Optimal design of pulsed arterial spin labeling MRI experiments

Abstract

Quantitative measurement of cerebral blood flow (CBF) using arterial spin labeling (ASL) MRI requires the acquisition of multiple inversion times (TIs) and the application of an appropriate kinetic model. The choice of these sampling times will have an impact on the precision of the estimated parameters. Here, optimal sampling schedule (OSS) design techniques, based on the Fisher Information approach, are applied in order to derive an optimal sampling scheme for pulsed arterial spin labeling (PASL) experiments. Such an approach should improve the precision of parameter estimation from experimental data, and provide a formal framework for optimally selecting a limited number of samples. In this study, we aimed to optimize the estimation precision of CBF and bolus arrival time from the PASL data. The performance of OSS was compared to a more standard evenly distributed sampling schedule (EDS) using both simulated and measured experimental data sets. It was found that OSS was able to significantly improve the precision of parameter estimation in PASL studies that sought to estimate either both CBF and bolus arrival time, or CBF alone.