qMRI-BIDS: An extension to the brain imaging data structure for quantitative magnetic resonance imaging data

Abstract

The Brain Imaging Data Structure (BIDS) established community consensus on the organization of data and metadata for several neuroimaging modalities. Traditionally, BIDS had a strong focus on functional magnetic resonance imaging (MRI) datasets and lacked guidance on how to store multimodal structural MRI datasets. Here, we present and describe the BIDS Extension Proposal 001 (BEP001), which adds a range of quantitative MRI (qMRI) applications to the BIDS. In general, the aim of qMRI is to characterize brain microstructure by quantifying the physical MR parameters of the tissue via computational, biophysical models. By proposing this new standard, we envision standardization of qMRI through multicenter dissemination of interoperable datasets. This way, BIDS can act as a catalyst of convergence between qMRI methods development and application-driven neuroimaging studies that can help develop quantitative biomarkers for neural tissue characterization. In conclusion, this BIDS extension offers a common ground for developers to exchange novel imaging data and tools, reducing the entrance barrier for qMRI in the field of neuroimaging.

Fig. 1

(a) Schematic representation of BIDS formatted raw (left) and derived (right) quantitative MRI (qMRI) data. MP2RAGE (anat) and TB1DAM (fmap) file collections highlight entity-linked metadata fields for the InversionTime (yellow and green), the FlipAngle (purple and pink), and for the reconstructed image type (cyan). Derivatives from these file collections are generated by using pymp2rage and qMRLab, yielding T1 and B1+ maps. (b) File organization of raw qMRI data for MP2RAGE and TB1DAM file collections, where respective linking entities are highlighted for the inv entity (yellow and green, InversionTime), the flip entity (purple and pink, FlipAngle) and the part entity (cyan, magnitude/phase). (c) File organization of qMRI derivatives indicating how sidecar JSON files of quantitative maps generated by open-source software keeps a log of the input files (the BasedOn field) and associated acquisition parameters (FlipAngle in TB1map and InversionTime in B1map).

Fig. 2

Summary of the standard operational procedure for improving BEP001. Outcomes from the monthly meetings (a) are transferred to a central GitHub repository, opened for more elaborate public discussions via issues and merged into the proposal through peer-reviewed pull requests (b). BEP001 is inclusive to all communities who would like to contribute to the proposal or keep themselves up to date with the latest developments.