INS NYC 2024 Program

Poster

Poster Session 04 Program Schedule

02/15/2024
12:00 pm - 01:15 pm
Room: Shubert Complex (Posters 1-60)

Poster Session 04: Neuroimaging | Neurostimulation/Neuromodulation | Teleneuropsychology/Technology


Final Abstract #8

Relationships Among the Structural Connectome and Cognitive Outcome in Adolescents with Congenital Heart Disease

Holly Dustin, Georgia State University, Atlanta, United States
Ashley Ware, Georgia State University, Atlanta, United States
Kristen Hoskinson, Nationwide Children's Hospital, Columbus, United States
Thomas Burns, Children's Healthcare of Atlanta, Atlanta, United States
William Mahle, Children's Healthcare of Atlanta, Atlanta, United States
Tricia King, Georgia State University, Atlanta, United States

Category: Neuroimaging

Keyword 1: neuroimaging: structural
Keyword 2: congenital disorders
Keyword 3: neurocognition

Objective:

Congenital heart disease (CHD), one of the most prevalent birth defects globally, can impact brain development and, in severe forms, require surgery that increases risk of acquired brain injury. Together, altered brain development and increased rates of acquired brain injury place individuals with CHD at higher risk for adverse neurocognitive outcomes. Current research in CHD shows consistent relationships among broad domains of cognition and underlying brain pathology. However, these relationships examine brain regions of interest but do not consider brain networks. Graph theory analyses provide a statistical approach that allows for the examination of brain networks that may elucidate more nuanced relationships. The aim of the present study is to characterize the structural connectome and to investigate how structural brain networks relate to cognitive performance in adolescents with CHD compared to their healthy peers.

Participants and Methods:

Thirty-seven adolescents with CHD (20 double-ventricle and 17 single-ventricle; Mage=14.8, SD=3.5) and 38 healthy age- and gender-matched peers (Mage=16.0. SD=3.8) underwent neuroimaging and completed cognitive measures for processing seed (Symbol Digit Modalities Test or WISC-V Coding), intelligence (FSIQ; 2-subtest Wechsler Abbreviated Scale of Intelligence-II), and informant-reported executive function (Behavior Rating Inventory of Executive Function). For each participant, five global network metrics were derived from diffusion-weighted MRI scans (clustering coefficient, longest path length, global efficiency, local efficiency, and small-worldness). ANOVA tests investigated group differences, among participants with two CHD types and healthy controls, on cognitive measures and network metrics. Partial correlations and hierarchical regression analyses investigated brain-behavior relationships among cognitive performance and network metrics.

Results:

Both CHD groups had higher informant-reported executive function concerns compared to their healthy peers, with a large effect size (𝜂2=.15). On global network metrics, single-ventricle CHD participants showed lower small-worldness compared to both adolescents with double-ventricle CHD and healthy controls with a large effect size (𝜂2=.28). Adolescents with double-ventricle CHD showed lower global efficiency compared to healthy controls with a medium effect size (𝜂2=.09). FSIQ was significantly correlated with global efficiency (r=.304, p=.014), when controlling for age. Hierarchical linear regression showed that global efficiency was a significant predictor of FSIQ, controlling for age and group membership (R2=.19, F(4, 69)=4.16, p<.01; R2-change=.07, p=.01).

Conclusions:

This study sought to address the gaps in knowledge about the structural connectome and relationships with cognitive performance in CHD. With inclusion of a mixed sample of CHD types, these results allow for increased generalizability compared to previous research. The present study identified group differences in global network metrics and informant-reported executive function, including between CHD severity groups and healthy controls. Specifically global efficiency and small-worldness (a measure of brain segregation and integration) were significantly different among groups, suggesting that adolescents with CHD may have less organized and less efficient (i.e., increased number of white matter pathways between nodes) brain networks. Further, global efficiency was a significant predictor of FSIQ, suggesting more efficiency among network nodes is related to higher FSIQ. Continued research of the structural connectome across the severity spectrum of CHD can help understand potentially subtle differences in brain networks.