Disentangling in vivo the effects of iron content and atrophy on the ageing human brain.

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Serval ID
serval:BIB_9E9924BBE541
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Disentangling in vivo the effects of iron content and atrophy on the ageing human brain.
Journal
Neuroimage
Author(s)
Lorio S., Lutti A., Kherif F., Ruef A., Dukart J., Chowdhury R., Frackowiak R.S., Ashburner J., Helms G., Weiskopf N., Draganski B.
ISSN
1095-9572 (Electronic)
ISSN-L
1053-8119
Publication state
Published
Issued date
2014
Peer-reviewed
Oui
Volume
103
Pages
280-289
Language
english
Notes
Publication types: Journal Article ; Research Support, Non-U.S. Gov't
Abstract
Evidence from magnetic resonance imaging (MRI) studies shows that healthy aging is associated with profound changes in cortical and subcortical brain structures. The reliable delineation of cortex and basal ganglia using automated computational anatomy methods based on T1-weighted images remains challenging, which results in controversies in the literature. In this study we use quantitative MRI (qMRI) to gain an insight into the microstructural mechanisms underlying tissue ageing and look for potential interactions between ageing and brain tissue properties to assess their impact on automated tissue classification. To this end we acquired maps of longitudinal relaxation rate R1, effective transverse relaxation rate R2* and magnetization transfer - MT, from healthy subjects (n=96, aged 21-88 years) using a well-established multi-parameter mapping qMRI protocol. Within the framework of voxel-based quantification we find higher grey matter volume in basal ganglia, cerebellar dentate and prefrontal cortex when tissue classification is based on MT maps compared with T1 maps. These discrepancies between grey matter volume estimates can be attributed to R2* - a surrogate marker of iron concentration, and further modulation by an interaction between R2* and age, both in cortical and subcortical areas. We interpret our findings as direct evidence for the impact of ageing-related brain tissue property changes on automated tissue classification of brain structures using SPM12. Computational anatomy studies of ageing and neurodegeneration should acknowledge these effects, particularly when inferring about underlying pathophysiology from regional cortex and basal ganglia volume changes.
Pubmed
Web of science
Open Access
Yes
Create date
09/10/2014 15:43
Last modification date
20/08/2019 15:04
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