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PURPOSE: In vessel-encoded pseudo-continuous arterial spin labeling (ve-pCASL), vessel-selective labeling is achieved by modulation of the inversion efficiency across space. However, the spatial transition between the labeling and control conditions is rather gradual, which can cause partial labeling of vessels, reducing SNR-efficiency and necessitating complex postprocessing to decode the vessel-selective signals. The purpose of this study is to optimize the pCASL labeling parameters to obtain a sharper spatial inversion profile of the labeling and thereby minimizing the risk of partial labeling of untargeted arteries. METHODS: Bloch simulations were performed to investigate how the inversion profile was influenced by the pCASL labeling parameters: the maximum (Gmax ) and mean (Gmean ) labeling gradient were varied for ve-pCASL with unipolar and bipolar gradients. The findings in the simulation study were subsequently confirmed in an in vivo volunteer study. Moreover, conventional and optimized settings were compared for 4D-MRA using four-cycle Hadamard ve-pCASL; the visualization of arteries and the presence of the partial labeling were assessed by an expert observer. RESULTS: When using unipolar gradient, lower Gmean resulted in a steeper spatial transition, whereas the width of the control region was broader for higher Gmax . The in vivo study confirmed these findings. When using bipolar gradients, the control region was always very narrow. Qualitative comparison of the 4D-MRA demonstrated lower occurrence of partial labeling when using the optimized gradient parameters. CONCLUSION: The shape of the ve-pCASL inversion profile can be optimized by changing Gmean and Gmax to reduce partial labeling of untargeted arteries.

Original publication




Journal article


Magn Reson Med

Publication Date





410 - 423


ASL-based 4D-MRA, vessel selective labeling, vessel-encoded pCASL, Adult, Algorithms, Arteries, Blood Flow Velocity, Brain, Cerebrovascular Circulation, Computer Simulation, Contrast Media, Female, Healthy Volunteers, Humans, Image Interpretation, Computer-Assisted, Image Processing, Computer-Assisted, Imaging, Three-Dimensional, Magnetic Resonance Angiography, Male, Middle Aged, Motion, Risk, Signal-To-Noise Ratio, Spin Labels