Quantitative mapping of chemical compositions with MRI using compressed sensing

Area of Science:

• Magnetic Resonance Imaging
• Chemical Engineering
• Image Reconstruction

Background:

• Acquiring high-resolution 2D concentration maps using traditional magnetic resonance (MR) imaging is time-prohibitive.
• Compressed sensing (CS) offers a potential solution for accelerating MR data acquisition.

Purpose of the Study:

• To present and validate a compressed sensing (CS) magnetic resonance (MR) imaging method for rapid acquisition of 2D concentration maps.
• To demonstrate the method's ability to reconstruct quantitative concentration data from sub-sampled k-space data.

Main Methods:

• Utilized compressed sensing (CS) with spiral trajectories for sub-sampled k-space data acquisition.
• Reconstructed concentration maps from simulated and experimental data of binary mixtures (1,4-dioxane and cyclooctane).
• Employed L-curve approach or Bregman iterations for quantitative reconstruction, achieving high spatial resolution (344μm×344μm) within an 8-minute acquisition time.

Main Results:

• Successfully reconstructed quantitative 2D concentration maps with relative errors under 2mol-% without prior calibration.
• Achieved an 8-minute acquisition time, a substantial reduction compared to the 17 hours required by conventional chemical shift imaging at the same resolution.
• Identified that static magnetic field inhomogeneities can negatively impact reconstruction accuracy.

Conclusions:

• The developed CS-MR imaging method significantly accelerates the acquisition of high-resolution concentration maps.
• This technique provides a powerful tool for chemical engineering applications, enabling faster investigation of various phenomena.
• The method demonstrates high accuracy and quantitative capability, even with limited data and without calibration.