Normative data for subcortical regional volumes over the lifetime of the adult human brain

Authors: Potvin, Olivier; Duchesne, Simon
Abstract: Normative data for volumetric estimates of brain structures are necessary to adequately assess brain volume alterations in individuals with suspected neurological or psychiatric conditions. Although many studies have described age and sex effects in healthy individuals for brain morphometry assessed via magnetic resonance imaging, proper normative values allowing to quantify potential brain abnormalities are needed. We developed norms for volumetric estimates of subcortical brain regions based on cross-sectional magnetic resonance scans from 2790 healthy individuals aged 18 to 94 years using 23 samples provided by 21 independent research groups. The segmentation was conducted using FreeSurfer, a widely used and freely available automated segmentation software. Models predicting subcortical regional volumes of each hemisphere were produced including age, sex, estimated total intracranial volume (eTIV), scanner manufacturer, magnetic field strength, and interactions as predictors. The mean explained variance by the models was 48%. For most regions, age, sex and eTIV predicted most of the explained variance while manufacturer, magnetic field strength and interactions predicted a limited amount. Estimates of the expected volumes of an individual based on its characteristics and the scanner characteristics can be obtained using derived formulas. For a new individual, significance test for volume abnormality, effect size and estimated percentage of the normative population with a smaller volume can be obtained. Normative values were validated in independent samples of healthy adults and in adults with Alzheimer's disease and schizophrenia.
Issue Date: 7 May 2016
Open Access Date: 7 May 2017
Document version: AM
Permalink: http://hdl.handle.net/20.500.11794/1141
This document was published in: NeuroImage
http://dx.doi.org/10.1016/j.neuroimage.2016.05.016
Academic Press
Alternative version: 10.1016/j.neuroimage.2016.05.016
Collection:Articles publiés dans des revues avec comité de lecture

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