Department of Radiology, Children's Hospital, Zhejiang University School of Medicine, Hangzhou, China.
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.
Neuroimage. 2022 Jul 15;255:119178. doi: 10.1016/j.neuroimage.2022.119178. Epub 2022 Apr 14.
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).
从 1 岁到 6 岁的大脑发育为各种功能能力奠定了基础，并带有神经发育障碍的早期迹象。然而，缺乏描述大脑形态变化和进行个体化推断的定量模型，这阻碍了在此期间识别早期大脑异常。我们对 285 名神经正常儿童的大脑皮质厚度和皮质下体积的年龄依赖性进行了特征描述，并为学龄前儿童构建了所有脑区的定量生长图表。虽然大多数大脑区域的皮质厚度随年龄的增长而降低，但内嗅皮层和海马旁回区域的年龄依赖性呈倒 U 型。与皮质厚度相比，皮质下区域的归一化体积表现出更多发散的趋势，一些区域增加，一些区域减少，一些区域呈倒 U 型趋势。所有脑区的生长曲线模型都具有识别大脑异常的能力。从生长曲线得出的百分位数有助于识别发育性言语和语言障碍儿童，其准确性为 0.875（接收者操作特征曲线下面积：0.943）。我们的研究结果填补了关键发育阶段大脑形态计量学方面的知识空白，并为个体化大脑发育状况评估提供了一条具有敏感性的途径。大脑生长图表已在公共领域共享（http://phi-group.top/resources.html）。
