ArticleMagnetic resonance in medicine2026
An Open-Source, Reproducible MRI Data Acquisition and Reconstruction Workflow Using Pulseq: Multi-Site and Cross-Vendor Validation.
Article in Magnetic resonance in medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper 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
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors.
Funding
Abstract
purposeReproducibility in MRI is limited by variability in data acquisition, formatting, and reconstruction across sites and vendors. This work aimed to mitigate these challenges through an open-source, vendor-independent workflow originally developed for the 2023-24 ISMRM Repeat It with Me: Reproducibility Team Challenge.
methodsPulseq, extended with advanced features including LABELs and Sequence Definitions for k-space description and execution instructions, was used to harmonize data acquisition. Pulseq-generated raw k-space data were converted into the MRD format using these metadata. Open-source, vendor-independent image reconstruction and post-processing were performed with Gadgetron. Additionally, vendor-native online reconstructions on Siemens platforms (ICE and OpenRecon) were enabled for Pulseq-based sequences. The workflow was validated using MPRAGE and EPI protocols in phantoms and in vivo across nine scanners from five sites and four vendors. Vendor-native acquisition and reconstruction protocols were executed for comparison.
resultsPulseq-based sequences executed successfully on all systems, with all data converted and reconstructed without errors. Pulseq-based, Gadgetron-reconstructed images showed good agreement with corresponding vendor-native images across scanners; however, qualitative and quantitative differences remained. Despite detailed natural-language descriptions and meticulous console configuration, vendor-native protocols introduced subtle but notable cross-platform differences in sequence execution and reconstruction. In contrast, the proposed workflow achieved highly consistent sequence execution via Pulseq and standardized reconstruction through Gadgetron across scanners.
conclusionWe established an open-source MRI workflow that harmonizes data acquisition, formatting, and reconstruction across sites and vendors. This workflow represents a critical step toward fully open and reproducible MRI, facilitating transparency, standardization, and collaboration across the research community.
Indexed as
Identifiers
What OpenQuestion holds
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.