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Cross-Sectional Volumes and Trajectories of the Human Brain, Gray Matter, White Matter and Cerebrospinal Fluid in 9473 Typically Aging Adults.
- Source :
-
Neuroinformatics [Neuroinformatics] 2021 Apr; Vol. 19 (2), pp. 347-366. - Publication Year :
- 2021
-
Abstract
- Accurate knowledge of adult human brain volume (BV) is critical for studies of aging- and disease-related brain alterations, and for monitoring the trajectories of neural and cognitive functions in conditions like Alzheimer's disease and traumatic brain injury. This scoping meta-analysis aggregates normative reference values for BV and three related volumetrics-gray matter volume (GMV), white matter volume (WMV) and cerebrospinal fluid volume (CSFV)-from typically-aging adults studied cross-sectionally using magnetic resonance imaging (MRI). Drawing from an aggregate sample of 9473 adults, this study provides (A) regression coefficients β describing the age-dependent trajectories of volumetric measures by sex within the range from 20 to 70 years based on both linear and quadratic models, and (B) average values for BV, GMV, WMV and CSFV at the representative ages of 20 (young age), 45 (middle age) and 70 (old age). The results provided synthesize ~20 years of brain volumetrics research and allow one to estimate BV at any age between 20 and 70. Importantly, however, such estimates should be used and interpreted with caution because they depend on MRI hardware specifications (e.g. scanner manufacturer, magnetic field strength), data acquisition parameters (e.g. spatial resolution, weighting), and brain segmentation algorithms. Guidelines are proposed to facilitate future meta- and mega-analyses of brain volumetrics.
- Subjects :
- Aged
Algorithms
Brain physiology
Cerebrospinal Fluid physiology
Cognition physiology
Female
Gray Matter physiology
Humans
Magnetic Resonance Imaging methods
Male
Middle Aged
Organ Size physiology
White Matter physiology
Young Adult
Aging physiology
Brain diagnostic imaging
Cerebrospinal Fluid diagnostic imaging
Gray Matter diagnostic imaging
Magnetic Resonance Imaging trends
White Matter diagnostic imaging
Subjects
Details
- Language :
- English
- ISSN :
- 1559-0089
- Volume :
- 19
- Issue :
- 2
- Database :
- MEDLINE
- Journal :
- Neuroinformatics
- Publication Type :
- Academic Journal
- Accession number :
- 32856237
- Full Text :
- https://doi.org/10.1007/s12021-020-09480-w