Literature DB >> 28721539

[Computational neuroanatomy and microstructure imaging using magnetic resonance imaging].

S Mohammadi1,2,3, N Weiskopf4,5.   

Abstract

BACKGROUND: Current computational neuroanatomy focuses on morphological measurements of the brain using standard magnetic resonance imaging (MRI) techniques. In comparison quantitative MRI (qMRI) typically provides a better tissue contrast and also greatly improves the sensitivity and specificity with respect to the microstructural characteristics of tissue.
OBJECTIVE: Current methodological developments in qMRI are presented, which go beyond morphology because this provides standardized measurements of the microstructure of the brain. The concept of in-vivo histology is introduced, based on biophysical modelling of qMRI data (hMRI) for determination of quantitative histology-like markers of the microstructure.
RESULTS: The qMRI metrics can be used as direct biomarkers of the microstructural mechanisms driving observed morphological findings. The hMRI metrics utilize biophysical models of the MRI signal in order to determine 3‑dimensional maps of histology-like measurements in the white matter.
CONCLUSION: Non-invasive brain tissue characterization using qMRI or hMRI has significant implications for both scientific and clinical applications. Both approaches improve the comparability across sites and time points, facilitate multicenter and longitudinal studies as well as standardized diagnostics. The hMRI is expected to shed new light on the relationship between brain microstructure, function and behavior both in health and disease. In the future hMRI will play an indispensable role in the field of computational neuroanatomy.

Entities:  

Keywords:  In-vivo histology; Morphometry; Myelin; Quantitative magnetic resonance imaging; White matter

Mesh:

Year:  2017        PMID: 28721539     DOI: 10.1007/s00115-017-0373-4

Source DB:  PubMed          Journal:  Nervenarzt        ISSN: 0028-2804            Impact factor:   1.214


  66 in total

1.  Quantitative MR imaging of brain iron: a postmortem validation study.

Authors:  Christian Langkammer; Nikolaus Krebs; Walter Goessler; Eva Scheurer; Franz Ebner; Kathrin Yen; Franz Fazekas; Stefan Ropele
Journal:  Radiology       Date:  2010-09-15       Impact factor: 11.105

Review 2.  Magnetic resonance imaging at ultrahigh fields.

Authors:  Kamil Ugurbil
Journal:  IEEE Trans Biomed Eng       Date:  2014-03-25       Impact factor: 4.538

3.  Independent anatomical and functional measures of the V1/V2 boundary in human visual cortex.

Authors:  Holly Bridge; Stuart Clare; Mark Jenkinson; Peter Jezzard; Andrew J Parker; Paul M Matthews
Journal:  J Vis       Date:  2005-02-11       Impact factor: 2.240

4.  Diffusion-tensor imaging at 3 T: detection of white matter alterations in neurological patients on the basis of normal values.

Authors:  Michael Deppe; Thomas Duning; Siawoosh Mohammadi; Wolfram Schwindt; Harald Kugel; Stefan Knecht; E Bernd Ringelstein
Journal:  Invest Radiol       Date:  2007-06       Impact factor: 6.016

Review 5.  The current state-of-the-art of spinal cord imaging: applications.

Authors:  C A Wheeler-Kingshott; P W Stroman; J M Schwab; M Bacon; R Bosma; J Brooks; D W Cadotte; T Carlstedt; O Ciccarelli; J Cohen-Adad; A Curt; N Evangelou; M G Fehlings; M Filippi; B J Kelley; S Kollias; A Mackay; C A Porro; S Smith; S M Strittmatter; P Summers; A J Thompson; I Tracey
Journal:  Neuroimage       Date:  2013-07-14       Impact factor: 6.556

6.  Myelin water imaging in multiple sclerosis: quantitative correlations with histopathology.

Authors:  C Laule; E Leung; D K B Lis; A L Traboulsee; D W Paty; A L MacKay; G R W Moore
Journal:  Mult Scler       Date:  2006-12       Impact factor: 6.312

7.  Insights into brain microstructure from the T2 distribution.

Authors:  Alex MacKay; Cornelia Laule; Irene Vavasour; Thorarin Bjarnason; Shannon Kolind; Burkhard Mädler
Journal:  Magn Reson Imaging       Date:  2006-03-20       Impact factor: 2.546

8.  Mapping the human cortical surface by combining quantitative T(1) with retinotopy.

Authors:  Martin I Sereno; Antoine Lutti; Nikolaus Weiskopf; Frederic Dick
Journal:  Cereb Cortex       Date:  2012-07-23       Impact factor: 5.357

9.  A general linear relaxometry model of R1 using imaging data.

Authors:  Martina F Callaghan; Gunther Helms; Antoine Lutti; Siawoosh Mohammadi; Nikolaus Weiskopf
Journal:  Magn Reson Med       Date:  2014-04-03       Impact factor: 4.668

10.  Whole-Brain In-vivo Measurements of the Axonal G-Ratio in a Group of 37 Healthy Volunteers.

Authors:  Siawoosh Mohammadi; Daniel Carey; Fred Dick; Joern Diedrichsen; Martin I Sereno; Marco Reisert; Martina F Callaghan; Nikolaus Weiskopf
Journal:  Front Neurosci       Date:  2015-11-27       Impact factor: 4.677

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