Mapping gradient nonlinearity and miscalibration using diffusion-weighted MR images of a uniform isotropic phantom

Area of Science:

• Magnetic Resonance Imaging
• Biophysics
• Medical Physics

Background:

• Gradient nonlinearity and amplifier miscalibration in MRI scanners introduce errors in quantitative diffusion MRI (dMRI).
• Accurate magnetic field mapping is crucial for reliable dMRI data, especially for diffusion tensor imaging (DTI) and higher-order diffusion analysis.
• Existing methods may not sufficiently address these calibration issues, impacting data precision.

Purpose of the Study:

• To develop and validate a diffusion measurement technique for mapping the spatial dependence of MRI gradient coil magnetic fields.
• To accurately correct quantitative dMRI errors stemming from gradient nonlinearity and amplifier miscalibration.
• To enhance the precision of dMRI data for improved diagnostic and research applications.

Main Methods:

• Utilized diffusion-weighted images of an isotropic phantom to determine gradient coil field expansion coefficients.
• Employed a model fitting approach using regular solid harmonics to analyze the magnetic field.
• Computed corrected b-matrices and applied them to multi-shell DTI datasets with 32 directions per shell.

Main Results:

• Substantially reduced spatial inhomogeneity in computed mean diffusivities (MD) and fractional anisotropy (FA).
• Virtually eliminated artifactual directional bias in the tensor field caused by gradient nonlinearity.
• Accurately detected introduced gradient axis miscalibrations, demonstrating the method's sensitivity.

Conclusions:

• The presented method effectively detects and corrects gradient nonlinearity and gain miscalibration using a simple isotropic diffusion phantom.
• This correction improves the accuracy of dMRI measurements in various organs, benefiting DTI and advanced diffusion analyses.
• Enables precise calibration of MRI systems, fostering data consistency in multicenter research.