Literature DB >> 11378888

BISTRO: an outer-volume suppression method that tolerates RF field inhomogeneity.

Y Luo1, R A de Graaf, L DelaBarre, A Tannús, M Garwood.   

Abstract

A technique is described for performing frequency-selective signal suppression with a high degree of tolerance to RF field inhomogeneity. The method is called B1-insensitive train to obliterate signal (BISTRO). BISTRO consists of multiple amplitude- and frequency-modulated (FM) pulses interleaved with spoiler gradients. BISTRO was developed for the purpose of accomplishing band-selective signal removal, as in water suppression and outer-volume suppression (OVS), in applications requiring the use of an inhomogeneous RF transmitter, such as a surface coil. In the present work, Bloch simulations were used to illustrate the principles and theoretical performance of BISTRO. Its performance for OVS was evaluated experimentally using MRI and spectroscopic imaging of phantoms and in vivo animal and human brain. By using FM pulses featuring offset-independent adiabaticity, BISTRO permitted high-quality, broadband suppression with one (or two) discrete borders demarcating the edge(s) of the suppression band. Simulations and experiments demonstrated the ability to operate BISTRO with reasonably attainable peak RF power levels and with average RF energy deposition similar to other multipulse OVS techniques. Copyright 2001 Wiley-Liss, Inc.

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Year:  2001        PMID: 11378888     DOI: 10.1002/mrm.1144

Source DB:  PubMed          Journal:  Magn Reson Med        ISSN: 0740-3194            Impact factor:   4.668


  36 in total

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8.  A semiadiabatic spectral-spatial spectroscopic imaging (SASSI) sequence for improved high-field MR spectroscopic imaging.

Authors:  Rebecca E Feldman; Priti Balchandani
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9.  Combined T2 -preparation and multidimensional outer volume suppression for coronary artery imaging with 3D cones trajectories.

Authors:  David Y Zeng; Corey A Baron; Mario O Malavé; Adam B Kerr; Phillip C Yang; Bob S Hu; Dwight G Nishimura
Journal:  Magn Reson Med       Date:  2019-11-05       Impact factor: 4.668

10.  Removal of nuisance signals from limited and sparse 1H MRSI data using a union-of-subspaces model.

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Journal:  Magn Reson Med       Date:  2015-03-11       Impact factor: 4.668

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