Brain Development From Newborn to Adolescence: Evaluation by Neurite Orientation Dispersion and Density Imaging

• Published in: Frontiers in human neuroscience Vol. 15; p. 616132
• Main Authors: Zhao, Xueying, Shi, Jingjing, Dai, Fei, Wei, Lei, Zhang, Boyu, Yu, Xuchen, Wang, Chengyan, Zhu, Wenzhen, Wang, He
• Format: Journal Article
• Language: English
• Published: Switzerland Frontiers Research Foundation 15.03.2021; Frontiers Media S.A
• Subjects: Adolescents; Age; brain development; Brain research; Child development; Children; Datasets; Developmental stages; diffusion MRI; diffusion tensor imaging; Image processing; Magnetic resonance imaging; neurite density; Neuroimaging; Neuroscience; NODDI; pediatric; Pediatrics; Registration; Regression analysis; Substantia alba; Substantia grisea; brain development; NODDI; diffusion MRI; diffusion tensor imaging; neurite density; pediatric
• ISSN: 1662-5161; 1662-5161
• DOI: 10.3389/fnhum.2021.616132

Neurite orientation dispersion and density imaging (NODDI) is a diffusion model specifically designed for brain magnetic resonance imaging. Despite recent studies suggesting that NODDI modeling might be more sensitive to brain development than diffusion tensor imaging (DTI), these studies were limited to a relatively small age range and mainly based on the manually operated region of interest analysis. Therefore, this study applied NODDI to investigate brain development in a large sample size of 214 subjects ranging in ages from 0 to 14. The whole brain was automatically segmented into 122 regions. The maturation trajectory of each region was characterized by the time course of diffusion metrics and further quantified using nonlinear regression. The NODDI-derived metrics, neurite density index (NDI) and orientation dispersion index (ODI), increased with age. And these two metrics were superior to the DTI-derived metrics in SVM regression models of age. The NDI in white matter exhibited a more rapid growth than that in gray matter (including the cortex and deep nucleus). These diffusion indicators experienced conspicuous increases during early childhood and the growth speed slowed down in adolescence. Region-specific maturation patterns were described throughout the brain, including white matter, cortical and deep gray matter. These development patterns were evaluated and discussed on the basis of NODDI’s model assumptions. To summarize, this study verified the high sensitivity of NODDI to age over a crucial developmental period from newborn to adolescence. Moreover, the existing knowledge of brain development has been complemented, suggesting that NODDI has a potential capability in the investigation of brain development.