Graph analysis of resting state functional brain networks and associations with cognitive outcomes in survivors of pediatric brain tumor
Survivors of pediatric brain tumors often live with long-term cognitive difficulties related to brain changes associated with the tumor itself as well as treatments such as radiation therapy. The present study used graph theory to examine functional network properties in this population and whether...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2023-06-01
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| Series: | Neuroimage: Reports |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666956023000235 |
| _version_ | 1797813768397258752 |
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| author | Eric S. Semmel Vince D. Calhoun Frank Hillary Robin Morris Tricia Z. King |
| author_facet | Eric S. Semmel Vince D. Calhoun Frank Hillary Robin Morris Tricia Z. King |
| author_sort | Eric S. Semmel |
| collection | DOAJ |
| description | Survivors of pediatric brain tumors often live with long-term cognitive difficulties related to brain changes associated with the tumor itself as well as treatments such as radiation therapy. The present study used graph theory to examine functional network properties in this population and whether graph metrics relate to core cognitive skills: attention, working memory, and processing speed. 31 survivors and 31 matched controls completed neuropsychological testing and functional magnetic resonance imaging. Neuroimaging was preprocessed and spatially constrained ICA was completed, followed by calculation of area under the curve values of graph metrics. Results revealed a significant difference such that brain tumor survivors exhibited less small-world properties. This was found to be related to working memory, such that less small-worldness in the network was related to poorer performance. Furthermore, hub regions appear to be particularly vulnerable to disruption. Comparison to results of microstructural network analysis from a similar sample suggest functional connectivity graph metrics provide different and complementary information and additional post-hoc analyses are also discussed. These findings reveal that survivors of pediatric brain tumor indeed display significant differences in functional brain networks that are quantifiable by graph theory and build a foundation to better understand how metrics such as small-worldness can be used to predict long-term cognitive outcomes in adulthood. Ongoing neuroimaging research may play a part in precision medicine determining treatment protocols and interventions for pediatric brain tumor patients. |
| first_indexed | 2024-03-13T07:57:38Z |
| format | Article |
| id | doaj.art-f3815533a8ea44a1847bd41008885042 |
| institution | Directory Open Access Journal |
| issn | 2666-9560 |
| language | English |
| last_indexed | 2024-03-13T07:57:38Z |
| publishDate | 2023-06-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Neuroimage: Reports |
| spelling | doaj.art-f3815533a8ea44a1847bd410088850422023-06-02T04:23:58ZengElsevierNeuroimage: Reports2666-95602023-06-0132100178Graph analysis of resting state functional brain networks and associations with cognitive outcomes in survivors of pediatric brain tumorEric S. Semmel0Vince D. Calhoun1Frank Hillary2Robin Morris3Tricia Z. King4Department of Psychology, Georgia State University, Atlanta, GA, USATri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, USADepartment of Psychology, Pennsylvania State University, University Park, PA, USADepartment of Psychology, Georgia State University, Atlanta, GA, USA; Neuroscience Institute, Georgia State University, Atlanta, GA, USADepartment of Psychology, Georgia State University, Atlanta, GA, USA; Neuroscience Institute, Georgia State University, Atlanta, GA, USA; Corresponding author. Department of Psychology Georgia State University, P.O. Box 5010, Atlanta, GA, 30302-5010, USA.Survivors of pediatric brain tumors often live with long-term cognitive difficulties related to brain changes associated with the tumor itself as well as treatments such as radiation therapy. The present study used graph theory to examine functional network properties in this population and whether graph metrics relate to core cognitive skills: attention, working memory, and processing speed. 31 survivors and 31 matched controls completed neuropsychological testing and functional magnetic resonance imaging. Neuroimaging was preprocessed and spatially constrained ICA was completed, followed by calculation of area under the curve values of graph metrics. Results revealed a significant difference such that brain tumor survivors exhibited less small-world properties. This was found to be related to working memory, such that less small-worldness in the network was related to poorer performance. Furthermore, hub regions appear to be particularly vulnerable to disruption. Comparison to results of microstructural network analysis from a similar sample suggest functional connectivity graph metrics provide different and complementary information and additional post-hoc analyses are also discussed. These findings reveal that survivors of pediatric brain tumor indeed display significant differences in functional brain networks that are quantifiable by graph theory and build a foundation to better understand how metrics such as small-worldness can be used to predict long-term cognitive outcomes in adulthood. Ongoing neuroimaging research may play a part in precision medicine determining treatment protocols and interventions for pediatric brain tumor patients.http://www.sciencedirect.com/science/article/pii/S2666956023000235Brain tumorFunctional networkGraph theoryMagnetic resonance imaging |
| spellingShingle | Eric S. Semmel Vince D. Calhoun Frank Hillary Robin Morris Tricia Z. King Graph analysis of resting state functional brain networks and associations with cognitive outcomes in survivors of pediatric brain tumor Neuroimage: Reports Brain tumor Functional network Graph theory Magnetic resonance imaging |
| title | Graph analysis of resting state functional brain networks and associations with cognitive outcomes in survivors of pediatric brain tumor |
| title_full | Graph analysis of resting state functional brain networks and associations with cognitive outcomes in survivors of pediatric brain tumor |
| title_fullStr | Graph analysis of resting state functional brain networks and associations with cognitive outcomes in survivors of pediatric brain tumor |
| title_full_unstemmed | Graph analysis of resting state functional brain networks and associations with cognitive outcomes in survivors of pediatric brain tumor |
| title_short | Graph analysis of resting state functional brain networks and associations with cognitive outcomes in survivors of pediatric brain tumor |
| title_sort | graph analysis of resting state functional brain networks and associations with cognitive outcomes in survivors of pediatric brain tumor |
| topic | Brain tumor Functional network Graph theory Magnetic resonance imaging |
| url | http://www.sciencedirect.com/science/article/pii/S2666956023000235 |
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