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Abstract #2851

QuantiCEST: Bayesian Model-based Analysis of CEST MRI

Paula L. Croal1, Yunus Msayib1, Kevin J. Ray2,3, Martin Craig1, and Michael Chappell1

1Institute of Biomedical Engineering, University of Oxford, Oxford, United Kingdom, 2CRUK & MRC Oxford Institute for Radiation Oncology, University of Oxford, Oxford, United Kingdom, 3Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom

QuantiPhyse, a python-based software tool for quantitative image processing, has recently been released, to increase the accessibility of physiological modelling and quantification. Here, we present QuantiCEST, a QuantiPhyse plug-in offering Bayesian model-based analysis for quantification of CEST MRI. Using either the graphical user interface or command line, users can easily specify a multipool model of the Bloch-McConnell equations to quantify CEST data acquired with any combination of offset frequencies, saturation power and field strength. Additional information, such as relaxation times, can also be incorporated in the model, allowing flexibility to suit individual research needs. A typical analysis pipeline is presented.

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