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SINAPSE experts from around Scotland have developed ten online modules designed to explain medical imaging. They are freely available and are intended for non-specialists.


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Online Short Courses

Application of kt-BLAST acceleration to reduce cardiac MR imaging time in healthy and infarcted mice

Author(s): I. Marshall, M. A. Jansen, Y. Tao, G. D. Merrifield, G. A. Gray

Abstract:
OBJECT: We evaluated the use of kt-broad-use linear acquisition speed-up technique (kt-BLAST) acceleration of mouse cardiac imaging in order to reduce scan times, thereby minimising physiological variation and improving animal welfare. MATERIALS AND METHODS: Conventional cine cardiac MRI data acquired from healthy mice (n = 9) were subsampled to simulate kt-BLAST acceleration. Cardiological indices (left ventricular volume, ejection fraction and mass) were determined as a function of acceleration factor. kt-BLAST threefold undersampling was implemented on the scanner and applied to a second group of mice (n = 6 healthy plus 6 with myocardial infarct), being compared with standard cine imaging (3 signal averages) and cine imaging with one signal average. RESULTS: In the simulations, sufficient accuracy was achieved for undersampling factors up to three. Cardiological indices determined from the implemented kt-BLAST scanning showed no significant differences compared with the values determined from the standard sequence, and neither did indices derived from the cine scan with only one signal average despite its lower signal-to-noise ratio. Both techniques were applied successfully in the infarcted hearts. CONCLUSION: For cardiac imaging of mice, threefold undersampling of kt-space, or a similar reduction in the number of signal averages, are both feasible with subsequent reduction in imaging time.

Full version: Available here

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ISBN: 0968-5243 (Electronic)0968-5243 (Linking)
Publication Year: 2013
Periodical: MAGMA
Periodical Number:
Volume:
Pages:
Author Address: Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK, ian.marshall@ed.ac.uk.