TY - JOUR
T1 - Automated gradient-based electrical properties tomography in the human brain using 7 Tesla MRI
AU - Wang, Yicun
AU - Van de Moortele, Pierre Francois
AU - He, Bin
N1 - Publisher Copyright:
© 2019 Elsevier Inc.
PY - 2019/11
Y1 - 2019/11
N2 - Electrical properties of the brain tissues may yield useful biomarkers for neurological disorders and diseases, as well as contribute to safety assurance of ultra-high-field MRI. It has been reported that using B1 maps from a multi-channel RF coil, the spatial variation of the electrical properties can be robustly retrieved. The absolute electrical property values can then be obtained by spatial integration, given that an integration seed point is assigned. In this study, we propose to exploit automatically detected seed points based on tissue piece-wise homogeneity (Helmholtz equation) for spatial integration. Numerical simulations of a numerical brain model and experiments involving 12 healthy volunteers were performed to demonstrate its feasibility and robustness in various noisy conditions and head positions. For in vivo imaging, we consistently observed higher conductivity and permittivity values in the white and gray matter compared to tabulated ex vivo probe measurement results found in the literature, a discrepancy that may be attributed to ex vivo experimental constraints. Our results suggest that the proposed technique produces consistent brain electrical properties in vivo that may contribute to improving diagnostic and therapeutic decisions.
AB - Electrical properties of the brain tissues may yield useful biomarkers for neurological disorders and diseases, as well as contribute to safety assurance of ultra-high-field MRI. It has been reported that using B1 maps from a multi-channel RF coil, the spatial variation of the electrical properties can be robustly retrieved. The absolute electrical property values can then be obtained by spatial integration, given that an integration seed point is assigned. In this study, we propose to exploit automatically detected seed points based on tissue piece-wise homogeneity (Helmholtz equation) for spatial integration. Numerical simulations of a numerical brain model and experiments involving 12 healthy volunteers were performed to demonstrate its feasibility and robustness in various noisy conditions and head positions. For in vivo imaging, we consistently observed higher conductivity and permittivity values in the white and gray matter compared to tabulated ex vivo probe measurement results found in the literature, a discrepancy that may be attributed to ex vivo experimental constraints. Our results suggest that the proposed technique produces consistent brain electrical properties in vivo that may contribute to improving diagnostic and therapeutic decisions.
KW - 7 T MRI
KW - B mapping
KW - Electrical properties
KW - Human brain
KW - Magnetic resonance based electrical properties tomography
KW - Quantitative imaging
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U2 - 10.1016/j.mri.2019.08.003
DO - 10.1016/j.mri.2019.08.003
M3 - Article
C2 - 31425805
AN - SCOPUS:85071396351
SN - 0730-725X
VL - 63
SP - 258
EP - 266
JO - Magnetic Resonance Imaging
JF - Magnetic Resonance Imaging
ER -