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Abstract #2353

Bayesian Pharmacokinetic Modeling of Dynamic Contrast-Enhanced Magnetic Resonance Imaging: Validation and Application

Andreas Mittermeier1, Birgit Ertl-Wagner2, Jens Ricke1, Olaf Dietrich1, and Michael Ingrisch1

1Department of Radiology, LMU University of Munich, Munich, Germany, 2Div of Paediatric Neuroradiology, The Hospital for Sick Children, Toronto, ON, Canada

We implemented a tracer-kinetic model within a Bayesian framework which infers full posterior probability distributions for parameter estimates. We validate our Bayesian model using a digital reference object and compare it to a standard non-linear least squares approach. Furthermore, we use this approach to obtain pharmacokinetic parameter distributions during the course of a therapy for breast cancer DCE-MRI data, and we demonstrate how Bayesian posterior distributions can be utilized to assess treatment response.

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