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

Area of Science:

• Medical Imaging
• Magnetic Resonance Imaging (MRI)

Background:

• MRI reproducibility is hindered by variability in data acquisition, formatting, and reconstruction across institutions and vendors.
• Existing vendor-specific protocols often introduce subtle cross-platform differences, impacting research consistency.

Purpose of the Study:

• To develop and validate an open-source, vendor-independent workflow for harmonizing MRI data acquisition, formatting, and reconstruction.
• To mitigate challenges in MRI reproducibility by standardizing the entire imaging pipeline.

Main Methods:

• Utilized Pulseq with advanced features for harmonized data acquisition and sequence definition.
• Converted Pulseq-generated k-space data to MRD format using metadata.
• Performed open-source, vendor-independent image reconstruction and post-processing with Gadgetron.
• Enabled vendor-native online reconstructions on Siemens platforms for Pulseq-based sequences.
• Validated the workflow using MPRAGE and EPI protocols on nine scanners from five sites and four vendors, comparing with vendor-native protocols.

Main Results:

• Pulseq-based sequences executed successfully across all tested systems, with error-free data conversion and reconstruction.
• Pulseq-based, Gadgetron-reconstructed images showed good agreement with vendor-native images, though minor differences persisted.
• Vendor-native protocols exhibited subtle cross-platform execution and reconstruction variations.
• The proposed workflow demonstrated highly consistent sequence execution (Pulseq) and standardized reconstruction (Gadgetron) across scanners.

Conclusions:

• An open-source MRI workflow was established to harmonize acquisition, formatting, and reconstruction across sites and vendors.
• This workflow is a significant advancement toward fully open and reproducible MRI research.
• The system promotes transparency, standardization, and collaboration within the MRI research community.