MR sequence design to account for nonideal gradient performance

MR序列设计需考虑非理想梯度性能

阅读:1

Abstract

PURPOSE: 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. Although convenient, this requires system specifications exposed to the end user to be substantially down-rated, as 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 precompensated gradient waveforms that (i) explicitly respect hardware constraints and (ii) improve imaging performance by correcting k-space samples directly. METHODS: 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. RESULTS: 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 artifacts from echo-planar imaging was observed, including an average reduction of 77% in ghost amplitude in phantoms. CONCLUSIONS: This work demonstrates numerical optimization of gradient waveforms, yielding substantially improved image quality when given a model for system imperfections. Although the method as implemented has limited flexibility, it could enable more efficient hardware use and may prove particularly important for maximizing performance of lower-cost systems.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。