Frontiers in Radiology (Jun 2022)

A Beginner's Guide to Arterial Spin Labeling (ASL) Image Processing

  • Patricia Clement,
  • Jan Petr,
  • Jan Petr,
  • Mathijs B. J. Dijsselhof,
  • Mathijs B. J. Dijsselhof,
  • Beatriz Padrela,
  • Beatriz Padrela,
  • Maurice Pasternak,
  • Sudipto Dolui,
  • Lina Jarutyte,
  • Nandor Pinter,
  • Nandor Pinter,
  • Nandor Pinter,
  • Luis Hernandez-Garcia,
  • Andrew Jahn,
  • Joost P. A. Kuijer,
  • Frederik Barkhof,
  • Frederik Barkhof,
  • Frederik Barkhof,
  • Henk J. M. M. Mutsaerts,
  • Henk J. M. M. Mutsaerts,
  • Henk J. M. M. Mutsaerts,
  • Henk J. M. M. Mutsaerts,
  • Vera C. Keil,
  • Vera C. Keil,
  • Vera C. Keil

DOI
https://doi.org/10.3389/fradi.2022.929533
Journal volume & issue
Vol. 2

Abstract

Read online

Arterial spin labeling (ASL) is a non-invasive and cost-effective MRI technique for brain perfusion measurements. While it has developed into a robust technique for scientific and clinical use, its image processing can still be daunting. The 2019 Ann Arbor ISMRM ASL working group established that education is one of the main areas that can accelerate the use of ASL in research and clinical practice. Specifically, the post-acquisition processing of ASL images and their preparation for region-of-interest or voxel-wise statistical analyses is a topic that has not yet received much educational attention. This educational review is aimed at those with an interest in ASL image processing and analysis. We provide summaries of all typical ASL processing steps on both single-subject and group levels. The readers are assumed to have a basic understanding of cerebral perfusion (patho) physiology; a basic level of programming or image analysis is not required. Starting with an introduction of the physiology and MRI technique behind ASL, and how they interact with the image processing, we present an overview of processing pipelines and explain the specific ASL processing steps. Example video and image illustrations of ASL studies of different cases, as well as model calculations, help the reader develop an understanding of which processing steps to check for their own analyses. Some of the educational content can be extrapolated to the processing of other MRI data. We anticipate that this educational review will help accelerate the application of ASL MRI for clinical brain research.

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