tetano
Editor, Senior Moderator
Sci Rep
. 2025 Apr 5;15(1):11691.
doi: 10.1038/s41598-025-96191-4. Multimodal MRI analysis of COVID-19 effects on pediatric brain
Ting Peng[SUP] #[/SUP][SUP] 1 2 [/SUP], Chaowei Zhang[SUP] #[/SUP][SUP] 3 [/SUP], Pingping Xie[SUP] #[/SUP][SUP] 2 [/SUP], Ying Lin[SUP] 1 [/SUP], Lin Zhang[SUP] 4 [/SUP], Zuozhen Lan[SUP] 4 [/SUP], Mingwen Yang[SUP] 4 [/SUP], Xianghui Huang[SUP] 5 [/SUP], Jungang Liu[SUP] 6 [/SUP], Guoqiang Cheng[SUP] 7 [/SUP]
Affiliations
The COVID-19 pandemic has raised significant concerns regarding its impact on the central nervous system, including the brain. While the effects on adult populations are well documented, less is known about its implications for pediatric populations. This study investigates alterations in cortical metrics and structural covariance networks (SCNs) based on the Local Gyrification Index (LGI) in children with mild COVID-19, alongside changes in non-invasive MRI proxies related to glymphatic function. We enrolled 19 children with COVID-19 and 22 age-comparable healthy controls. High-resolution T1-weighted and diffusion-weighted MRI images were acquired. Cortical metrics, including thickness, surface area, volume, and LGI, were compared using vertex-wise general linear models. SCNs were analyzed for differences in global and nodal metrics, and MRI proxies, including diffusion tensor imaging along the perivascular space and choroid plexus (CP) volume, were also assessed. Our results showed increased cortical area, volume, and LGI in the left superior parietal cortex, as well as increased cortical thickness in the left lateral occipital cortex among children with COVID-19. SCN analysis revealed altered network topology and larger CP volumes in the COVID group, suggesting virus-induced neuroinflammation. These findings provide evidence of potential brain alterations in children following mild COVID-19, emphasizing the need for further investigation into long-term neurodevelopmental outcomes.
Keywords: COVID; Glymphatic function; Structural covariance network.
. 2025 Apr 5;15(1):11691.
doi: 10.1038/s41598-025-96191-4. Multimodal MRI analysis of COVID-19 effects on pediatric brain
Ting Peng[SUP] #[/SUP][SUP] 1 2 [/SUP], Chaowei Zhang[SUP] #[/SUP][SUP] 3 [/SUP], Pingping Xie[SUP] #[/SUP][SUP] 2 [/SUP], Ying Lin[SUP] 1 [/SUP], Lin Zhang[SUP] 4 [/SUP], Zuozhen Lan[SUP] 4 [/SUP], Mingwen Yang[SUP] 4 [/SUP], Xianghui Huang[SUP] 5 [/SUP], Jungang Liu[SUP] 6 [/SUP], Guoqiang Cheng[SUP] 7 [/SUP]
Affiliations
- PMID: 40188214
- PMCID: PMC11972372
- DOI: 10.1038/s41598-025-96191-4
The COVID-19 pandemic has raised significant concerns regarding its impact on the central nervous system, including the brain. While the effects on adult populations are well documented, less is known about its implications for pediatric populations. This study investigates alterations in cortical metrics and structural covariance networks (SCNs) based on the Local Gyrification Index (LGI) in children with mild COVID-19, alongside changes in non-invasive MRI proxies related to glymphatic function. We enrolled 19 children with COVID-19 and 22 age-comparable healthy controls. High-resolution T1-weighted and diffusion-weighted MRI images were acquired. Cortical metrics, including thickness, surface area, volume, and LGI, were compared using vertex-wise general linear models. SCNs were analyzed for differences in global and nodal metrics, and MRI proxies, including diffusion tensor imaging along the perivascular space and choroid plexus (CP) volume, were also assessed. Our results showed increased cortical area, volume, and LGI in the left superior parietal cortex, as well as increased cortical thickness in the left lateral occipital cortex among children with COVID-19. SCN analysis revealed altered network topology and larger CP volumes in the COVID group, suggesting virus-induced neuroinflammation. These findings provide evidence of potential brain alterations in children following mild COVID-19, emphasizing the need for further investigation into long-term neurodevelopmental outcomes.
Keywords: COVID; Glymphatic function; Structural covariance network.