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Computational and Mathematical Methods in Medicine
Volume 2013, Article ID 704829, 10 pages
Research Article

Numerical Simulations of MREIT Conductivity Imaging for Brain Tumor Detection

1Department of Biomedical Engineering, Impedance Imaging Research Center (IIRC), Kyung Hee University, Yongin, Republic of Korea
2Department of Biomedical Engineering, University of Florida, Gainesville, FL, USA
3Department of Mathematics, Konkuk University, Seoul, Republic of Korea

Received 21 December 2012; Revised 21 February 2013; Accepted 5 April 2013

Academic Editor: Ulrich Katscher

Copyright © 2013 Zi Jun Meng et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Magnetic resonance electrical impedance tomography (MREIT) is a new modality capable of imaging the electrical properties of human body using MRI phase information in conjunction with external current injection. Recent in vivo animal and human MREIT studies have revealed unique conductivity contrasts related to different physiological and pathological conditions of tissues or organs. When performing in vivo brain imaging, small imaging currents must be injected so as not to stimulate peripheral nerves in the skin, while delivery of imaging currents to the brain is relatively small due to the skull’s low conductivity. As a result, injected imaging currents may induce small phase signals and the overall low phase SNR in brain tissues. In this study, we present numerical simulation results of the use of head MREIT for brain tumor detection. We used a realistic three-dimensional head model to compute signal levels produced as a consequence of a predicted doubling of conductivity occurring within simulated tumorous brain tissues. We determined the feasibility of measuring these changes in a time acceptable to human subjects by adding realistic noise levels measured from a candidate 3 T system. We also reconstructed conductivity contrast images, showing that such conductivity differences can be both detected and imaged.