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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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