Zhensen Chen1, Xingxing Zhang2,3, Chun Yuan1,4, Xihai Zhao1, Matthias J P van Osch2,3. 1. Center for Biomedical Imaging Research, Department of Biomedical Engineering, Tsinghua University, Beijing, China. 2. C.J. Gorter Center for High Field MRI, Department of Radiology, Leiden University Medical Center, Leiden, Netherlands. 3. Leiden Institute for Brain and Cognition, Leiden, Netherlands. 4. Department of Radiology, University of Washington, Seattle, Washington, USA.
Abstract
PURPOSE: Optimization and validation of a sequence for measuring the labeling efficiency of pseudocontinuous arterial spin labeling (pCASL) perfusion MRI. METHODS: The proposed sequence consists of a labeling module and a single slice Look-Locker echo planar imaging readout. A model-based algorithm was used to calculate labeling efficiency from the signal acquired from the main brain-feeding arteries. Stability of the labeling efficiency measurement was evaluated with regard to the use of cardiac triggering, flow compensation and vein signal suppression. Accuracy of the measurement was assessed by comparing the measured labeling efficiency to mean brain pCASL signal intensity over a wide range of flip angles as applied in the pCASL labeling. RESULTS: Simulations show that the proposed algorithm can effectively calculate labeling efficiency when correcting for T1 relaxation of the blood spins. Use of cardiac triggering and vein signal suppression improved stability of the labeling efficiency measurement, while flow compensation resulted in little improvement. The measured labeling efficiency was found to be linearly (R = 0.973; P < 0.001) related to brain pCASL signal intensity over a wide range of pCASL flip angles. CONCLUSION: The optimized labeling efficiency sequence provides robust artery-specific labeling efficiency measurement within a short acquisition time (∼30 s), thereby enabling improved accuracy of pCASL CBF quantification. Magn Reson Med 77:1841-1852, 2017.
PURPOSE: Optimization and validation of a sequence for measuring the labeling efficiency of pseudocontinuous arterial spin labeling (pCASL) perfusion MRI. METHODS: The proposed sequence consists of a labeling module and a single slice Look-Locker echo planar imaging readout. A model-based algorithm was used to calculate labeling efficiency from the signal acquired from the main brain-feeding arteries. Stability of the labeling efficiency measurement was evaluated with regard to the use of cardiac triggering, flow compensation and vein signal suppression. Accuracy of the measurement was assessed by comparing the measured labeling efficiency to mean brain pCASL signal intensity over a wide range of flip angles as applied in the pCASL labeling. RESULTS: Simulations show that the proposed algorithm can effectively calculate labeling efficiency when correcting for T1 relaxation of the blood spins. Use of cardiac triggering and vein signal suppression improved stability of the labeling efficiency measurement, while flow compensation resulted in little improvement. The measured labeling efficiency was found to be linearly (R = 0.973; P < 0.001) related to brain pCASL signal intensity over a wide range of pCASL flip angles. CONCLUSION: The optimized labeling efficiency sequence provides robust artery-specific labeling efficiency measurement within a short acquisition time (∼30 s), thereby enabling improved accuracy of pCASL CBF quantification. Magn Reson Med 77:1841-1852, 2017.
Authors: Jonas Schollenberger; C Alberto Figueroa; Jon-Fredrik Nielsen; Luis Hernandez-Garcia Journal: Magn Reson Med Date: 2019-08-16 Impact factor: 4.668
Authors: Meher R Juttukonda; Lori C Jordan; Melissa C Gindville; Larry T Davis; Jennifer M Watchmaker; Sumit Pruthi; Manus J Donahue Journal: NMR Biomed Date: 2017-01-04 Impact factor: 4.044
Authors: James H Holmes; Mu-Lan Jen; Laura B Eisenmenger; Tilman Schubert; Patrick A Turski; Kevin M Johnson Journal: Magn Reson Med Date: 2021-02-21 Impact factor: 3.737
Authors: Piet Bladt; Matthias J P van Osch; Patricia Clement; Eric Achten; Jan Sijbers; Arnold J den Dekker Journal: Magn Reson Med Date: 2020-05-19 Impact factor: 4.668