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Spatial encoding in MR-systems is subject to gradient non-linearity. If ignored or inadequately calibrated during system install, non-linear gradient fields manifest as spatial distortions impacting image quality, diminish accuracy for applications requiring MR guided intervention and introduce systematic errors in quantitative imaging such as diffusion MRI. High-performance, high-efficiency gradient systems, such as MAGNUS, require accurate calibration for imaging precision. In this study, a fiducial phantom was utilized to characterize and correct for residual distortions after standard gradient calibrations. Results highlight that distortion due to gradient non-linearity can be successfully reduced by phantom-based calibration for improved accuracy inline with QC metrics.
Abad et al. (Wed,) studied this question.