Literature DB >> 31016802

Application of radial GRAPPA techniques to single- and multislice dynamic speech MRI using a 16-channel neurovascular coil.

Matthieu Ruthven1, Andreia C Freitas2,3, Redha Boubertakh1,2, Marc E Miquel1,2.   

Abstract

PURPOSE: To investigate: (1) the feasibility of using through-time radial GeneRalized Autocalibrating Partially Parallel Acquisitions (rGRAPPA) and hybrid radial GRAPPA (h-rGRAPPA) in single- and multislice dynamic speech MRI; (2) whether single-slice dynamic speech MRI at a rate of 15 frames per second (fps) or higher and with adequate image quality can be achieved using these radial GRAPPA techniques.
METHODS: Seven healthy adult volunteers were imaged at 3T using a 16-channel neurovascular coil and 2 spoiled gradient echo sequences (radial trajectory, field of view = 192 × 192 mm2 , acquired pixel size = 2.4 × 2.4 mm2 ). One sequence imaged a single slice at 16.8 fps, the other imaged 2 interleaved slices at 7.8 fps per slice. Image sets were reconstructed using rGRAPPA and h-rGRAPPA, and their image quality was compared using the root mean square error, structural similarity index, and visual assessments.
RESULTS: Image quality deteriorated when fewer than 170 calibration frames were used in the rGRAPPA reconstruction. rGRAPPA image sets demonstrated: (1) in 97% of cases, a similar image quality to h-rGRAPPA image sets reconstructed using a k-space segment size of 4, (2) in 98% of cases, a better image quality than h-rGRAPPA image sets reconstructed using a k-space segment size of 32.
CONCLUSION: This study confirmed: (1) the feasibility of using rGRAPPA and h-rGRAPPA in single- and multislice dynamic speech MRI, (2) that single-slice speech imaging at a frame rate higher than 15 fps and with adequate image quality can be achieved using these radial GRAPPA techniques.
© 2019 International Society for Magnetic Resonance in Medicine.

Keywords:  dynamic MRI; multislice; radial GRAPPA; speech; velum

Mesh:

Year:  2019        PMID: 31016802     DOI: 10.1002/mrm.27779

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


  2 in total

1.  Improved real-time tagged MRI using REALTAG.

Authors:  Weiyi Chen; Nam Gyun Lee; Dani Byrd; Shrikanth Narayanan; Krishna S Nayak
Journal:  Magn Reson Med       Date:  2019-12-24       Impact factor: 4.668

Review 2.  Real-Time Magnetic Resonance Imaging.

Authors:  Krishna S Nayak; Yongwan Lim; Adrienne E Campbell-Washburn; Jennifer Steeden
Journal:  J Magn Reson Imaging       Date:  2020-12-09       Impact factor: 4.813

  2 in total

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