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Phantom-based gradient waveform measurements with compensated variable-prephasing: Description and application to EPI
Hannah Scholten1, Tobias Wech1,2, Istvan Homolya3
1Department of Diagnostic and Interventional Radiology, University Hospital Würzburg, Würzburg, Germany.
Magnetic Resonance in Medicine
|January 21, 2025
Summary
Compensated variable-prephasing (CVP) offers precise phantom-based gradient waveform measurements. This new method improves upon variable-prephasing (VP) for accurate gradient characterization in MRI.
Area of Science:
- Magnetic Resonance Imaging (MRI)
- Gradient Coil Engineering
- Signal Processing in MRI
Background:
- Accurate gradient waveform measurement is crucial for advanced MRI techniques.
- Existing methods like variable-prephasing (VP) have limitations due to uncompensated gradient effects.
- Precise gradient characterization is essential for trajectory corrections in fast imaging sequences.
Purpose of the Study:
- Introduce compensated variable-prephasing (CVP), an enhanced phantom-based method for gradient waveform measurement.
- To evaluate the performance of CVP against traditional VP and fully compensated variable-prephasing (FCVP).
- To assess the utility of measured gradient waveforms for trajectory corrections in echo-planar imaging (EPI).
Main Methods:
- Measurements of trapezoidal and EPI readout gradients using VP, CVP, and FCVP techniques.
- Comparison of measured waveforms with predictions derived from the gradient system transfer function.
- Application of measured and predicted EPI gradients for trajectory corrections in phantom imaging at 7T.
Main Results:
- VP measurements were affected by prephasing gradient oscillations, which CVP and FCVP successfully compensated.
- FCVP demonstrated vulnerability to sign asymmetry within the gradient system.
- Despite method variations, all three approaches yielded comparable high-quality EPI images.
Conclusions:
- Compensated variable-prephasing (CVP) provides a highly precise method for phantom-based gradient waveform measurements.
- This technique is valuable for trajectory corrections in non-Cartesian and single-shot MRI sequences.
- CVP emerged as the most reliable method for gradient measurements in the comparative experimental setup.

