Literature DB >> 23036448

Toward in vivo histology: a comparison of quantitative susceptibility mapping (QSM) with magnitude-, phase-, and R2*-imaging at ultra-high magnetic field strength.

Andreas Deistung1, Andreas Schäfer, Ferdinand Schweser, Uta Biedermann, Robert Turner, Jürgen R Reichenbach.   

Abstract

Quantitative magnetic susceptibility mapping (QSM) has recently been introduced to provide a novel quantitative and local MRI contrast. However, the anatomical contrast represented by in vivo susceptibility maps has not yet been compared systematically and comprehensively with gradient (recalled) echo (GRE) magnitude, frequency, and R(2)(*) images. Therefore, this study compares high-resolution quantitative susceptibility maps with conventional GRE imaging approaches (magnitude, frequency, R(2)(*)) in healthy individuals at 7 T with respect to anatomic tissue contrast. Volumes-of-interest were analyzed in deep and cortical gray matter (GM) as well as in white matter (WM) on R(2)(*) and susceptibility maps. High-resolution magnetic susceptibility maps of the human brain exhibited superb contrast that allowed the identification of substructures of the thalamus, midbrain and basal ganglia, as well as of the cerebral cortex. These were consistent with histology but not generally visible on magnitude, frequency or R(2)(*)-maps. Common target structures for deep brain stimulation, including substantia nigra pars reticulata, ventral intermediate nucleus, subthalamic nucleus, and the substructure of the internal globus pallidus, were clearly distinguishable from surrounding tissue on magnetic susceptibility maps. The laminar substructure of the cortical GM differed depending on the anatomical region, i.e., a cortical layer with increased magnetic susceptibility, corresponding to the Stria of Gennari, was found in the GM of the primary visual cortex, V1, whereas a layer with reduced magnetic susceptibility was observed in the GM of the temporal cortex. Both magnetic susceptibility and R(2)(*) values differed substantially in cortical GM depending on the anatomic regions. Regression analysis between magnetic susceptibility and R(2)(*) values of WM and GM structures suggested that variations in myelin content cause the overall contrast between gray and white matter on susceptibility maps and that both R(2)(*) and susceptibility values provide linear measures for iron content in GM. In conclusion, quantitative magnetic susceptibility mapping provides a non-invasive and spatially specific contrast that opens the door to the assessment of diseases characterized by variation in iron and/or myelin concentrations. Its ability to reflect anatomy of deep GM structures with superb delineation may be useful for neurosurgical applications.
Copyright © 2012 Elsevier Inc. All rights reserved.

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Year:  2012        PMID: 23036448     DOI: 10.1016/j.neuroimage.2012.09.055

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


  141 in total

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Authors:  Michael Iv; Peyman Samghabadi; Samantha Holdsworth; Andrew Gentles; Paymon Rezaii; Griffith Harsh; Gordon Li; Reena Thomas; Michael Moseley; Heike E Daldrup-Link; Hannes Vogel; Max Wintermark; Samuel Cheshier; Kristen W Yeom
Journal:  Radiology       Date:  2018-11-06       Impact factor: 11.105

2.  Rapid multi-orientation quantitative susceptibility mapping.

Authors:  Berkin Bilgic; Luke Xie; Russell Dibb; Christian Langkammer; Aysegul Mutluay; Huihui Ye; Jonathan R Polimeni; Jean Augustinack; Chunlei Liu; Lawrence L Wald; Kawin Setsompop
Journal:  Neuroimage       Date:  2015-08-12       Impact factor: 6.556

3.  Quantitative Susceptibility Mapping Suggests Altered Brain Iron in Premanifest Huntington Disease.

Authors:  J M G van Bergen; J Hua; P G Unschuld; I A L Lim; C K Jones; R L Margolis; C A Ross; P C M van Zijl; X Li
Journal:  AJNR Am J Neuroradiol       Date:  2015-12-17       Impact factor: 3.825

4.  Methods for the computation of templates from quantitative magnetic susceptibility maps (QSM): Toward improved atlas- and voxel-based analyses (VBA).

Authors:  Jannis Hanspach; Michael G Dwyer; Niels P Bergsland; Xiang Feng; Jesper Hagemeier; Nicola Bertolino; Paul Polak; Jürgen R Reichenbach; Robert Zivadinov; Ferdinand Schweser
Journal:  J Magn Reson Imaging       Date:  2017-03-06       Impact factor: 4.813

5.  Potential usefulness of signal intensity of cerebral gyri on quantitative susceptibility mapping for discriminating corticobasal degeneration from progressive supranuclear palsy and Parkinson's disease.

Authors:  Mari Miyata; Shingo Kakeda; Yasuko Toyoshima; Satoru Ide; Kazumasa Okada; Hiroaki Adachi; Yi Wang; Yukunori Korogi
Journal:  Neuroradiology       Date:  2019-07-02       Impact factor: 2.804

6.  Cortical fibers orientation mapping using in-vivo whole brain 7 T diffusion MRI.

Authors:  Omer F Gulban; Federico De Martino; An T Vu; Essa Yacoub; Kamil Uğurbil; Christophe Lenglet
Journal:  Neuroimage       Date:  2018-05-10       Impact factor: 6.556

7.  Simultaneous quantitative susceptibility mapping and Flutemetamol-PET suggests local correlation of iron and β-amyloid as an indicator of cognitive performance at high age.

Authors:  J M G van Bergen; X Li; F C Quevenco; A F Gietl; V Treyer; R Meyer; A Buck; P A Kaufmann; R M Nitsch; P C M van Zijl; C Hock; P G Unschuld
Journal:  Neuroimage       Date:  2018-03-13       Impact factor: 6.556

8.  Altered brain iron content and deposition rate in Huntington's disease as indicated by quantitative susceptibility MRI.

Authors:  Lin Chen; Jun Hua; Christopher A Ross; Shuhui Cai; Peter C M van Zijl; Xu Li
Journal:  J Neurosci Res       Date:  2018-11-29       Impact factor: 4.164

9.  Dentate nucleus iron deposition is a potential biomarker for tremor-dominant Parkinson's disease.

Authors:  Naying He; Pei Huang; Huawei Ling; Jason Langley; Chunlei Liu; Bei Ding; Juan Huang; Hongmin Xu; Yong Zhang; Zhongping Zhang; Xiaoping Hu; Shengdi Chen; Fuhua Yan
Journal:  NMR Biomed       Date:  2016-05-18       Impact factor: 4.044

Review 10.  Magnetic susceptibility anisotropy outside the central nervous system.

Authors:  Russell Dibb; Luke Xie; Hongjiang Wei; Chunlei Liu
Journal:  NMR Biomed       Date:  2016-05-16       Impact factor: 4.044

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