Manav Bhushan1, Julia Schnabel1, Lydia Tanner2, Fergus Gleeson3, Sir Michael Brady2, Mark Jenkinson4
1Institute of Biomedical Engineering, Oxford University, Oxford, United Kingdom; 2Department of Radiation Oncology and Biology, Oxford University; 3Department of Radiology, Churchill Hospital; 4Centre for Functional MRI of the Brain, Oxford University
We present a novel Bayesian framework for non-rigid motion correction and Pharmacokinetic (PK) parameter estimation in dynamic contrast-enhanced MRI. We use our algorithm to co-register image volumes from dceMRI scans acquired for Colorectal cancer patients before, and after 5 weeks of chemoradiotherapy and estimate the PK-parameter maps for the same. We then classify each patient as a responder or non-responder to therapy on the basis of the difference between the pre- and post-therapy distributions of PK-parameters. We show that there is a significant benefit in using motion-correction within this framework, and also compare the results obtained using two AIFs.