Literature DB >> 29890327

The influence of brain iron and myelin on magnetic susceptibility and effective transverse relaxation - A biochemical and histological validation study.

Simon Hametner1, Verena Endmayr2, Andreas Deistung3, Pilar Palmrich2, Max Prihoda4, Evelin Haimburger4, Christian Menard5, Xiang Feng6, Thomas Haider7, Marianne Leisser2, Ulrike Köck2, Alexandra Kaider8, Romana Höftberger9, Simon Robinson10, Jürgen R Reichenbach6, Hans Lassmann2, Hannes Traxler11, Siegfried Trattnig12, Günther Grabner13.   

Abstract

Quantitative susceptibility mapping (QSM) and effective transverse relaxation rate (R2*) mapping are both highly sensitive to variations in brain iron content. Clinical Magnetic Resonance Imaging (MRI) studies report changes of susceptibilities and relaxation rates in various neurological diseases which are often equated with changes in regional brain iron content. However, these mentioned metrics lack specificity for iron, since they are also influenced by the presence of myelin. In this study, we assessed the extent to which QSM and R2* reflect iron concentration as well as histological iron and myelin intensities. Six unfixed human post-mortem brains were imaged in situ with a 7 T MRI scanner. After formalin fixation, the brains were sliced axially and punched. 671 tissue punches were subjected to ferrozine iron quantification. Subsequently, brain slices were embedded in paraffin, and histological double-hemispheric axial brain slices were stained for Luxol fast blue (myelin) and diaminobenzidine (DAB)-enhanced Turnbull blue (iron). 3331 regions of interest (ROIs) were drawn on the histological stainings to assess myelin and iron intensities, which were compared with MRI data in corresponding ROIs. QSM more closely reflected quantitative ferrozine iron values (r = 0.755 vs. 0.738), whereas R2* correlated better with iron staining intensities (r = 0.619 vs. 0.445). Myelin intensities correlated negatively with QSM (r = -0.352), indicating a diamagnetic effect of myelin on susceptibility. Myelin intensities were higher in the thalamus than in the basal ganglia. A significant relationship was nonetheless observed between quantitative iron values and QSM, confirming the applicability of the latter in this brain region for iron quantification.
Copyright © 2018 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Iron; Myelin; Quantitative susceptibility mapping; R2* mapping

Mesh:

Substances:

Year:  2018        PMID: 29890327     DOI: 10.1016/j.neuroimage.2018.06.007

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


  37 in total

1.  Targeting Iron Dyshomeostasis for Treatment of Neurodegenerative Disorders.

Authors:  Niels Bergsland; Eleonora Tavazzi; Ferdinand Schweser; Dejan Jakimovski; Jesper Hagemeier; Michael G Dwyer; Robert Zivadinov
Journal:  CNS Drugs       Date:  2019-11       Impact factor: 5.749

2.  Iron distribution in the lentiform nucleus: A post-mortem MRI and histology study.

Authors:  Amaury De Barros; Germain Arribarat; Jean Albert Lotterie; Gaelle Dominguez; Patrick Chaynes; Patrice Péran
Journal:  Brain Struct Funct       Date:  2021-01-02       Impact factor: 3.270

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Authors:  Laura E Jonkman; Boyd Kenkhuis; Jeroen J G Geurts; Wilma D J van de Berg
Journal:  Neurosci Bull       Date:  2019-02-21       Impact factor: 5.203

4.  The association of myelination in the internal capsule with iron deposition in the basal ganglia in macaques: a magnetic resonance imaging study.

Authors:  Run Pu; Zhe Wu; Wenwen Yu; Hongjian He; Zuofu Zhou; Zheng Wang; Jianhui Zhong
Journal:  Quant Imaging Med Surg       Date:  2020-07

Review 5.  Magnetic Resonance Imaging Studies of Neurodegenerative Disease: From Methods to Translational Research.

Authors:  Peiyu Huang; Minming Zhang
Journal:  Neurosci Bull       Date:  2022-06-30       Impact factor: 5.203

Review 6.  Positron emission tomography in multiple sclerosis - straight to the target.

Authors:  Benedetta Bodini; Matteo Tonietto; Laura Airas; Bruno Stankoff
Journal:  Nat Rev Neurol       Date:  2021-09-20       Impact factor: 42.937

7.  Volumetric imaging of myelin in vivo using 3D inversion recovery-prepared ultrashort echo time cones magnetic resonance imaging.

Authors:  Ya-Jun Ma; Adam C Searleman; Hyungseok Jang; Shu-Juan Fan; Jonathan Wong; Yanping Xue; Zhenyu Cai; Eric Y Chang; Jody Corey-Bloom; Jiang Du
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8.  [Correlation of cardiovascular risk factors with brain iron deposition: A magnetic resonance imaging study].

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9.  Quantitative magnetic resonance imaging towards clinical application in multiple sclerosis.

Authors:  Cristina Granziera; Jens Wuerfel; Frederik Barkhof; Massimiliano Calabrese; Nicola De Stefano; Christian Enzinger; Nikos Evangelou; Massimo Filippi; Jeroen J G Geurts; Daniel S Reich; Maria A Rocca; Stefan Ropele; Àlex Rovira; Pascal Sati; Ahmed T Toosy; Hugo Vrenken; Claudia A M Gandini Wheeler-Kingshott; Ludwig Kappos
Journal:  Brain       Date:  2021-06-22       Impact factor: 13.501

10.  Methods for quantitative susceptibility and R2* mapping in whole post-mortem brains at 7T applied to amyotrophic lateral sclerosis.

Authors:  Chaoyue Wang; Sean Foxley; Olaf Ansorge; Sarah Bangerter-Christensen; Mark Chiew; Anna Leonte; Ricarda Al Menke; Jeroen Mollink; Menuka Pallebage-Gamarallage; Martin R Turner; Karla L Miller; Benjamin C Tendler
Journal:  Neuroimage       Date:  2020-08-01       Impact factor: 6.556

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