Magnetic resonance in medicine · 2026
An Open-Source, Reproducible MRI Data Acquisition and Reconstruction Workflow Using Pulseq: Multi-Site and Cross-Vendor Validation.
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Chen Qingping, Roos Thomas H M, Murguia Amaya, Xie Yuhai, Liu Zheng, Xu Pengcheng, Fujita Shohei, Littin Sebastian, Rathi Yogesh, Zhu Jiayu, Bilgic Berkin, Nielsen Jon-Fredrik, Zaitsev Maxim
Аннотация
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 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.
RESULTS: Pulseq-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.
CONCLUSION: We 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.
METHODS: Pulseq, 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.
RESULTS: Pulseq-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.
CONCLUSION: We 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.