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Updated: Sep 11, 2025

Magnetic Resonance Imaging Quantification of Pulmonary Perfusion using Calibrated Arterial Spin Labeling

Magnetic Resonance Imaging Quantification of Pulmonary Perfusion using Calibrated Arterial Spin Labeling

Published on: May 30, 2011

BASIL: A toolbox for perfusion quantification using arterial spin labelling.

Michael A Chappell^1,2,3, Thomas F Kirk^1,3, Martin S Craig^1,2,3

¹Sir Peter Mansfield Imaging Center, School of Medicine, University of Nottingham, Nottingham, United Kingdom.

Imaging Neuroscience (Cambridge, Mass.)

|August 13, 2025

Summary

This summary is machine-generated.

The BASIL toolbox enhances Arterial Spin Labelling (ASL) MRI analysis for research, offering precise quantification of cerebral blood flow and haemodynamics. It provides advanced tools for interpreting complex ASL data beyond standard perfusion measurements.

Keywords:

arterial spin labelling arterial transit time cerebral blood flow perfusion variational Bayesian inference

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Area of Science:

Neuroimaging
Medical Physics
Biomedical Engineering

Background:

Arterial Spin Labelling (ASL) MRI is a non-invasive technique for quantifying cerebral blood flow.
There is a growing need for advanced methods to gain deeper insights into haemodynamics beyond basic perfusion.
Existing ASL analysis tools may lack the precision or flexibility for complex research applications.

Purpose of the Study:

Introduce the BASIL toolbox, a novel research tool for Arterial Spin Labelling (ASL) MRI data analysis.
Demonstrate the utility of BASIL in quantifying perfusion and other haemodynamic measures, including arterial transit times.
Highlight BASIL's capability to analyze advanced multi-delay ASL acquisitions for enhanced quantitative precision.

Main Methods:

BASIL toolbox, integrated within the FMRIB Software Library (FSL).
Bayesian model-based inference algorithm for quantitative analysis.
Graphical User Interface (GUI) and command-line tools for versatile data analysis.
Exploitation of complementary FSL neuroimaging tools for integrated study designs.

Main Results:

BASIL enables precise quantification of cerebral blood flow and haemodynamic parameters from ASL MRI data.
The toolbox effectively analyzes advanced multi-delay ASL acquisitions, extracting richer information.
Both user-friendly GUI and customizable command-line options are available for diverse research needs.

Conclusions:

The BASIL toolbox provides a powerful and flexible platform for advanced ASL MRI research.
It facilitates the integration of ASL data with other neuroimaging modalities within the FSL ecosystem.
BASIL advances the quantitative analysis of cerebral haemodynamics using non-invasive ASL MRI techniques.