Dual-echo ASL based assessment of motor networks: a feasibility study.

Objective: Dual-echo arterial spin labeling (DE-ASL) technique has been recently proposed for the simultaneous acquisition of ASL and blood-oxygenation-level-dependent (BOLD)-functional magnetic resonance imaging (fMRI) data. The assessment of this technique in detecting functional connectivity at rest or during motor and motor imagery tasks is still unexplored both per-se and in comparison with conventional methods. The purpose is to quantify the sensitivity of the DE-ASL sequence with respect to the conventional fMRI sequence (cvBOLD) in detecting brain activations, and to assess and compare the relevance of node features in decoding the network structure.

Approach: Thirteen volunteers were scanned acquiring a pseudo-continuous DE-ASL sequence from which the concomitant BOLD (ccBOLD) simultaneously to the ASL can be extracted. The approach consists of two steps: (i) model-based analyses for assessing brain activations at individual and group levels, followed by statistical analysis for comparing the activation elicited by the three sequences under two conditions (motor and motor imagery), respectively; (ii) brain connectivity graph-theoretical analysis for assessing and comparing the network models properties.

Main Results: Our results suggest that cvBOLD and ccBOLD have comparable sensitivity in detecting the regions involved in the active task, whereas ASL offers a higher degree of co-localization with smaller activation volumes. The connectivity results and the comparative analysis of node features across sequences revealed that there are no strong changes between rest and tasks and that the differences between the sequences are limited to few connections.

Significance: Considering the comparable sensitivity of the ccBOLD and cvBOLD sequences in detecting activated brain regions, the results demonstrate that DE-ASL can be successfully applied in functional studies allowing to obtain both ASL and BOLD information within a single sequence. Further, DE-ASL is a powerful technique for research and clinical applications allowing to perform quantitative comparisons as well as to characterize functional connectivity.