Estimation of perfusion properties with MR Fingerprinting Arterial Spin Labeling.

In this study, the acquisition of ASL data and quantification of multiple hemodynamic parameters was explored using a Magnetic Resonance Fingerprinting (MRF) approach. A pseudo-continuous ASL labeling scheme was used with pseudo-randomized timings to acquire the MRF ASL data in a 2.5 min acquisition. A large dictionary of MRF ASL signals was generated by combining a wide range of physical and hemodynamic properties with the pseudo-random MRF ASL sequence and a two-compartment model. The acquired signals were matched to the dictionary to provide simultaneous quantification of cerebral blood flow, tissue time-to-peak, cerebral blood volume, arterial time-to-peak, B1, and T1. A study in seven healthy volunteers resulted in the following values across the population in grey matter (mean ± standard deviation): cerebral blood flow of 69.1 ± 6.1 ml/min/100 g, arterial time-to-peak of 1.5 ± 0.1 s, tissue time-to-peak of 1.5 ± 0.1 s, T1 of 1634 ms, cerebral blood volume of 0.0048 ± 0.0005. The CBF measurements were compared to standard pCASL CBF estimates using a one-compartment model, and a Bland-Altman analysis showed good agreement with a minor bias. Repeatability was tested in five volunteers in the same exam session, and no statistical difference was seen. In addition to this validation, the MRF ASL acquisition's sensitivity to the physical and physiological parameters of interest was studied numerically.

Duke Scholars

Author Dan Ma Neurosurgery