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Abstract #3891

Diffusion Model Complexity Reduces Repeatability in Multiple B-Value DWI Fitting : Impact of Tumour Volume & Fitting Methodology in a Phase I Clinical Trial Setting

Matthew R. Orton1, David J. Collins1, Christina Messiou1, Jean Tessier2, Martin 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


Diffusion Weighted Imaging with multiple b-values is being used more widely in many application areas, including clinical trials for assessment of novel cancer therapeutics. Complex models are being increasingly used to extract more information from the data, and the suitability and interpretation of these is a matter of current debate. In this abstract we present results obtained from data acquired in a phase I clinical trial setting which demonstrate the effect of the diffusion model complexity, fitting methodology and tumour volume on the repeatability of functional parameter estimates.

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