TY - JOUR
T1 - ExploreASL: An image processing pipeline for multi-center ASL perfusion MRI studies
T2 - an image processing pipeline for multi-center ASL perfusion MRI studies
AU - Mutsaerts, Henk J. M. M.
AU - Petr, Jan
AU - Groot, Paul
AU - Vandemaele, Pieter
AU - Ingala, Silvia
AU - Robertson, Andrew D.
AU - Václavů, Lena
AU - Groote, Inge
AU - Kuijf, Hugo
AU - Zelaya, Fernando
AU - O'Daly, Owen
AU - Hilal, Saima
AU - Wink, Alle Meije
AU - Kant, Ilse
AU - Caan, Matthan W. A.
AU - Morgan, Catherine
AU - de Bresser, Jeroen
AU - Lysvik, Elisabeth
AU - Schrantee, Anouk
AU - Bjørnebekk, Astrid
AU - Clement, Patricia
AU - Shirzadi, Zahra
AU - Kuijer, Joost P. A.
AU - Wottschel, Viktor
AU - Anazodo, Udunna C.
AU - Pajkrt, Dasja
AU - Richard, Edo
AU - Bokkers, Reinoud P. H.
AU - Reneman, Liesbeth
AU - Masellis, Mario
AU - Günther, Matthias
AU - MacIntosh, Bradley J.
AU - Achten, Eric
AU - Chappell, Michael A.
AU - van Osch, Matthias J. P.
AU - Golay, Xavier
AU - Thomas, David L.
AU - de Vita, Enrico
AU - Bjørnerud, Atle
AU - Nederveen, Aart
AU - Hendrikse, Jeroen
AU - Asllani, Iris
AU - Barkhof, Frederik
AU - Vaclave, Lena
AU - Bjornebekk, Astrid
AU - Guenther, Matthias
AU - Bjornerud, Atle
N1 - Copyright © 2020. Published by Elsevier Inc.
PY - 2020/10/1
Y1 - 2020/10/1
N2 - 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. To facilitate collaboration and data-exchange, the toolbox follows several standards and recommendations 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 which may increase statistical power and discover between-group perfusion differences. Ultimately, this workflow may advance ASL for wider adoption in clinical studies, trials, and practice.
AB - 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. To facilitate collaboration and data-exchange, the toolbox follows several standards and recommendations 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 which may increase statistical power and discover between-group perfusion differences. Ultimately, this workflow may advance ASL for wider adoption in clinical studies, trials, and practice.
KW - Arterial spin labeling
KW - Cerebral perfusion
KW - Image processing
KW - Multi-center
KW - Quality control
UR - http://www.scopus.com/inward/record.url?scp=85086718032&partnerID=8YFLogxK
U2 - https://doi.org/10.1016/j.neuroimage.2020.117031
DO - https://doi.org/10.1016/j.neuroimage.2020.117031
M3 - Article
C2 - 32526385
SN - 1053-8119
VL - 219
SP - 117031
JO - NEUROIMAGE
JF - NEUROIMAGE
M1 - 117031
ER -