Zhipeng Cao1,2, Xinqiang Yan1,3, William A Grissom4,5,6,7. 1. Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, Tennessee, USA. 2. Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, USA. 3. Department of Radiology, Vanderbilt University, Nashville, Tennessee, USA. 4. Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, Tennessee, USA. will.grissom@vanderbilt.edu. 5. Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, USA. will.grissom@vanderbilt.edu. 6. Department of Radiology, Vanderbilt University, Nashville, Tennessee, USA. will.grissom@vanderbilt.edu. 7. Department of Electrical Engineering, Vanderbilt University, Nashville, Tennessee, USA. will.grissom@vanderbilt.edu.
Abstract
PURPOSE: To design array-compressed parallel transmit radiofrequency (RF) pulses and compare them to pulses designed with existing transmit array compression strategies. THEORY AND METHODS: Array-compressed parallel RF pulse design is proposed as the joint optimization of a matrix of complex-valued compression weights that relate a full-channel physical array to a reduced-channel virtual array, along with a set of RF pulses for the virtual array. In this way, the physics of the RF pulse application determine the coil combination weights. Array-compressed pulse design algorithms are described for four parallel transmit applications: accelerated two-dimensional spiral excitation, multislice RF shimming, small-tip-angle kT -points excitation, and slice-selective spokes refocusing. Array-compressed designs are compared in simulations and an experiment to pulses designed using four existing array compression strategies. RESULTS: In all cases, array-compressed pulses achieved the lowest root-mean-square excitation error among the array compression approaches. Low errors were generally achieved without increasing root-mean-square RF amplitudes or maximum local 10-gram specific absorption rate. Leave-one-out multisubject shimming simulations demonstrated that array-compressed RF shimming can identify useful fixed coil combination weights that perform well across a population. CONCLUSION: Array-compressed pulse design jointly identifies the transmit coil array compression weights and RF pulses that perform best for a specific parallel excitation application. Magn Reson Med 76:1158-1169, 2016.
PURPOSE: To design array-compressed parallel transmit radiofrequency (RF) pulses and compare them to pulses designed with existing transmit array compression strategies. THEORY AND METHODS: Array-compressed parallel RF pulse design is proposed as the joint optimization of a matrix of complex-valued compression weights that relate a full-channel physical array to a reduced-channel virtual array, along with a set of RF pulses for the virtual array. In this way, the physics of the RF pulse application determine the coil combination weights. Array-compressed pulse design algorithms are described for four parallel transmit applications: accelerated two-dimensional spiral excitation, multislice RF shimming, small-tip-angle kT -points excitation, and slice-selective spokes refocusing. Array-compressed designs are compared in simulations and an experiment to pulses designed using four existing array compression strategies. RESULTS: In all cases, array-compressed pulses achieved the lowest root-mean-square excitation error among the array compression approaches. Low errors were generally achieved without increasing root-mean-square RF amplitudes or maximum local 10-gram specific absorption rate. Leave-one-out multisubject shimming simulations demonstrated that array-compressed RF shimming can identify useful fixed coil combination weights that perform well across a population. CONCLUSION: Array-compressed pulse design jointly identifies the transmit coil array compression weights and RF pulses that perform best for a specific parallel excitation application. Magn Reson Med 76:1158-1169, 2016.
Authors: William Grissom; Chun-yu Yip; Zhenghui Zhang; V Andrew Stenger; Jeffrey A Fessler; Douglas C Noll Journal: Magn Reson Med Date: 2006-09 Impact factor: 4.668
Authors: Zhenghui Zhang; Chun-Yu Yip; William Grissom; Douglas C Noll; Fernando E Boada; V Andrew Stenger Journal: Magn Reson Med Date: 2007-05 Impact factor: 4.668
Authors: William A Grissom; Mohammad-Mehdi Khalighi; Laura I Sacolick; Brian K Rutt; Mika W Vogel Journal: Magn Reson Med Date: 2012-03-05 Impact factor: 4.668