ArticleScientific data2022
qMRI-BIDS: An extension to the brain imaging data structure for quantitative magnetic resonance imaging data.
Article in Scientific data, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
19 citing papers in PubMed.
- An Open-Source, Reproducible MRI Data Acquisition and Reconstruction Workflow Using Pulseq: Multi-Site and Cross-Vendor Validation.Magnetic resonance in medicine · 2026Article
- Article
- FAIR m-BIDS: Advancing brain data utilization through multimodal and FAIR principles.Scientific data · 2026Article
- Multidimensional correlation magnetic resonance imaging in low- and middle-income countries: opportunities and barriers to equitable deployment.Frontiers in public health · 2026Review
- Multi-center benchmarking of cervical spinal cord RF coils for 7 T MRI: A traveling spines study.Magnetic resonance in medicine · 2025Article
- MRS-BIDS, an extension to the Brain Imaging Data Structure for magnetic resonance spectroscopy.Scientific data · 2025Article
- Sharing Neuroimaging Data with Squirrel - A Relational Data Format to Store Raw to Analyzed Data and Everything in Between.Neuroinformatics · 2025Article
- Rethinking MRI as a measurement device through modular and portable pipelines.Magma (New York, N.Y.) · 2025Review
- Longitudinal reproducibility of brain and spinal cord quantitative MRI biomarkers.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Automated algorithm for medical data structuring, and segmentation using artificial intelligence within secured environment for dataset creation.European journal of radiology open · 2024Article
- Reproducible Research Practices in Magnetic Resonance Neuroimaging: A Review Informed by Advanced Language Models.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2024Review
- Reproducible Spinal Cord Quantitative MRI Analysis with the Spinal Cord Toolbox.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2024Review
- The past, present, and future of the brain imaging data structure (BIDS).Imaging neuroscience (Cambridge, Mass.) · 2024Review
- ezBIDS: Guided standardization of neuroimaging data interoperable with major data archives and platforms.Scientific data · 2024Article
- Article
- A database of the healthy human spinal cord morphometry in the PAM50 template space.Imaging neuroscience (Cambridge, Mass.) · 2024Article
- The relaxometry hype cycle.Frontiers in physiology · 2023Article
- Review
- Microscopy-BIDS: An Extension to the Brain Imaging Data Structure for Microscopy Data.Frontiers in neuroscience · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
14 authors.
Funding
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.