A general framework for optimizing arterial spin labeling MRI experiments

<strong>Purpose:</strong> Arterial spin labeling (ASL) MRI is a non‐invasive perfusion imaging technique that is inherently SNR limited, so scan protocols ideally need to be rigorously optimized to provide the most accurate measurements. A general framework is presented for optimizing AS...

Full description

Bibliographic Details
Main Authors: Woods, JG, Chappell, MA, Okell, TW
Format: Journal article
Published: Wiley 2018
_version_ 1826285939801980928
author Woods, JG
Chappell, MA
Okell, TW
author_facet Woods, JG
Chappell, MA
Okell, TW
author_sort Woods, JG
collection OXFORD
description <strong>Purpose:</strong> Arterial spin labeling (ASL) MRI is a non‐invasive perfusion imaging technique that is inherently SNR limited, so scan protocols ideally need to be rigorously optimized to provide the most accurate measurements. A general framework is presented for optimizing ASL experiments to achieve optimal accuracy for perfusion estimates and, if required, other hemodynamic parameters, within a fixed scan time. The effectiveness of this framework is then demonstrated by optimizing the post‐labeling delays (PLDs) of a multi‐PLD pseudo‐continuous ASL experiment and validating the improvement using simulations and in vivo data. <strong>Theory and Methods:</strong> A simple framework is proposed based on the use of the Cramér‐Rao lower bound to find the protocol design which minimizes the predicted parameter estimation errors. Protocols were optimized for cerebral blood flow (CBF) accuracy or both CBF and arterial transit time (ATT) accuracy and compared to a conventional multi‐PLD protocol, with evenly spaced PLDs, and a single‐PLD protocol, using simulations and in vivo experiments in healthy volunteers. <strong>Results:</strong> Simulations and in vivo data agreed extremely well with the predicted performance of all protocols. For the in vivo experiments, optimizing for just CBF resulted in a 48% and 15% decrease in CBF errors, relative to the reference multi‐PLD and single‐PLD protocols, respectively. Optimizing for both CBF and ATT reduced CBF errors by 37%, without a reduction in ATT accuracy, relative to the reference multi‐PLD protocol. <strong>Conclusion:</strong> The presented framework can effectively design ASL experiments to minimize measurement errors based on the requirements of the scan.
first_indexed 2024-03-07T01:36:21Z
format Journal article
id oxford-uuid:955258c5-1421-4611-a11d-6a004c7f8df5
institution University of Oxford
last_indexed 2024-03-07T01:36:21Z
publishDate 2018
publisher Wiley
record_format dspace
spelling oxford-uuid:955258c5-1421-4611-a11d-6a004c7f8df52022-03-26T23:45:24ZA general framework for optimizing arterial spin labeling MRI experimentsJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:955258c5-1421-4611-a11d-6a004c7f8df5Symplectic Elements at OxfordWiley2018Woods, JGChappell, MAOkell, TW<strong>Purpose:</strong> Arterial spin labeling (ASL) MRI is a non‐invasive perfusion imaging technique that is inherently SNR limited, so scan protocols ideally need to be rigorously optimized to provide the most accurate measurements. A general framework is presented for optimizing ASL experiments to achieve optimal accuracy for perfusion estimates and, if required, other hemodynamic parameters, within a fixed scan time. The effectiveness of this framework is then demonstrated by optimizing the post‐labeling delays (PLDs) of a multi‐PLD pseudo‐continuous ASL experiment and validating the improvement using simulations and in vivo data. <strong>Theory and Methods:</strong> A simple framework is proposed based on the use of the Cramér‐Rao lower bound to find the protocol design which minimizes the predicted parameter estimation errors. Protocols were optimized for cerebral blood flow (CBF) accuracy or both CBF and arterial transit time (ATT) accuracy and compared to a conventional multi‐PLD protocol, with evenly spaced PLDs, and a single‐PLD protocol, using simulations and in vivo experiments in healthy volunteers. <strong>Results:</strong> Simulations and in vivo data agreed extremely well with the predicted performance of all protocols. For the in vivo experiments, optimizing for just CBF resulted in a 48% and 15% decrease in CBF errors, relative to the reference multi‐PLD and single‐PLD protocols, respectively. Optimizing for both CBF and ATT reduced CBF errors by 37%, without a reduction in ATT accuracy, relative to the reference multi‐PLD protocol. <strong>Conclusion:</strong> The presented framework can effectively design ASL experiments to minimize measurement errors based on the requirements of the scan.
spellingShingle Woods, JG
Chappell, MA
Okell, TW
A general framework for optimizing arterial spin labeling MRI experiments
title A general framework for optimizing arterial spin labeling MRI experiments
title_full A general framework for optimizing arterial spin labeling MRI experiments
title_fullStr A general framework for optimizing arterial spin labeling MRI experiments
title_full_unstemmed A general framework for optimizing arterial spin labeling MRI experiments
title_short A general framework for optimizing arterial spin labeling MRI experiments
title_sort general framework for optimizing arterial spin labeling mri experiments
work_keys_str_mv AT woodsjg ageneralframeworkforoptimizingarterialspinlabelingmriexperiments
AT chappellma ageneralframeworkforoptimizingarterialspinlabelingmriexperiments
AT okelltw ageneralframeworkforoptimizingarterialspinlabelingmriexperiments
AT woodsjg generalframeworkforoptimizingarterialspinlabelingmriexperiments
AT chappellma generalframeworkforoptimizingarterialspinlabelingmriexperiments
AT okelltw generalframeworkforoptimizingarterialspinlabelingmriexperiments