Literature DB >> 36002782

Development and practical evaluation of a saturation effect learning simulator for inflow magnetic resonance angiography.

Norishige Hatakeyama1,2, Shunichi Kobayashi3.   

Abstract

The quality of visualization in inflow magnetic resonance angiography (MRA) depends highly on the excitation state of the longitudinal magnetization obtained using specified imaging parameters. In addition, signal intensity changes controlled by the preparation pulse-such as inversion recovery (IR) and saturation recovery (SR)-can potentially be used as quantitative physiological values. Although having practitioners understand these relationships both qualitatively and quantitatively is important, handling clinical equipment in practical learning or experiments involves limited opportunities. The simulator corresponds to a three-dimensional spoiled gradient echo sequence and allows users to freely input multiple virtual excitation effects in space and time. The purpose of this study was to quantitatively evaluate the agreement between the measured MRAs obtained in flow phantom tests and virtual MRAs simulated under similar conditions. We imaged two vascular flow phantoms on a 3.0 T MR system using three-dimensional (3D) time-of-flight (TOF) MRA and 3D inversion recovery tissue signal suppression (IR-suppression) MRA protocols. We evaluated quantitative values for consistency between the measured and virtual MRAs images with matched spatial resolution. Then we assessed the coincidence by reformatting maximum-intensity projection images with 1 mm isotropic pixels, with it ranging from 89.6 to 92.0% and 89.1 to 92.9% for TOF MRA and IR-suppression MRA, respectively. These results may be useful as a reference index for the theoretical study of MRA images by practitioners, for complementary validation by phantom testing, or for the development of MRI-related simulators.
© 2022. The Author(s), under exclusive licence to Japanese Society of Radiological Technology and Japan Society of Medical Physics.

Entities:  

Keywords:  Learning simulator; Longitudinal magnetization control; Magnetic resonance angiography (MRA)

Year:  2022        PMID: 36002782     DOI: 10.1007/s12194-022-00671-5

Source DB:  PubMed          Journal:  Radiol Phys Technol        ISSN: 1865-0333


  4 in total

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Journal:  Acta Radiol       Date:  1997-03       Impact factor: 1.990

2.  Flow MRI simulation in complex 3D geometries: Application to the cerebral venous network.

Authors:  Alexandre Fortin; Stéphanie Salmon; Joseph Baruthio; Maya Delbany; Emmanuel Durand
Journal:  Magn Reson Med       Date:  2018-02-05       Impact factor: 4.668

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Authors:  H Tamura; I Yanagawa; T Hikichi; K Matsumoto; S Takahashi; K Sakamoto
Journal:  Tohoku J Exp Med       Date:  1995-04       Impact factor: 1.848

Review 4.  Myocardial arterial spin labeling.

Authors:  Frank Kober; Terrence Jao; Thomas Troalen; Krishna S Nayak
Journal:  J Cardiovasc Magn Reson       Date:  2016-04-12       Impact factor: 5.364

  4 in total

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