Optimization of multiply acquired magnetic flux density B(z) using ICNE-Multiecho train in MREIT.
The aim of magnetic resonance electrical impedance tomography (MREIT) is to visualize the electrical properties, conductivity or current density of an object by injection of current. Recently, the prolonged data acquisition time when using the injected current nonlinear encoding (ICNE) method has been advantageous for measurement of magnetic flux density data, Bz, for MREIT in the signal-to-noise ratio (SNR). However, the ICNE method results in undesirable side artifacts, such as blurring, chemical shift and phase artifacts, due to the long data acquisition under an inhomogeneous static field. In this paper, we apply the ICNE method to a gradient and spin echo (GRASE) multi-echo train pulse sequence in order to provide the multiple k-space lines during a single RF pulse period. We analyze the SNR of the measured multiple B(z) data using the proposed ICNE-Multiecho MR pulse sequence. By determining a weighting factor for B(z) data in each of the echoes, an optimized inversion formula for the magnetic flux density data is proposed for the ICNE-Multiecho MR sequence. Using the ICNE-Multiecho method, the quality of the measured magnetic flux density is considerably increased by the injection of a long current through the echo train length and by optimization of the voxel-by-voxel noise level of the B(z) value. Agarose-gel phantom experiments have demonstrated fewer artifacts and a better SNR using the ICNE-Multiecho method. Experimenting with the brain of an anesthetized dog, we collected valuable echoes by taking into account the noise level of each of the echoes and determined B(z) data by determining optimized weighting factors for the multiply acquired magnetic flux density data.
Nam
Hyun Soo
HS
Department of Mathematics, Konkuk University, Seoul, Korea.
Kwon
Oh In
OI
D000818:Animals; D001921:Brain; D004285:Dogs; D017097:Electric Impedance; D007091:Image Processing, Computer-Assisted; D008280:Magnetics; D019047:Phantoms, Imaging; D014054:Tomography / Q000379:methods*