TY - JOUR
T1 - ISMRM Open Science Initiative for Perfusion Imaging (OSIPI)
T2 - ASL pipeline inventory
AU - Fan, Hongli
AU - Mutsaerts, Henk J. M. M.
AU - Anazodo, Udunna
AU - Arteaga, Daniel
AU - Baas, Koen P. A.
AU - Buchanan, Charlotte
AU - Camargo, Aldo
AU - Keil, Vera C.
AU - Lin, Zixuan
AU - Lindner, Thomas
AU - Hirschler, Lydiane
AU - Hu, Jian
AU - Padrela, Beatriz E.
AU - Taghvaei, Mohammad
AU - Thomas, David L.
AU - Dolui, Sudipto
AU - Petr, Jan
N1 - Funding Information: SD is supported by National Institutes of Health (NIH) grant R03 AG063213. HM is supported by the Dutch Heart Foundation (2020T049) and by the Eurostars‐2 joint program with co‐funding from the European Union Horizon 2020 research and innovation program, provided by the Netherlands Enterprise Agency. KB is supported by NIH grant 1R01‐HL136484‐01A1. LH, VK, HM, BP, and JP are part of the COST Action CA18206 Glioma MR Imaging 2.0, supported by COST (European Cooperation in Science and Technology; www.cost.eu and www.glimr.eu ). JH is supported by the NIHR Nottingham Biomedical Research Center. UA is supported by Canada First Research Excellence Fund and Healthy Brain Healthy Lives (2b‐NISU‐17). DLT is supported by the UCL Leonard Wolfson Experimental Neurology Center (PR/ylr/18575), UCLH NIHR Biomedical Research Center, and Wellcome Trust (539208). Open Access funding enabled and organized by Projekt DEAL. Publisher Copyright: © 2023 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine.
PY - 2023/10/9
Y1 - 2023/10/9
N2 - Purpose: To create an inventory of image processing pipelines of arterial spin labeling (ASL) and list their main features, and to evaluate the capability, flexibility, and ease of use of publicly available pipelines to guide novice ASL users in selecting their optimal pipeline. Methods: Developers self-assessed their pipelines using a questionnaire developed by the Task Force 1.1 of the ISMRM Open Science Initiative for Perfusion Imaging. Additionally, each publicly available pipeline was evaluated by two independent testers with basic ASL experience using a scoring system created for this purpose. Results: The developers of 21 pipelines filled the questionnaire. Most pipelines are free for noncommercial use (n = 18) and work with the standard NIfTI (Neuroimaging Informatics Technology Initiative) data format (n = 15). All pipelines can process standard 3D single postlabeling delay pseudo-continuous ASL images and primarily differ in their support of advanced sequences and features. The publicly available pipelines (n = 9) were included in the independent testing, all of them being free for noncommercial use. The pipelines, in general, provided a trade-off between ease of use and flexibility for configuring advanced processing options. Conclusion: Although most ASL pipelines can process the common ASL data types, only some (namely, ASLPrep, ASLtbx, BASIL/Quantiphyse, ExploreASL, and MRICloud) are well-documented, publicly available, support multiple ASL types, have a user-friendly interface, and can provide a useful starting point for ASL processing. The choice of an optimal pipeline should be driven by specific data to be processed and user experience, and can be guided by the information provided in this ASL inventory.
AB - Purpose: To create an inventory of image processing pipelines of arterial spin labeling (ASL) and list their main features, and to evaluate the capability, flexibility, and ease of use of publicly available pipelines to guide novice ASL users in selecting their optimal pipeline. Methods: Developers self-assessed their pipelines using a questionnaire developed by the Task Force 1.1 of the ISMRM Open Science Initiative for Perfusion Imaging. Additionally, each publicly available pipeline was evaluated by two independent testers with basic ASL experience using a scoring system created for this purpose. Results: The developers of 21 pipelines filled the questionnaire. Most pipelines are free for noncommercial use (n = 18) and work with the standard NIfTI (Neuroimaging Informatics Technology Initiative) data format (n = 15). All pipelines can process standard 3D single postlabeling delay pseudo-continuous ASL images and primarily differ in their support of advanced sequences and features. The publicly available pipelines (n = 9) were included in the independent testing, all of them being free for noncommercial use. The pipelines, in general, provided a trade-off between ease of use and flexibility for configuring advanced processing options. Conclusion: Although most ASL pipelines can process the common ASL data types, only some (namely, ASLPrep, ASLtbx, BASIL/Quantiphyse, ExploreASL, and MRICloud) are well-documented, publicly available, support multiple ASL types, have a user-friendly interface, and can provide a useful starting point for ASL processing. The choice of an optimal pipeline should be driven by specific data to be processed and user experience, and can be guided by the information provided in this ASL inventory.
KW - arterial spin labeling
KW - automated processing pipeline
KW - cerebral blood flow
KW - open science
KW - perfusion
UR - http://www.scopus.com/inward/record.url?scp=85173934563&partnerID=8YFLogxK
U2 - https://doi.org/10.1002/mrm.29869
DO - https://doi.org/10.1002/mrm.29869
M3 - Article
C2 - 37811778
SN - 0740-3194
JO - Magnetic resonance in medicine
JF - Magnetic resonance in medicine
ER -