Literature DB >> 27037715

Quantitative analysis of the reconstruction errors of the currently popular algorithm of magnetic resonance electrical property tomography at the interfaces of adjacent tissues.

Song Duan1, Chao Xu1, Guanhua Deng1, Jiajia Wang1, Feng Liu2, Sherman Xuegang Xin1.   

Abstract

This work quantitatively analyzed the reconstruction errors (REs) of electrical property (EP) images using a currently popular algorithm of magnetic resonance electrical property tomography (MREPT), which occurred along the tissue interfaces. Transmitted magnetic fields B1+ were acquired at 3 T using a birdcage coil loaded with a phantom consisting of various adjacent tissues. Homogeneous Helmholtz was employed to calculate the EP maps by Laplacian computation of central differences. The maps of absolute REs (aREs) and relative REs (rREs) were calculated. The maximum and mean rREs, in addition to rRE distributions at the interfaces, were presented. Reconstructed EP maps showed various REs along different interface boundaries. Among all the investigated tissue interfaces, the kidney-fat interface presented the maximum mean rREs for both conductivity and relative permittivity. The minimum mean rRE of conductivity was observed at the spleen-muscle interface, and the minimum mean rRE of relative permittivity was detected along the lung-heart interface. The mean rREs ranged from 0.3986 to 36.11 for conductivity and 0.2218 to 11.96 for relative permittivity. Overall, this research indicates that different REs occur at various tissue boundaries, as shown by the currently popular algorithm of MREPT. Thus, REs should be considered when applying MREPT to reconstruct the EP distributions inside the human body.
Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Entities:  

Keywords:  electrical properties; errors analysis; magnetic resonance electrical property tomography; tissue interfaces

Mesh:

Year:  2016        PMID: 27037715     DOI: 10.1002/nbm.3522

Source DB:  PubMed          Journal:  NMR Biomed        ISSN: 0952-3480            Impact factor:   4.044


  8 in total

1.  Automated gradient-based electrical properties tomography in the human brain using 7 Tesla MRI.

Authors:  Yicun Wang; Pierre-Francois Van de Moortele; Bin He
Journal:  Magn Reson Imaging       Date:  2019-08-16       Impact factor: 2.546

2.  Mapping electrical properties heterogeneity of tumor using boundary informed electrical properties tomography (BIEPT) at 7T.

Authors:  Yicun Wang; Qi Shao; Pierre-Francois Van de Moortele; Emilian Racila; Jiaen Liu; John Bischof; Bin He
Journal:  Magn Reson Med       Date:  2018-09-19       Impact factor: 4.668

3.  Brain Tissue Conductivity Measurements with MR-Electrical Properties Tomography: An In Vivo Study.

Authors:  Stefano Mandija; Petar I Petrov; Jord J T Vink; Sebastian F W Neggers; Cornelis A T van den Berg
Journal:  Brain Topogr       Date:  2020-12-08       Impact factor: 3.020

4.  Magnetic resonance electrical property mapping at 21.1 T: a study of conductivity and permittivity in phantoms, ex vivo tissue and in vivo ischemia.

Authors:  Ghoncheh Amouzandeh; Frederic Mentink-Vigier; Shannon Helsper; F Andrew Bagdasarian; Jens T Rosenberg; Samuel C Grant
Journal:  Phys Med Biol       Date:  2020-02-28       Impact factor: 3.609

5.  In vivo imaging of electrical properties of an animal tumor model with an 8-channel transceiver array at 7 T using electrical properties tomography.

Authors:  Jiaen Liu; Qi Shao; Yicun Wang; Gregor Adriany; John Bischof; Pierre-Francois Van de Moortele; Bin He
Journal:  Magn Reson Med       Date:  2017-01-23       Impact factor: 4.668

6.  Electrical Properties Tomography Based on $B_{{1}}$ Maps in MRI: Principles, Applications, and Challenges.

Authors:  Jiaen Liu; Yicun Wang; Ulrich Katscher; Bin He
Journal:  IEEE Trans Biomed Eng       Date:  2017-08-21       Impact factor: 4.538

7.  Opening a new window on MR-based Electrical Properties Tomography with deep learning.

Authors:  Stefano Mandija; Ettore F Meliadò; Niek R F Huttinga; Peter R Luijten; Cornelis A T van den Berg
Journal:  Sci Rep       Date:  2019-06-20       Impact factor: 4.379

8.  Numerical Experiments on the Contrast Capability of Magnetic Resonance Electrical Property Tomography.

Authors:  Song Duan; Yurong Zhu; Feng Liu; Sherman Xuegang Xin
Journal:  Magn Reson Med Sci       Date:  2019-04-24       Impact factor: 2.471

  8 in total

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