MR sequence design to account for non-ideal gradient performance

Abstract

MRI systems are traditionally engineered to produce close to idealized performance, enabling a simplified pulse sequence design philosophy. An example of this is control of eddy currents produced by gradient fields; usually these are compensated by pre-emphasizing demanded waveforms. This process typically happens invisibly to the pulse sequence designer, allowing them to assume achieved gradient waveforms will be as desired. Whilst convenient, this requires system specifications exposed to the end-user to be substantially down-rated, since pre-emphasis adds an extra overhead to the waveforms. This strategy is undesirable for lower performance or resource-limited hardware. Instead, we propose an optimization-based method to design pre-compensated gradient waveforms that: (i) explicitly respect hardware constraints and (ii) improve imaging performance by correcting k-space samples directly. Gradient waveforms are numerically optimized by including a model for system imperfections. This is investigated in simulation using an exponential eddy current model, then experimentally using an empirical gradient system transfer function on a 7T MRI system. Our proposed method discovers solutions that produce negligible reconstruction errors while satisfying gradient system limits, even when classic pre-emphasis produces infeasible results. Substantial reduction in ghosting artefacts from EPI imaging was observed, including an average reduction of 77% in ghost amplitude in phantoms. This work demonstrates numerical optimization of gradient waveforms, yielding substantially improved image quality when given a model for system imperfections. While the method as implemented has limited flexibility, it could enable more efficient hardware usage, and may prove particularly important for maximizing performance of lower-cost systems.