AI Article Synopsis

  • The article reviews recent advancements in advanced arterial spin labeling (ASL) techniques since the last consensus paper, focusing on areas like image reconstruction, noise reduction, and deep learning.
  • It aims to help researchers and MRI vendors understand and implement these new methods to improve imaging quality and functionality.
  • Topics not covered in detail include velocity selective ASL, multiple-timepoint ASL, and clinical recommendations, which are discussed in separate articles.

Article Abstract

This review article provides an overview of a range of recent technical developments in advanced arterial spin labeling (ASL) methods that have been developed or adopted by the community since the publication of a previous ASL consensus paper by Alsop et al. It is part of a series of review/recommendation papers from the International Society for Magnetic Resonance in Medicine Perfusion Study Group. Here, we focus on advancements in readouts and trajectories, image reconstruction, noise reduction, partial volume correction, quantification of nonperfusion parameters, fMRI, fingerprinting, vessel selective ASL, angiography, deep learning, and ultrahigh field ASL. We aim to provide a high level of understanding of these new approaches and some guidance for their implementation, with the goal of facilitating the adoption of such advances by research groups and by MRI vendors. Topics outside the scope of this article that are reviewed at length in separate articles include velocity selective ASL, multiple-timepoint ASL, body ASL, and clinical ASL recommendations.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9420802PMC
http://dx.doi.org/10.1002/mrm.29381DOI Listing

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