The arterial input function: Spatial dependence within the imaging volume and its influence on 3D quantitative dynamic contrast-enhanced MRI for head and neck cancer

Abstract

PurposeTo evaluate the dependence of the arterial input function (AIF) on the imaging z-axis and its effect on 3D DCE MRI pharmacokinetic parameters as mediated by the SPGR signal equation and Extended Tofts-Kermode model. TheoryFor SPGR-based 3D DCE MRI acquisition of the head and neck, inflow effects within vessels violate the assumptions underlying the SPGR signal model. Errors in the SPGR-based AIF estimate propagate through the Extended Tofts-Kermode model to affect the output pharmacokinetic parameters. Materials and methods3D DCE-MRI data were acquired for six newly diagnosed HNC patients in a prospective single arm cohort study. AIF were selected within the carotid arteries at each z-axis location. A region of interest (ROI) was placed in normal paravertebral muscle and the Extended Tofts-Kermode model solved for each pixel within the ROI for each AIF. Results were compared to those obtained with a published population average AIF. ResultsDue to inflow effect, the AIF showed extreme variation in their temporal shapes. Ktrans was most sensitive to the initial bolus concentration and showed more variation over the muscle ROI with AIF taken from the upstream portion of the carotid. kep was less sensitive to the peak bolus concentration and showed less variation for AIF taken from the upstream portion of the carotid. ConclusionInflow effects may introduce an unknown bias to SPGR-based 3D DCE pharmacokinetic parameters. Variation in the computed parameters depends on the selected AIF location. In the context of high flow, measurements may be limited to relative rather than absolute quantitative parameters.