Stochastic variational inference improves quantification of multiple timepoint arterial spin labelling perfusion MRI

Kirk, Thomas F.; Kenyon, Georgia G.; Craig, Martin S.; Chappell, Michael A.

doi:10.3389/fnins.2025.1536752

Stochastic variational inference improves quantification of multiple timepoint arterial spin labelling perfusion MRI

Kirk, Thomas F.; Kenyon, Georgia G.; Craig, Martin S.; Chappell, Michael A.

Authors

Thomas F. Kirk

Georgia G. Kenyon

Dr MARTIN CRAIG MARTIN.CRAIG@NOTTINGHAM.AC.UK
DIGITAL RESEARCH DEVELOPER (IMAGE PROCESSING AND ANALYSIS)

Professor MICHAEL CHAPPELL MICHAEL.CHAPPELL@NOTTINGHAM.AC.UK
PROFESSOR OF BIOMEDICAL IMAGING

Abstract

Multiple-timepoint arterial spin labelling MRI is a non-invasive imaging technique that permits measurement of both cerebral blood flow and arterial transit time, the latter of which is an emerging biomarker of interest for cerebrovascular health. Quantification of arterial spin labelling data is challenging due to the low signal to noise ratio and non-linear tracer kinetics of this technique. In this work, we introduce a new quantification method called SSVB that addresses limitations in existing methods and demonstrate its performance using simulations and acquisition data. Simulations showed that the method is more accurate, particularly for estimating arterial transit time, and more robust to noise than existing techniques. On high spatial resolution data acquired at 3 T, the method produced less noisy parameter maps than the comparator method and captured greater variation in arterial transit time on a cross-sectional cohort.

Citation

Kirk, T. F., Kenyon, G. G., Craig, M. S., & Chappell, M. A. (2025). Stochastic variational inference improves quantification of multiple timepoint arterial spin labelling perfusion MRI. Frontiers in Neuroscience, 19, Article 1536752. https://doi.org/10.3389/fnins.2025.1536752

Journal Article Type	Article
Acceptance Date	Jan 10, 2025
Online Publication Date	Feb 4, 2025
Publication Date	Feb 4, 2025
Deposit Date	Feb 4, 2025
Publicly Available Date	Feb 4, 2025
Journal	Frontiers in Neuroscience
Print ISSN	1662-4548
Electronic ISSN	1662-453X
Publisher	Frontiers Media
Peer Reviewed	Peer Reviewed
Volume	19
Article Number	1536752
DOI	https://doi.org/10.3389/fnins.2025.1536752
Public URL	https://nottingham-repository.worktribe.com/output/45035675
Publisher URL	https://www.frontiersin.org/journals/neuroscience/articles/10.3389/fnins.2025.1536752/full