4.7 Article

Allometric scaling of brain regions to intra-cranial volume: An epidemiological MRI study

期刊

HUMAN BRAIN MAPPING
卷 38, 期 1, 页码 151-164

出版社

WILEY
DOI: 10.1002/hbm.23351

关键词

MRI; allometry; intra-cranial volume; brain; cortex; striatum; white matter; thalamus; AGES-Reykjavik; ADNI; CARDIA

资金

  1. National Institutes of Health [N01-AG-1-2100]
  2. National Institute on Aging Intramural Research Program
  3. Hjartavernd (Icelandic Heart Association)
  4. Althingi (Icelandic Parliament)
  5. Netherlands Organisation for Health Research and Development (AGIKO) [92003536]
  6. Dutch Genomics Initiative [NCHA 050-060-810]

向作者/读者索取更多资源

There is growing evidence that sub-structures of the brain scale allometrically to total brain size, that is, in a non-proportional and non-linear way. Here, scaling of different volumes of interest (VOI) to intra-cranial volume (ICV) was examined. It was assessed whether scaling was allometric or isometric and whether scaling coefficients significantly differed from each other. We also tested to what extent allometric scaling of VOI was introduced by the automated segmentation technique. Furthermore, reproducibility of allometric scaling was studied different age groups and study populations. Study samples included samples of cognitively healthy adults from the community-based Age Gene/Environment Susceptibility-Reykjavik Study (AGES-Reykjavik Study) (N=3,883), the Coronary Artery Risk Development in Young Adults Study (CARDIA) (N =709), and the Alzheimer's Disease Neuroimaging Initiative (ADNI) (N=180). Data encompassed participants with different age, ethnicity, risk factor profile, and ICV and VOI obtained with different automated MRI segmentation techniques. Our analysis showed that (1) allometric scaling is a trait of all parts of the brain, (2) scaling of neo-cortical white matter, neo-cortical gray matter, and deep gray matter structures including the cerebellum are significantly different from each other, and (3) allometric scaling of brain structures cannot solely be explained by age-associated atrophy, sex, ethnicity, or a systematic bias from study-specific segmentation algorithm, but appears to be a true feature of brain geometry. Hum Brain Mapp 38:151-164, 2017. (c) 2016 Wiley Periodicals, Inc.

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