Age-specific structural fetal brain atlases construction and cortical development quantification for chinese population

• Published in: NeuroImage (Orlando, Fla.) Vol. 241; p. 118412
• Main Authors: Wu, Jiangjie, Sun, Taotao, Yu, Boliang, Li, Zhenghao, Wu, Qing, Wang, Yutong, Qian, Zhaoxia, Zhang, Yuyao, Jiang, Ling, Wei, Hongjiang
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier Inc 01.11.2021; Elsevier Limited; Elsevier
• Subjects: Age; Algorithms; Anatomy; Brain; Brain architecture; Chinese fetal brain atlas; Fetuses; Genetic factors; Gestation; Gestational age; Magnetic resonance imaging; Morphology; MRI – magnetic resonance imaging; Neuroimaging; Optimization; Population; Registration; Segmentation; MRI – magnetic resonance imaging; Chinese fetal brain atlas
• ISSN: 1053-8119; 1095-9572; 1095-9572
• DOI: 10.1016/j.neuroimage.2021.118412

In magnetic resonance imaging (MRI) studies of fetal brain development, structural brain atlases usually serve as essential references for the fetal population. Individual images are usually normalized into a common or standard space for analysis. However, the existing fetal brain atlases are mostly based on MR images obtained from Caucasian populations and thus are not ideal for the characterization of the fetal Chinese population due to neuroanatomical differences related to genetic factors. In this paper, we use an unbiased template construction algorithm to create a set of age-specific Chinese fetal atlases between 21-35 weeks of gestation from 115 normal fetal brains. Based on the 4D spatiotemporal atlas, the morphological development patterns, e.g., cortical thickness, cortical surface area, sulcal and gyral patterns, were quantified. The fetal brain abnormalities were detected when referencing the age-specific template. Additionally, a direct comparison of the Chinese fetal atlases and Caucasian fetal atlases reveals dramatic anatomical differences, mainly in the medial frontal and temporal regions. After applying the Chinese and Caucasian fetal atlases separately to an independent Chinese fetal brain dataset, we find that the Chinese fetal atlases result in significantly higher accuracy than the Caucasian fetal atlases in guiding brain tissue segmentation. These results suggest that the Chinese fetal brain atlases are necessary for quantitative analysis of the typical and atypical development of the Chinese fetal population in the future. The atlases with their parcellations are now publicly available at https://github.com/DeepBMI/FBA-Chinese.