henhaobio
Sign in

Magnetic Resonance in MedicineNeurosciencePeer-reviewed journal article

Bidirectional crusher gradient method for estimating the labeling efficiency of pseudo-continuous arterial spin labeling MRI in mice

Xiuli YangiD, Yuguo LiiD, Adnan BibiciD, María Guadalupe Mora ÁlvareziD, Hanzhang LuiD, Zhiliang WeiiD

PDFDOIPreprint

Abstract

Pseudo-continuous arterial spin labeling (pCASL) MRI is a widely used imaging technique for studying brain perfusion in health and disease due to its non-invasive and non-contrast nature. Accurate quantification of absolute perfusion values from pCASL signals requires the knowledge of labeling efficiency. However, to date, a reliable technique to measure pCASL labeling efficiency has not been available. In this study, we propose a method using bidirectional crusher gradients to modulate vascular signals in the azygos pericallosal artery (azPA) of the mouse brain, applied with and without pCASL labeling. The combination of corresponding signals allows the estimation of labeling efficiency. Upon systematic testing, optimal acquisition parameters included a labeling duration [≥] 1170 ms, a repetition time of 3 seconds, and an imaging slice thickness of 0.75 mm. In order to quantitatively estimate labeling efficiency, the bolus arrival time to azPA is required and found to be 218.7 +/- 13.3 ms. Typical labeling efficiencies in mouse pCASL scans were 0.780 +/- 0.048 (mean +/- standard deviation). Furthermore, faster arterial flow induced by hypercapnia was found to increase pCASL labeling efficiency. Our method can improve the accuracy of pCASL quantification in mice, offering great potential for advancing its applications in pathophysiological studies.

Citations
5
FWCI
2.87
Field percentile
top 9%

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISYang '25Monteiro '24Woods '25Woods '20Ji '24Okell '25
81% semantic matchBioengineering
Xiuli Yang, Yuguo Li, Adnan Bibic+1 more·bioRxiv·Dec 5, 2025