Phase stabilization with motion compensated diffusion weighted imaging.

Purpose: Diffusion encoding gradient waveforms can impart intra-voxel and inter-voxel dephasing owing to bulk motion, limiting achievable signal-to-noise and complicating multishot acquisitions. In this study, we characterize improvements in phase consistency via gradient moment nulling of diffusion encoding waveforms.

Methods: Healthy volunteers received neuro ( ) and cardiac ( ) MRI. Three gradient moment nulling levels were evaluated: compensation for position ( ), position + velocity ( ), and position + velocity + acceleration ( ). Three experiments were completed: (Exp-1) Fixed Trigger Delay Neuro DWI; (Exp-2) Mixed Trigger Delay Neuro DWI; and (Exp-3) Fixed Trigger Delay Cardiac DWI. Significant differences ( ) of the temporal phase SD between repeated acquisitions and the spatial phase gradient across a given image were assessed.

Results: moment nulling was a reference for all measures. In Exp-1, temporal phase SD for diffusion encoding was significantly reduced with (35% of t-tests) and (68% of t-tests). The spatial phase gradient was reduced in 23% of t-tests for and 2% of cases for . In Exp-2, temporal phase SD significantly decreased with gradient moment nulling only for (83% of t-tests), but spatial phase gradient significantly decreased with only (50% of t-tests). In Exp-3, gradient moment nulling significantly reduced temporal phase SD and spatial phase gradients (100% of t-tests), resulting in less signal attenuation and more accurate ADCs.

Conclusion: We characterized gradient moment nulling phase consistency for DWI. Using M for neuroimaging and M + M for cardiac imaging minimized temporal phase SDs and spatial phase gradients.