The temperature dependence of gradient system response characteristics.

Manuel Stich, Christiane Pfaff, Tobias Wech, Anne Slawig, Gudrun Ruyters, Andrew Dewdney, Ralf Ringler, Herbert Köstler
Author Information
  1. Manuel Stich: Department of Diagnostic and Interventional Radiology, University Hospital Würzburg, Würzburg, Germany. ORCID
  2. Christiane Pfaff: Department of Diagnostic and Interventional Radiology, University Hospital Würzburg, Würzburg, Germany.
  3. Tobias Wech: Department of Diagnostic and Interventional Radiology, University Hospital Würzburg, Würzburg, Germany. ORCID
  4. Anne Slawig: Department of Diagnostic and Interventional Radiology, University Hospital Würzburg, Würzburg, Germany. ORCID
  5. Gudrun Ruyters: Siemens Healthcare, Erlangen, Germany.
  6. Andrew Dewdney: Siemens Healthcare, Erlangen, Germany.
  7. Ralf Ringler: X-Ray & Molecular Imaging Lab, Technical University Amberg-Weiden, Weiden, Germany.
  8. Herbert Köstler: Department of Diagnostic and Interventional Radiology, University Hospital Würzburg, Würzburg, Germany. ORCID

Abstract

PURPOSE: The gradient system transfer function (GSTF) characterizes the frequency transfer behavior of a dynamic gradient system and can be used to correct non-Cartesian k-space trajectories. This study analyzes the impact of the gradient coil temperature of a 3T scanner on the GSTF.
METHODS: GSTF self- and B -cross-terms were acquired for a 3T Siemens scanner (Siemens Healthcare, Erlangen, Germany) using a phantom-based measurement technique. The GSTF terms were measured for various temperature states up to 45°C. The gradient coil temperatures were measured continuously utilizing 12 temperature sensors which are integrated by the vendor. Different modeling approaches were applied and compared.
RESULTS: The self-terms depend linearly on temperature, whereas the B -cross-term does not. Effects induced by thermal variation are negligible for the phase response. The self-terms are best represented by a linear model including the three gradient coil sensors that showed the maximum temperature dependence for the three axes. The use of time derivatives of the temperature did not lead to an improvement of the model. The B -cross-terms can be modeled by a convolution model which considers coil-specific heat transportation.
CONCLUSION: The temperature dependency of the GSTF was analyzed for a 3T Siemens scanner. The self- and B -cross-terms can be modeled using a linear and convolution modeling approach based on the three main temperature sensor elements.

Keywords

References

Wu YH, Chronik BA, Bowen C, Mechefske CK, Rutt BK. Gradient induced acoustic and magnetic field fluctuations in a 4 T wholebody MR imager. Magn Reson Med. 2000;44:532-536.
Clayton DB, Elliott MA, Leigh JS, Lenkinski RE. 1H Spectroscopy without solvent suppression: characterization of signal modulations at short echo times. J Magn Reson. 2001;153:203-209.
Foerster BU, Tomasi D, Caparelli EC. Magnetic field shift due to mechanical vibration in functional magnetic resonance imaging. Magn Reson Med. 2005;54:1261-1267.
Jehenson P, Westphal M, Schuff N. Analytical method for the compensation of eddy-current effects induced by pulsed magnetic field gradients in NMR systems. J Magn Reson. 1990;90:264-278.
Van Vaals JJ, Bergman AH. Optimization of eddy-current compensation. J Magn Reson. 1990;90:52-70.
Wysong RE, Madio DP, Lowe IJ. A novel eddy current compensation scheme for pulsed gradient systems. Magn Reson Med. 1994;31:572-575.
Vannesjo SJ, Graedel NN, Kasper L, et al. Image reconstruction using a gradient impulse response model for trajectory prediction. Magn Reson Med. 2016;76:45-58.
Campbell-Washburn AE, Xue H, Lederman RJ, Faranesh AZ, Hansen MS. Real-time distortion correction of spiral and echo planar images using the gradient system impulse response function. Magn Reson Med. 2016;75:2278-2285.
Stich M, Wech T, Slawig A, et al. Gradient waveform pre-emphasis based on the gradient system transfer function. Magn Reson Med. 2018;80:1521-1532.
Jehenson P, Westphal M, Schuff N. Analytical method for the compensation of eddy-current effects induced by pulsed magnetic field gradients in NMR systems. J Magn Reson. 1990;90:264-278.
Zur Y, Stokar S. An algorithm for eddy currents symmetrization and compensation. Magn Reson Med. 1996;35:252-260.
Bieri O, Markl M, Scheffler K. Analysis and compensation of eddy currents in balanced SSFP. Magn Reson Med. 2005;54:129-137.
Tan H, Meyer CH. Estimation of k-space trajectories in spiral MRI. Magn Reson Med. 2009;61:1396-1404.
Block K, Ücker M. Simple method for adaptive gradient-delay compensation in radial MRI. In Proceedings of the 19th Annual Meeting of ISMRM, Montréal, Canada, 2011. p. 2816.
Peters DC, Korosec FR, Grist TM, et al. Undersampled projection reconstruction applied to MR angiography. Magn Reson Med. 2000;45:91-101.
Wech T, Tran-Gia J, Bley TA, Köstler H. Using self-consistency for an iterative trajectory adjustment (SCITA). Magn Reson Med. 2015;73:1151-1157.
Duyn JH, Yang Y, Frank JA, van der Veen JW. Simple correction method for k-space trajectory deviations in MRI. J Magn Reson. 1998;132:150-153.
Zhang Y, Hetherington HP, Stokely EM, Mason GF, Twieg DB. A novel k-space trajectory measurement technique. Magn Reson Med. 1998;39:999-1004.
Vannesjo SJ, Haeberlin M, Kasper L, et al. Gradient system characterization by impulse response measurements with a dynamic field camera. Magn Reson Med. 2013;69:583-593.
Liu H, Matson GB. Accurate measurement of magnetic resonance imaging gradient characteristics. Materials (Basel). 2014;7:1-15.
Addy NO, Wu HH, Nishimura DG. Simple method for MR gradientsystem characterization and k-space trajectory estimation. Magn Reson Med. 2012;68:120-129.
Robison RK, Li Z, Wang D, et al. Correction of B0 eddy current effects in spiral MRI. Magn Reson Med. 2018;81:2501-2513.
Goora FG, Colpitts BG, Balcom BJ. Arbitrary magnetic field gradient waveform correction using an impulse response based pre-equalization technique. J Mag Reson. 2014;238:70-76.
Brodsky EK, Samsonov AA, Block WF. Characterizing and correcting gradient errors in non-cartesian imaging: Are gradient errors linear time-invariant (LTI)? Magn Reson Med. 2009;62:1466-1476.
Busch J, Vannesjo SJ, Barmet C, Pruessmann KP, Kozerke S. Analysis of temperature dependence of background phase errors in phase-contrast cardiovascular magnetic resonance. J Cardiovasc Magn Reson. 2014;16:97.
Stich M, Wech T, Slawig A, et al. B0-component determination of the gradient system transfer function using standard MR scanner hardware. In Proceedings of the Joint Annual Meeting of ISMRM-ESMRMB, Paris, France, 2018. p. 0942.
Brodsky EK, Klaers JL, Samsonov AA, et al. Rapid measurement and correction of phase errors from B0 eddy currents: impact on image quality for non-Cartesian imaging. Magn Reson Med. 2013;69:509-515.
Dietrich BE, Nussbaum J, Wilm BJ, et al. Thermal variation and temperature-based prediction of gradient response. In Proceedings of the 25th Annual Meeting of ISMRM, Honolulu, HI, 2017. p. 0079.
Nussbaum J, Wilm BJ, Dietrich BE, et al. Improved thermal modelling and prediction of gradient response using sensor placement guided by infrared photography. In Proceedings of the Joint Annual Meeting of ISMRM-ESMRMB, Paris, France, 2018. p. 4210.
Hermann KH, Krämer M, Reichenbach JR. Global and spatially varying B0 drifts due to gradient system heating. In Proceedings of the 21st Annual Meeting of the ISMRM, Melbourne, Australia, 2012. p. 2411.

MeSH Term

Germany
Linear Models
Magnetic Resonance Imaging
Phantoms, Imaging
Temperature

Word Cloud

Similar Articles

Cited By