Gestational age-specific DTI templates of the neonatal brain: Application in preterm developmental study

Due to significant differences in brain volume, morphology, and white matter integrity among neonates of varying gestational ages, using a single full-term template for preterm analysis inevitably introduces analytical errors. To address this, we aimed to develop gestational-age-specific stereotaxic DTI templates using retrospective diffusion MRI scans from 161 neonates acquired between August 2021 and January 2024. The cohort was stratified into four WHO-defined subgroups: extremely preterm (n = 31), very preterm (n = 29), moderate to late preterm (n = 28), and full-term (n = 73). Templates were constructed via iterative registration, with corresponding atlases transformed from JHU space and manually corrected. Quantitative evaluation using the Jacobian determinant and standard deviation revealed that our age-specific templates demonstrated significantly lower deformation magnitude and registration error compared to a standard full-term template. When applied to investigate developmental differences, we observed progressively more extensive fractional anisotropy reductions from moderate-to-late to extremely preterm neonates. Notably, commissural fibers, particularly the corpus callosum body (0.194 ± 0.005 in extremely preterm vs. 0.230 ± 0.003 in full-term, p < 0.001), exhibited significant developmental gradients. Consequently, these constructed gestational-age-specific DTI templates offer a robust tool to improve the accuracy of morbidity risk predictions and facilitate multicenter studies of preterm neonates.

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Publication Details

Journal
NeuroImage
Published
2026-02-14
DOI
https://doi.org/10.1016/j.neuroimage.2026.121811
Primary Topic
Advanced Neuroimaging Techniques and Applications
Type
article
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article

Gestational age-specific DTI templates of the neonatal brain: Application in preterm developmental study

Xiaochen Jiang, Guangjuan Mao, Bingyan Nie, Qi Zhou et al.
NeuroImage
Advanced Neuroimaging Techniques and Applications
article

Gestational age-specific DTI templates of the neonatal brain: Application in preterm developmental study

Xiaochen Jiang, Guangjuan Mao, Bingyan Nie, Qi Zhou, Shilun Zhao, Y Liu, Mengyi Wang, Tianhao Zhang, Baoci Shan, Xuetao Mu
article en

Abstract

Due to significant differences in brain volume, morphology, and white matter integrity among neonates of varying gestational ages, using a single full-term template for preterm analysis inevitably introduces analytical errors. To address this, we aimed to develop gestational-age-specific stereotaxic DTI templates using retrospective diffusion MRI scans from 161 neonates acquired between August 2021 and January 2024. The cohort was stratified into four WHO-defined subgroups: extremely preterm (n = 31), very preterm (n = 29), moderate to late preterm (n = 28), and full-term (n = 73). Templates were constructed via iterative registration, with corresponding atlases transformed from JHU space and manually corrected. Quantitative evaluation using the Jacobian determinant and standard deviation revealed that our age-specific templates demonstrated significantly lower deformation magnitude and registration error compared to a standard full-term template. When applied to investigate developmental differences, we observed progressively more extensive fractional anisotropy reductions from moderate-to-late to extremely preterm neonates. Notably, commissural fibers, particularly the corpus callosum body (0.194 ± 0.005 in extremely preterm vs. 0.230 ± 0.003 in full-term, p < 0.001), exhibited significant developmental gradients. Consequently, these constructed gestational-age-specific DTI templates offer a robust tool to improve the accuracy of morbidity risk predictions and facilitate multicenter studies of preterm neonates.

NeuroImageVol. 328
Tianjin Medical University General Hospital (CN), Chinese PLA General Hospital (CN), Key Laboratory of Nuclear Radiation and Nuclear Energy Technology (CN), Institute of High Energy Physics (CN), Jinzhou Medical University (CN)
Good health and well-being
Openalex Percentile: Top 55%
Advanced Neuroimaging Techniques and Applications
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