Time‐resolved angiography with stochastic trajectories for dynamic contrast‐enhanced MRI in head and neck cancer: Are pharmacokinetic parameters affected?. Issue 11 (18th October 2016) - Panek, Rafal; Schmidt, Maria A.; Borri, Marco; Koh, Dow‐Mu; Riddell, Angela; Welsh, Liam; Dunlop, Alex; Powell, Ceri; Bhide, Shreerang A.; Nutting, Christopher M.; Harrington, Kevin J.; Newbold, Kate L.; et al.
Abstract : Purpose: To investigate the effects of different time‐resolved angiography with stochastic trajectories (TWIST) k ‐space undersampling schemes on calculated pharmacokinetic dynamic contrast‐enhanced (DCE) vascular parameters. Methods: A digital perfusion phantom was employed to simulate effects of TWIST on characteristics of signal changes in DCE. Furthermore, DCE‐MRI was acquired without undersampling in a group of patients with head and neck squamous cell carcinoma and used to simulate a range of TWIST schemes. Errors were calculated as differences between reference and TWIST‐simulated DCE parameters. Parametrical error maps were used to display the averaged results from all tumors. Results: For a relatively wide range of undersampling schemes, errors in pharmacokinetic parameters due to TWIST were under 10% for the volume transfer constant, K trans, and total extracellular extravascular space volume, Ve . TWIST induced errors in the total blood plasma volume, Vp, were the largest observed, and these were inversely dependent on the area of the fully sampled k ‐space. The magnitudes of errors were not correlated with K trans, Vp and weakly correlated with Ve . Conclusions: The authors demonstrated methods to validate and optimize k ‐space view‐sharing techniques for pharmacokinetic DCE studies using a range of clinically relevant spatial and temporal patient derived data. The authors found a range of undersampling patterns for which the TWIST sequence can be reliably used in pharmacokinetic DCE‐MRI. The parameter maps created in the study can help to make a decision between temporal and spatial resolution demands and the quality of enhancement curve characterization.