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

Lorio, S., Lutti, A., Kherif, F., Ruef, A., Dukart, J., Chowdury, R., et al. (2014). Disentangling in vivo the effects of iron content and atrophy on the ageing human brain. NeuroImage, 103, 280-289. doi:10.1016/j.neuroimage.2014.09.044.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0025-1AF2-8 Version Permalink: http://hdl.handle.net/21.11116/0000-0003-149F-4
Genre: Journal Article

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 Creators:
Lorio, S.1, Author
Lutti, A.1, Author
Kherif, F.1, Author
Ruef, A.1, Author
Dukart, Jürgen1, Author              
Chowdury, R.2, Author
Frackowiak, R. S.1, Author
Ashburner, J.2, Author
Helms, G.3, Author
Weiskopf, Nikolaus2, Author              
Draganski, Bogdan1, 4, Author              
Affiliations:
1Département des Neurosciences Cliniques, Laboratoire de Recherche en Neuroimagerie (LREN), Centre hospitalier universitaire vaudois, Lausanne, Switzerland, ou_persistent22              
2Wellcome Trust Centre for Neuroimaging, University College London, United Kingdom, ou_persistent22              
3Department of Cognitive Neurology, University Medical Center, Göttingen, Germany, ou_persistent22              
4Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634549              

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Free keywords: Quantitative magnetic imaging; Magnetization transfer; R1; Voxel-based morphometry; Voxel-based quantification; Basal ganglia
 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.

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Language(s): eng - English
 Dates: 2014-09-172014-09-242014-12
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Method: Peer
 Identifiers: DOI: 10.1016/j.neuroimage.2014.09.044
PMID: 25264230
PMC: PMC4263529
Other: Epub 2014
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Title: NeuroImage
Source Genre: Journal
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Pages: - Volume / Issue: 103 Sequence Number: - Start / End Page: 280 - 289 Identifier: ISSN: 1053-8119
CoNE: https://pure.mpg.de/cone/journals/resource/954922650166