Multi-contrast Human Neonatal Brain Atlas: Application to Normal Neonate Development Analysis
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MRI is a sensitive method for detecting subtle anatomic abnormalities in the neonatal brain. To optimize the usefulness for neonatal and pediatric care, systematic research, based on quantitative image analysis and functional correlation, is required. Normalization-based image analysis is one of the most effective methods for image quantification and statistical comparison. However, the application of this methodology to neonatal brain MRI scans is rare. Some of the difficulties are the rapid changes in T1 and T2 contrasts and the lack of contrast between brain structures, which prohibits accurate cross-subject image registration. Diffusion tensor imaging (DTI), which provides rich and quantitative anatomical contrast in neonate brains, is an ideal technology for normalization-based neonatal brain analysis. In this paper, we report the development of neonatal brain atlases with detailed anatomic information derived from DTI and co-registered anatomical MRI. Combined with a diffeomorphic transformation, we were able to normalize neonatal brain images to the atlas space and three-dimensionally parcellate images into 122 regions. The accuracy of the normalization was comparable to the reliability of human raters. This method was then applied to babies of 37-53 post-conceptional weeks to characterize developmental changes of the white matter, which indicated a posterior-to-anterior and a central-to-peripheral direction of maturation. We expect that future applications of this atlas will include investigations of the effect of prenatal events and the effects of preterm birth or low birth weights, as well as clinical applications, such as determining imaging biomarkers for various neurological disorders.
Dynamics of infant white matter maturation from birth to 6 months.
Risk B, Li L, Jones W, Shultz S bioRxiv. 2025; .
PMID: 39990497 PMC: 11844443. DOI: 10.1101/2025.02.13.638114.
Machine-learning based prediction of future outcome using multimodal MRI during early childhood.
Ouyang M, Whitehead M, Mohapatra S, Zhu T, Huang H Semin Fetal Neonatal Med. 2024; 29(2-3):101561.
PMID: 39528363 PMC: 11654837. DOI: 10.1016/j.siny.2024.101561.
Nishimaki K, Onda K, Ikuta K, Chotiyanonta J, Uchida Y, Mori S Hum Brain Mapp. 2024; 45(16):e70063.
PMID: 39523990 PMC: 11551626. DOI: 10.1002/hbm.70063.
Assessment of the Depiction of Superficial White Matter Using Ultra-High-Resolution Diffusion MRI.
Zhang F, Chen Y, Ning L, Rushmore J, Liu Q, Du M Hum Brain Mapp. 2024; 45(14):e70041.
PMID: 39392220 PMC: 11467805. DOI: 10.1002/hbm.70041.
Functional connectivity of the pediatric brain.
Argyropoulou M, Xydis V, Astrakas L Neuroradiology. 2024; 66(11):2071-2082.
PMID: 39230715 DOI: 10.1007/s00234-024-03453-5.