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Optimal acquisition schemes for in vivo quantitative magnetization transfer MRI
Author(s) -
Cercignani Mara,
Alexander Daniel C.
Publication year - 2006
Publication title -
magnetic resonance in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.696
H-Index - 225
eISSN - 1522-2594
pISSN - 0740-3194
DOI - 10.1002/mrm.21003
Subject(s) - magnetization transfer , sampling (signal processing) , cramér–rao bound , computer science , offset (computer science) , sampling scheme , simulated annealing , algorithm , amplitude , range (aeronautics) , mathematics , magnetic resonance imaging , physics , statistics , estimation theory , materials science , medicine , filter (signal processing) , quantum mechanics , estimator , composite material , computer vision , radiology , programming language
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. Magn Reson Med, 2006. © 2006 Wiley‐Liss, Inc.