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ExploreASL: an image processing pipeline for multi-center ASL perfusion MRI studies

Authors :
Frederik Barkhof
Mario Masellis
Pieter Vandemaele
Silvia Ingala
David L. Thomas
Ilse M. J. Kant
Elisabeth Lysvik
Patricia Clement
Bradley J. MacIntosh
Michael A. Chappell
Dasja Pajkrt
Enrico De Vita
Jan Petr
Aart J. Nederveen
Reinoud P H Bokkers
Catherine Morgan
Owen O'Daly
Fernando Zelaya
Liesbeth Reneman
Atle Bjørnerud
Andrew D. Robertson
Edo Richard
Anouk Schrantee
Jeroen de Bresser
Matthan W.A. Caan
Paul F. C. Groot
Joost P.A. Kuijer
Iris Asllani
Eric Achten
Xavier Golay
Zahra Shirzadi
Matthias J.P. van Osch
Lena Václavů
Jeroen Hendrikse
Inge Rasmus Groote
Astrid Bjørnebekk
Henri J.M.M. Mutsaerts
Alle Meije Wink
Udunna C. Anazodo
Hugo J. Kuijf
Saima Hilal
Matthias Günther
Source :
NeuroImage 219(2020), 117031
Publication Year :
2019
Publisher :
Cold Spring Harbor Laboratory, 2019.

Abstract

Arterial spin labeling (ASL) has undergone significant development since its inception, with a focus on improving standardization and reproducibility of its acquisition and quantification. In a community-wide effort towards robust and reproducible clinical ASL image processing, we developed the software package ExploreASL, allowing standardized analyses across centers and scanners.The procedures used in ExploreASL capitalize on published image processing advancements and address the challenges of multi-center datasets with scanner-specific processing and artifact reduction to limit patient exclusion. ExploreASL is self-contained, written in MATLAB and based on Statistical Parameter Mapping (SPM) and runs on multiple operating systems. The toolbox adheres to previously defined international standards for data structure, provenance, and best analysis practice.ExploreASL was iteratively refined and tested in the analysis of >10,000 ASL scans using different pulse-sequences in a variety of clinical populations, resulting in four processing modules: Import, Structural, ASL, and Population that perform tasks, respectively, for data curation, structural and ASL image processing and quality control, and finally preparing the results for statistical analyses on both single-subject and group level. We illustrate ExploreASL processing results from three cohorts: perinatally HIV-infected children, healthy adults, and elderly at risk for neurodegenerative disease. We show the reproducibility for each cohort when processed at different centers with different operating systems and MATLAB versions, and its effects on the quantification of gray matter cerebral blood flow.ExploreASL facilitates the standardization of image processing and quality control, allowing the pooling of cohorts to increase statistical power and discover between-group perfusion differences. Ultimately, this workflow may advance ASL for wider adoption in clinical studies, trials, and practice.

Details

Language :
English
Database :
OpenAIRE
Journal :
NeuroImage 219(2020), 117031
Accession number :
edsair.doi.dedup.....f926a8ed072e4209af8c761285145e27
Full Text :
https://doi.org/10.1101/845842