Multi-stage automated local arterial input function selection in perfusion MRI
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RESEARCH ARTICLE
Multi‑stage automated local arterial input function selection in perfusion MRI Rami Tabbara1 · Alan Connelly1,2 · Fernando Calamante1,2,3 Received: 11 June 2019 / Revised: 21 October 2019 / Accepted: 5 November 2019 © European Society for Magnetic Resonance in Medicine and Biology (ESMRMB) 2019
Abstract Objective Cerebral blood flow (CBF) quantification using dynamic-susceptibility contrast MRI can be achieved via modelindependent deconvolution, with local arterial input function (AIF) deconvolution methods identifying multiple arterial regions with unique corresponding arterial input functions. The clinical application of local AIF methods necessitates an efficient and fully automated solution. To date, such local AIF methods have relied on the computation of a singular surrogate measure of bolus arrival time or custom arterial scoring functions to infer vascular supply origins. This paper aims to introduce a new local AIF method that alternatively utilises a multi-stage approach to perform AIF selection. Material and methods A fully automated, multi-stage local AIF method is proposed, leveraging both signal-based cluster analysis and priority flooding to define arterial regions and their corresponding vascular supply origins. The introduced method was applied to data from four patients with cerebrovascular disease who showed significant artefacts when using a prevailing automated local AIF method. Results The immediately apparent image artefacts found using the pre-existing method due to poor AIF selection were found to be absent when using the proposed method. Conclusion The results suggest the proposed solution provides a more robust approach to perfusion quantification than currently available fully automated local AIF methods. Keywords Perfusion MRI · Arterial input function · Bolus dispersion · Cerebral blood flow · Stroke
Introduction Dynamic susceptibility contrast MRI (DSC-MRI) is commonly used for measuring cerebral blood flow (CBF, also referred to as cerebral perfusion) [1–3], which is an important metric for the diagnosis and management of acute stroke Electronic supplementary material The online version of this article (https://doi.org/10.1007/s10334-019-00798-4) contains supplementary material, which is available to authorized users. * Alan Connelly [email protected] 1
The Florey Institute of Neuroscience and Mental Health, 245 Burgundy Street, Heidelberg, Melbourne, VIC 3084, Australia
2
Florey Department of Neuroscience and Mental Health, University of Melbourne, Melbourne, VIC, Australia
3
The University of Sydney, Sydney Imaging, and School of Aeronautical, Mechanical and Mechatronic Engineering, Sydney, NSW, Australia
[4]. DSC-MRI relies on the intravenous injection of a paramagnetic contrast agent to induce signal intensity variations as the bolus passes through the cerebral vasculature [2, 5]. The acquired signal time-course can subsequently be transformed to infer the corresponding time-dependent bolus concentration C(t) , which can be ex
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