Yuriko Suzuki1, Matthias J P van Osch1, Noriyuki Fujima2, Thomas W Okell3. 1. C.J. Gorter Center for High Field MRI, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands. 2. Department of Diagnostic and Interventional Radiology, Hokkaido University Hospital, Hokkaido, Japan. 3. Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom.
Abstract
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.
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.
Authors: Luis Hernandez-Garcia; Verónica Aramendía-Vidaurreta; Divya S Bolar; Weiying Dai; Maria A Fernández-Seara; Jia Guo; Ananth J Madhuranthakam; Henk Mutsaerts; Jan Petr; Qin Qin; Jonas Schollenberger; Yuriko Suzuki; Manuel Taso; David L Thomas; Matthias J P van Osch; Joseph Woods; Moss Y Zhao; Lirong Yan; Ze Wang; Li Zhao; Thomas W Okell Journal: Magn Reson Med Date: 2022-08-19 Impact factor: 3.737