Parallel MRI at microtesla fields.

Area of Science:

• Medical Imaging
• Biophysics
• Sensor Technology

Background:

• High-field MRI commonly uses parallel imaging with multiple receiver coils for better quality and faster scans.
• Ultra-low field MRI (ULF MRI) is an emerging technique using SQUID sensors for microtesla-range measurements.
• ULF MRI offers potential for novel imaging applications but requires optimization for performance.

Purpose of the Study:

• To systematically investigate parallel imaging techniques for ULF MRI for the first time.
• To evaluate the impact of multiple SQUID channels on image quality and acquisition speed in ULF MRI.
• To demonstrate accelerated imaging capabilities in ULF MRI using parallel imaging methods.

Main Methods:

• Utilized a seven-channel SQUID system for ULF MRI at a 46 µT measurement field with 40 mT pre-polarization.
• Acquired 3D images of a human hand and 2D images of a water phantom.
• Implemented 1D undersampling and 1D SENSE reconstruction for accelerated imaging studies.
• Analyzed noise propagation and developed a method for concomitant gradient artifact correction.

Main Results:

• Increased field of view and improved signal-to-noise ratio for hand images with seven channels.
• Demonstrated threefold acceleration in 2D phantom imaging compared to standard Fourier imaging.
• Identified the primary source of correlated noise in the ULF MRI system.
• Successfully corrected for concomitant gradient artifacts.

Conclusions:

• Parallel imaging is effective for ULF MRI, significantly enhancing performance.
• Increasing the number of SQUID channels substantially improves ULF MRI imaging capabilities.
• This work validates parallel imaging as a key technology for advancing SQUID-based ULF MRI systems.