Correction of gradient nonlinearity artifacts in prospective motion correction for 7T MRI

Area of Science:

• Medical Imaging
• Magnetic Resonance Imaging (MRI)
• Image Reconstruction

Background:

• Gradient nonlinearity in MRI induces geometric distortions, causing pixel shifts and affecting anatomical localization.
• Prospective motion correction (Mo-Co) is crucial for accurate MRI but can be affected by gradient field inconsistencies.

Purpose of the Study:

• To demonstrate the impact of gradient nonlinearity on Mo-Co.
• To develop and evaluate a method for correcting gradient nonlinearity artifacts in Mo-Co.

Main Methods:

• Extended prospective Mo-Co with gradient warp correction using spherical harmonic functions.
• Evaluated a combined approach with retrospective correction of coil sensitivity profiles (augmented SENSE reconstruction).
• Tested the method using simulation and experimental MRI data.

Main Results:

• Prospective Mo-Co without correction shows residual blurring, spatial distortion, and sensitivity mismatch artifacts.
• The proposed correction method significantly mitigated these artifacts, achieving high image quality.
• Relative image errors reduced from 25.7% to below 17.3% after 10 iterations.

Conclusions:

• Combined correction of gradient nonlinearity and sensitivity map variations markedly reduces residual motion artifacts in prospectively motion-corrected MRI data.
• The developed method enhances the robustness and accuracy of Mo-Co in the presence of gradient imperfections.