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Peer-Reviewed Publication
Magn Reson Med2026August 6, 2026Journal Article

An Open-Source, Reproducible MRI Data Acquisition and Reconstruction Workflow Using Pulseq: Multi-Site and Cross-Vendor Validation.

Qingping Chen1, Thomas H M Roos2, Amaya Murguia3, Yuhai Xie4, Zheng Liu5, Pengcheng Xu6,7,8, Shohei Fujita6,7,9,10, Sebastian Littin1, Yogesh Rathi11, Jiayu Zhu4, Berkin Bilgic6,7,12, Jon-Fredrik Nielsen13,14, Maxim Zaitsev1
1Division of Medical Physics, Department of Radiology, University Medical Center Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.
2Department of Radiology and Oncology, Center for Image Sciences, University Medical Center Utrecht, Utrecht, the Netherlands.
3Department of Electrical and Computer Engineering, University of Michigan, Ann Arbor, Michigan, USA.
4Shanghai United Imaging Healthcare Co. Ltd., Shanghai, China.
5Wuhan United Imaging Life Science Instrument Co. Ltd., Wuhan, China.
6Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, Massachusetts, USA.
7Department of Radiology, Harvard Medical School, Boston, Massachusetts, USA.
8State Key Laboratory of Extreme Optics and Instrumentation, College of Optical Science and Engineering, Zhejiang University, Hangzhou, China.
9Department of Radiology, Juntendo University, Tokyo, Japan.
10Department of Radiology, The University of Tokyo, Tokyo, Japan.
11Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA.
12Harvard/MIT Health Sciences and Technology, Cambridge, Massachusetts, USA.
13Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan, USA.
14Functional MRI Laboratory, Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA.
PubMed DOI

Abstract

PURPOSE: Reproducibility 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. METHODS: Pulseq, extended with advanced features including LABELs and Se…

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