Frequency-dependent conductivity contrast for tissue characterization using a dual-frequency range conductivity mapping magnetic resonance method

Donghyun Kim, Munish Chauhan, Min Oh Kim, Woo Chul Jeong, Hyung Joong Kim, Igor Serša, Oh In Kwon, Eung Je Woo

Research output: Contribution to journalArticle

6 Citations (Scopus)


Electrical conductivities of biological tissues show frequency-dependent behaviors, and these values at different frequencies may provide clinically useful diagnostic information. MR-based tissue property mapping techniques such as magnetic resonance electrical impedance tomography (MREIT) and magnetic resonance electrical property tomography (MREPT) are widely used and provide unique conductivity contrast information over different frequency ranges. Recently, a new method for data acquisition and reconstruction for low- and high-frequency conductivity images from a single MR scan was proposed. In this study, we applied this simultaneous dual-frequency range conductivity mapping MR method to evaluate its utility in a designed phantom and two in vivo animal disease models. Magnetic flux density and B1+ phase map for dual-frequency conductivity images were acquired using a modified spin-echo pulse sequence. Low-frequency conductivity was reconstructed from MREIT data by the projected current density method, while high-frequency conductivity was reconstructed from MREPT data by B1+ mapping. Two different conductivity phantoms comprising varying ion concentrations separated by insulating films with or without holes were used to study the contrast mechanism of the frequency-dependent conductivities related to ion concentration and mobility. Canine brain abscess and ischemia were used as in vivo models to evaluate the capability of the proposed method to identify new electrical properties-based contrast at two different frequencies. The simultaneous dual-frequency range conductivity mapping MR method provides unique contrast information related to the concentration and mobility of ions inside tissues. This method has potential to monitor dynamic changes of the state of disease.

Original languageEnglish
Article number6917025
Pages (from-to)507-513
Number of pages7
JournalIEEE Transactions on Medical Imaging
Issue number2
Publication statusPublished - 2015 Feb 1


All Science Journal Classification (ASJC) codes

  • Software
  • Radiological and Ultrasound Technology
  • Computer Science Applications
  • Electrical and Electronic Engineering

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