4.7 Article

Conductivity Tensor Imaging of In Vivo Human Brain and Experimental Validation Using Giant Vesicle Suspension

Journal

IEEE TRANSACTIONS ON MEDICAL IMAGING
Volume 38, Issue 7, Pages 1569-1577

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TMI.2018.2884440

Keywords

Conductivity tensor imaging (CTI); anisotropy; diffusion weighted imaging; magnetic resonance imaging

Funding

  1. National Research Foundation of Korea
  2. Korea Government through the Korea Institute of Radiological and Medical Sciences [2016R1A2B4014534, 2017R1A2A1A05001330, 2018R1D1A1B07046619, 50461-2018]
  3. National Research Foundation of Korea [2018R1D1A1B07046619, 2016R1A2B4014534] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)

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Human brain mapping of low-frequency electrical conductivity tensors can realize patient-specific volume conductor models for neuroimaging and electrical stimulation. We report experimental validation and in vivo human experiments of a new electrodeless conductivity tensor imaging (CTI) method. From CTI imaging of a giant vesicle suspension using a 9.4-T MRI scanner, the relative error in the reconstructed conductivity tensor image was found to be less than 1.7% compared with the measured value using an impedance analyzer. In vivo human brain imaging experiments of five subjects were followed using a 3-T clinical MRI scanner. With the spatial resolution of 1.87 mm, the white matter conductivity showed considerably more position dependency compared with the gray matter and cerebrospinal fluid (CSF). The anisotropy ratio of the white matter was in the range of 1.96-3.25 with a mean value of 2.43, whereas that of the gray matter was in the range of 1.12-1.19 with a mean value of 1.16. The three diagonal components of the reconstructed conductivity tensors were from 0.08 to 0.27 S/m for the white matter, from 0.20 to 0.30 S/m for the gray matter, and from 1.55 to 1.82 S/m for the CSF. The reconstructed conductivity tensor images exhibited significant inter-subject variabilities in terms of frequency and position dependencies. The high-frequency and low-frequency conductivity values can quantify the total and extracellular water contents, respectively, at every pixel. Their difference can quantify the intracellular water content at every pixel. The CTI method can separately quantify the contributions of ion concentrations and mobility to the conductivity tensor.

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