Ettore Flavio Meliadò1,2,3, Alessandro Sbrizzi1,2, Cornelis A T van den Berg2,4, Peter R Luijten1, Alexander J E Raaijmakers1,2,5. 1. Department of Radiology, University Medical Center Utrecht, Utrecht, the Netherlands. 2. Computational Imaging Group for MR diagnostics & therapy, Center for Image Sciences, University Medical Center Utrecht, Utrecht, the Netherlands. 3. Tesla Dynamic Coils BV, Zaltbommel, the Netherlands. 4. Department of Radiotherapy, Division of Imaging & Oncology, University Medical Center Utrecht, Utrecht, the Netherlands. 5. Biomedical Image Analysis, Department Biomedical Engineering, Eindhoven University of Technology, Eindhoven, the Netherlands.
Abstract
PURPOSE: Multi-transmit MRI systems are typically equipped with dedicated hardware to sample the reflected/lost power in the transmit channels. After extensive calibration, the amplitude and phase of the signal at the feed of each array element can be accurately determined. However, determining the phase is more difficult and monitoring errors can lead to a hazardous peak local specific absorption rate (pSAR10g ) underestimation. For this purpose, methods were published for online maximum potential pSAR10g estimation without relying on phase monitoring, but these methods produce considerable overestimation. We present a trigonometric maximization method to determine the actual worst-case pSAR10g without any overestimation. THEORY AND METHOD: The proposed method takes advantage of the sinusoidal relation between the SAR10g in each voxel and the phases of input signals, to return the maximum achievable SAR10g in a few iterations. The method is applied to determine the worst-case pSAR10g for three multi-transmit array configurations at 7T: (1) body array with eight fractionated dipoles; (2) head array with eight fractionated dipoles; (3) head array with eight rectangular loops. The obtained worst-case pSAR10g values are compared with the pSAR10g values determined with a commonly used method and with a more efficient method based on reference-phases. RESULTS: For each voxel, the maximum achievable SAR10g is determined in less than 0.1 ms. Compared to the reference-phases-based method, the proposed method reduces the mean overestimation of the actual pSAR10g up to 52%, while never underestimating the true pSAR10g . CONCLUSION: The proposed method can widely improve the performance of parallel transmission MRI systems without phase monitoring.
PURPOSE: Multi-transmit MRI systems are typically equipped with dedicated hardware to sample the reflected/lost power in the transmit channels. After extensive calibration, the amplitude and phase of the signal at the feed of each array element can be accurately determined. However, determining the phase is more difficult and monitoring errors can lead to a hazardous peak local specific absorption rate (pSAR10g ) underestimation. For this purpose, methods were published for online maximum potential pSAR10g estimation without relying on phase monitoring, but these methods produce considerable overestimation. We present a trigonometric maximization method to determine the actual worst-case pSAR10g without any overestimation. THEORY AND METHOD: The proposed method takes advantage of the sinusoidal relation between the SAR10g in each voxel and the phases of input signals, to return the maximum achievable SAR10g in a few iterations. The method is applied to determine the worst-case pSAR10g for three multi-transmit array configurations at 7T: (1) body array with eight fractionated dipoles; (2) head array with eight fractionated dipoles; (3) head array with eight rectangular loops. The obtained worst-case pSAR10g values are compared with the pSAR10g values determined with a commonly used method and with a more efficient method based on reference-phases. RESULTS: For each voxel, the maximum achievable SAR10g is determined in less than 0.1 ms. Compared to the reference-phases-based method, the proposed method reduces the mean overestimation of the actual pSAR10g up to 52%, while never underestimating the true pSAR10g . CONCLUSION: The proposed method can widely improve the performance of parallel transmission MRI systems without phase monitoring.
Authors: J T Vaughan; M Garwood; C M Collins; W Liu; L DelaBarre; G Adriany; P Andersen; H Merkle; R Goebel; M B Smith; K Ugurbil Journal: Magn Reson Med Date: 2001-07 Impact factor: 4.668
Authors: Ingmar Graesslin; Hanno Homann; Sven Biederer; Peter Börnert; Kay Nehrke; Peter Vernickel; Giel Mens; Paul Harvey; Ulrich Katscher Journal: Magn Reson Med Date: 2012-01-09 Impact factor: 4.668
Authors: Alessandro Sbrizzi; Hans Hoogduin; Jan J Lagendijk; Peter Luijten; Gerard L G Sleijpen; Cornelis A T van den Berg Journal: Magn Reson Med Date: 2011-11-29 Impact factor: 4.668
Authors: Ozlem Ipek; Alexander J Raaijmakers; Jan J Lagendijk; Peter R Luijten; Cornelis A T van den Berg Journal: Magn Reson Med Date: 2013-06-10 Impact factor: 4.668
Authors: Bart R Steensma; Mariska Luttje; Ingmar J Voogt; Dennis W J Klomp; Peter R Luijten; Cornelis A T van den Berg; Alexander J E Raaijmakers Journal: J Magn Reson Imaging Date: 2018-10-22 Impact factor: 4.813
Authors: Ettore Flavio Meliadò; Alessandro Sbrizzi; Cornelis A T van den Berg; Peter R Luijten; Alexander J E Raaijmakers Journal: Magn Reson Med Date: 2020-12-22 Impact factor: 4.668
Authors: Bart R Steensma; Ettore F Meliadò; Peter Luijten; Dennis W J Klomp; Cornelis A T van den Berg; Alexander J E Raaijmakers Journal: NMR Biomed Date: 2021-05-06 Impact factor: 4.044
Authors: Nikos Priovoulos; Thomas Roos; Özlem Ipek; Ettore F Meliado; Richard O Nkrumah; Dennis W J Klomp; Wietske van der Zwaag Journal: NMR Biomed Date: 2021-07-06 Impact factor: 4.044