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Optimal acquisition schemes for in vivo quantitative magnetization transfer MRI

Cercignani, M; Alexander, DC; (2006) Optimal acquisition schemes for in vivo quantitative magnetization transfer MRI. MAGN RESON MED , 56 (4) 803 - 810. 10.1002/mrm.21003. Green open access

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Abstract

This paper uses the theory of Cramer-Rao lower bounds [CRLB) to obtain optimal acquisition schemes for in vivo quantitative magnetization transfer (MT) imaging, although the method is generally applicable to any multiparametric MRI technique. Quantitative MT fits a two-pool model to data collected at different sampling points or settings of amplitude and offset frequency in the MT saturation pulses. Here we use simple objective functions based on the CRLB to optimize sampling strategies for multiple parameters simultaneously, and use simulated annealing to minimize these objective functions with respect to the sampling configuration. Experiments compare optimal schemes derived for quantitative MT in the human white matter (WM) at 1.5T with previously published schemes using both synthetic and human-brain data. Results show large reductions in error of the fitted parameters with the new schemes, which greatly increases the clinical potential of in vivo quantitative MT. Since the sampling-scheme optimization requires specific settings of the MT parameters, we also show that the optimum schemes are robust to these settings within the range of MT parameters observed in the brain.

Type: Article
Title: Optimal acquisition schemes for in vivo quantitative magnetization transfer MRI
Open access status: An open access version is available from UCL Discovery
DOI: 10.1002/mrm.21003
Publisher version: http://dx.doi.org/10.1002/mrm.21003
Additional information: © 2006 Wiley-Liss, Inc. Text made available to UCL Discovery by kind permission of Wiley.
Keywords: magnetization transfer, Cramer-Rao lower bound, optimal sampling, quantitative MRI, brain, HUMAN BRAIN, MULTIPLE-SCLEROSIS, TRANSFER CONTRAST, DIFFUSION, PARAMETERS, WATER, ECHO, IMAGES, TIMES, T-2
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery.ucl.ac.uk/id/eprint/116265
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