OPTIKS: Optimized Gradient Properties Through Timing in K-Space

TL;DR

OPTIKS is a novel method for designing gradient waveforms in MRI that optimizes timing to reduce peripheral nerve stimulation, mechanical resonance, and acoustic noise, while improving efficiency across various trajectories.

Contribution

The paper introduces OPTIKS, a customizable and open-source method for optimizing gradient waveform timing in MRI to enhance safety and performance.

Findings

Achieved up to 94% reduction in back-EMF.

Reduced acoustic noise by up to 9.22 dB.

Increased traversal speed by up to 11.4%.

Abstract

A customizable method (OPTIKS) for designing fast trajectory-constrained gradient waveforms with optimized time domain properties was developed. Given a specified multidimensional k-space trajectory, the method optimizes traversal speed (and therefore timing) with position along the trajectory. OPTIKS facilitates optimization of objectives dependent on the time domain gradient waveform and the arc-length domain k-space speed. OPTIKS is applied to design waveforms which limit peripheral nerve stimulation (PNS), minimize mechanical resonance excitation, and reduce acoustic noise. A variety of trajectory examples are presented including spirals, circular echo-planar-imaging, and rosettes. Design performance is evaluated based on duration, standardized PNS models, field measurements, gradient coil back-EMF measurements, and calibrated acoustic measurements. We show reductions in back-EMF of up to 94% and field oscillations up to 91.1%, acoustic noise decreases of up to 9.22 dB, and with efficient use of PNS models speed increases of up to 11.4%. The design method implementation is made available as an open source Python package through GitHub.