Multi-modal pharmacokinetic modelling for DCE-MRI: using diffusion weighted imaging to constrain the local arterial input function

The routine acquisition of multi-modal magnetic resonance imaging data in oncology yields the possibility of combined model fitting of traditionally separate models of tissue structure and function. In this work we hypothesise that diffusion weighted imaging data may help constrain the fitting of pharmacokinetic models to dynamic contrast enhanced (DCE) MRI data. Parameters related to tissue perfusion in the intra-voxel incoherent motion (IVIM) modelling of diffusion weighted MRI provide local information on how tissue is likely to perfuse that can be utilised to guide DCE modelling via local modification of the arterial input function (AIF). In this study we investigate, based on multi-parametric head and neck MRI of 8 subjects (4 with head and neck tumours), the benefit of incorporating parameters derived from the IVIM model within the DCE modelling procedure. Although we find the benefit of this procedure to be marginal on the data used in this work, it is conceivable that a technique of this type will be of greater use in a different application.