OBJECTIVE : To experimentally characterize the effectiveness of a gradient nonlinearity correction method in removing ADC bias for different motion-compensated diffusion encoding waveforms.
Methods: The diffusion encoding waveforms used were the standard monopolar Stejskal-Tanner pulsed gradient spin echo (pgse) waveform, the symmetric bipolar velocity-compensated waveform (sym-vc), the asymmetric bipolar velocity-compensated waveform (asym-vc) and the asymmetric bipolar partial velocity-compensated waveform (asym-pvc). The effectiveness of the gradient nonlinearity correction method using the spherical harmonic expansion of the gradient coil field was tested with the aforementioned waveforms in a phantom and in four healthy subjects.
Results: The gradient nonlinearity correction method reduced the ADC bias in the phantom experiments for all used waveforms. The range of the ADC values over a distance of ± 67.2 mm from isocenter reduced from 1.29 × 10-4 to 0.32 × 10-4 mm2/s for pgse, 1.04 × 10-4 to 0.22 × 10-4 mm2/s for sym-vc, 1.22 × 10-4 to 0.24 × 10-4 mm2/s for asym-vc and 1.07 × 10-4 to 0.11 × 10-4 mm2/s for asym-pvc. The in vivo results showed that ADC overestimation due to motion or bright vessels can be increased even further by the gradient nonlinearity correction.
Conclusion: The investigated gradient nonlinearity correction method can be used effectively with various motion-compensated diffusion encoding waveforms. In coronal liver DWI, ADC errors caused by motion and residual vessel signal can be increased even further by the gradient nonlinearity correction.
Keywords: ADC mapping; Diffusion-weighted imaging; Gradient nonlinearity; Liver imaging; Motion compensation.
© 2021. The Author(s).