Literature DB >> 27165761

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

Olivier Potvin1, Abderazzak Mouiha1, Louis Dieumegarde1, Simon Duchesne2.   

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 94years 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.
Copyright © 2016 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Aging; Atrophy; Magnetic resonance imaging; Morphometry; Normality; Sex

Mesh:

Year:  2016        PMID: 27165761     DOI: 10.1016/j.neuroimage.2016.05.016

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


  31 in total

1.  Effects of aging on brain volumes in healthy individuals across adulthood.

Authors:  Iman Beheshti; Norihide Maikusa; Hiroshi Matsuda
Journal:  Neurol Sci       Date:  2019-03-09       Impact factor: 3.307

2.  Towards a unified analysis of brain maturation and aging across the entire lifespan: A MRI analysis.

Authors:  Pierrick Coupé; Gwenaelle Catheline; Enrique Lanuza; José Vicente Manjón
Journal:  Hum Brain Mapp       Date:  2017-07-24       Impact factor: 5.038

3.  Quantitative assessment of field strength, total intracranial volume, sex, and age effects on the goodness of harmonization for volumetric analysis on the ADNI database.

Authors:  Da Ma; Karteek Popuri; Mahadev Bhalla; Oshin Sangha; Donghuan Lu; Jiguo Cao; Claudia Jacova; Lei Wang; Mirza Faisal Beg
Journal:  Hum Brain Mapp       Date:  2018-11-15       Impact factor: 5.038

4.  Predicting age from cortical structure across the lifespan.

Authors:  Christopher R Madan; Elizabeth A Kensinger
Journal:  Eur J Neurosci       Date:  2018-02-12       Impact factor: 3.386

5.  Age-related differences in the structural complexity of subcortical and ventricular structures.

Authors:  Christopher R Madan; Elizabeth A Kensinger
Journal:  Neurobiol Aging       Date:  2016-10-27       Impact factor: 4.673

6.  Data-Driven Analyses of Longitudinal Hippocampal Imaging Trajectories: Discrimination and Biomarker Prediction of Change Classes.

Authors:  Shannon M Drouin; G Peggy McFall; Olivier Potvin; Pierre Bellec; Mario Masellis; Simon Duchesne; Roger A Dixon
Journal:  J Alzheimers Dis       Date:  2022       Impact factor: 4.160

7.  Structural covariance across the lifespan: Brain development and aging through the lens of inter-network relationships.

Authors:  Katherine S Aboud; Yuankai Huo; Hakmook Kang; Ashley Ealey; Susan M Resnick; Bennett A Landman; Laurie E Cutting
Journal:  Hum Brain Mapp       Date:  2018-10-03       Impact factor: 5.038

8.  Improving data availability for brain image biobanking in healthy subjects: Practice-based suggestions from an international multidisciplinary working group.

Authors:  Susan D Shenkin; Cyril Pernet; Thomas E Nichols; Jean-Baptiste Poline; Paul M Matthews; Aad van der Lugt; Clare Mackay; Linda Lanyon; Bernard Mazoyer; James P Boardman; Paul M Thompson; Nick Fox; Daniel S Marcus; Aziz Sheikh; Simon R Cox; Devasuda Anblagan; Dominic E Job; David Alexander Dickie; David Rodriguez; Joanna M Wardlaw
Journal:  Neuroimage       Date:  2017-02-14       Impact factor: 6.556

9.  Beware of white matter hyperintensities causing systematic errors in FreeSurfer gray matter segmentations!

Authors:  Mahsa Dadar; Olivier Potvin; Richard Camicioli; Simon Duchesne
Journal:  Hum Brain Mapp       Date:  2021-03-30       Impact factor: 5.038

10.  Norms for Automatic Estimation of Hippocampal Atrophy and a Step Forward for Applicability to the Italian Population.

Authors:  Silvia De Francesco; Samantha Galluzzi; Nicola Vanacore; Cristina Festari; Paolo Maria Rossini; Stefano F Cappa; Giovanni B Frisoni; Alberto Redolfi
Journal:  Front Neurosci       Date:  2021-06-28       Impact factor: 4.677

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