Reliable Detection of Default Mode Network in Resting-State Perfusion FMRI Using PCASL 3D GRASE with Background Suppression

Lirong Yan¹, Yong Fan², Danny JJ Wang¹

Resting-state functional connectivity (RSFC) analysis of ASL perfusion fMRI may improve the understanding of the biophysical mechanism of resting connectivity, and may provide a quantitative alternative to resting state BOLD fMRI. In this study, pseudo-continuous ASL (pCASL) with 3D background suppressed (BS) GRASE readout was used to detect RSFC arising from spontaneous perfusion fluctuations. By comparison with a standard resting-state BOLD fMRI scan and a pCASL GRASE scan with compromised BS, the present study shows that the default mode network can be reliably detected in resting-state perfusion image series without BOLD contamination.