Title: Early assessment of lateralization and sex influences on the microstructure of the white matter corticospinal tract in healthy term neonates
Abstract: Abstract We assessed the sex and the lateralization differences in the corticospinal tract (CST) during the early postnatal period. Twenty‐five healthy term neonates (13 girls, aged 39.2 ± 1.2 weeks, and 12 boys aged 38.6 ± 3.0 weeks) underwent Diffusion Tensor Imaging (DTI). Fiber tracking was performed to extract bilaterally the CST pathways and to quantify the parallel ( E 1 ) and perpendicular ( E 23 ) diffusions, the apparent diffusion coefficient (ADC), and fractional anisotropy (FA). The measurements were performed on the entire CST fibers and on four segments: base of the pons (CST‐Po), cerebral peduncles (CST‐CP), posterior limb of the internal capsule (CST‐PLIC), and corona‐radiata (CST‐CR). Significantly higher E 1 , lower E 23, and higher FA in the right compared to the left were noted in the CST‐PLIC of the girls. Significantly lower E 23 and lower ADC with higher FA in the right compared to left were observed in the CST‐CP of the boys. Moreover, the CST‐PLIC of the boys had significantly higher E 1 in the right compared to the left. There was a significant increase in left CST E 1 of boys when compared with girls. Girls had a significantly lower E 1 , lower E 23 and, lower ADC in the left CST‐CP compared with boys. In addition, girls had a significantly lower E 23 and higher FA in the right CST‐PLIC compared with boys. Sex differences and lateralization in structure‐based segments of the CST were found in healthy term infants during early postnatal period. These findings are vital to understanding motor development of healthy term born neonates to better interpret newborn infants with abnormal neurodevelopment.
Publication Year: 2018
Publication Date: 2018-12-13
Language: en
Type: article
Indexed In: ['crossref', 'pubmed']
Access and Citation
Cited By Count: 9
AI Researcher Chatbot
Get quick answers to your questions about the article from our AI researcher chatbot