Noise analysis and MR pulse sequence optimization in MREIT using an injected current nonlinear encoding (ICNE) method.
Magnetic resonance current density imaging (MRCDI) and magnetic resonance electrical impedance tomography (MREIT) visualize an internal distribution of current density and/or conductivity by injecting current into an electrically conductive object such as the human body using an MRI scanner. MREIT measures the induced magnetic flux density which appears in the phase part of the acquired MR image data. Recently, the injected current nonlinear encoding (ICNE) method in MREIT extended the duration of the current injection until the end of a reading gradient to maximize the signal intensity of the magnetic flux density. In this paper, we investigate the signal-to-noise ratio (SNR) of the magnetic flux density measured by the ICNE method in the presence of a zero-mean Gaussian random noise in measured k-space MR data. Based on the analysis of the noise standard deviation s(B(z)) of the magnetic flux density, we determine an optimal combination between the current injection pulse width T(c) and data acquisition time T(s) which minimize the noise level of the measured magnetic flux density for a given echo time T(E). On one hand, theoretically, the proposed ICNE MR pulse sequence using the optimal data acquisition time T(s)* reduces the noise level of the measured magnetic flux density by about 42.3% compared with the optimal data acquisition time of the conventional MREIT pulse sequence. On the other hand, practically, the prolonged T(s)* may result in undesirable artifacts including blurring, chemical shift and phase error along the phase encoding direction. We observe that the noise level is a function of the data acquisition time T(s) and the rate of change in the noise level is slow near T(s)=T(s)*. Numerical phantom experiments show that a compromised T(s) between the ordinary data acquisition time and the optimal T(s)* reduces a relatively large amount of undesirable artifacts and almost maintains the optimized noise level of the measured magnetic flux density.
Kwon
Oh In
OI
Department of Mathematics, Konkuk University, Korea.
Lee
Byung Il
BI
Nam
Hyun Soo
HS
Park
Chunjae
C
D000465:Algorithms; D016880:Anisotropy; D016477:Artifacts; D004553:Electric Conductivity; D004566:Electrodes; D005246:Feedback; D007089:Image Enhancement / Q000379:methods; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008280:Magnetics; D017711:Nonlinear Dynamics; D016011:Normal Distribution; D010363:Pattern Recognition, Automated / Q000379:methods; D019047:Phantoms, Imaging; D012107:Research Design; D012680:Sensitivity and Specificity; D013997:Time Factors