Magnetic resonance imaging (MRI) in the presence of metallic structures is very common in medical and non-medical fields. Metallic structures cause MRI image distortions by three mechanisms: (1) static field distortion through magnetic susceptibility mismatch, (2) eddy currents induced by switched magnetic field gradients and (3) radio frequency (RF) induced eddy currents. Single point ramped imaging with T1 enhancement (SPRITE) MRI measurements are largely immune to susceptibility and gradient induced eddy current artifacts. As a result, one can isolate the effects of metal objects on the RF field. The RF field affects both the excitation and detection of the magnetic resonance (MR) signal. This is challenging with conventional MRI methods, which cannot readily separate the three effects. RF induced MRI artifacts were investigated experimentally at 2.4 T by analyzing image distortions surrounding two geometrically identical metallic strips of aluminum and lead. The strips were immersed in agar gel doped with contrast agent and imaged employing the conical SPRITE sequence. B1 mapping with pure phase encode SPRITE was employed to measure the B1 field around the strips of metal. The strip geometry was chosen to mimic metal electrodes employed in electrochemistry studies. Simulations are employed to investigate the RF field induced eddy currents in the two metallic strips. The RF simulation results are in good agreement with experimental results. Experimental and simulation results show that the metal has a pronounced effect on the B1 distribution and B1 amplitude in the surrounding space. The electrical conductivity of the metal has a minimal effect.
The magnetic field gradient waveform monitor (MFGM) technique permits characterization of the temporal evolution of magnetic field gradients in magnetic resonance (MR) instruments (MRIs). Knowledge of the gradient waveform performance permits the development of further techniques, such as gradient waveform pre‐equalization, that correct and optimize gradient waveform distortions due to eddy currents induced during the application of switched magnetic fields and other system limitations. The accuracy of the MFGM technique is important since the overall uncertainty of the gradient waveform measurement will propagate into an uncertainty in corrected gradient waveforms impacting the precision of the resulting MR/MRI measurements. The accuracy of MFGM is investigated through a treatment of the noise present in a MRI. A noisy receiver model provides the basis for characterization of the noise and permits examination of the overall impact of noise on the phase accumulated in a pure‐phase encoded MR signal. Ultimately, a relationship between the signal‐to‐noise ratio of a measurement and the corresponding MFGM uncertainty is developed. The theoretical development is supported through simulation in conjunction with experimental results. The propagation of uncertainties to gradient waveform pre‐equalization is also discussed.
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