Efficient eddy current characterization using a 2D image‐based sampling scheme and a model‐based fitting approach

Magnetic Resonance in Medicine, vol. 85, pp. 2892–2903

Abstract

PURPOSE: To propose two innovations to existing eddy current characterization techniques, which include (1) an efficient spatio-temporal sampling scheme and (2) a model-based fitting of spherical harmonic eddy current components. THEORY AND METHODS: This work introduces a three-plane 2D image-based acquisition scheme to efficiently sample eddy current fields. Additionally, a model-based spherical harmonic decomposition is presented, which reduces fitting noise using a rank minimization to impose an exponential decay on the eddy current amplitude evolution. Both techniques are applied in combination and analyzed in simulations for their applicability in reconstructing suitable pre-emphasis parameters. In a proof-of-concept measurement, the routine is tested for its propriety to correctly quantify user-defined field dynamics. Furthermore, based on acquired precompensation and postcompensation eddy current data, the suitability of pre-emphasis parameters calculated based on the proposed technique is evaluated. RESULTS: Simulation results derived from 500 data sets demonstrate the applicability of the acquisition scheme for the spatio-temporal sampling of eddy current fields. Compared with a conventional data processing strategy, the proposed model-based approach yields pre-emphasis parameters that reduce the average maximum residual field offset within a 10-cm-diameter spherical volume from 3.17 Hz to 0.58 Hz. Experimental data prove the proposed routine to be suitable to measure and effectively compensate for eddy currents within 10 minutes of acquisition time. CONCLUSION: shimming applications.

Authors 4

1. Michael Schwerter Aachen

   RWTH Aachen University · Forschungszentrum Jülich

   Affiliation as printed

   Institute of Neuroscience and Medicine 4 INM‐4, Forschungszentrum Jülich Jülich Germany

   RWTH Aachen University Aachen Germany

2. Markus Zimmermann Aachen

   RWTH Aachen University · Forschungszentrum Jülich

   Affiliation as printed

   Institute of Neuroscience and Medicine 4 INM‐4, Forschungszentrum Jülich Jülich Germany

   RWTH Aachen University Aachen Germany

3. Jörg Felder

   Forschungszentrum Jülich

   Affiliation as printed

   Institute of Neuroscience and Medicine 4 INM‐4, Forschungszentrum Jülich Jülich Germany

4. Nadim Jon Shah corresponding Aachen Department of Neurology

   RWTH Aachen University · Forschungszentrum Jülich · Jülich Aachen Research Alliance

   Affiliation as printed

   Department of Neurology RWTH Aachen University Aachen Germany

   Institute of Neuroscience and Medicine 11 INM‐11, JARA, Forschungszentrum Jülich Jülich Germany

   Institute of Neuroscience and Medicine 4 INM‐4, Forschungszentrum Jülich Jülich Germany

   JARA–BRAIN–Translational Medicine Aachen Germany