A Bayesian framework for the estimation of OEF by calibrated MRI
Michael Germuska 1 , Alberto Merola 1 , Alan Stone 2 , Kevin Murphy 1 , and Richard Wise 1
Cardiff University, Cardiff, Wales, United
University, Oxfordshire, United Kingdom
Recently, calibrated MRI methods of estimating resting
oxygen extraction fraction (OEF) have been developed.
These methods rely on the independent quantification of
BOLD and blood flow responses to respiratory challenges.
The resulting estimates are then fed into a
physiological model to solve for OEF. Data analysed in
such a step-wise manner are susceptible to the
propagation of errors along the pipeline, producing
unstable estimates of OEF. Here we re-pose the analysis
in a Bayesian framework to solve for the underlying
physiological parameters in a one-step solution. In-vivo
data demonstrates stable estimates of OEF within the
expected range for healthy tissue.
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