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  Advances in MRI-based computational neuroanatomy: From morphometry to in-vivo histology

Weiskopf, N., Mohammadi, S., Lutti, A., & Callaghan, M. F. (2015). Advances in MRI-based computational neuroanatomy: From morphometry to in-vivo histology. Current Opinion in Neurology, 28(4), 313-322. doi:10.1097/WCO.0000000000000222.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0027-D54F-2 Version Permalink: http://hdl.handle.net/21.11116/0000-0003-AB91-8
Genre: Journal Article

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 Creators:
Weiskopf, Nikolaus1, 2, Author              
Mohammadi, Siawoosh3, Author
Lutti, Antoine4, Author
Callaghan, Martina F.3, Author
Affiliations:
1Department Neurophysics (Weiskopf), MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_2205649              
2Wellcome Trust Centre for Neuroimaging, University College London, United Kingdom, ou_persistent22              
3Department of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Germany, ou_persistent22              
4Laboratoire de Recherche en Neuroimagerie (LREN), Centre hospitalier universitaire vaudois, Lausanne, Switzerland, ou_persistent22              

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Free keywords: In-vivo histology (hMRI); Quantitative MRI (qMRI); Tissue microstructure; Voxel-based morphometry (VBM)
 Abstract: PURPOSE OF REVIEW: Current computational neuroanatomy based on MRI focuses on morphological measures of the brain. We present recent methodological developments in quantitative MRI (qMRI) that provide standardized measures of the brain, which go beyond morphology. We show how biophysical modelling of qMRI data can provide quantitative histological measures of brain tissue, leading to the emerging field of in-vivo histology using MRI (hMRI). RECENT FINDINGS: qMRI has greatly improved the sensitivity and specificity of computational neuroanatomy studies. qMRI metrics can also be used as direct indicators of the mechanisms driving observed morphological findings. For hMRI, biophysical models of the MRI signal are being developed to directly access histological information such as cortical myelination, axonal diameters or axonal g-ratio in white matter. Emerging results indicate promising prospects for the combined study of brain microstructure and function. SUMMARY: Non-invasive brain tissue characterization using qMRI or hMRI has significant implications for both research and clinics. Both approaches improve comparability across sites and time points, facilitating multicentre/longitudinal studies and standardized diagnostics. hMRI is expected to shed new light on the relationship between brain microstructure, function and behaviour, both in health and disease, and become an indispensable addition to computational neuroanatomy.

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Language(s): eng - English
 Dates: 2015-07-162015-08-01
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1097/WCO.0000000000000222
PMID: 26132532
 Degree: -

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Project name : Non-invasive in vivo histology in health and disease using Magnetic Resonance Imaging (MRI) / HMRI
Grant ID : 616905
Funding program : Funding Programme 7 (FP7)
Funding organization : European Commission (EC)
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Funding program : -
Funding organization : Wings for Life, UCL SLMS Captial Equipment
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Funding organization : Medical Research Council (MRC)
Project name : Taking imaging into the therapeutic domain: Self-regulation of brain systems for mental disorders / BRAINTRAIN
Grant ID : 602186
Funding program : Funding Programme 7 (FP7)
Funding organization : European Commission (EC)
Project name : -
Grant ID : MO 2397/1-1
Funding program : -
Funding organization : Deutsche Forschungsgemeinschaft (DFG)
Project name : -
Grant ID : 0915/Z/10/Z
Funding program : -
Funding organization : Wellcome Trust
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Funding program : -
Funding organization : Roger de Spoelberg Foundation
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Funding program : -
Funding organization : Partridge Foundation

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Title: Current Opinion in Neurology
Source Genre: Journal
 Creator(s):
Affiliations:
Publ. Info: -
Pages: - Volume / Issue: 28 (4) Sequence Number: - Start / End Page: 313 - 322 Identifier: ISSN: 1535-3850
CoNE: https://pure.mpg.de/cone/journals/resource/991042727070048