Automated, open-source, vendor-independent quality assurance protocol based on the Pulseq framework.

Objectives: Consistent image quality and signal stability are crucial for neuroimaging, particularly fMRI studies that rely on detecting small BOLD signal changes. Regular MR system performance monitoring is essential, especially for longitudinal and multi-site studies. This work aims to establish a robust quality assurance (QA) protocol to enhance data comparability across days, scanner versions, vendors, and sites.

Materials and methods: We implemented an open-source, vendor-independent QA protocol using Pulseq for standardized data acquisition and ISMRMRD/Gadgetron for harmonized image reconstruction, accompanied by an automated post-processing pipeline to evaluate structural and temporal image quality. The protocol was thoroughly tested on three Siemens 3T scanners with different software versions at one site, and one GE 3T scanner at another site. The test was repeated on an fBIRN phantom for at least 4 days.

Results: The vendor-independent protocol produced image quality comparable to a closely matched vendor-based protocol. It showed similar day-to-day repeatability to the vendor-based protocol across the Siemens scanners and high inter-day repeatability on the GE scanner.

Conclusion: We successfully developed and implemented an open-source, vendor-independent QA protocol, accompanied by an automated post-processing pipeline. The results demonstrate the feasibility and repeatability of the protocol across different days, system versions, vendors, and sites.