MR sequence design to account for nonideal gradient performance
Article Swipe
Daniel J. West
,
Felix Glang
,
Jonathan Endres
,
David Leitão
,
Moritz Zaiß
,
Joseph V. Hajnal
,
Shaihan Malik
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1002/mrm.70093
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1002/mrm.70093
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.
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MR sequence design to account for nonideal gradient performanceWork title - Type
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2025Year of publication
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2025-09-22Full publication date if available
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Daniel J. West, Felix Glang, Jonathan Endres, David Leitão, Moritz Zaiß, Joseph V. Hajnal, Shaihan MalikList of authors in order
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https://doi.org/10.1002/mrm.70093Publisher landing page
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hybridOpen access status per OpenAlex
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