To design and evaluate eddy current-nulled convex optimized diffusion encoding gradient waveforms for efficient diffusion tensor imaging that is free of eddy current-induced image distortions.The EN-CODE framework was used to generate diffusion-encoding waveforms that are eddy current-compensated. The EN-CODE DTI waveform was compared with the existing eddy current-nulled twice refocused spin echo sequence as well as monopolar and non-eddy current-compensated CODE in terms of echo time and image…
Read moreTo design and evaluate eddy current-nulled convex optimized diffusion encoding gradient waveforms for efficient diffusion tensor imaging that is free of eddy current-induced image distortions.The EN-CODE framework was used to generate diffusion-encoding waveforms that are eddy current-compensated. The EN-CODE DTI waveform was compared with the existing eddy current-nulled twice refocused spin echo sequence as well as monopolar and non-eddy current-compensated CODE in terms of echo time and image distortions. Comparisons were made in simulations, phantom experiments, and neuro imaging in 10 healthy volunteers.The EN-CODE sequence achieved eddy current compensation with a significantly shorter TE than TRSE and a slightly shorter TE than MONO. Intravoxel signal variance was lower in phantoms with EN-CODE than with MONO and not different from TRSE, indicating good robustness to eddy current-induced image distortions. Mean fractional anisotropy values in brain edges were also significantly lower with EN-CODE than with MONO ) and not different from TRSE.The EN-CODE sequence eliminated eddy current-induced image distortions in DTI with a TE comparable to MONO and substantially shorter than TRSE. Magn Reson Med, 2017. © 2017 International Society for Magnetic Resonance in Medicine.