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Abstract #2131

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

1 Cardiff University, Cardiff, Wales, United Kingdom, 2 Oxford 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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