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

被引:23
作者
Katoch, Nitish [1 ]
Choi, Bup Kyung [2 ]
Sajib, Saurav Z. K. [3 ]
Lee, EunAh [3 ]
Kim, Hyung Joong [3 ]
Kwon, Oh In [4 ]
Woo, Eung Je [3 ]
机构
[1] Kyung Hee Univ, Grad Sch, Dept Biomed Engn, Yongin 17104, South Korea
[2] Kyung Hee Univ, Grad Sch, Dept Med Engn, Seoul 02447, South Korea
[3] Kyung Hee Univ, Dept Biomed Engn, Seoul 02447, South Korea
[4] Konkuk Univ, Dept Math, Seoul 05029, South Korea
基金
新加坡国家研究基金会;
关键词
Conductivity tensor imaging (CTI); anisotropy; diffusion weighted imaging; magnetic resonance imaging; ELECTRICAL-CONDUCTIVITY;
D O I
10.1109/TMI.2018.2884440
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
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.
引用
收藏
页码:1569 / 1577
页数:9
相关论文
共 25 条
[11]   Determination of Electric Conductivity and Local SAR Via B1 Mapping [J].
Katscher, Ulrich ;
Voigt, Tobias ;
Findeklee, Christian ;
Vernickel, Peter ;
Nehrke, Kay ;
Doessel, Olaf .
IEEE TRANSACTIONS ON MEDICAL IMAGING, 2009, 28 (09) :1365-1374
[12]   Looking into the functional architecture of the brain with diffusion MRI [J].
Le Bihan, D .
NATURE REVIEWS NEUROSCIENCE, 2003, 4 (06) :469-480
[13]   Multiplicative intrinsic component optimization (MICO) for MRI bias field estimation and tissue segmentation [J].
Li, Chunming ;
Gore, John C. ;
Davatzikos, Christos .
MAGNETIC RESONANCE IMAGING, 2014, 32 (07) :913-923
[14]   Rapid preparation of giant unilamellar vesicles [J].
Moscho, A ;
Orwar, O ;
Chiu, DT ;
Modi, BP ;
Zare, RN .
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 1996, 93 (21) :11443-11447
[15]   Electrodeless conductivity tensor imaging (CTI) using MRI: basic theory and animal experiments [J].
Sajib S.Z.K. ;
Kwon O.I. ;
Kim H.J. ;
Woo E.J. .
Biomedical Engineering Letters, 2018, 8 (3) :273-282
[16]   Extracellular Total Electrolyte Concentration Imaging for Electrical Brain Stimulation (EBS) [J].
Sajib, Saurav Z. K. ;
Lee, Mun Bae ;
Kim, Hyung Joong ;
Woo, Eung Je ;
Kwon, Oh In .
SCIENTIFIC REPORTS, 2018, 8
[17]   Software Toolbox for Low-Frequency Conductivity and Current Density Imaging Using MRI [J].
Sajib, Saurav Z. K. ;
Katoch, Nitish ;
Kim, Hyung Joong ;
Kwon, Oh In ;
Woo, Eung Je .
IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 2017, 64 (11) :2505-2514
[18]   Time-dependent diffusion coefficient as a probe of geometry [J].
Sen, PN .
CONCEPTS IN MAGNETIC RESONANCE PART A, 2004, 23A (01) :1-21
[19]   Electrical Tissue Property Imaging at Low Frequency Using MREIT [J].
Seo, Jin Keun ;
Woo, Eung Je .
IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 2014, 61 (05) :1390-1399
[20]   Error Analysis of Nonconstant Admittivity for MR-Based Electric Property Imaging [J].
Seo, Jin Keun ;
Kim, Min-Oh ;
Lee, Joonsung ;
Choi, Narae ;
Woo, Eung Je ;
Kim, Hyung Joong ;
Kwon, Oh In ;
Kim, Dong-Hyun .
IEEE TRANSACTIONS ON MEDICAL IMAGING, 2012, 31 (02) :430-437