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Abstract #3911

Bayesian Estimation Improves Plasma Volume Repeatability with Compartmental Modelling of DCE-MRI Data

Matthew R. Orton1, David J. Collins1, Christina Messiou1, Jean Tessier2, M. O. Leach1

1CR-UK & EPSRC Cancer Imaging Centre, Institute of Cancer Research, Sutton, Surrey, United Kingdom; 2Formerly with Early Clinical Development, AstraZeneca, Alderley Park, Macclesfield, United Kingdom

The Extended Kety model is widely used for modelling DCE-MRI data. It is well known that estimates of the plasma volume fraction are subject to large errors compared with other parameters obtained with this model, which limits the utility of such estimates in trials and clinical practice. In this abstract we present a Bayesian estimation methodology that reduces test-retest repeatability of estimates by around 50% in comparison to least-squares estimates. This results in a more reliable measure that has similar repeatability to DC-CT based measures, and therefore has the potential to detect smaller changes as a result of therapeutic interventions.