Abstract #2716
Robust and Fast Quantification of CBF measures for Multiphase PCASL using Bayesian Nonlinear Model Fitting
David D Shin 1 , Michael A Chappell 2 , and Thomas T Liu 1
1
Center for Functional MRI, University of
California, San Diego, La Jolla, CA, United States,
2
Institute
of Biomedical Engineering & FMRIB Centre, University of
Oxford, Oxford, United Kingdom
Multiphase PCASL is a variant of PCASL that mitigates
the tagging efficiency loss resulting from off-resonance
fields and gradient imperfections. Instead of acquiring
the ASL data at two RF phase offsets, the signals from
multiple phase offsets are acquired and then fit to an
expected inversion response curve to form an estimate of
the perfusion signal. In this work, an alternate
Bayesian nonlinear method is presented that incorporates
a spatial prior on the model parameters. Using ten
healthy subjects, the quantified CBF maps from the two
methods are compared within gray matter, white matter,
and in regions where the original fitting approach
greatly overestimates CBF.
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