Abstract

Resting-state, low-frequency (<0.08 Hz) fluctuations of blood oxygenation level-dependent (BOLD) magnetic resonance signal have been shown to exhibit high correlation among functionally connected regions. However, correlations of cerebral blood flow (CBF) fluctuations during the resting state have not been extensively studied. The main challenges of using arterial spin labeling perfusion magnetic resonance imaging to detect CBF fluctuations are low sensitivity, low temporal resolution, and contamination from BOLD. This work demonstrates CBF-based quantitative functional connectivity mapping by combining continuous arterial spin labeling (CASL) with a neck labeling coil and a multi-channel receiver coil to achieve high perfusion sensitivity. In order to reduce BOLD contamination, the CBF signal was extracted from the CASL signal time course by high frequency filtering. This processing strategy is compatible with sinc interpolation for reducing the timing mismatch between control and label images and has the flexibility of choosing an optimal filter cutoff frequency to minimize BOLD fluctuations. Most subjects studied showed high CBF correlation in bilateral sensorimotor areas with good suppression of BOLD contamination. Root-mean-square CBF fluctuation contributing to bilateral correlation was estimated to be 29±19% (N=13) of the baseline perfusion, while BOLD fluctuation was 0.26±0.14% of the mean intensity (at 3 T and 12.5 ms echo time).

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