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

Abstract

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.

Fig. 1

illustrates the ASL-BIDS example dataset asl_004, which is a multi-PLD PCASL dataset composed of several control-label repetitions, and a separate M0 image repeated with an opposite phase-encoding, posterior-anterior (PA), direction for distortion correction. The directory structure, NIfTI files and sidecars such as json and tsv (tab separated values), and other generic files are shown. The ASL data are in the specific folder for perfusion-related files (perf), except for the reversed phase-encoding direction (fmap). For each json, a selection of important fields is shown. Fields given in bold in ASL.json refer to fields that were included manually in DICOM to BIDS conversion as they were not present in the DICOM files.