The cingulum in very preterm infants relates to language and social-emotional impairment at 2 years of term-equivalent ageopen access
- Authors
- Lee, Hyun Ju; Kwon, Hyeokjin; Kim, Johanna Inhyang; Lee, Joo Young; Lee, Ji Young; Bang, SungKyu; Lee, Jong-Min
- Issue Date
- Dec-2021
- Publisher
- ELSEVIER SCI LTD
- Keywords
- Very preterm infants; Diffusion tensor imaging (DTI); White matter (WM); Elastic net logistic regression model; Bayley scales
- Citation
- NEUROIMAGE-CLINICAL, v.29, pp.1 - 12
- Indexed
- SCIE
SCOPUS
- Journal Title
- NEUROIMAGE-CLINICAL
- Volume
- 29
- Start Page
- 1
- End Page
- 12
- URI
- https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/140287
- DOI
- 10.1016/j.nicl.2020.102528
- ISSN
- 2213-1582
- Abstract
- Background
Relative to full-term infants, very preterm infants exhibit disrupted white matter (WM) maturation and problems related to development, including motor, cognitive, social-emotional, and receptive and expressive language processing.
Objective
The present study aimed to determine whether regional abnormalities in the WM microstructure of very preterm infants, as defined relative to those of full-term infants at a near-term age, are associated with neurodevelopmental outcomes at the age of 18–22 months.
Methods
We prospectively enrolled 89 very preterm infants (birth weight < 1500 g) and 43 normal full-term control infants born between 2016 and 2018. All infants underwent a structural brain magnetic resonance imaging scan at near-term age. The diffusion tensor imaging (DTI) metrics of the whole-brain WM tracts were extracted based on the neonatal probabilistic WM pathway. The elastic net logistic regression model was used to identify altered WM tracts in the preterm brain. We evaluated the associations between the altered WM microstructure at near-term age and motor, cognitive, social-emotional, and receptive and expressive language developments at 18–22 months of age, as measured using the Bayley Scales of Infant Development, Third Edition.
Results
We found that the elastic net logistic regression model could classify preterm and full-term neonates with an accuracy of 87.9% (corrected p < 0.008) using the DTI metrics in the pathway of interest with a 10% threshold level. The fractional anisotropy (FA) values of the body and splenium of the corpus callosum, middle cerebellar peduncle, left and right uncinate fasciculi, and right portion of the pathway between the premotor and primary motor cortices (premotor-PMC), as well as the mean axial diffusivity (AD) values of the left cingulum, were identified as contributive features for classification. Increased adjusted AD values in the left cingulum pathway were significantly correlated with language scores after false discovery rate (FDR) correction (r = 0.217, p = 0.043). The expressive language and social-emotional composite scores showed a significant positive correlation with the AD values in the left cingulum pathway (r = 0.226 [p = 0.036] and r = 0.31 [p = 0.003], respectively) after FDR correction.
Conclusion
Our approach suggests that the cingulum pathways of very preterm infants differ from those of full-term infants and significantly contribute to the prediction of the subsequent development of the language and social-emotional domains. This finding could improve our understanding of how specific neural substrates influence neurodevelopment at later ages, and individual risk prediction, thus helping to inform early intervention strategies that address developmental delay.
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