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Correction of concomitant gradient artifacts in experimental microtesla MRI
Whittier R Myers1, Michael Mössle, John Clarke
1Department of Physics, University of California, Berkeley, CA 94720-7300, USA. wmyers@berkeley.edu
Abstract:
Magnetic resonance imaging (MRI) suffers from artifacts caused by concomitant gradients when the product of the magnetic field gradient and the dimension of the sample becomes comparable to the static magnetic field. To investigate and correct for these artifacts at very low magnetic fields, we have acquired MR images of a 165-mm phantom in a 66-microT field using gradients up to 350 microT/m. We prepolarize the protons in a field of about 100 mT, apply a spin-echo pulse sequence, and detect the precessing spins using a superconducting gradiometer coupled to a superconducting quantum interference device (SQUID). Distortion and blurring are readily apparent at the edges of the images; by comparing the experimental images to computer simulations, we show that concomitant gradients cause these artifacts. We develop a non-perturbative, post-acquisition phase correction algorithm that eliminates the effects of concomitant gradients in both the simulated and the experimental images. This algorithm assumes that the switching time of the phase-encoding gradient is long compared to the spin precession period. In a second technique, we demonstrate that raising the precession field during phase encoding can also eliminate blurring caused by concomitant phase-encoding gradients; this technique enables one to correct concomitant gradient artifacts even when the detector has a restricted bandwidth that sets an upper limit on the precession frequency. In particular, the combination of phase correction and precession field cycling should allow one to add MRI capabilities to existing 300-channel SQUID systems used to detect neuronal currents in the brain because frequency encoding could be performed within the 1-2 kHz bandwidth of the readout system.
Insights
Magnetic resonance imaging (MRI) artifacts at low fields are caused by concomitant gradients. New phase correction and precession field cycling methods effectively eliminate these distortions, improving image quality.
Area of Science:
- Physics
- Biophysics
- Medical Imaging
Background:
- Magnetic resonance imaging (MRI) is susceptible to artifacts from concomitant magnetic field gradients, particularly at very low static magnetic fields.
- These artifacts, including distortion and blurring, arise when gradient strength relative to sample size approaches static field strength.
- Investigating and correcting these artifacts is crucial for advancing low-field MRI applications.
Purpose of the Study:
- To investigate and correct artifacts caused by concomitant gradients in very low magnetic field MRI.
- To develop and validate novel algorithms for artifact reduction in low-field MRI.
- To explore the potential of integrating corrected low-field MRI with existing magnetoencephalography systems.
Main Methods:
- Acquired MR images of a phantom in a 66-microT field using gradients up to 350 microT/m.
- Employed a spin-echo pulse sequence with proton prepolarization and detection via a SQUID-coupled gradiometer.
- Developed and applied a post-acquisition phase correction algorithm and a precession field cycling technique.
Main Results:
- Concomitant gradients were identified as the cause of distortion and blurring artifacts in experimental and simulated images.
- A non-perturbative phase correction algorithm successfully eliminated concomitant gradient effects.
- Precession field cycling during phase encoding also corrected blurring artifacts, even with detector bandwidth limitations.
Conclusions:
- Concomitant gradient artifacts in low-field MRI can be effectively corrected using post-acquisition phase correction or precession field cycling.
- These correction techniques enhance image quality and enable the integration of MRI capabilities with existing SQUID systems for neuroscience research.
- The findings pave the way for improved low-field MRI systems and novel neuroimaging approaches.
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