title: Voxel-based analysis of white matter during adolescence and young adulthood.
abstract: OBJECTIVE
  To evaluate differences in age-related brain white matter by voxel-based analysis of healthy adolescents and young adults.
  
  
  METHODS
  Echo-planar diffusion-tensor magnetic resonance (MR) imaging was performed in healthy subjects of 3 groups (aged 11-13, 16-18 and 23-25, respectively). Linear correlative analyses were applied to determining age-related fractional anisotropy (FA) and mean diffusivity (MD), and t-test was performed to compare FA and mean diffusion maps between different age groups.
  
  
  RESULTS
  Significant positive correlation of FA with age was found in the internal capsule, the external capsule, the frontal white matter, and the body and genu of the corpus callosum. Compared with the 11-13 age group, FA in the 16-18 age group increased in the internal capsule, the frontal white matter, the body and the splenium of the corpus callosum. Compared to the 16-18 age group, FA in the 23-25 age group increased in the frontal white matter, the posterior limb of internal capsule, and the genu of the corpus callosum. Statistically significant negative correlation of the mean diffusion with age was found in the frontal and parietal white matter. Compared with the 11-13 age group, MD in the 16-18 age group decreased in the prefrontal and the temporo-parietal white matter. Compared with the 16-18 age group, MD in the 23-25 age group decreased in the frontal white matter.
  
  
  CONCLUSIONS
  Diffusion-tensor MR imaging results indicate that white matter maturation assessed at different ages involves increases in FA and decreases in mean diffusion of the white matter during adolescence and young adulthood. FA and mean diffusion may reflect different physiologic processes in healthy adolescents and young adults. Taken together, these data show that maturation of white matter is an important part of brain maturation during adolescence and young adulthood.
authors.affiliation: Department of Medical Informatics and Medical Image, College of Biomedical Engineering and Medical Imaging, Third Military Medical University, Chongqing 400038, China. qiumingguo@yahoo.com
authors.forename: Mingguo
authors.initials: M
authors.lastname: Qiu
authors.forename: Qiyu
authors.initials: Q
authors.lastname: Li
authors.forename: Guangjiu
authors.initials: G
authors.lastname: Liu
authors.forename: Bing
authors.initials: B
authors.lastname: Xie
authors.forename: Jiang
authors.initials: J
authors.lastname: Wang
mesh_terms: D000293:Adolescent; D000328:Adult; D016880:Anisotropy; D001921:Brain / Q000033:anatomy & histology* / Q000254:growth & development*; D002648:Child; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods*; D017352:Echo-Planar Imaging / Q000379:methods*; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008297:Male; D009413:Nerve Fibers, Myelinated / Q000502:physiology; D055815:Young Adult