Simultaneous Hemodynamic and Structural Imaging of Ischemic Stroke With Magnetic Resonance Fingerprinting Arterial Spin Labeling

Abstract

Background: Perfusion and structural imaging play an important role in ischemic stroke. Magnetic resonance fingerprinting (MRF) arterial spin labeling (ASL) is a novel noninvasive method of ASL perfusion that allows simultaneous estimation of cerebral blood flow (CBF), bolus arrival time (BAT), and tissue T 1 map in a single scan of <4 minutes. Here, we evaluated the utility of MRF-ASL in patients with ischemic stroke in terms of detecting hemodynamic and structural damage and predicting neurological deficits and disability. Methods: A total of 34 patients were scanned on 3T magnetic resonance imaging. MRF-ASL, standard single-delay pseudo-continuous ASL, T 2 -weighted, and diffusion magnetic resonance imaging were performed. Regions of interest of lesion and contralateral normal tissues were manually delineated. CBF (with 2 different compartmental models), BAT, and tissue T 1 parameters were quantified. Cross-sectional linear regression analyses were performed to examine the relationship between MRF-ASL parameters and National Institutes of Health Stroke Scale (NIHSS) and modified Rankin Scale. Receiver operating characteristic analyses were performed to determine the utility of MRF-ASL in the classification of stroke lesion voxels. Results: MRF-ASL derived parameters revealed a significant difference between stroke lesion and contralateral normal regions of interest, in that lesion regions manifested a lower CBF 1-compartment ( P <0.001), lower CBF 2-compartment ( P <0.001), longer BAT ( P =0.002), and longer T 1 ( P <0.001) compared with normal regions of interest. NIHSS scores at acute stage revealed a strong association with lesion-normal differences in CBF 1-compartment,diff (β=−0.11, P =0.008), CBF 2-compartment,diff (β=−0.16, P =0.003), and T 1,diff (β=0.008, P =0.001). MRF-ASL parameters were also predictive of NIHSS score and modified Rankin Scale scale measured at a later stage, although the degree of the associations was weaker. These associations tended to be even stronger when the MRF-ASL data were acquired at the acute/subacute stage. Compared with standard pseudo-continuous ASL, the multiparametric capability of MRF-ASL yielded higher area under curve values in the receiver operating characteristic analyses of stroke voxel classifications. Conclusions: MRF-ASL may provide a new approach for quantitative hemodynamic and structural imaging in ischemic stroke.