Quantification of cerebral blood flow in nonhuman primates using arterial spin labeling and a two-compartment model

Abstract

Noninvasive absolute quantification of cerebral blood flow (CBF) with high spatial resolution is still a challenging task. Arterial spin labeling (ASL) is a promising magnetic resonance imaging (MRI) method for accurate perfusion quantification. However, modeling of ASL data is far from being standardized and has not been investigated in great detail. In this study, two-compartment modeling of monkey ASL data in three physiological conditions (baseline, sensory activated and globally elevated CBF) is reported. Absolute perfusion and arterial transit times were derived for gray matter (GM) and white matter (WM) separately. The uncertainties of the model's result were determined by Monte Carlo simulations. The fitted CBF values for GM were 133 ml/min/100 ml at baseline condition, 165 ml/min/100 ml during visual stimulation and 234 ml/min/100 ml for globally elevated CBF after intravenous injection of acetazolamide. The ratio of GM to WM CBF was 2.5 at baseline and was found to decrease to 1.6 after application of acetazolamide. The corresponding arterial transit times decreased from 742 to 607 ms in GM and from 985 to 875 ms in WM. Monte Carlo simulations showed that absolute CBF values can be determined with an error of 11-15%, while the arterial transit time values have a coefficient of variation of 25-31%. With an alternative acquisition scheme, the precision of the arterial transit times can be improved significantly. The CBF values in the occipital lobe of the monkey brain quantified with ASL are higher than previously reported in positron emission tomography studies.