BASIL: A Toolbox for Perfusion Quantification using Arterial Spin Labelling

Chappell, Michael A.; Kirk, Thomas F.; Craig, Martin S.; McConnell, Flora A. Kennedy; Zhao, Moss Y.; MacIntosh, Bradley J.; Okell, Thomas W.; Woolrich, Mark W.

Abstract

Arterial Spin Labelling (ASL) MRI is now an established non-invasive method to quantify cerebral blood flow and is increasingly being used in a variety of neuroimaging applications. With standard ASL acquisition protocols widely available, there is a growing interest in advanced options that offer added quantitative precision and information about haemodynamics beyond perfusion. In this article we introduce the BASIL toolbox, a research tool for the analysis of ASL data included within the FMRIB Software Library (FSL) and explain its operation in a variety of typical use cases. BASIL is not offered as a clinical tool, and nor is this work intended to guide the clinical application of ASL. Built around a Bayesian model-based inference algorithm, the toolbox is designed to quantify perfusion and other haemodynamic measures, such as arterial transit times, from a variety of possible ASL input data, particularly exploiting the information available in more advanced multi-delay acquisitions. At its simplest, the BASIL toolbox offers a graphical user interface that provides the analysis options needed by most users; through command line tools, it offers more bespoke options for users needing customised analyses. As part of FSL, the toolbox exploits a range of complementary neuroimaging analysis tools so that ASL data can be easily integrated into neuroimaging studies and used alongside other modalities.

Citation

Chappell, M. A., Kirk, T. F., Craig, M. S., McConnell, F. A. K., Zhao, M. Y., MacIntosh, B. J., …Woolrich, M. W. (2023). BASIL: A Toolbox for Perfusion Quantification using Arterial Spin Labelling. Imaging Neuroscience, https://doi.org/10.1162/imag_a_00041

• Journal Article Type: Article
• Acceptance Date: Nov 10, 2023
• Online Publication Date: Nov 20, 2023
• Publication Date: Nov 20, 2023
• Deposit Date: Nov 23, 2023
• Publicly Available Date: Nov 23, 2023
• Journal: Imaging Neuroscience
• Print ISSN: 2837-6056
• Publisher: Massachusetts Institute of Technology Press
• Peer Reviewed: Peer Reviewed
• DOI: https://doi.org/10.1162/imag_a_00041
• Keywords: arterial spin labelling, perfusion, cerebral blood flow, arterial transit time, variational Bayesian inference
• Public URL: https://nottingham-repository.worktribe.com/output/27595087
• Publisher URL: https://direct.mit.edu/imag/article/doi/10.1162/imag_a_00041/118215/BASIL-A-Toolbox-for-Perfusion-Quantification-using
• Additional Information: © 2023 Massachusetts Institute of Technology. Published under a Creative Commons Attribution 4.0 International (CC BY 4.0) license.