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Abstract #2577

Extracting CBF and ATT from One or Two Post-labeling Delays-based Arterial Spin Labeled Perfusion MRI via Deep Learning

Yiran Li1, Xiufeng Li2, John A Detre3, and Ze Wang1
1University of Maryland School of Medicine, Baltimore, MD, United States, 2University of Minnesota, Minneapolis, MN, United States, 3University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States

Synopsis

Keywords: Arterial spin labelling, Arterial spin labellingCerebral blood flow (CBF) and arterial transit time (ATT) can be quantified through fitting the arterial spin labeling (ASL) perfusion MRI signal acquired at different post-labeling delays (PLDs) into a kinetic model. Acquiring multiple-PLD ASL MRI needs exponentially prolonged total scan time compared to the single-PLD acquisition, making it highly sensitive to motions and impractical for clinical use. We proposed a deep neural network that can reliably estimate ATT and CBF maps from significantly fewer PLD ASL MRI acquisitions without image quality loss.

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Keywords