Estimation of arterial arrival time and cerebral blood flow from QUASAR arterial spin labeling using stable spline

QUASAR arterial spin labeling (ASL) permits the application of deconvolution approaches for the absolute quantification of cerebral perfusion. Currently, oscillation index regularized singular value decomposition (oSVD) combined with edge-detection (ED) is the most commonly used method. Its major drawbacks are nonphysiological oscillations in the impulse response function and underestimation of perfusion. The aim of this work is to introduce a novel method to overcome these limitations.

A system identification method, stable spline (SS), was extended to address ASL peculiarities such as the delay in arrival of the arterial blood in the tissue. The proposed framework was compared with oSVD + ED in both simulated and real data. SS was used to investigate the validity of using a voxel-wise tissue T1 value instead of using a single global value (of blood T1 ).

SS outperformed oSVD + ED in 79.9% of simulations. When applied to real data, SS exhibited a physiologically realistic range for perfusion and a higher mean value with respect to oSVD + ED (55.5 ± 9.5 SS, 34.9 ± 5.2 oSVD + ED mL/100 g/min).

SS can represent an alternative to oSVD + ED for the quantification of QUASAR ASL data. Analysis of the retrieved impulse response function revealed that using a voxel wise tissue T1 might be suboptimal.