{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,29]],"date-time":"2026-09-29T16:37:15Z","timestamp":1790699835619,"version":"4.1.0"},"reference-count":67,"publisher":"Wiley","issue":"9","license":[{"start":{"date-parts":[[2025,9,21]],"date-time":"2025-09-21T00:00:00Z","timestamp":1758412800000},"content-version":"vor","delay-in-days":20,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2025,9,1]],"date-time":"2025-09-01T00:00:00Z","timestamp":1756684800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Brain and Behavior"],"published-print":{"date-parts":[[2025,9]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Children represent a particularly vulnerable group to the long\u2010term consequences of COVID\u201019 due to their ongoing neurodevelopment. This study aimed to identify transient and persistent structural alterations in children recovering from the infection by comparing pretreatment and posttreatment MRI scans and to evaluate differences in brain morphology and network organization relative to age\u2010 and sex\u2010matched healthy controls.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>A retrospective cohort of 26 children aged 8\u201312\u00a0years with confirmed COVID\u201019 was compared to 26 healthy controls. All participants underwent high\u2010resolution T1\u2010weighted MRI on a 3T scanner using identical acquisition protocols. Standard VBM and SBM pipelines were applied to quantify cortical volume, thickness, and sulcal depth, followed by SCN analysis to construct correlation matrices based on gray matter metrics. Graph theoretic metrics, including clustering coefficients, eigenpath lengths, small\u2010worldness, and global\/local efficiencies, were computed under different network sparsity thresholds.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Cortical volume analyses revealed reductions in regions including the cingulate cortex, hippocampus, and superior temporal gyrus among children post\u2010COVID\u201019, with within\u2010group comparisons showing decreases in the left middle cingulate cortex (7.4\u20136.9\u00a0cm\n                      <jats:sup>3<\/jats:sup>\n                      ), left postcentral gyrus (12.2\u201310.8\u00a0cm\n                      <jats:sup>3<\/jats:sup>\n                      ), and right anterior cingulate cortex (2.1\u20131.8\u00a0cm\n                      <jats:sup>3<\/jats:sup>\n                      ). Partial recovery of sulcal depth and cortical thickness was observed in the superior temporal gyrus (sulcal depth from 210.3 to 198.5\u00a0mm\n                      <jats:sup>2<\/jats:sup>\n                      , thickness from 2.34 to 2.15\u00a0mm). Structural covariance network analysis demonstrated lower global efficiency and higher small\u2010worldness in the post\u2010COVID\u201019 group compared to controls, along with increased characteristic path length, whereas local connectivity measures (clustering coefficient and local efficiency) remained relatively stable.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Children recovering from COVID\u201019 may exhibit structural brain changes and network connectivity disruptions, some of which show partial resolution over time, whereas others persist. Long\u2010term follow\u2010up through comprehensive neuroimaging and clinical evaluation is necessary to clarify the potential impact on development.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/brb3.70905","type":"journal-article","created":{"date-parts":[[2025,9,22]],"date-time":"2025-09-22T06:37:21Z","timestamp":1758523041000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Brain Microstructural Alterations in Children Post\u2010COVID\u201019 Infection Through VBM, SBM, and Structural Covariance Network Analysis"],"prefix":"10.1002","volume":"15","author":[{"given":"Rui","family":"Wang","sequence":"first","affiliation":[{"name":"Department of Radiology West China Second University Hospital Sichuan University  Chengdu Sichuan People's Republic of China"},{"name":"Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, West China Second 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