to reference Madhavan R, Joel SE, Mullick R, Cogsil T, Niogi SN, Tsiouris AJ, Mukherjee P, Masdeu JC, Marinelli L, Shetty T. Longitudinal Resting State Functional Connectivity Predicts Clinical Outcome in Mild Traumatic Brain Injury. J Neurotrauma. 2019;36(5):650–60.CrossRef Madhavan R, Joel SE, Mullick R, Cogsil T, Niogi SN, Tsiouris AJ, Mukherjee P, Masdeu JC, Marinelli L, Shetty T. Longitudinal Resting State Functional Connectivity Predicts Clinical Outcome in Mild Traumatic Brain Injury. J Neurotrauma. 2019;36(5):650–60.CrossRef
32.
go back to reference Piazzini A, Turner K, Chifari R, Morabito A, Canger R, Canevini MP. Attention and psychomotor speed decline in patients with temporal lobe epilepsy: a longitudinal study. Epilepsy Res. 2006;72(2–3):89–96.CrossRef Piazzini A, Turner K, Chifari R, Morabito A, Canger R, Canevini MP. Attention and psychomotor speed decline in patients with temporal lobe epilepsy: a longitudinal study. Epilepsy Res. 2006;72(2–3):89–96.CrossRef
33.
go back to reference Era P, Sainio P, Koskinen S, Ohlgren J, Harkanen T, Aromaa A. Psychomotor speed in a random sample of 7,979 subjects aged 30 years and over. Aging Clin Exp Res. 2011;23(2):135–44.CrossRef Era P, Sainio P, Koskinen S, Ohlgren J, Harkanen T, Aromaa A. Psychomotor speed in a random sample of 7,979 subjects aged 30 years and over. Aging Clin Exp Res. 2011;23(2):135–44.CrossRef
34.
go back to reference Amieva H, Meillon C, Proust-Lima C, Dartigues JF. Is Low Psychomotor Speed a Marker of Brain Vulnerability in Late Life? Digit Symbol Substitution Test in the Prediction of Alzheimer, Parkinson, Stroke, Disability, and Depression. Dement Geriatr Cogn Disord. 2019;47(4–6):297–305.CrossRef Amieva H, Meillon C, Proust-Lima C, Dartigues JF. Is Low Psychomotor Speed a Marker of Brain Vulnerability in Late Life? Digit Symbol Substitution Test in the Prediction of Alzheimer, Parkinson, Stroke, Disability, and Depression. Dement Geriatr Cogn Disord. 2019;47(4–6):297–305.CrossRef
35.
go back to reference Simchick G, Scheulin KM, Sun WW, Sneed SE, Fagan MM, Cheek SR, West FD, Zhao Q. Detecting functional connectivity disruptions in a translational pediatric traumatic brain injury porcine model using resting-state and task-based fMRI. Sci Rep. 2021;11(1):19.CrossRef Simchick G, Scheulin KM, Sun WW, Sneed SE, Fagan MM, Cheek SR, West FD, Zhao Q. Detecting functional connectivity disruptions in a translational pediatric traumatic brain injury porcine model using resting-state and task-based fMRI. Sci Rep. 2021;11(1):19.CrossRef
36.
go back to reference Chan MY, Park DC, Savalia NK, Petersen SE, Wig GS. Decreased segregation of brain systems across the healthy adult lifespan. Proc Natl Acad Sci USA. 2014;111(46):E4997-5006.CrossRef Chan MY, Park DC, Savalia NK, Petersen SE, Wig GS. Decreased segregation of brain systems across the healthy adult lifespan. Proc Natl Acad Sci USA. 2014;111(46):E4997-5006.CrossRef
37.
go back to reference Wei HL, Chen J, Chen YC, Yu YS, Guo X, Zhou GP, Zhou QQ, He ZZ, Yang L, Yin X, et al. Impaired effective functional connectivity of the sensorimotor network in interictal episodic migraineurs without aura. J Headache Pain. 2020;21(1):111.CrossRef Wei HL, Chen J, Chen YC, Yu YS, Guo X, Zhou GP, Zhou QQ, He ZZ, Yang L, Yin X, et al. Impaired effective functional connectivity of the sensorimotor network in interictal episodic migraineurs without aura. J Headache Pain. 2020;21(1):111.CrossRef
38.
go back to reference Barulli D, Stern Y. Efficiency, capacity, compensation, maintenance, plasticity: emerging concepts in cognitive reserve. Trends Cogn Sci. 2013;17(10):502–9.CrossRef Barulli D, Stern Y. Efficiency, capacity, compensation, maintenance, plasticity: emerging concepts in cognitive reserve. Trends Cogn Sci. 2013;17(10):502–9.CrossRef
39.
go back to reference Stern Y. What is cognitive reserve? Theory and research application of the reserve concept. J Int Neuropsychol Soc. 2002;8(3):448–60.CrossRef Stern Y. What is cognitive reserve? Theory and research application of the reserve concept. J Int Neuropsychol Soc. 2002;8(3):448–60.CrossRef
Metadata
Title
Changes in a sensorimotor network, occipital network, and psychomotor speed within three months after focal surgical injury in pediatric patients with intracranial space-occupying lesions
Authors
Xue-Yi Guan
Wen-Jian Zheng
Kai-Yu Fan
Xu Han
Xiang Li
Zi-Han Yan
Zheng Lu
Jian Gong
Publication date
01-12-2022
Publisher
BioMed Central
Published in
BMC Pediatrics / Issue 1/2022
Electronic ISSN: 1471-2431
DOI
https://doi.org/10.1186/s12887-022-03348-5

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