ASL-BIDS, the brain imaging data structure extension for arterial spin labeling

Arterial spin labeling (ASL) is a non-invasive MRI technique that allows for quantitative measurement of cerebral perfusion. Incomplete or inaccurate reporting of acquisition parameters complicates quantification, analysis, and sharing of ASL data, particularly for studies across multiple sites, pla...

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Vydané v:Scientific data Ročník 9; číslo 1; s. 543 - 8
Hlavní autori: Clement, Patricia, Castellaro, Marco, Okell, Thomas W., Thomas, David L., Vandemaele, Pieter, Elgayar, Sara, Oliver-Taylor, Aaron, Kirk, Thomas, Woods, Joseph G., Vos, Sjoerd B., Kuijer, Joost P. A., Achten, Eric, van Osch, Matthias J. P., Detre, John A., Lu, Hanzhang, Alsop, David C., Chappell, Michael A., Hernandez-Garcia, Luis, Petr, Jan, Mutsaerts, Henk J. M. M.
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: London Nature Publishing Group UK 06.09.2022
Nature Publishing Group
Nature Portfolio
Predmet:
692/700/1421/65
706/648/276
706/648/697
Brain - diagnostic imaging
Brain research
Data storage
Humanities and Social Sciences
Humans
Magnetic resonance imaging
Magnetic Resonance Imaging - standards
Medical imaging
Medical research
Medicine
Metadata
multidisciplinary
Neuroimaging
Neuroimaging - methods
Neurology
Neurosciences
Reproducibility
Reproducibility of Results
Science
Science (multidisciplinary)
Spin labeling
Spin Labels
Standardization
University colleges
ISSN:2052-4463, 2052-4463
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Popis
Shrnutí:Arterial spin labeling (ASL) is a non-invasive MRI technique that allows for quantitative measurement of cerebral perfusion. Incomplete or inaccurate reporting of acquisition parameters complicates quantification, analysis, and sharing of ASL data, particularly for studies across multiple sites, platforms, and ASL methods. There is a strong need for standardization of ASL data storage, including acquisition metadata. Recently, ASL-BIDS, the BIDS extension for ASL, was developed and released in BIDS 1.5.0. This manuscript provides an overview of the development and design choices of this first ASL-BIDS extension, which is mainly aimed at clinical ASL applications. Discussed are the structure of the ASL data, focussing on storage order of the ASL time series and implementation of calibration approaches, unit scaling, ASL-related BIDS fields, and storage of the labeling plane information. Additionally, an overview of ASL-BIDS compatible conversion and ASL analysis software and ASL example datasets in BIDS format is provided. We anticipate that large-scale adoption of ASL-BIDS will improve the reproducibility of ASL research.
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ISSN:2052-4463
2052-4463
DOI:10.1038/s41597-022-01615-9