Growth charts of brain morphometry for preschool children

Hongxi Zhang; Jia Li; Xiaoli Su; Yang Hu; Tianmei Liu; Shaoqing Ni; Haifeng Li; Xi-Nian Zuo; Junfen Fu; Ti-Fei Yuan; Zhi Yang

doi:10.1016/j.neuroimage.2022.119178

Growth charts of brain morphometry for preschool children

Neuroimage. 2022 Jul 15:255:119178. doi: 10.1016/j.neuroimage.2022.119178. Epub 2022 Apr 14.

Authors

Hongxi Zhang¹, Jia Li², Xiaoli Su¹, Yang Hu³, Tianmei Liu¹, Shaoqing Ni⁴, Haifeng Li⁵, Xi-Nian Zuo⁶, Junfen Fu⁷, Ti-Fei Yuan⁸, Zhi Yang⁹

Affiliations

¹ Department of Radiology, Children's Hospital, Zhejiang University School of Medicine, Hangzhou, China.
² Laboratory of Psychological Health and Imaging, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Faculty of Psychology and Educational Sciences, KU Leuven, Leuven, Belgium.
³ Laboratory of Psychological Health and Imaging, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Shanghai Key laboratory of Psychotic disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
⁴ Clinical Trial Institute, Children's Hospital, Zhejiang University School of Medicine, Hangzhou, China.
⁵ Department of Rehabilitation, Children's Hospital, Zhejiang University School of Medicine, Hangzhou, China.
⁶ State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China; National Basic Science Data Center, Beijing, China; Developmental Population Neuroscience Research Center, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China.
⁷ Department of Endocrinology, Children's Hospital, Zhejiang University School of Medicine, Hangzhou, China. Electronic address: fjf68@zju.edu.cn.
⁸ Shanghai Key laboratory of Psychotic disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Co-innovation Center of Neuroregeneration, Nantong University, Nantong, Jiangsu, China; Translational Research Institute of Brain and Brain-Like Intelligence, Shanghai Fourth People's Hospital Affiliated to Tongji University School of Medicine, Shanghai, China. Electronic address: ytf0707@126.com.
⁹ Laboratory of Psychological Health and Imaging, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Shanghai Key laboratory of Psychotic disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Brain Science and Technology Research Center, Shanghai Jiao Tong University, Shanghai, China; Institute of Psychological and Behavioral Sciences, Shanghai Jiao Tong University, Shanghai, China. Electronic address: yangz@smhc.org.cn.

PMID: 35430358
DOI: 10.1016/j.neuroimage.2022.119178

Abstract

Brain development from 1 to 6 years of age anchors a wide range of functional capabilities and carries early signs of neurodevelopmental disorders. However, quantitative models for depicting brain morphology changes and making individualized inferences are lacking, preventing the identification of early brain atypicality during this period. With a sample size of 285, we characterized the age dependence of the cortical thickness and subcortical volume in neurologically normal children and constructed quantitative growth charts of all brain regions for preschool children. While the cortical thickness of most brain regions decreased with age, the entorhinal and parahippocampal regions displayed an inverted-U shape of age dependence. Compared to the cortical thickness, the normalized volume of subcortical regions exhibited more divergent trends, with some regions increasing, some decreasing, and some displaying inverted-U-shaped trends. The growth curve models for all brain regions demonstrated utilities in identifying brain atypicality. The percentile measures derived from the growth curves facilitate the identification of children with developmental speech and language disorders with an accuracy of 0.875 (area under the receiver operating characteristic curve: 0.943). Our results fill the knowledge gap in brain morphometrics in a critical development period and provide an avenue for individualized brain developmental status evaluation with demonstrated sensitivity. The brain growth charts are shared with the public (http://phi-group.top/resources.html).

Keywords: Brain development; Brain structure; Childhood development; Developmental brain disorder; Diagnostic imaging; Growth curve.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Brain
Brain Mapping / methods
Child, Preschool
Growth Charts
Humans
Magnetic Resonance Imaging* / methods
Neurodevelopmental Disorders*