SMASH imaging with an eight element multiplexed RF coil array

被引:0
作者
James A. Bankson
Mark A. Griswold
Steven M. Wright
Daniel K. Sodickson
机构
[1] Texas A&M University,Magnetic Resonance Systems Labs., Department of Electrical Engineering
[2] Beth Israel Deaconess Medical Center and Harvard Medical School,Department of Radiology
[3] Beth Israel Deaconess Medical Center and Harvard Medical School,Department of Medicine, Cardiovascular Division
关键词
MRI; SMASH; Parallel imaging; RF coils; Arrays;
D O I
10.1007/BF02601844
中图分类号
学科分类号
摘要
SMASH (SiMultaneous Acquisition of Spatial Harmonics) is a technique which can be used to acquire multiple lines ofk-space in parallel, by using spatial information from a radiofrequency coil array to perform some of the encoding normally produced by gradients. Using SMASH, imaging speed can be increased up to a maximum acceleration factor equal to the number of coil array elements. This work is a feasibility study which examines the use of SMASH with specialized coil array and data reception hardware to achieve previously unattainable accelerations. An eight element linear SMASH array was designed to operate in conjunction with a time domain multiplexing system to examine the effectiveness of SMASH imaging with as much as eightfold acceleration factors. Time domain multiplexing allowed the multiple independent array elements to be sampled through a standard single-channel receiver. SMASH-reconstructed images using this system were compared with reference images, and signal to noise ratio and reconstruction artifact power were measured as a function of acceleration factor. Results of the imaging experiments showed an almost constant SNR for SMASH acceleration factors of up to eight. Artifact power remained low within this range of acceleration factors. This study demonstrates that efficient SMASH imaging at high acceleration factors is feasible using appropriate hardware, and that time domain multiplexing is a convenient strategy to provide the multiple channels required for rapid imaging with large arrays.
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页码:93 / 104
页数:11
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