Reproducibility of arterial spin labeling cerebral blood flow image processing: A report of the ISMRM open science initiative for perfusion imaging (OSIPI) and the ASL MRI challenge

Arterial spin labeling (ASL) is a widely used contrast-free MRI method for assessing cerebral blood flow (CBF). Despite the generally adopted ASL acquisition guidelines, there is still wide variability in ASL analysis. We explored this variability through the ISMRM-OSIPI ASL-MRI Challenge, aiming to...

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Bibliographic Details
Published in:	Magnetic resonance in medicine Vol. 92; no. 2; pp. 836 - 852
Main Authors:	Paschoal, Andre M, Woods, Joseph G, Pinto, Joana, Bron, Esther E, Petr, Jan, Kennedy McConnell, Flora A, Bell, Laura, Dounavi, Maria-Eleni, van Praag, Cassandra Gould, Mutsaerts, Henk J M M, Taylor, Aaron Oliver, Zhao, Moss Y, Brumer, Irène, Chan, Wei Siang Marcus, Toner, Jack, Hu, Jian, Zhang, Logan X, Domingos, Catarina, Monteiro, Sara P, Figueiredo, Patrícia, Harms, Alexander G J, Padrela, Beatriz E, Tham, Channelle, Abdalle, Ahmed, Croal, Paula L, Anazodo, Udunna
Format:	Journal Article
Language:	English
Published:	United States Wiley Subscription Services, Inc 01-08-2024 John Wiley and Sons Inc
Subjects:	Adult Algorithms Best practice Blood flow Brain - blood supply Brain - diagnostic imaging Cerebral blood flow Cerebrovascular Circulation - physiology Computer Processing and Modeling Correlation coefficient Correlation coefficients Datasets Digital imaging Errors Estimates Female Humans Image processing Image Processing, Computer-Assisted - methods Labeling Magnetic resonance imaging Magnetic Resonance Imaging - methods Male Medical imaging Neuroimaging Perfusion Imaging - methods Reproducibility Reproducibility of Results Spin labeling Spin Labels Standardization Synthetic data Teams cerebral blood flow ASL challenges image analysis reproducibility
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Summary:	Arterial spin labeling (ASL) is a widely used contrast-free MRI method for assessing cerebral blood flow (CBF). Despite the generally adopted ASL acquisition guidelines, there is still wide variability in ASL analysis. We explored this variability through the ISMRM-OSIPI ASL-MRI Challenge, aiming to establish best practices for more reproducible ASL analysis. Eight teams analyzed the challenge data, which included a high-resolution T1-weighted anatomical image and 10 pseudo-continuous ASL datasets simulated using a digital reference object to generate ground-truth CBF values in normal and pathological states. We compared the accuracy of CBF quantification from each team's analysis to the ground truth across all voxels and within predefined brain regions. Reproducibility of CBF across analysis pipelines was assessed using the intra-class correlation coefficient (ICC), limits of agreement (LOA), and replicability of generating similar CBF estimates from different processing approaches. Absolute errors in CBF estimates compared to ground-truth synthetic data ranged from 18.36 to 48.12 mL/100 g/min. Realistic motion incorporated into three datasets produced the largest absolute error and variability between teams, with the least agreement (ICC and LOA) with ground-truth results. Fifty percent of the submissions were replicated, and one produced three times larger CBF errors (46.59 mL/100 g/min) compared to submitted results. Variability in CBF measurements, influenced by differences in image processing, especially to compensate for motion, highlights the significance of standardizing ASL analysis workflows. We provide a recommendation for ASL processing based on top-performing approaches as a step toward ASL standardization.
Bibliography:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23
ISSN:	0740-3194 1522-2594 1522-2594
DOI:	10.1002/mrm.30081