Poster Session 09 Program Schedule
02/16/2024
03:30 pm - 04:45 pm
Room: Majestic Complex (Posters 61-120)
Poster Session 09: Epilepsy | Oncology | MS | Infectious Disease
Final Abstract #106
Executive and Adaptive Outcomes in Pediatric Brain Tumor: Comparing Associations with Structural and Functional Brain Network Characteristics
Eric Semmel, Mayo Clinic, Rochester, United States
Sabrina Hickle, Emory University School of Medicine, Atlanta, United States
Tricia King, Georgia State University, Atlanta, United States
Category: Cancer
Keyword 1: brain tumor
Keyword 2: pediatric neuropsychology
Keyword 3: neuroimaging: functional connectivity
Objective:
Adolescent and young adult survivors of pediatric brain tumor often live with long-term neuropsychological deficits associated with the presence of the tumor as well as life-saving treatments. Graph theory has been an increasingly used method to evaluate brain network characteristics, and previous studies have found relationships between both structural and functional network metrics and neuropsychological outcomes. While some have argued for the direct comparability of graph metrics across imaging modalities (e.g., fMRI vs. DTI), others have posited that each modality offers unique information. To shed light on this debate, the present study aimed to use functional magnetic resonance imaging (fMRI) data to replicate previous structural (i.e., DTI) network analyses, using the same participant pool from a larger parent study. The peer-reviewed study being replicated found relationships between global efficiency and adaptive outcomes and identified inhibition as a mediating variable in this relationship (Semmel, Na, & King, 2022). We expect that this relationship will be replicated using functional brain network data.
Participants and Methods:
31 survivors and 31 age- and sex-matched controls completed a comprehensive neuropsychological battery as part of a larger study. Specifically, for the purposes of this study, the Delis-Kaplan Executive Function System (D-KEFS) Color-Word Interference Test and Scales of Independent Behavior – Revised (SIB-R) were used. Participants also underwent resting state fMRI. Resting state data were preprocessed and spatially constrained independent component analysis was completed to construct connectivity matrices. Finally, graph metrics were calculated utilizing an area under the curve method, including global efficiency and clustering coefficient. Group differences and associations between graph metrics and normed scores for executive functioning and adaptive functioning were analyzed using SPSS version 28.0. Pearson correlations were used to evaluate relationships between graph metrics and neuropsychological outcomes.
Results:
In contrast to the previous study utilizing structural brain network data, there were no significant relationships between functional brain network characteristics and adaptive functioning or executive functioning. There were trend-level findings of small-to-medium effect sizes suggesting positive associations between network clustering and global adaptive functioning, adaptive social/communication functioning, and community living skills, but these did not reach statistical significance. Unsurprisingly based on these findings, mediation analyses were nonsignificant when inhibition was evaluated as a mediator variable between executive and adaptive outcomes.
Conclusions:
The results of these analyses indicate that functional network characteristics do not display the same relationships to executive and adaptive outcomes as structural network metrics calculated on the same sample. While there were trend-level associations between network clustering and adaptive outcomes, these relationships did not reach statistical significance, potentially due to a lack of statistical power. These findings lend support to the argument that identical graph metrics calculated on imaging derived from different modalities offer unique information and demonstrate the complementary nature of functional and structural MRI. This suggests the importance of using multimodal imaging techniques to better understand the structure and function of the brain in pediatric brain tumor patients.
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