Motivation: Arterial-spin labeling (ASL) MRI in newborns less than one week of age is arguably the most challenging application of ASL. Goal(s): To develop an ASL scheme that provides high-fidelity perfusion maps while minimizing noise and biases. Approach: We developed a projection-based data processing method to reduced CBF overestimation, and verified its efficacy using simulation, phantom and neonatal ASL data. We further identified optimal arterial saturation to suppress pulsation noise while preserving SNR. Results: Projection-based complex-subtraction method can mitigate perfusion overestimation bias. Arterial saturation with a 15 cm/s cutoff velocity effectively reduced large-vessel signal fluctuations without affecting tissue perfusion signal. Impact: Using the proposed ASL acquisition and processing method, high-fidelity perfusion maps can be obtained from early neonates in less than 4 minutes. This technique holds potentials for studying neonatal brain diseases involving perfusion abnormalities.
Hu et al. (Tue,) studied this question.
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