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  Neurobiological origin of spurious brain morphological changes: A quantitative MRI study

Lorio, S., Kherif, F., Ruef, A., Melie-Garcia, L., Frackowiak, R., Ashburner, J., et al. (2016). Neurobiological origin of spurious brain morphological changes: A quantitative MRI study. Human Brain Mapping, 37(5), 1801-1815. doi:10.1002/hbm.23137.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-002B-192E-0 Version Permalink: http://hdl.handle.net/21.11116/0000-0003-1E3E-8
Genre: Journal Article

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 Creators:
Lorio, Sara1, Author
Kherif, Ferath1, Author
Ruef, Anne1, Author
Melie-Garcia, Lester1, Author
Frackowiak, Richard1, Author
Ashburner, John2, Author
Helms, Gunther3, Author
Lutti, Antoine1, Author
Draganski, Bogdan1, 4, Author              
Affiliations:
1Laboratoire 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 Clinical Sciences, Lund University, Sweden, ou_persistent22              
4Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634549              

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Free keywords: Quantitative MRI; MPRAGE; Voxel-based morphometry; Gray-matter volume; Cortical thickness; In vivo histology; T1 mapping; T1-weighted images
 Abstract: The high gray-white matter contrast and spatial resolution provided by T1-weighted magnetic resonance imaging (MRI) has made it a widely used imaging protocol for computational anatomy studies of the brain. While the image intensity in T1-weighted images is predominantly driven by T1, other MRI parameters affect the image contrast, and hence brain morphological measures derived from the data. Because MRI parameters are correlates of different histological properties of brain tissue, this mixed contribution hampers the neurobiological interpretation of morphometry findings, an issue which remains largely ignored in the community. We acquired quantitative maps of the MRI parameters that determine signal intensities in T1-weighted images (R1 (=1/T1), R2*, and PD) in a large cohort of healthy subjects (n = 120, aged 18–87 years). Synthetic T1-weighted images were calculated from these quantitative maps and used to extract morphometry features—gray matter volume and cortical thickness. We observed significant variations in morphometry measures obtained from synthetic images derived from different subsets of MRI parameters. We also detected a modulation of these variations by age. Our findings highlight the impact of microstructural properties of brain tissue—myelination, iron, and water content—on automated measures of brain morphology and show that microstructural tissue changes might lead to the detection of spurious morphological changes in computational anatomy studies. They motivate a review of previous morphological results obtained from standard anatomical MRI images and highlight the value of quantitative MRI data for the inference of microscopic tissue changes in the healthy and diseased brain.

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Language(s): eng - English
 Dates: 2016-01-182015-08-192016-01-262016-02-152016-05
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Method: Peer
 Identifiers: DOI: 10.1002/hbm.23137
PMID: 26876452
PMC: PMC4855623
Other: Epub 2016
 Degree: -

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Title: Human Brain Mapping
Source Genre: Journal
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Publ. Info: New York : Wiley-Liss
Pages: - Volume / Issue: 37 (5) Sequence Number: - Start / End Page: 1801 - 1815 Identifier: ISSN: 1065-9471
CoNE: https://pure.mpg.de/cone/journals/resource/954925601686