Literature DB >> 20615474

Whole-brain susceptibility mapping at high field: a comparison of multiple- and single-orientation methods.

Sam Wharton1, Richard Bowtell.   

Abstract

Optimisation and comparison of the performance of three different methods for calculating three-dimensional susceptibility maps of the whole brain from gradient-echo (phase and modulus) image data acquired at 7 T is described. The methods studied are a multiple-orientation method in which image data acquired with the head at several different angles to the main field are combined and two methods which use data acquired at a single orientation: the first of these is based on exclusion of some k-space data from the calculation (through thresholding of the dipolar field kernel), while the second incorporates a regularisation method that is based on using information from the modulus images. The methods were initially optimised via analysis of data from a phantom containing different compartments of known susceptibility. As part of this work, a novel high-pass filtering methodology was introduced to remove background fields from field maps based on phase data. The optimised methods were successfully applied to high-resolution (0.7 mm isotropic) whole-brain modulus and phase data acquired in vivo from five healthy male subjects, 25-30 years of age. The multiple-orientation method yielded high quality susceptibility maps, out-performing the single-orientation methods. Venous blood vessels as well as the substantia nigra and globus pallidus brain regions showed particularly high positive susceptibility offsets relative to surrounding tissue, consistent with high deoxyhemoglobin and non-heme iron content, respectively. To compare the performance of the different methods, regions of interest were drawn in deep grey matter structures and in cortical grey and white matter. The threshold-based approach was fast and simple to use, but underestimated susceptibility differences and showed significant artefacts due to noise amplification in difficult regions of k-space. The regularised single-orientation method yielded contrast dependent on the choice of spatial priors, but demonstrated the potential to yield susceptibility maps of a similar quality to those calculated using data acquired at multiple orientations to the field. Copyright 2010 Elsevier Inc. All rights reserved.

Entities:  

Mesh:

Substances:

Year:  2010        PMID: 20615474     DOI: 10.1016/j.neuroimage.2010.06.070

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


  83 in total

1.  Direct visualization of the subthalamic nucleus and its iron distribution using high-resolution susceptibility mapping.

Authors:  Andreas Schäfer; Birte U Forstmann; Jane Neumann; Sam Wharton; Alexander Mietke; Richard Bowtell; Robert Turner
Journal:  Hum Brain Mapp       Date:  2011-09-20       Impact factor: 5.038

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.  Streaking artifact reduction for quantitative susceptibility mapping of sources with large dynamic range.

Authors:  Hongjiang Wei; Russell Dibb; Yan Zhou; Yawen Sun; Jianrong Xu; Nian Wang; Chunlei Liu
Journal:  NMR Biomed       Date:  2015-08-27       Impact factor: 4.044

4.  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

5.  In vivo normative atlas of the hippocampal subfields using multi-echo susceptibility imaging at 7 Tesla.

Authors:  Maged Goubran; David A Rudko; Brendan Santyr; Joe Gati; Trevor Szekeres; Terry M Peters; Ali R Khan
Journal:  Hum Brain Mapp       Date:  2013-12-13       Impact factor: 5.038

6.  Whole brain susceptibility mapping using compressed sensing.

Authors:  Bing Wu; Wei Li; Arnaud Guidon; Chunlei Liu
Journal:  Magn Reson Med       Date:  2011-06-10       Impact factor: 4.668

7.  Detection of cerebral microbleeds with quantitative susceptibility mapping in the ArcAbeta mouse model of cerebral amyloidosis.

Authors:  Jan Klohs; Andreas Deistung; Ferdinand Schweser; Joanes Grandjean; Marco Dominietto; Conny Waschkies; Roger M Nitsch; Irene Knuesel; Jürgen R Reichenbach; Markus Rudin
Journal:  J Cereb Blood Flow Metab       Date:  2011-08-17       Impact factor: 6.200

8.  Quantitative susceptibility mapping of human brain reflects spatial variation in tissue composition.

Authors:  Wei Li; Bing Wu; Chunlei Liu
Journal:  Neuroimage       Date:  2011-01-09       Impact factor: 6.556

9.  Quantitative mapping of cerebral metabolic rate of oxygen (CMRO2 ) using quantitative susceptibility mapping (QSM).

Authors:  Jingwei Zhang; Tian Liu; Ajay Gupta; Pascal Spincemaille; Thanh D Nguyen; Yi Wang
Journal:  Magn Reson Med       Date:  2014-09-26       Impact factor: 4.668

10.  Micro-compartment specific T2* relaxation in the brain.

Authors:  Pascal Sati; Peter van Gelderen; Afonso C Silva; Daniel S Reich; Hellmut Merkle; Jacco A de Zwart; Jeff H Duyn
Journal:  Neuroimage       Date:  2013-03-22       Impact factor: 6.556

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.